Three months ago, during a flashy event at its Washington, DC, headquarters, NASA announced that it was shifting the focus of its lunar plans from an orbital space station to a Moon base on the surface.
As part of this, officials said work would be paused on the Lunar Gateway planned to orbit the Moon. Of the two elements that were furthest along, NASA also revealed that one of them—the Power and Propulsion Element—would be repurposed to serve as a core module for a nuclear-electric propulsion demonstration in deep space.
Less was said about the fate of the other major component, the Habitation and Logistics Outpost (HALO). This is the large pressurized module, 6.1 meters long, in which visiting astronauts would spend the majority of their time when visiting the Lunar Gateway. NASA has awarded contracts worth $1.1 billion to Northrop Grumman to design, build, and integrate the habitation module with the Power and Propulsion Element.
What we found was that delicensing reduced wages, reduced prices, and caused a shift towards cremation rather than the more expensive mortuary services preferred by funeral directors. Here’s a key figure.
Average weekly wages in the funeral services industry in Colorado and the US (excluding Colorado), pre and post Colorado’s delicensing in 1983.
But that is not the end of the story. In 2023 a series of gruesome abuses came to light involving the sale of body parts, rotting bodies, and worse. Newspapers repeatedly noted that Colorado was the only state not to license funeral service workers. As a result, Colorado is relicensing funeral service workers as of 2027.
The problem is that there is no evidence that abuses were worse in Colorado. It’s easy to find similar abuses—including sexual abuse of corpses—in states with heavy licensing. Pizzola and I didn’t examine the rate of necrophilia among funeral workers in our paper (silly us), but we did cite the following:
A recent US government review of occupational licensing concluded that “the empirical research does not find large improvements in quality or health and safety from more stringent licensing” (CEA, 2015). Similarly, Colorado revisited their decision in a 1990 sunrise review that considered reinstating occupational licensing. The Colorado Department of Regulatory Agencies found that since the 1983 occupational delicensing: (1) “there had been incidents of malpractice within the profession but no widespread pattern of abuse,” (2) “[a]llegations of significant threats to the public health, safety and welfare perpetrated by the death care industry in Colorado regarding the improper disposal of human or infectious wastes had not been supported by verifiable evidence,” and (3) “claims that the public in Colorado had suffered or might suffer significant detriment due to a lack of trained mortuary science practitioners caused by the abolition of the Board were unsupported” (Colorado Department of Regulatory Agencies, 2007).
Moreover, the licensing requirements—mandating various hours of training and so forth—have very little to do with the types of abuses that generated public support for relicensing. How many hours of “don’t have sex with corpses” training is required? And the funeral director in the worst Colorado case was in fact sentenced to 40 years in jail. Isn’t that incentive enough?
People want what cannot be guaranteed: good behavior in all circumstances. And they will reach for a licensing regime if it promises that, even when such promises are empty.
In this episode of Space Minds, David Ariosto talks with Mike Kincaid, president and chief executive of the Challenger Center. They discuss the space workforce pipeline and the center’s role […]
In January 2026 alone, the Federal Communications Commission authorized 15,000 Starlink Gen2 satellites. Starcloud has filed for 88,000 orbital data center satellites. SpaceX has filed for 1 million. There is […]
PORTLAND, Ore. – Boeing demonstrated a key quantum networking protocol in ground testing of a compact payload ahead of on-orbit experiment in 2027. “High-fidelity entanglement swapping” was demonstrated earlier this […]
A startup has acquired an aircraft to offer commercial parabolic flight services even as NASA seeks to acquire its own aircraft for reduced-gravity research.
Austrian satellite propulsion startup Gate Space has won 6.3 million euros in funding from Europe’s government-backed accelerator program, joining a wave of European companies attracting capital for greater space sovereignty.
Private equity firm EQT is acquiring Exolaunch, a company that has handled the rideshare launches of hundreds of satellites, to help it meet growing launch demand.
Chinese startup Spark Space has secured a series of funding rounds for what it claims will be the world's largest electric-pump-fed rocket, following engine tests.
A spacecraft developed by Tsinghua University is set to join international missions to study the asteroid Apophis during its close approach to Earth in 2029.
Europe is finally waking up from many decades of naive pacifism. While the continent is loath to give America credit, this is largely where it's due, as Trump has pulled back on blanket security guarantees. Well, that and a major war on its doorstep going on four years now.
That's the thing about delusions. Their upkeep seems free until reality intrudes. And that reality has finally gate-crashed the European continent with all the tact and timing of a drunken sailor. So now what?
"Buy, buy, buy" was what the Danish prime minister declared last year, as she committed another 50 billion kroner to buy weaponry in that year and this. But buy what and from whom? Sadly, there aren't many top European weapon and equipment makers ready, as the continent's defense industry has been starved of investment for thirty years.
As late as 2018, nearly two-thirds of European investors excluded companies involved in conventional weapons production due to ESG considerations, per Eurosif. And this has been going on since the early 1990s.
As always, the best time to plant a tree was twenty years ago. The second-best time is now. And this also applies to the tech industry because the next war will depend on it more than ever.
Like drones. They've become the main vector in the war in Ukraine. Fiber-optic cables have covered the battlefield like a spiderweb, and many of the recent advances on the Ukrainian side have been attributed to their superior drone operations.
We need drones in Europe. Lots of them. In all shapes and sizes. Made by European companies, built on open-source platforms, and with local supply chains. And that's exactly what the Danish startup Upteko has been working on for nearly a decade, and is now ready to scale up.
So I invested in Upteko. It's outside my normal, boring invest-in-what-you-know strategy of putting money in Danish SaaS startups, but also not that far away. The future of drones is as much in software as in propulsion. And I know something about that.
But really, it wasn't so much about knowledge as it was motivation. And nobody has brought more of a motivating example to the tech-meets-defense question than Palmer Luckey. His Anduril company is infusing modern weapon-making with the zest and innovation of a Valley startup. It's sorely needed, and deeply inspiring.
Europe needs its own Andurils. Not because it can't also continue to buy systems from the Americans, but because a good ally is self-sufficient, equally inventive, and armed to the teeth with a diverse fleet of awesome, native weapons.
One of the underrated joys of hardware tech development is having the opportunity to tell and retell the story until it gradually becomes less mysterious. To me, what Terraform is doing was as obvious as breathing five years ago. To others, even long standing employees and investors, some of the finer points are not yet as obvious as they should be. When I stumble on one of these areas, it provides an opportunity to write a blog about it.
How does new technology enter the market?
New technology costs more. Adoption at scale requires two strategies: A beachhead market willing to pay enough to make early production profitable, and economies of scale that drive down costs as adoption increases, with cost falling at least as fast as the beachhead is exhausted.
Think of Tesla’s strategy around electric cars. First, the Roadster, an overpriced toy to mature the tech at a smaller and cheaper scale. Then the Model S and X, premium cars that addressed a much larger market. Finally, the 3 and Y for the mass market. This pattern even continues with the piloting of cybercab tech through the cybertruck, e.g. the 48 V bus and large aluminum castings.
What are economies of scale?
Bigger things are cheaper, everyone knows this! But hang on a second. Foxconn makes phones cheap by making millions of them. TSMC makes chips cheap by making millions of them. Hanwha Ocean makes container ships cheap by making them enormous. Wärtsilä makes marine Diesels cheap by making them enormous.
Is it strictly correct to label both of these economies of scale? One gigantic thing vs trillions of tiny things? I think this is fine, provided one understands what is actually delivering improved value in this operation. The world does not need one gigantic chip or a trillion tiny container ships. What delivers value is the repetition and ultimately automation of numerous atomic processes. For ships and chips the square-cube law also comes into play – I will leave the unification of this observation as an exercise for the reader.
I will note that scale doesn’t automatically make things cheaper. There are also profligacies of scale, with examples too numerous and obvious to even mention.
Why does repetition make things cheap? What is the learning rate?
The learning rate, also called Wright’s Law, is a phenomenological description of a real world process. Manufacturing engineers optimizing US production of warplanes in WW2 noticed that cost dropped by a fixed percentage, typically about 15%, per cumulative doubling of production. In the context of WW2 plants churning out thousands of airplanes, this became a powerful driver in US over-production of war materiel, hastening the end of the war.
This curve, for B-29 production, shows a late time acceleration of the learning rate, which has been observed in a few other industries, typically when scale of production finally breaks through whatever the previous limiting factor was.
For example, solar photovoltaic module production turned a corner in 2009 when scale finally justified dedicated silicon processes rather than using leftovers from chip manufacturing. Since then, the solar learning curve has continued to steepen, reaching 48% last year! Currently, global production doubles roughly every 24 months, so the price of modules falls by nearly a factor of two in that time.
In contrast, the lithium ion battery learning curve is a more modest 23%, similar to Boeing’s B-29 plant. As a result the price halves roughly every three years, even though manufacturing is doubling at a faster pace than solar, doubling every year for most of the years since 2018.
To first order, the more complicated the product, the lower the learning rate. Solar modules contain no moving parts, relatively few materials, have a fungible supply chain, an efficient market for production tooling, and so there’s a broad attack surface for process engineers to suck out cost and increase production rate. SWRO, in contrast, involves lots of parts, lots of moving parts, corrosive, fouling chemistry, high pressures, and rather finicky membranes. Still, 15% is far better than zero, and the most advanced plants churn out fresh water for just 40c per cubic meter!
So what does Terraform’s learning rate need to be?
There’s an aspect of Terraform Industries’ market expansion that I always thought was extremely obvious, but recently an investor pushed back on it so I actually did the math. It turns out not to be super obvious, but after this post it will be, so strap in!
Question
Okay, fine, your beach head market is premium chemically pure methane with higher revenue, but what does your learning rate have to be to ensure that your cost of goods sold (COGS) drops fast enough that as you expand you can still sell profitably, even as your beachhead premiums go away? That is, we believe you can produce chemically pure methane and sell it profitably, but that market is worth only a few hundred million dollars per year globally, and that’s just not enough to justify venture returns. The global oil and gas industry is worth over eight trillion dollars annually, but your current cost is nowhere near competitive, so what’s the plan? Economies of scale?
Answer
The oil and gas market is big. You just won’t believe how vastly, hugely, mind-bogglingly big it is. I mean, you may think, say, Google, earns a lot of money, but that’s just peanuts to oil and gas.
You might spend 15 minutes reading this post. In that time, the oil and gas industry turned over $250m.
The way to think about this is to consider the size of the incremental market expansion bought by a trivial cost improvement, say 1%. Short run oil demand is highly inelastic, but even so, a 1% reduction in price will increase newly addressable demand by about 0.08%, or $7b/year. $7b on top of Apple’s iPhone sales would be a 12% sales bump – enormous! In the oil industry, that’s Tuesday evening.
Short run elasticity isn’t the right measure, though. Below are two charts demonstrating methane’s long run addressable market elasticity is 2.6, while methanol, the oil precursor, is 5.0. That means that when Terraform decreases at-scale production cost by 1%, the methane market expands by 2.6% ($41b), while the methanol market expands by 5% ($115b). It is difficult to imagine a more inviting addressable market!
Because we have 24 doublings of production before saturation, even a 10% learning rate cuts cost faster than the beachhead premium decays. We never sell at a loss on the way down. Indeed, if we can compound our production skill with a learning rate of more than 12%, our margins will strictly increase as we scale out. 24 doublings is a lot of runway to push our production costs down by the factor of four required to unconditionally undercut drilling in any market, no questions asked.
That’s the intuition, let’s make it rigorous.
Here is our current estimate for the global methane market ladder. Currently we can produce methane for under $30/MCF – an achievement in itself! The red curve shows a 10% learning rate. 10% is nothing spectacular – it’s less than half the improvement seen in B-29 production, during war time, in the 1940s, on a plane whose size and complexity was so unprecedented that the flight test program took the lives of the test pilot Edmund T. Allen and 31 other people.
This curve also assumes that the bulk Henry Hub market remains artificially depressed by natural gas co-production during fracking for oil products. Pure play gas fracking projects typically turn a profit at about $9/MCF, which would necessitate a learning rate of only about 6%, which is even more ludicrously unambitious. To be blunt, we have designed the Terraformer from Day 1 to be scalable in production and as simple as possible. We will exceed a 10% learning rate!
Natural gas is about a fifth of the oil and gas market. The remainder can be addressed with methanol and its derivatives, so we’ve accelerated our progress on methanol production and expect to begin direct-to-consumer sales soon! The methanol ladder is more complex, showing higher purity premium product tiers (green) and methanol-to-X downstream products such as gasoline, aviation fuel, plastics, etc (purple). A mere 6% learning rate easily clears this ladder retaining at least 25% margins. A 20% learning rate will result in accelerating margins and substantial additional induced demand and economic growth.
Of course, if we doubled production every six months for a decade it is possible that we could temporarily outrun the solar learning rate before becoming its primary driver, but this would be an excellent outcome for everyone.
Further implications of these facts?
While mass scale deployment of Terraformers is capital intensive, it is readily financeable with quantifiable risk and solid returns above 20% IRR, and at times far higher. You can explore various configurations at terraform-simulator.com. The Amazon fulfillment center build out might be a good parallel for this process. The business will expand as quickly as possible while retaining positive EBITDA less re-investment in growth.
Once we get the ball rolling, expansion and strategy is straightforward. Just try not to be drowned by the nearly infinite money gusher.
What is the smallest possible catalytic spark? What is the key to unlocking growth?
Terraform is in the process of deploying our first ever full scale Terraformer at our Muroc test site in Rosamond, California. We expect this development unit to have positive unit economics. The pilot will actually generate value, no $1b leap of faith required. This is critically important to avoiding the so-called “Valley of Death”. From there, we scale up production by bringing up new sites. Each site generates net revenue. We expect company level profitability to occur with between 15 and 25 Terraformers operational and will size our second development site well in excess of this.
With well over 6,000 exoplanets now confirmed and a continuing flow of data containing new detections, it has been clear for some time that our own Solar System’s model is hardly a template. I enjoy dipping into the bewildering variety of new systems and pondering the contingencies that have led to their architecture. Science fiction is an intensely visual genre, so I naturally try to imagine the more extreme systems. But more than most, today’s catch at HD 39474, an F-class star in Pictor some 360 light years out, is just begging for a gifted SF writer to go to work on it. Here we have, in addition to the central star, a long-period transiting brown dwarf with a planetary system, coplanar and aligned with the brown dwarf, packed inside its orbit.
HD 39474 is also, at least for now, known as TOI-201, TOI standing for TESS Object of Interest, an indication that while the Transiting Exoplanet Survey Satellite’s photometry has found what looks like a planetary transit, that result has not yet been confirmed. Various things can mimic a transit, including stars in an eclipsing binary system, so confirmation through radial velocity methods or additional transits is necessary. Nonetheless, a new study in Nature looks solid, and the system it points to is of exceptional interest. The work describes a ‘mono-transit’ in TESS data sets that is tentatively identified as a massive brown dwarf designated TOI-201c.
A single transit can indicate a planet or brown dwarf whose orbit greatly exceeds the observational period, which is why such a transit is not enough to confirm the detection. But there is a lot more going on here. In fact, according to Alessandro Sozzetti (INAF-Astrophysical Observatory of Turin), TOI-201c has been characterized by transit timing variations of an inner planet as well as the photometric transit and radial velocity measurements, with upcoming confirmation through GAIA astrometric data. Being characterized through four different methods appears to be a first.
The work, led by the European Southern Observatory (with strong involvement from Italy’s National Institute for Astrophysics (INAF) reminds us of the blurred star/planet distinction. Brown dwarfs can have planetary systems of their own, warmed by their exceedingly faint light. TOI-201c has the longest orbital period, some 2,881 days, for which a mass has been confirmed, in this case through radial velocity readings.
Within the brown dwarf’s orbit are two further transiting objects that are aligned with it. Getting into the dynamics of system formation here is going to be interesting work. TOI-201d has a period of 5.8 days and appears to be a rocky super-Earth, while the gas giant TOI-201b is in a 53-day orbit. With an orbital eccentricity of 0.622, the brown dwarf is a significant perturber. According to the researchers, anything much farther from the star than the orbit of Mars around the Sun would be dynamically unstable.
Luca Naponiello (INAF), second author of the paper on this work, takes note of the brown dwarf’s impact:
“The presence of the brown dwarf on such an elliptical orbit forced the planets to form and survive by occupying the innermost and hottest edges of the primordial disk. Furthermore, the data show that during the close approach of the brown dwarf, the warm Jupiter undergoes strong and sudden variations in its transit timing, bearing witness to an intense and vigorous dynamic interaction currently underway between the two giants,”
Image: Close-up artistic representation of the TOI-201 system. In the foreground is the massive brown dwarf TOI-201 c, followed by the hot Jupiter TOI-201 b (subject to strong gravitational perturbations), the star TOI-201, and finally the super-Earth TOI-201 d. Credits: INAF / generated with AI Gemini.
ESO spectography from its FEROS and PLATOSPEC instruments complemented the TESS data to offer up this extremely stressed system, which makes the case that even in environments as challenging as these, planets find a way to form. How long they last is another question, and I assume future work may give us some thoughts on the survival of the gas giant here. In any case, finding an inner gas giant in these circumstances draws into question theories of gas giant formation that assume distances beyond several AU from the central star. We should be hearing a lot more about the system at TOI-201 given the stress it puts upon earlier formation models.
The paper is Jones et al., “A distant brown dwarf coplanar to a warm Jupiter and a hot super-Earth,” Nature 654 (17 June 2026), 614-618 (abstract).
I'll be speaking Sunday at the American Transplant Congress, on kidney exchange. It will be hard to squeeze in all the recent developments in my half hour, including current controversies.
This week, Qantas Airways announced it will begin its long-awaited London-Sydney nonstops late next year. With an expected time aloft of around 22 hours, this will be, by a wide margin, the longest flight in the world — indeed, the longest scheduled nonstop in history.
This is the culmination of a decades-long quest — of challenges so vast that Qantas even gave its quest a name: Project Sunrise. (Personally I would’ve gone with Project Horizon, but nobody asked.) After a series delays and setbacks, the airline now feels confident enough to give us a launch month: October 2027.
The route will be flown using a fleet of specially modified, ultra-long range (ULR) Airbus A350s, the first of which is undergoing a series of test flights as we speak.
The “Kangaroo route” as it was called as early as the 1930s, once took twelve days and required more than a dozen stops. By the 1960s, with the advent of jets like the 707, two or three stops was the norm. In the 1990s, with the introduction of the Boeing 747-400, a single stop became the standard. Even after all that progress, the idea of a nonstop still seemed a dream, well, too far.
The newest generation of aircraft, including the A350, changed that thinking, and here we are.
A New York-Sydney nonstop, slightly shorter in distance, is planned following launch of the London flights.
Qantas says fares will run about 20 percent higher than those charged for its current one-stops along the same routes, citing a “massive demand” for direct service.
Cabins will feature a premium-heavy configuration of only 238 seats. The lower density layout stands to reason. As I’ve pointed out before, the real challenges of long-haul flying are perhaps no longer technological so much as human. That is, how do you keep passengers comfortable, or even sane, on a journey stretching ten-thousand miles? We’re basically at the limits of what people can endure, at least in economy class.
So, what’s left?
Does the success of Project Sunrise end the range game? Is this aviation’s ultimate triumph over distance? After all, London to Sydney is about as far as it gets, and it’s hard to come up with another pair of cities that couldn’t be connected nonstop.
Looking at the map, however, we do see a last unconquered frontier: Asia to South America. No airline has ever flown a nonstop between these two continents, and the biggest reason is distance.
The mileage between Tokyo and Sao Paulo — arguably the most likely market — is actually longer than London-Sydney. As are routes like Beijing-Sao Paulo and Shanghai-Buenos Aires.
Tokyo-Lima, another potential pairing, is about equal to the mileage between New York and Singapore, which as of 2026 is the longest flight in the world. It’s doable, but not by much.
Could the A350 ULR, or Boeing’s newest 777, close those gaps? Possibly, but technical hurdles are only part of what makes a route viable. You need enough passenger demand, at particular fares, to warrant the expenses of running such a flight. Just because a plane can fly nonstop from Tokyo to Sao Paulo, or from Shanghai to Buenos Aires, doesn’t mean it’s a smart idea.
For now, unless the Chinese become too envious and rush into something, Qantas and Project Sunrise will hold the crown.
Jerry’s Map is still going strong. For decades, Jerry Gretzinger has been creating a map made up of thousands of individual paper tiles that are created, revised and even painted over based on an arcane,… More
Tropical Storm Arthur’s white storm clouds cover the waters off the U.S. Gulf Coast. Some clouds extend inland over parts of Texas and Louisiana.
NASA Earth Observatory/Michala Garrison
White and purple areas of cloud off the Gulf Coast indicate the cooler areas of cloud tops associated with Tropical Storm Arthur.
NASA Earth Observatory/Michala Garrison
Tropical Storm Arthur’s white storm clouds cover the waters off the U.S. Gulf Coast. Some clouds extend inland over parts of Texas and Louisiana.
NASA Earth Observatory/Michala Garrison
White and purple areas of cloud off the Gulf Coast indicate the cooler areas of cloud tops associated with Tropical Storm Arthur.
NASA Earth Observatory/Michala Garrison
Natural color
brightness temperature
Images from the MODIS (Moderate Resolution Imaging Spectroradiometer) on NASA’s Terra satellite show Tropical Storm Arthur on the morning of June 17, 2026. The left image is natural color; the right shows infrared signals known as brightness temperature. NASA Earth Observatory images by Michala Garrison.
Tropical Storm Arthur, the first named storm of the 2026 Atlantic hurricane season, brought high winds and heavy rain to the U.S. Gulf Coast in mid-June.
NASA’s Terra satellite captured this natural-color image (left) at 10:30 a.m. Central Time (15:30 Universal Time) on June 17. The second image (right) depicts infrared signals known as brightness temperature, which help distinguish cooler cloud tops (white and purple) from the warmer surface below (yellow and orange). Around the time these images were acquired, the system had just recently been designated a tropical storm, according to the National Hurricane Center (NHC).
Though Arthur stayed below hurricane strength, it still delivered strong winds to parts of the Gulf Coast as it tracked northeast. The storm had maximum sustained winds of 40 miles (65 kilometers) per hour around the time these images were captured. Tropical-storm-force winds extended 175 miles (280 kilometers) from the storm’s center, the NHC reported. Measurements at Galveston, Texas, for instance, showed a gust of 48 miles per hour.
The storm also produced heavy rainfall that the National Weather Service warned could lead to life-threatening flash flooding. Estimates from IMERG (the Integrated Multi-Satellite Retrievals for GPM), a product of the GPM (Global Precipitation Measurement) mission, showed high rainfall rates over Gulf waters and extending inland on June 17.
As Arthur weakened and became less organized, it continued to bring abundant moisture to central Gulf Coast states on June 18. The National Weather Service reported rainfall rates of 3 inches (7.6 centimeters) per hour in southeastern Louisiana. Forecasts indicated that storm-total rainfall amounts could exceed 12 inches (30 centimeters) in areas, with some locations seeing totals approaching 20 inches (51 centimeters).
NASA Earth Observatory images by Michala Garrison, using MODIS data from NASA EOSDIS LANCE and GIBS/Worldview. Story by Kathryn Hansen.
I am a mathematician…and some of your recent comments on MR about the role of AI in Econ research as well as the (disappearing?) role of academic papers inspired this response. (It is partially but not exclusively about academia, so I hope it is ok that I’m sending it to your GMU address. Also, I’m hoping it doesn’t get flagged as spam because of the ai in the title…)
In no particular order:
-In the course of a math career, one accumulates lots of computational guesses, now one can test those with minimal effort.
-One also accumulates lots of incomplete and half formed drafts, proofs of special cases, etc, etc. Running those past claude and chatgpt can (does!) pay off. A lot of math is cleverly applying linear algebra and while I’m very good at linear algebra, I’m not as good at it as the AI’s are.
-The lower hanging fruit here are slightly off the beaten track, but not esoteric subjects. If you have a good overview of such, you can pretty quickly prod ai’s into making progress on them. (Before, you needed to have a school of grad students for that). Basic techniques (graph theory, algebra, calculus..) that ai’s are already good at can push these forward already. Making progress on truly hot topics is harder.
-There are some quite smart people trying to measure just how good autonomous ai’s are at math (e.g. the first batch project). That’s a fun game, but for practical purposes right now, what is relevant is how good an ai is when guided by a motivated human. I suspect we’ll see some remarkable things on that front in the next few years once math people really grok the good routines.
-For instance, getting claude and chatgpt to referee each other’s arguments is fun, and they genuinely have different insights on parts of the same problem.
-The kids will be all right. Right now, they are making pocket change doing ai training developed a better “feel” for the different ai’s that I probably ever will. And they learn things by asking the ai to explain an argument to them instead of trying to decipher a math book or paper.
-Which brings me to your papers point. I notice that a project informed with the right context is much more informative to me than the physical pdf of a math paper, and much easier to extract information out of by just asking the thing.
-Refereeing will look very different very soon. All the referee reports that have been collected by the journals should be valuable, hard to get data. And running all the accepted and published math papers through ai’s as the `control’ will end with quite a few people having egg on their face. It’s like self-driving cars, but there is no refereeing union.
-The last really big math revolution was all the stuff in the wake of Witten and 4-manifold stuff predicted by string theory in the early 90’s. This is going to be so much bigger than that. Buckle up.
Hi-ho, we’ve reached the moment, in this movie we’re all watching together on X, where model intelligence has become dangerous. Dario predicted years ago that it would happen this year. With Fable being (briefly) shut off by the USG, it’s the first highly visible sign that we’ve crossed into treacherous waters.
Which is too bad, really. I was hoping that we’d get a couple more generations of model upgrades, powerful enough to convince all remaining skeptics, before we got to one that was a security problem. But the Mythos class (Fable being the sloppily-guardrailed version they released last week) has everyone spooked.
Now that we know models are getting dangerous, we can do some extrapolating.
The AI race isn’t going to slow down, and AI will continue to grow exponentially in capability. Unfortunately, most of you aren’t going to see it progress anymore.
I am now in the camp who believe that we are only at most two or three model generations away from AI finally being controlled like nuclear weapons. Only a few will have access to superintelligence above the classes of models we’re seeing this year. As far as I can tell, most Fortune 500 companies will either not have access at all, or it will be tightly controlled for only a small subset of the company. And it will be supervised.
I think those with access to powerful frontier models will sell intelligence like a vending machine: You send them a software spec or a problem to solve, and their models implement it for you, on their servers, with your dollars. And since most companies aren’t going to want to send their code and problems to the model vendors, I think the world will learn to live with the models we do have access to.
Superintelligence Under Lock and Key
Every government will restrict access, acting on its own. Nuclear weapons are scarce because it’s hard to get enriched uranium. AI is going the same way, with the chokepoint being the supply chain — something governments can actually clamp down on. China will lock superintelligence inside its own borders as hard as the USG will. And if China ends up taking the frontier lead, it just changes where the power is concentrated, but not the overall shape of the world we’re going to be operating in.
A World of Mediocre Models
Many of us hoped OSS models would keep us on the exponential curve. They trail the frontier by roughly seven months. But they stay on that curve by training on compute which increasingly takes international-relations-level dealmaking to secure. Maybe distillation or some clever peer-to-peer training scheme keeps them in the race. But to push past Fable class they’d have to do it while the whole hardware-and-software supply chain gets locked down the way the nuclear chain was. And the frontier labs themselves are going to decline to help train the next dangerous open model.
If OSS hits Fable class next year anyway, that’s great for the world. But open models are not going to blow past Fable class, not with a huge compute wall and government lockdowns looming.
So again, today’s models are roughly as good as we’re going to get.
As disappointing as I find that in some ways, I find it still has a lot of upside to be happy about. Because today’s models, particularly Fable-class, are plenty good enough. They will still utterly transform coding and knowledge work. It’s just not going to be a walk in the park. It will take a big, multi-year effort to pivot.
I’m going to assume for the rest of this post that we will all get Fable back, and that we may even get one higher class of model before further advancements become inaccessible to all but a very few.
Many of you have been expecting the hockey-stick AI advancement curve to level out soon, refusing to believe that it’s truly on an exponential curve that could lead to it being so much smarter than humans. You predicted AI would not be able to replace human engineers.
In a way, you turned out to be right. A very practical way.
In reality, behind the scenes, the curve is NOT flattening at all; the exponential growth will continue, and you will be able to see outwardly observable signs of it, e.g. in data center growth.
But the curve will appear to flatten out for you, through two separate phenomena.
The first reason is the one we already mentioned: they’re going to keep the smartest (and thus dangerous) models out of our hands. So most of us never get a chance to try them out. And those models certainly won’t be replacing engineers, if we can’t use them.
The other reason’s kind of interesting, and it took me a while to see that it’s really the same reason wearing a different hat.
A World of Mediocre Users
Some people are already reporting they can’t tell the difference between Opus 4.8 and Fable 5. I’ve been calling this the “discernment horizon”: every human has a ceiling on model intelligence past which all the models start to feel about the same.
But there are actually two ceilings, both instructive lenses on what’s happening.
The first I’ll call the demand horizon. It’s set by the hardest problem you bring. If all you have handy are easy problems, they don’t give a smarter model any room to pull ahead — the outputs look the same because the problem never stretched either one. The demand horizon is where you can’t tell two models apart because you don’t have a hard enough problem.
I call my hard problems “back-pocket evals,” and I collect them. Whenever I give a project to a model, and it can’t do the project, I add it to my pocket-eval list. Then every time a new model drops, it’s like Christmas. I try it out on all my pocket evals and see which ones it can now solve.
Pocket Evals
Concrete example: No Opus-class model has been able to write the React client for my game; it’s just way too complicated and fiddly. Fable was absolutely smashing it. Easy way for me to see the difference vs. Opus. But I also have other problems that will prove too hard for Fable. I will collect them eagerly as it chomps through my work. All you need is ambition, and you can create your own pocket eval collection.
So my demand horizon is super high, and will last at least three or four more model generations, if I can manage to get access to that level of intelligence, which seems unlikely. I don’t have my hopes up. But at least I will be able to tell if it’s actually that smart, using my evals.
The demand horizon is benign enough, even kind of flattering: it just means your work isn’t hard enough right now. But bring an unusually hard problem one day, and your horizon widens on the spot, as you watch the cheaper model fumble some task the expensive one nails. Like my React client.
There is a darker horizon, which I think of as the discernment horizon proper. This one is set not by the hardest problem you can pose, but by the hardest answer you can judge. Past this scary line, you can’t tell whether the model is right, because checking the work is itself beyond you.
I’ve been chewing on this problem since my Drunken Rants days, when I’d write about how hard it is to interview someone smarter than you. How do you know they’re not a charlatan, if they’re professing expertise in an area you know nothing about? You can’t, really.
Everyone has a discernment horizon, even Dario. Past some level of capability there is no human alive who can verify the model output.
The Discernment Horizon
This takes us full circle to why they are starting to lock down the models. You can’t hand out an intelligence engine that nobody can supervise. It’s pointless to own because you won’t know if it’s helping you or walking you off a cliff. Superhuman means unverifiable.
So the safety people see a potential weapon, and the rest of us see a tool that we can’t effectively supervise. In both cases, you don’t need or want the more powerful model. You want the safer one, even if it’s less capable.
Companies also have both of these horizons. For plenty of companies, Fable is already past the demand horizon — every problem they’ve got, it handles, and a smarter model would change nothing they could measure. For the harder shops the binding limit is discernment: the AI produces work that nobody can grade. A terrible outcome, assuming you don’t want to surrender your business to AI entirely.
As a result of all this, the curve is flattening for most of us. I think commodity intelligence will soon stop growing exponentially, or at least, it will appear that way, and we’ll all operate as if it’s true.
I had never spent much time considering the possibility that the intelligence curve would flatten out. But now that it seems to be happening, let’s look at some of the clear and obvious implications for the industry.
SaaS is Back, Baby
It’s clearly going to be too expensive to rebuild all the SaaS at the top of the pyramid. Yes, there will be models that can do it, but access and cost will both be prohibitive.
SaaS actually came rocketing back over the past month all on its own, after spending much of the past year on the ropes, pummeled from all directions by threats of in-house rewrites and fears of Claude taking it all.
Then companies learned about token efficiency the hard way, with huge firms blowing their yearly budgets in months. A few months ago, everyone was planning to tell their CFO they could cancel a bunch of SaaS subscriptions and bring their dependencies in-house. No longer. Now the buy-vs-build decision is tilted heavily towards buy. If you despise your current SaaS enough, then sure, you may be motivated to rewrite it with AI. But buying SaaS has predictable costs that are usually already in the budget, whereas vibe-coding replacements could be an expensive gamble.
If we see a plateau in accessible model capabilities, then the other dreams we had about AI in SaaS fade too: not just replacing it, but transforming it with agentic behaviors and monitoring. Today’s models aren’t good enough to replace a person yet (jailbreakable, confusable, etc.), so you can’t just swap an agent in for an SRE or a trained customer service rep. And the models that could reliably replace humans may be too dangerous to give to most people.
So SaaS looks like it might be fine, even without agentic behaviors. It just needs to save you the money of building and maintaining it in-house.
SaaS still has its problems: users subsidizing the 80% of the features they don’t use, dollars extracted from local economies to enrich Silicon Valley, enshittification creeping up the pyramid. But it remains fundamentally about crystallization of knowledge. Groups of people build stuff that’s tricky, stuff you wouldn’t want to do yourself, and rent it to you. The AI models powerful enough to replace most of that “easily” will either be unavailable or prohibitively expensive.
It feels to me like the SaaS model is here to stay.
AI Literacy 101
Today’s models, while quite capable, are still very difficult to work with. Even Fable likely struggles with large monoliths and other complex legacy code arrangements. It’s hard to get a consistently high quality bar. And of course efficiency is a monstrous issue.
I’d been hoping for models that are smart enough that you don’t need much training to work with them. But with today’s models, you cannot expect people to be born AI-literate. They need help in order to use today’s coding agents and harnesses.
In the next section I will provide a fairly precise and measurable definition of AI literacy. I did not invent it, but I believe it is good enough for your planning, and mine.
First, though, why does it matter whether your employees are AI literate? The answer is a bit complicated, but it boils down to two factors. One is that your company will have to pivot to using AI. And the other is that all your employees are feeling anxious about AI. This tension is actively playing out at all companies around the globe.
Pivoting to AI will change everyone’s job at least a little, and probably change the shape of your company a lot. Which just feeds the anxiety, in a loop.
If you are pushing on change in your company without first having addressed AI literacy, in a quantitative but also deeply empathetic way, then you are fueling anxiety, resentment, and pushback. Your org will resist change.
AI adoption is the key culture challenge of 2026–2027. If you can manage to get your (hostile) employees past the hurdle, and genuinely get them excited about how they can use AI to accelerate themselves, then magic happens. They will automatically begin reshaping your business processes together towards using supervised agentic flows.
I’ve seen this happening all over, but concretely, Gene and I saw it at Arkana Labs in April under the guidance of their VP Eng, Owen Parker. Arkana offers world-class overnight kidney-disease diagnosis, and they have utterly unique business processes. But those processes can all be sped up here and there with AI. Given how obsessed Arkana is, culturally, with fast and accurate turnaround, the employees themselves are getting excited about the opportunities, and pushing hard on what might be possible with agents.
Having seen enough of this I maintain that once most people “get” AI, you just need to guide them, and they’ll start broadly doing the right things for your team.
Conversely, as long as your teammates remain non-AI-savvy, they will resist AI. Which means that until you can get your org over the hump, you’re facing resistance, anxiety, and potentially even morale issues.
So how do we fix it? How do we get people to “get” AI?
It turns out, Netflix has handed us the answer. Thank you, Netflix!
AI Literacy: Beginner Cohorts
Vibe Coding Workshops
I watched a mind-blowing presentation in April from Ezra Savard, who ran a training study/experiment at Netflix from December through March. He gave the presentation at Gene Kim’s AI Summit in San Jose. The study’s goal was to train Netflix engineers on agentic coding, and measure the impact.
Ezra’s presentation was all properly rigorous and disclaimed (e.g. for minor selection bias), but they felt pretty strongly about the results being directionally correct, so I’ll skip all that.
Note that I’ll be framing this as “AI literacy” but that’s my term, not Ezra’s, and he never mentions literacy in his talk. He talks about the journey from being non-users, to users, to power users. But AI is becoming a foundational skill for modern knowledge work, so I will make the case in this post that we are talking about a new form of literacy.
Ezra’s first big discovery to share is that they found three cohorts, which I’m calling the beginner levels of AI literacy. Ezra characterized the cohorts in terms of their average token spend on a “qualified” day using AI, meaning a day where they are using it heavily. They needed at least 3 days a week to be in the cohort.
Here are the three beginner cohorts they found, defined by spend:
0M tokens/day: devs who aren’t using coding agents for their regular work
4M tokens/day: using a single agent synchronously throughout the workday
12M-15M tokens/day: letting 2 to 4 agents work without watching
So: No agent, then single-agent, then multi-agent. I think this is a solid working definition of baseline AI literacy. If your entire org isn’t at least at single-agent literacy, then they will be fighting you on bringing in more AI, even if it’s just passive resistance.
Ezra shared that some power-user graduates of his course were legitimately spending much higher amounts, over 50M/day.
But he also cautioned that beyond the 15M/day mark, token spend is no longer a valuable measure, since people are by then clever enough to invent reasons to burn tokens. (After that, you switch to measuring outcomes, as I’ll discuss below.)
However, and this is the wonderful part, up to that point (15M tokens/day), measuring your employees’ token spend at a coarse level can provide powerful insight into where your organization stands on AI literacy, and how much training lies ahead of you.
Fortunately, Ezra has good news for you there: People can jump cohorts in 5 hours. That’s how long it takes people, in the right training setting, to graduate from AI illiteracy to AI savviness. And they stay there. It’s like flipping a switch. 96% of the trainees remained in the second cohort for six weeks after the course without showing signs of slowing down.
What’s the right training setup, you ask? Ezra’s team spent considerable effort honing the formula. The training must be done a team at a time, with 5 to 10 people, including their manager. The manager _must_ opt the team in, during regular work hours, as “blessed” company time. The trainees must bring their actual work, and the instructor(s) will help them learn how to do it with agents.
They found that if they cut corners anywhere — shorter classes, larger audiences, individual opt-in classes — they didn’t get the same results. It didn’t “stick.”
As for the third cohort: once a manager has a team full of single-agent users, they can opt their team into the multi-agent course. This is another 5 hours, and teaches them the additional skills needed to wrangle multiple asynchronous agents, while maintaining a high quality bar. This course saw the same strong adoption, with the vast majority jumping into multi-agent work and staying there.
So it takes roughly 5 hours of focused training per employee to get them to basic literacy. And after a few weeks of practice, another 5 hours to get them to become power users.
And as for impact, Ezra reported some surprising findings, such as there being a large difference in the amount of code produced by agentic coders. But when they dug in, they found it was entirely attributable to the additional test code they were writing. Overall, they found that the course had a large positive impact on productivity for those who attended.
If you want to start having conversations with your company about pivoting to AI, then I strongly recommend you begin with an AI literacy audit, followed by training everyone up at least into the single-agent cohort.
Advanced Cohorts
Getting people over the FUD hump, and teaching them to spend tokens to accelerate their own work, solves your first culture problem. And it will help you tremendously in your conversations about how to bring in AI, without getting so much pushback.
Netflix gave us an optimized solution to the FUD hump. You train up some “Line Cook” instructors who teach the intro course. Ezra told me and Gene that they had started with our book, which was kinda cool. But the exact curriculum barely matters; you can teach it however you like. And then you get everyone through it, 5 hours and ten people at a time.
Once you’ve taught everyone how to spend tokens, your second culture problem emerges, which is teaching people how NOT to spend tokens. Token efficiency is a fairly advanced topic. There are many, many ways that models can steer you wrong, and the most efficient agentic coders focus on maximizing their outcomes for a given token budget.
At this point I should share a joke made by Pierre Racz, the brilliant Founder/CEO of Genetec, one of the world’s largest physical-security monitoring companies. He prefers to write his code by hand, and when I described how these measurements work, he observed wryly, “Well then it’s not that I’m not using AI, I’m just extremely token-efficient.”
And it’s a funny joke, but there’s an underlying lesson there too, which is that if you can trivially do a task by hand, then do it by hand! Over time, you can save a bunch of tokens just by being thoughtful. Type !git push instead of asking the agent to do it, and your habit probably saves you 100k tokens on average, each time you push.
You know the meme with the bell curve and the troglodyte at the bottom and the Jedi at the top, and they’re doing the same thing? Well here the beginner-thing that the Jedi masters is low token spend.
The journey from beginner to master
Token spend only signals literacy on the way up. It’s a skill you build. But then it flips, and the thing you need to start measuring is token waste. Minimizing that is another set of skills.
You will find that your beginner cohorts are absolute token pigs, and that’s OK. Encourage them to explore and learn. They need to master the skill of spending before they can focus on savings.
You will find that people don’t automatically know how to conserve tokens. They will be 200k tokens deep into a conversation and ask the AI what time it is. Argh! Or maybe whether a specific file exists in their home directory. This is a skill that needs training, too.
So at some point you will probably want to have a third training course, this one on efficiency techniques and good token hygiene.
Then, give your newly AI-savvy people budgets. Make them earn budget increases with real outcomes. However you do it, measuring outcomes is going to become critically important, so you can differentiate your effective builders from your vanity builders.
We’ve talked about the beginner literacy cohorts (spend-based), and the advanced cohorts (efficiency, waste management). At the top of the AI literacy curve, your thinking becomes more strategic. You worry about saving large numbers of tokens while achieving your desired outcomes.
The first example everyone hits is buy vs build. Will you let your engineers try to rewrite random SaaS, or will you just re-up and go with the known spend? You have to start being strategic with agentic project allocation.
Another interesting challenge you face: How will you route every task to the dumbest model that can handle it? You will need to be able to tag work with intelligence tiers, and build a router. That router is the discernment horizon encoded as infrastructure. Most work sits below the line and goes to the cheap model, and the occasional task that pokes above it gets escalated to the expensive tier.
At the highest levels, AI literacy turns into the art of achieving great outcomes with the least spend.
A Craft Needs a Plateau
We are seeing a plateau in intelligence. It is artificial: the exponential increase continues behind the scenes, gated away from you. And at some point you won’t be able to tell it’s getting better, even if you could see it. The intelligence curve is as real as the Earth is round, but just as flat from where you stand. Welcome to the Flat Curve Society.
The Mythos graduating class will become the accepted trade-off between capability and risk for the general public. And we will see incremental updates that patch edge-case behavior, but nothing like the jumps we have enjoyed for the past several years.
The plateau is not a bad thing. A plateau lets us set up a camp and start building. We’ve been on unstable ground. Think how hard it has been lately to be a startup founder, with everything you build being obsoleted with each model release. That’s finally slowing down now, and it will give us firm footing.
We have an engineering problem ahead of us. As good as Opus and Fable are, they have their limits. We all need to learn the art of task decomposition and breaking up software monoliths, to keep them within those limits. We will still need engineers, and engineering. We’ll have super smart helpers, but it will still be pretty similar to the landscape today.
I kind of like the plateau that’s coming. Stability feels like a precondition for the new craft of building software with these super smart helpers. It is a craft that only gets harder, and more valuable, the weaker your models are. Sonnet-class and Opus-class will stay relevant for years, because they save money and stay broadly available even after the frontier moves on. The models that would obsolete today’s hard-won techniques of the craft are evidently too dangerous to give to us anyway.
The world is currently tinkering with setting up 24x7 autonomous agents, and it looks like the difficulties we face there today will remain with us tomorrow. There is a large engineering effort underway to build the control plane(s) that allows today’s models to run today’s large businesses. That, too, is a craft, or at least, it’s part of the tools of the trade.
Train Your Flat-Curvers
The key takeaway here (beyond not committing seppuku just yet if you’re a SaaS vendor) is that we have a massive AI training and literacy problem ahead of us. But it’s solvable. It will just take time and effort.
The models we have today, and the ones coming this year, will not one-shot your entire Fortune 100 code base. They are capable of amazing things, but they will still require grown-up human supervision.
This means you’ll need engineers. All the cool things that we’ve talked about — with impromptu 2-pizza teams forming, 2- to 3-person teams being a sweet spot, and roles starting to blur together (or at least talk to each other more) — will likely continue. But everyone will need training and time and patience and careful budget management.
AI Literacy does not come for free. The only thing you get for free is AI Anxiety. But it’s fairly easy to teach people to spend tokens. Teaching them to save tokens? Well, that’s the new meta. Good luck. Make sure they can do it Pierre’s way first.
That’s all I had for today’s post. Hope you enjoyed it. See you at the AI Engineer Conference in San Francisco at the end of the month!
On Sept. 10, Katie Porter was polling as the No. 1 candidate for California governor at 17.4 percent. Now, she has only garnered 4.4 percent of the primary vote and has conceded the race.
What really shot Porter to a solid level of stardom were the props she used during House hearings. In one particular instance, she challenged Wells Fargo CEO Tim Sloan’s assertion that his bank would rebuild trust with consumers by whipping out a whiteboard and showing that his own lawyers contradicted that statement.
Tim Sloan resigned two weeks later. Porter had won that battle. It was exactly what she went to Washington to do. It gave her national recognition and proved, in a way, that a representative from Orange County didn’t have to cozy up to moderates and Republicans. She wanted to challenge the wealthy and affluent, and it didn’t cost her the seat.
But this candidacy didn’t have the same fire or verve that Porter became associated with. Through conversations with political insiders, political science scholars and research, The Truth OC has developed multiple reasons that the Porter campaign ultimately fell from grace.
The money
Flat out, Porter did not have the same war chest afforded to Xavier Becerra and Tom Steyer, the two leading Democrats in the race. Steyer is a self funded billionaire — who was able to put advertisements on seemingly every TV channel and YouTube video in the state via $213 million — and Becerra had corporate donors backing groups supporting him.1
But Porter was never going to be the candidate who took money from special interests. She built her career on standing up to Wall Street bullies. A bigger problem was that she didn’t have the ability to crowd fund well enough to battle in the upper echelon of this race. While she has over 210k followers on Instagram, her posts on there rarely sparked attention in the same way that Steyer or Becerra’s advertisements could. Even if she was a social media star, though, it may not have been enough to compete monetarily.
Data shows that the average winner for a House or Senate seat in 2022 spent essentially double what their opponents did. California currently has a ban on public funding in elections (although this will be put to a vote in November).
This statute gets very messy and confusing, but know that it hurt Porter a lot. Look to New York City. Their publicly funded structure means that grassroots donors, those giving under $250 to a candidate, will have their donation matched by the city. The city also matches donations between $10-$50 at a higher ratio. It is meant to incentivize candidates moving away from taking special interest money, and instead they can focus on the community which will be their constituents.
NYC’s structure is what allowed Zohran Mamdani to win the mayorship. He was able to stick to his morals and focus on his ideas for the betterment of the city, and it resonated with everyday people. He had enough money through this system to win. But in California, that just doesn’t exist currently.
If Porter had access to this system, and also if there was an overall cap on campaign spending, she could have reached voters more directly. Her message could have risen above the money, because she was a good candidate. But as the election went on, and Steyer and Becerra entered the race, it became harder to keep up. That wasn’t the only issue that plagued Porter, however.
The videos
Early October was tough for the Porter campaign. Although she maintained a lead in the polls until January, two videos surfaced that gave Porter an image that was hard to shake the entire campaign.
The first showed Porter having a rough exchange with a CBS News reporter. It painted the image of an abrasive and annoying person. But the second is what killed a lot of trust with the general public.
Politico obtained the video, which showed Porter — when she was a US representative — yelling at a staffer to “get out of her fucking shot”. In any election, leaders have to come off as somebody that you can work with. Talking with a friend a month before the election, he told me that when he saw that video he immediately had no desire to vote for Porter. If you aren’t nice to the people closest to you, then how can constituents trust you to have their best interests in mind?
From then on, Porter was on the defensive. She had to rebuild her reputation, but it is hard to get past damning evidence such as that. Chapman University political science professor John Compton said the idea of Porter’s workplace being toxic was not a new one.
“The videos seemed to reinforce past allegations from staffers that Porter was a volatile boss and that her Hill office was a toxic workplace,” he said. “There was a major Washington Post story on this back in 2023 that featured anonymous allegations from eight former staffers. I don’t think the videos necessarily doomed her campaign, but they seem to have started her downhill slide.”
Not for nothing, dozens of former staffers defended Porter in an open letter saying that she always shows up for her team. This came after Eric Swalwell dropped from the race but it came too late to rebuild enough goodwill for Porter.
These videos created a perception of Porter as, simply put, an asshole. Whether that is fair or not is beside the point, and this image was almost certainly made worse because of Porter’s gender.
Her gender
There has never been a female governor of California. Compton believes that comes down to a lack of enough strong female candidates rather than voter sentiment, saying that if Kamala Harris ran for governor she would’ve won. A political insider who only spoke on background said that many people just aren’t willing to vote for a woman.
However you spin it, though, there is a consistent underlying perception that surrounds female candidates. It plagued Hillary Clinton and Kamala Harris in the presidential elections. It plagued women like Amy Klobuchar or even AOC to some extent. They have to be perfect when campaigning. Put on even one slightly sour face in front of the cameras, and it will kill you more than it will kill a man. Yell at a staffer, and your campaign might be over right then.
This has never been more true than it is today, when the president has a history of doing much worse than cursing out somebody on his campaign staff. Donald Trump can grab women by their genitals, or at least allude to it, and he’s fine. He can be heavily linked to Jeffery Epstein, and he’s fine.
There is simply a double standard. When a female candidate makes a mistake it’s amplified. That may not have been the only/main reason that Porter’s campaign failed, but it is worth mentioning. In the public eye, combative women don’t come off as powerful and great leaders. They get seen as irritating and rude.
The candidates
From the jump, there was never a candidate in the Democratic party that wowed voters. Nobody got them juiced and excited. Hell, most voters held their ballots until the final days just to make sure two Republicans didn’t make it to the general election. By that point, Porter simply didn’t have the umph to be voted in. Even if people saw her as the strongest candidate, she wasn’t the most viable. Becerra and Steyer had a much better chance of making it through, and so people bit the bullet.
California’s jungle primary system means that the state’s Democratic Party often eats its best and brightest candidates in favor of more presentable candidates. Those who can have as wide of an appeal as possible. Porter found herself in-between two camps. She has never been a moderate. She is the woman who fought Wall Street with a whiteboard. But she has never been as progressive as somebody like Tom Steyer. Hailing from Orange County — an area far away from being representative of the general California public — she has had to toe the line between moderate and progressive often.
When Swalwell dropped out after sexual assault allegations emerged, Porter should have filled the void immediately. But she never did anything with enough force. Porter didn’t address the ICE raids strongly, didn’t reach out to the communities around her (such as Santa Ana). She didn’t have boots on the ground in a meaningful way. Immigration is the issue of our time in California, and Porter missed a chance to garner support by giving a human touch to people in need.
The fact remains that in a jungle primary system, when you lose viability as a candidate it is very hard to win it back. Compton categorized her failures as representative of voters’ worries rather than her being a terrible candidate.
“On paper, (Becerra’s) resume is more impressive than Porter’s, given that he has served in Congress, served as attorney general, and held a cabinet post in the Biden Administration. I do think Porter was a viable candidate — as you point out, she was leading in the polls at one point. However, I think the weirdness of the jungle primary system, coupled with Eric Swalwell’s flame out, left Democratic voters in a risk-averse mood, which is why a majority of them went for Becerra.”
What’s next for Porter will be interesting. Failed bids at both a Senate seat and at the governorship have placed her on the back foot, but it seems unlikely that she fades away. And maybe if Californian voters allow for public financing of elections, and she can shake off the abrasive image surrounding her, then she can make a strong challenge at any office she desires.
Caleb Otte is a recent Chapman University grad and one helluva writer. One can visit his substack here.
Via CalMatters, “Chevron, McDonald’s, dialysis giant DaVita and one of the state’s largest oil drillers, California Resources Corp., are funding one of the largest pro-Becerra groups, with each of them contributing $500,000. Meta and AirBnB chipped in about $1 million each and health insurance corporation Centene, which runs California-based HealthNet, put in $100,000.”
A senior U.S. official read the text of the fourteen-point memorandum of understanding with Iran over the phone to reporters today, and there’s a reason it has ignited a firestorm.
A memorandum of understanding is usually a nonbinding agreement outlining shared goals and intentions, but in this case, although there is much vague or confusing language in the text, what the White House says is an MOU actually has firm language in it.
First of all, after months of the White House insisting Trump does not need congressional approval for his strikes against Iran because they did not constitute a war, the MOU straight up calls the conflict “the current war.”
The MOU commits the U.S. and Iran “and their allies” to stop military operations “on all fronts, including in Lebanon,” a reference to Israel’s bombing of what it says are Hezbollah camps there. Israel has suggested it will not consider itself bound by any such agreement, but as Anton Troianvoski points out in the New York Times, the language will enable Iran to pressure the U.S. over Israeli attacks in Lebanon or Israel’s occupation of southern Lebanon in what Israel calls a “security zone.”
The MOU says the U.S. will “terminate all types of sanctions” against Iran, and it lifts the U.S. blockade of Iranian ports, giving Iran the access to world trade the U.S. previously prevented in order to pressure the regime. It also permits Iran to begin selling oil immediately on the world market.
The MOU says Iran will use “its best efforts”—not a guarantee—“for the safe passage of commercial vessels” through the Strait of Hormuz “with no charge for 60 days only.” It continues: Iran and Oman will decide how to “define the future administration and maritime services in the Strait of Hormuz,” an indication that Iran intends to charge fees for transit of the strait.
The MOU says the U.S. will thaw frozen Iranian assets immediately and also “develop a definitive, mutually agreed plan with at least $300 billion for the reconstruction and economic development” of Iran to repair the damage from U.S. and Israeli strikes. It says the U.S. will grant “[a]ll required licenses, waivers, and permissions needed for the relevant financial transactions,” apparently readmitting Iran to full participation in world financial markets.
In exchange for these concessions, Iran “reaffirms” in the MOU that it will not try to develop or procure a nuclear weapon. That word “reaffirms” is important: it signals that Iran is simply reiterating what it said in the 2015 Joint Comprehensive Plan of Action (JCPOA) that Trump tore up in 2018.
But, unlike the JCPOA, the MOU contains no language about a process to guarantee Iran’s promise not to pursue a nuclear weapon. When a reporter asked Trump about that absence, he said that what would guarantee Iran’s compliance is fear of renewed U.S. bombing. But Iran has shown it can withstand such attacks, and in any case, the U.S. has no stomach for them.
It looks as if Trump’s war on Iran has cost the U.S. the lives of thirteen service members, injuries to 400 more, and at least $132 billion so far in immediate costs, lost income, and higher consumer costs, only to leave the U.S. in a significantly worse place with regard to Iran than before Trump started bombing.
The costs to the world have been significantly higher in terms both of lives—beginning with more than 175 Iranian schoolchildren and their teachers—and of economies.
Journalist David Shuster reported that the Iranian government is declaring “total victory.”
Former secretary of state Antony Blinken posted: “By President Trump’s own terms, the war is a failure. The Iranian regime is intact and its military wing more empowered, while the Iranian people are more impoverished, repressed and desperate…. The only ‘achievement’ of the ceasefire is the likely re-opening [of] the Strait of Hormuz—which was open before the war started. And we will apparently pay Iran to do so…. Don’t expect a return to normal any time soon, if at all,” he warned.
In a press opportunity today in France, where he was attending the Group of Seven (G7) conference, an informal forum of industrialized democracies, Trump twice told reporters that he didn’t want to be like President Herbert Hoover. Although he got the history of Hoover’s role in the Great Depression wrong, Trump’s point seemed clear: he didn’t want to be the person to trigger an “economic catastrophe.”
And therein lay the rub for Trump in his war on Iran: so long as Iranian leaders could credibly threaten the passage of ships through the Strait of Hormuz, they could throttle about a fifth of the world’s oil supply and much of its fertilizer, plunging the globe into crisis. The terms of the MOU heavily favor Iran, but the strait gives its leaders leverage over Trump and the U.S. This was precisely the scenario that past U.S. presidents sought to avoid by negotiating with Iran rather than bombing it.
Selling the MOU in the U.S. is going to be rough. When a reporter asked Trump today why he didn’t “stick around for the signing ceremony with this Iran peace deal,” the famously camera-courting president answered: “I might, but I’d rather, this is a memorandum of understanding. It’s very important, but it might not be the kind of a document that I should be signing.” The reporter responded: “There is some element to this where you send the vice president. If it works out, great. You look like a genius for sending him. If it doesn’t work out, it’s the vice president’s fault.”
Trump responded: “I like that idea…. This way, if it works out, I’m gonna take the credit; if it doesn’t work out, I’m blaming J.D. You better be careful, J.D. He’s gonna turn his plane around and get the hell outta here. Yeah, I like that idea. I think that’s a good idea.”
MAGA lawmakers like Senator Tommy Tuberville (R-AL) seemed willing to go along with the measure, saying: “I trust President Trump. I trust Vice President Vance. We don’t need to listen to anybody up here on Capitol Hill. Let’s trust these two.” But John Knefel of Media Matters reported that MAGA figures who have been all-in on the war on Iran are revolting against the MOU. “Trump’s Iran deal gives the Islamic Republic big wins upfront—and America nothing,” wrote the New York Post.
Journalist David Shuster reported that Republican senators are furious with Trump. Senator Bill Cassidy (R-LA), who lost his primary to a Trump-backed challenger a month ago, posted: “Reagan is rolling over in his grave. Iran’s nuclear ambitions were not curbed, and they have learned that threatening the Strait of Hormuz works and will undoubtedly leverage it in the future. Now, Iran gets to build brand-new infrastructure under this deal.
“Before the war, the strait was open, Iran was being crushed by sanctions, and 13 service members were still alive. Now, 13 Americans are dead, families have paid billions at the pump, sanctions will be lifted, and the bombing has stopped. This is the worst foreign policy blunder in decades.”
By tonight, Trump loyalist Senator Roger Marshall (R-KS) was defending the idea of Iran having missiles, despite the fact that ending Iran’s missile program was one of Trump’s stated reasons for starting the war in the first place. Marshall told CNN’s Kaitlan Collins that he preferred that they not have missiles, but that “the key issue” is that “they have to be able to defend themselves.”
National security scholar Joseph Stieb posted: “It’s like the last 40 years of the Republican Party’s foreign policy didn’t happen.”
After setting Vance up to take the fall for the deal, tonight at a dinner with French president Emmanuel Macron at the Palace of Versailles, Trump signed the MOU himself. It was a moment when a knowledge of history would have been useful. As MeidasTouch noted, it was at Versailles after World War I that the Allied powers forced Germany to sign the Treaty of Versailles, “one of the most famous surrender documents in modern history.”
Earlier in the day, asked by a MeidasTouch reporter about Trump’s cognitive decline at the G7, Senator Jon Ossoff (D-GA) said: “The president has been humiliated on the world stage, and many Americans are increasingly concerned about his stability and his capacity in the office. It’s deeply distressing to Americans across the political spectrum to see a president so incompetent and so incapable attempting and failing to represent the nation internationally.”
Over a GIF of James Bond saying, “He’s quite mad, you know,” national security scholar Tom Nichols called today “the weirdest and most astonishing day in US foreign policy in decades.”
My hope for retirement was to get a lot of work done on
NetNewsWire.
A year ago it was in sore need of modernization, tech debt
pay-off, and bug fixes. People were asking for features, but the
foundation needed a ton of work before I could get on to adding
new rooms.
Here are some highlights of what we’ve done with 2,188 commits in
the past year.
NetNewsWire was already one of my favorite, most-used, most indispensable apps. Now it’s much better and improving steadily at a rapid clip. You love to see it.
In November, Cursor said it crossed $1 billion in annualized
revenue, according to a release at the time. Cursor was also
ranked at No. 37 on the annual CNBC Disruptor 50 list in 2026. The
$60 billion in class A common stock that SpaceX has agreed to pay
to acquire Cursor represented a 3.4% dilution at the aerospace and
tech conglomerate’s IPO valuation.
Shares of SpaceX gained roughly 16% on Tuesday, topping Amazon and
Microsoft by market cap and making it the fourth most valuable
company in the U.S.
SpaceX is an amazing company but this valuation is insane. The idea that it’s even close to as valuable as Microsoft or Amazon is bananas. SpaceX still isn’t even profitable, so its price-to-earnings ratio is literally infinity. It’s halfway through Thursday as I post this and SpaceX is down ~10 percent on the day, so a touch of sanity is being restored, at least at the moment.
Cursor, with $1 billion in sales, certainly isn’t worth 60× revenue — especially in a business where it too isn’t profitable. But who cares when you’re paying with funny-money stock?
Rolfe Winkler, reporting for The Wall Street Journal (gift link):
Apple plans to raise prices on its products to offset the surging
costs of memory and storage chips, Chief Executive Tim Cook said
in an exclusive interview with The Wall Street Journal.
“Unfortunately, price increases are unavoidable,” he said. “We’re
doing our best to mitigate the huge increases that are being
passed to us, and we’ve been trying to shield our customers from
the increases, but the situation has become unsustainable.”
Cook declined to offer details on the timing or scale of the
planned price increases, nor which products would be affected.
Apple’s next major product launch is likely to be in September
when it releases the iPhone 18 lineup, expected to include a new
foldable iPhone. [...]
Cook said Apple wouldn’t use its cash and silicon expertise to
build its own memory and storage factories. “We can’t do
everything,” said Cook. “We know what we’re good at.” [...] Cook
said during his time working in the electronics supply chain, from
IBM to Compaq to Apple, he had never seen a commodity price swing
like the one from the past six months. “This is a hundred-year
flood,” said Cook. “I’ve never seen anything like it in any area
in over 40 years.”
Apple, to my recollection, has never before issued a warning about price increases. Keep in mind that Apple deals with prices in a very different way from its competitors. For Apple, prices are part of a product’s brand, so they don’t fluctuate with component costs. The trash can Mac Pro held its $3000 starting price for six years, despite its specs remaining effectively unchanged in that span.
So when Apple raises prices on the iPhone 18 Pro models this September (and, presumably, launches the folding iPhone “Ultra” with an eye-watering price), expect those prices to stick. And if Apple expects RAM and SSD component pricing to continue rising through 2027 — which is what many anticipate — they might build that into the pricing now. Raise prices by (say) $200 now rather than $100 this year and another $100 next year.
Also, credit to Tim Cook for taking this one personally, months ahead of the iPhone 18 launch, rather than leaving it to John Ternus to serve up a surprise shit sandwich in his first keynote as CEO.
We seem to be in one of those very MAGA interludes in which members of Donald Trump’s base are not so much rebelling as in a process of mourning. They are struggling to find a path to discovering that up turns out to be down, or that the things that they have always professed to care about do not matter because Trump has announced they do not matter. Lindsey Graham seems to be maybe 3/4s through the process. Ted Cruz is working on it. But some of his supporters, especially a number of those who aren’t in elective politics are having a harder time, at least for now. The dynamic, the level of shock is very straightforward. Most of MAGAworld has gone along with the premise that the war in Iran, or Trump’s management of it, has actually been going great all along. Trump is underestimated, the Lamestream media, etcetera. Wait to see the final deal. Trump won’t let Iran get away with anything.
A lot of these folks are now coming into contact with the reality of the situation, from zero to 60 in two or three seconds. It’s pretty jarring. The deal as structured, from what I can tell at least, contains more or less exactly the details that Iranian state media has been reporting for weeks and which the White House claimed was IRGC propaganda. Maybe the U.S. isn’t contributing to the $300 billion Iran rebuilding fund. But it’s overseeing and guaranteeing its creation. So it’s a fairly minor distinction. There are also some odd signals from within the White House that they might pull the plug on the whole thing. For instance, JD Vance agreed with Megyn Kelly that the deal could be scrapped if Trump’s supporters had an “utter meltdown.” Trump has hinted that he might scrap the deal too but has mainly focused on attacking those who are pointing out that the emperor has no clothes, perhaps not even an agreement.
Imagine a universe in which anyone but Trump was president and he ended a war which promised regime change, denuclearization and an end to Iran’s proxies and missile program by making a peace deal focused on Iran getting a $300 billion redevelopment grant. Multiple Trump surrogates, including Vance, are now defending the lack of limits on Iran’s missile program by arguing that Iran has a right to be able to defend itself. That’s true of course. That’s the nature of what a state is. But it’s not a very good argument for a regime you said four months ago was a danger to the world and had to cease to exist.
I’ve seen a number of foreign policy hands arguing that Trump could have had this deal without going to war at all. That is accurate as far as it goes. But it’s also an example of how D.C. foreign policy analysts can be disinclined or ill-equipped to capture the true enormity of some global pratfalls. As I noted earlier this week, my own sense is that neither the nuclear deal or the cash payments ever happen; and that both sides know this. These are just chatter to build domestic support. But if we take the deal on its face, do we think that Iran in January would have accepted a robust Marshall Plan for itself in exchange for the pre-war status quo and a de facto, if not a de jure, right to close off oil and gas shipments out of the Persian Gulf at will? Hard to imagine why they wouldn’t agree to that, right?
Trump in a way gave away the game when he said that he’s signing this deal to avoid an “economic catastrophe.” That’s at least closer to the truth: I had no choice. I had to pull the plug. Of course it’s probably an “economic” or rather a political catastrophe for him more than the country, at least in terms of how he sees it. But there you are at least getting to the heart of the matter. Of course that “catastrophe” is entirely the result of the war which he didn’t have to launch in the first place.
There’s a perfectly good chance that Trump will end up pulling the plug on this deal because of the extent of domestic opposition, especially from within the GOP. That would represent a continuation of the cycle going back to February: Trump wants out but is unwilling to undergo either the psychic or coalitional costs of doing so. More likely though is that it will go as planned: the war stops, something both sides need though for very different reasons, and most of the money and the nuclear stuff never happens.
The DOJ is attempting to strip a Somalia-born Minneapolis man of his citizenship, citing actions he took after he became a citizen. To do so, it’s relying solely on a McCarthy-era law. Its a first, experts told Josh Kovensky.
TPM is the first outlet to note the DOJ’s novel use of the 1952 law, alone, for this purpose — to denaturalize someone who had already become a citizen. Read our story here.
Verizon has sprung for a new ad campaign set in the Austin Powers world, with four stars from the cast — Mike Myers, of course, as Dr. Evil; Rob Lowe as Number Two (Robert Wagner is alive but is 96); Seth Green as Evil’s son Scott, and Mindy Sterling as Frau Farbissina — and director Jay Roach. The premise of the two-minute spot is that Dr. Evil is proposing “Menace Mobile”, a wireless carrier with confusing pricing and plans. Scott pooh-poohs the idea on the grounds that “This isn’t evil. This is just typical phone company stuff.” Then, after some back-and-forth, comes this exchange:
Scott: Diabolical phone companies are why we’re all switching to
Verizon.
Dr. Evil: I thought Verizon was just like the rest of the wireless
organizations.
Scott: Well, they were, but not anymore. They just got rid of
activation and upgrade fees. They’re changing everything.
I don’t think the commercial is particularly funny, alas, but I do find it extraordinary, because of the exchange quoted above. “Well, they were, but not anymore” is one the most extraordinary lines I’ve heard in a commercial. They’re just flat out admitting that, until recently, they ran their business like a scheme from Dr. Evil.
I’ve been on Verizon for a long time. It’s expensive, but so was AT&T, and I’ve always felt like I got better service and better coverage from Verizon (which is why I switched in the first place). But just last year I did the wrong thing when I bought my iPhone 17 Pro. I should have bought it unlocked, but instead I bought it as a device upgrade tied to my Verizon account, and the bastards nicked me for a $30 upgrade fee. I’d like to think that will never happen again because they’re actually dropping all of their bullshit fees, but I’ll believe it when I see it.
Austin Powers, by the way, came out in 1997. In the film, Powers was frozen since 1967. That means next year, we’ll be as far removed from the debut of the movie as unfrozen Austin Powers was from the groovy 60s in the film.
Usually when I link to a new app, it’s something that I find useful personally. Cotypist is something else. It’s an AI-powered autocomplete utility for the Mac, using on-device models and processing, by developer Daniel Gräfe of Accelerated Thought. It is very well-designed, and remarkably Mac-assed (right down to where it stores its local data and AI models). It respects your privacy and all the best conventions of MacOS. Cotypist suggests a few words ahead of your insertion point at a time, and you can accept them by hitting Tab; if you want to ignore them, you just keep typing. The autocomplete suggestions appear inline, in whatever app you’re typing in, using your current font. I wasn’t even aware that was possible, but it is via MacOS’s rich accessibility APIs. Cotypist’s suggestions are eerily good. It’s even got a great name.
Personally, I can’t stand using it.
For me, it’s actually worse that the suggestions are so good, and so often on-point for what I intend to write. That’s why I can’t stand it. It’s like having a voice in my ear whispering my own thoughts before I think them. But are they my thoughts, or are they just close to my thoughts? They’re so close I can’t tell. And thus the experience of seeing these words appear before I’ve typed them feels more like a curse than a blessing, and a never-ending distraction. I’d find Cotypist far less distracting if its suggestions weren’t as good — but in that case it wouldn’t be nearly as interesting or useful, and I wouldn’t be writing about it at all.
But I’m a writer. I enjoy writing. Writing is probably the most satisfying and fulfilling thing I do in life. I enjoy picking every word as I get to it. I find a blinking insertion point in the middle of a good but half-written sentence to be thrilling. But you might feel otherwise. Perhaps you find all writing to be a laborious chore, like washing dishes. Or you might have a job that requires answering a lot of repetitive emails. I’ve done email technical support in the past, and I would have killed for Cotypist then. I would imagine Cotypist is simply marvelous for someone who writes English as a second language.
It’s absolutely worth trying if you think you might want to use it, and probably worth trying just to see it in action even if, like me, you don’t want something like this. Trying it out might change your mind. There’s a free tier for casual use (100 completed words per day), and Plus and Pro paid tiers for $6 and $9 per month. New installations get a 30-day free trial of the Pro tier.
Later this summer, Apple will unify the email domains used by Sign
in with Apple and iCloud+ Hide My Email under a single, shared
domain: private.icloud.com.
New addresses generated for both features will be issued on the
new domain. For example:
Sign in with Apple addresses, previously issued on
privaterelay.appleid.com, will be issued on
private.icloud.com.
iCloud+ Hide My Email addresses, previously issued on
icloud.com, will be issued on private.icloud.com.
Existing addresses on the legacy domains will continue to work and
forward mail to users without interruption.
Initial reaction to this change is that it might render “Hide My Email” ineffective, because shitbird services will simply ban the domain, trying to force you to use your primary email address. It seems inevitable that some number of services will do this. But my retort is that a service that won’t accept these email addresses is one that I probably don’t want to have anything to do with. The only reason not to accept private.icloud.com email addresses is if you want to do something invasive with users’ actual email addresses.
As part of his round of media appearances JD Vance was asked today about critics of Donald Trump’s Iran deal in the Israeli government. He said …
Donald J. Trump is the only head of state in the entire world who is sympathetic to the nation of Israel at this moment in time. If I was in the cabinet of the Israeli government, I might not be attacking the only powerful ally that I have anywhere left in the entire world.
Just on the facts it’s pretty hard to disagree. This is not only an example of how fast things can change for you in Trumpworld. It is also a perfect illustration of how your own loyalism, your own Trumpiness almost always gets wheeled around and used against it as soon as you zig when you were supposed to zag. Prime Minister Benjamin Netanyahu has left Israel marvelously exposed and isolated. And he seems increasingly likely to pay the price for that in October.
And what is Israel going to do now? Leverage its relationships with Democrats to push back against Trump’s diktats? Good luck with that.
For decades, it was central to Israeli geopolitical and security doctrines that it needed to maintain strong ties with both dominant political parties in the United States. Needless to say that has changed pretty dramatically.
Let me sound one discordant note. There’s a decent argument that the Trump-Netanyahu alliance isn’t really matter of personalities. It’s the inevitable result of the increasingly rightist/authoritarian bent of Israeli politics and the growth of authoritarianism within the American Republican Party. There’s real truth to that. But Netanyahu leaned into that in ways that transcend those structural realities. He made his primary interlocutor in the U.S.-Israel bilateral relationship a former GOP Republican operative, under Republican and Democratic administrations. In the most noteworthy example, he connived with House Republicans not only to meddle in U.S. domestic politics but to gratuitous insult and humiliate the then-President, Barack Obama. In those and countless other ways, he’s made Israel as a political and geopolitical force into a sidecar of the Republican Party.
As I and many others noted at the time, young Americans love President Obama (that was certainly true in 2015). They are different ideologically and demographically than previous generations of Americans. You are providing a lesson to a generation of young Americans who will now see Israel through the prism of this gratuitous insult to a beloved, Black president. Now you have a generation of Americans who see Israel almost entirely through the prism of that snub, Gaza and the country’s general role as Donald Trump’s best friend.
And here we are. Trump and Vance are both now saying to Netanyahu and really the whole country: don’t fuck with us. We’re all you’ve got. And they’re mostly right.
I wanted to zero in on something that was mentioned mostly in passing in the latest set of filings from the former Broadview Six defendants. The DOJ, through the Chicago U.S. Attorney’s office, told the defense on June 5 that they would not contest the defendants petition that Judge April Perry rule that the government must reimburse the defendants’ legal expenses. (David mentioned this yesterday in Morning Memo.) It’s true that this agreement in principle leaves undetermined an exact dollar amount that the defendants would be reimbursed. But it’s difficult to overstate how rare it is for the government ever to agree to reimburse defendants’ legal fees or how unheard of it for defendants to succeed in these requests, even though there is a law — the 1977 Hyde Amendment — that provides for it.
The conclusion here is clear: it seems likely that something really, really bad went on here that goes far beyond what was contained in the already released grand jury transcripts. What the government is doing here is trying to cut off the defense’s argument for discovery. They need to know more facts to convince the judge to order the government to pay the fees. This is what the government has done at every point at which the judge has given them the choice between saying what they did and facing a sanction or repercussion of some sort. It certainly sounds like the defense elected not to take the government up on its offer. Otherwise we wouldn’t still be doing filings. This would be over. That’s good. We need to know everything that happened because it seems likely that it goes far beyond this single case.
This release expands datasette-acl from table-only permissions toward a general resource-sharing system.
Alex Garcia did most of the work for this release - we're fleshing out the plugin that will allow multi-user Datasette instances finely grained control over who can access which resources within Datasette.
One of the tricks Silicon Valley pulls on people is making it seem cool to raise tons of money. The sums can be so vast, especially in this moment of AI frenzy, that it looks awesome to pry billions of dollars away from investors in the hopes that you might make billions of dollars for yourself. The better, more awesome approach, of course, is to make your billions without taking any money from investors and without giving up any control of your company. It’s a very hard outcome to engineer but glorious when it occurs.
David Holz is living this dream, and we’re now catching a glimpse of what his version of rich, smart, eccentric guy with no one to answer to looks like.
WALLOPS ISLAND, Virginia—Just 10 months ago, NASA asked three companies if they could do something nobody had done before. Could they build and launch a satellite to save a $500 million astronomy mission at risk of crashing back to Earth? What's more, could they do it in less than a year on a tight budget?
Katalyst Space Technologies, a startup founded in 2020, presented the most compelling solution. "They came back with a response that was technically and programmatically plausible, and then we were like, 'Yeah, let’s do it,'" said Shawn Domagal-Goldman, director of NASA's astrophysics division.
That was in August of last year. In September, NASA awarded Katalyst a $30 million contract to build, test, and launch a small satellite to chase down Swift and latch onto it with three robotic arms. Then, Katalyst's Link servicing spacecraft will boost Swift's orbit back to a safe operating altitude, allowing it to resume scientific observations. Easier said than done.
Hi everyone. Instead of a regular post today, I’m going to put up a video. There are a number of reasons why I feel like doing that instead of the usual. One of them is that this is a dry run for a talk that I will be giving virtually later today.
There’s a conference on the economics of digital transformation taking place in Croatia, although I’ll be doing it remotely. And they have asked me to talk about global power, geoeconomics, and Europe. Those are all themes that I’ve been thinking about quite a lot. And today’s miniature talk is an opportunity to try talking through those themes.
And the way I want to structure it is as what has changed, at least in the way that we all now understand the world, since, well, basically since Donald Trump returned to power. That’s an American-centric point of view, if you like, but it’s kind of a natural bracket.
And of course, everything really has changed, mostly not for the better, under Trump. And it has, as it turns out, big implications for Europe as well. So let me just try to get into that.
Start by talking about the world as it seemed to be at the beginning of 2025.
There were, and still are, three great economic superpowers in the world: China, the United States, and the European Union, in that order. If we measure GDP in 2024 at purchasing power parity, which is basically just adjusting for differences in national price levels, you had China with a GDP of something like $37 trillion, the United States with something like 29 trillion and the EU with something like 28 trillion. That last bit may be a bit of a surprise — maybe all of it is a surprise to some people — but yes, in terms of the actual amount of stuff it produces the Chinese economy is now substantially bigger than the US economy. And the European economy is almost the same size as the US economy. If you think that Europe is backward and poor and helplessly dependent, it’s not. It is an economic superpower.
And in fact, by this measure, Europe has basically maintained this position of being about comparable to the United States for a long time. This is a whole other topic that I’ve been writing about and will continue to write about in the future.
In that world, basically, two things were really kind of striking. One is that the United States seemed to perceive itself as being a dominant power, even though China was bigger and even though Europe was about the same size, and Europe acted as if it seemed to perceive itself as not being in the same league, as being not a superpower at all. All of that may be changing, and events are part of the reason, so let’s talk about the events.
Now, the most obvious: the United States just lost a war. Just lost it bigly, as Trump used to say. It’s an astonishing story. We went up against Iran, which was definitely not a major military power or a major economic power, a sort of middle-ranked power, if that, and utterly failed to achieve our war goals.
In the process, we inflicted a lot of damage on the world economy and depleted our stocks of high-tech weapons that will take years to replace. Altogether, immense damage was inflicted on Iran, but Iran has clearly emerged stronger. The United States has emerged humiliated.
The attempts by Trump and minions to pretend that it was a victory don’t help. They only make the United States look not just humiliated but delusional.
So that’s a big deal. It has large implications for US power and influence going forward as well. To explain those implications, it’s helpful to talk about one of the other things that really dramatically changed with Trump coming back into office, which was trade policy.
The United States began really seriously trying to throw its weight around. Liberation Day, the tariffs on everybody, basically trying to pressure all of the world into giving us various kinds of concessions. Give us what we want or we won’t let you sell in our market and everybody needs to sell in our market.
Okay, what we learned from now well over a year of trade war is that U.S. power in that dimension is substantially less than certainly than Trump appeared to believe it was. And just in general, trade, leverage and trade negotiations, leverage in trade disputes has less to do with market access than a lot of people assumed and more to do with supply chains, with getting stuff that you use in your economy, means of production, not in the sense of capital, but intermediate inputs or just inputs in general. The nation that has more ability to strangle its rivals by cutting off supply chains is the one that has the upper hand.
So it turns out, and we had already learned this from the trade stuff, that China with its dominant position in rare earths and some other crucial industrial materials actually had a stronger hand than the United States. Yes, we have a big market, but loss of a market can be offset to some extent by domestic stimulus, domestic support programs. Not having crucial industrial materials is not so easy to make up for. So we learned that the power in international trade disputes in a fundamental sense reflects power over supply, not power over demand, which is something economists have always tried to say.
The point of trade is not to sell. The point of trade is to get stuff. You sell as a way to pay for things that you get from other countries. But now we have it demonstrated very obviously in real life. So that in itself meant that we’ve had a blow to the perception of US power. It turns out the US market is not almighty; access to the US market is not anything like as powerful a tool as we thought and Chinese strangleholds over key inputs are much more important.
And then of course we’ve seen that even more graphically demonstrated by war with Iran and it turns out that Iran’s ability to disrupt traffic through the Strait of Hormuz was a really huge empowering point, and it was the kind of thing that the United States really didn’t think about, and certainly the Trump administration didn’t think about.
And it shows the true rules of global economic power, because largely Iran was able to win this war through economic power rather than strictly military action, the rules of economic power are not what a lot of people thought they were.
Who benefits from that? Well, obviously China. What we’ve seen now is that in terms of a global power competition, China has demonstrated that they have substantial power over supply chains. They’ve also demonstrated that they can weather a cutoff of oil pretty well.
And global power is a zero-sum game. So the United States, by weakening itself, by showing that we don’t have the ability to impose our will militarily, we don’t even have the ability to keep international shipping routes open, has emerged as just a much less formidable player, which means that China by comparison looks better. Add to that the fact that the United States has been erratic and unreliable. Our current leadership just doesn’t understand that a reputation for doing what you promised, honoring your agreements, is itself a source of power, and we have done an enormous amount to undermine that. Not news to anybody.
Trump looks much weaker. America looks much weaker. To a certain extent, China is the beneficiary of all that, at least in terms of power.
Now, of course, life is not all about power. And in the end, you don’t run a country to maximize global power. Maybe the Chinese do. I’m not sure about that. But in any case, it’s not a zero-sum game in terms of living. But in terms of power, it is a zero-sum game. And the United States share of that power, however you measure it, is clearly down as a result of the war.
Europe is a little bit interesting here. Europe played essentially no role in any of this. Europe wasn’t involved, obviously, in the war. Europe didn’t do very much at all except to suffer. Still, one thing that is kind of important is that Europe — at least to some degree, not really through emergency responses but just through the general way that the Hormuz shock played out — Europe demonstrated or some European countries demonstrated that they can be much more independent of global hydrocarbon resources than they have been.
Europe is not a major oil producing area. It has some, but not a lot. It’s not a major gas producing area anymore. It’s essentially a very resource poor economy relative to the size of its GDP, relative to its population. But it is an economy that increasingly relies on renewable energy. And those countries that have gone especially far in relying on renewables weathered this really well. That’s the lesson of Spain’s ability to ride through this with very little rise in electricity costs compared with some other countries. Italy, which has very little in the way of renewables and is very heavily reliant on natural gas for electricity generation, Italy did much worse.
But Spain has given an illustration of how the renewable energy revolution — solar plus batteries is what really runs Spain now — has made Europe more independent and can make it more independent still in a world economy where control of natural resources used to be really critical and it’s becoming increasingly less critical.
So that’s actually a point in Europe’s favor. That’s one piece Another piece of this is that Europe has always, in my lifetime, literally, and from a bit before my lifetime, Europe has always been far less of a global power player than you would expect given its sheer economic weight.
Now that’s partly because Europe doesn’t exist as a political entity. though it’s more of one than it used to be; the common market has gradually turned into something more than that and Europe is able in some important ways to operate as one and is finding ad hoc ways of cooperating more. But it was always in a secondary position very much — or tertiary position given the rise of China — largely because the United States in addition to having a big economy was overwhelmingly the dominant military force.
Now until just the other day there was never a question that the United States would use its military force against Europe; but Europe depended on the United States. Europe’s defense, its security, all depended on the United States.
Okay, now where are we? The United States is quite simply just less credible as a security guarantor, not just because of crazy stuff where we threaten Denmark over Greenland, and not just because we’re erratic all the time, but because we’ve just demonstrated that our military capability is a lot less than we thought it was. The United States could not batter Iran into doing what it wanted. It could not keep the Strait of Hormuz open. So U.S. military preeminence is a lot less intimidating, also a lot less reassuring if you thought you had America on your good side than it used to be.
And on the other hand the prospect that Europe might be able to defend itself, achieve its own security without the United States, looks a lot stronger than it did not very long ago. And that’s not just because of the war in Iran but also because of the war in Ukraine.
Now, there are many, many horrifying things that have happened under Trump. One of the ones that is particularly horrifying to some of us is the abandonment of Ukraine, the clear tilt towards siding with Putin in his attempt to destroy a democratic nation. The United States basically stopped giving any aid to Ukraine at all. almost as soon as Trump took office. U.S. aid of all kinds, but especially, of course, military aid, is all gone.
But a funny thing has happened. Ukraine is still standing. If anything, the war seems to be tilting in its direction. Now, that reflects partly the fact that Europe did step up. particularly with economic aid: Europe has filled the gap, pretty much, that the United States left so the flow of money to Ukraine continues.
But it’s also because war has changed. To the extent that the United States appeared to be essential it wasn’t just the money — we knew that Europe could come up with some money — but it appeared that what would what How could Ukraine defend itself without U.S. weapons?
Well, it turns out that in this age of drone warfare that Ukraine can mostly defend itself. Actually, what they can’t really stop is Russian missiles that destroy civilian targets, which is horrifying, but it doesn’t appear to really work in terms of altering the military balance.
And Ukraine has developed its own suite of weapons, and quite aside from the fact that Ukraine is hanging in there, this says that one of the sources of perceived US superpower status— super duper power? versus Europe is a mere superpower? — was that, well, we had the weapons, that we had the technology, that even if Europe could come up with the money, they needed U.S. weapons to be effective, as did Ukraine. And if the United States cut off the flow of weapons, what could you do? You really could not stand without all of those sophisticated, high-tech weapons that only the United States knew how to produce.
Well, those weapons are kind of looking obsolete right now. Not entirely, but we just saw Iran do a lot of damage with drones that the United States didn’t appear prepared to stop. And the United States, with all of its super-duper weapons, was not able to suppress them.
We had the spectacle of million-dollar patriots shooting down $30,000 Shaheds. This is not a good look. And Ukraine has become a major arms producer ,has become in many ways the expert in this new age of drone warfare. The Europeans are picking up some of that, and there’s a lot of new cooperation on weapons with Ukraine.
But maybe the most important thing to say is that, well, that special U.S. advantage, because we had the weapons and no one else did, it’s not much of an advantage now that it appears that those weapons are largely obsolete.
Not totally, of course. The Ukrainians would really love to get more Patriot missiles to stop some of those Russian missiles that are destroying 11th century churches and so on. But the balance has shifted in a way that means that the United States is not indispensable at any level. We’re not indispensable financially, and we’re not even indispensable militarily. It’s like we have the world’s best cavalry in an age of machine guns. What good does that do?
Okay the Chinese presumably have immense capacity. Chinese dominance of manufacturing means that on almost any dimension China is the super super duper power, they’re really way out in front. But there’s much more parity between between Europe and the United States than there was because the United States doesn’t really have economic dominance and we don’t have military dominance anymore. We dominated an age of warfare that now appears to be behind us.
So where does Europe stand here?
In a rational world, the rise of China and the coordinated, concerted, efforts of the United States and Europe to deal with that rise would be the central story of geopolitics in the year 2026. Unfortunately, things are not rational. And so we have a belligerent, erratic United States with Europe largely on its own.
But Europe being on its own is not nearly as impossible to imagine as it used to be. This is a world that has tilted towards China. That’s probably the biggest story. But it is also, in effect, tilted towards Europe because it’s tilted away from us here in the United States.
Today we launched a new plugin for Datasette, datasette-apps, with this launch announcement post on the Datasette project blog. That post has the what, but I'm going to expand on that a little bit here to provide the why.
The TL;DR
Datasette Apps are self-contained HTML+JavaScript applications that run in a tightly constrained <iframe> sandbox hosted on your Datasette application. They can use JavaScript to run read-only SQL queries against data in Datasette, and can run write queries too if you configure them with some stored queries.
Apps are allowed to run JavaScript and render HTML and CSS. They are limited in terms of access - the <iframe sandbox="allow-scripts allow-forms"> they run in prevents them from accessing cookies or localStorage and they also have an injected CSP header (thanks to this research) which prevents them from making HTTP requests to outside hosts, preventing a malicious or buggy app from exfiltrating private data.
Datasette Apps started out as my attempt at building a Claude Artifacts mechanism for Datasette Agent, but I quickly realised that the sandboxed pattern is interesting for way more than just adding custom apps to the interface surface and promoted it to its own top-level concept within the Datasette ecosystem.
You can try out Datasette Apps by signing in with GitHub to the agent.datasette.io demo instance.
Why build this?
Since the very first release, Datasette has offered a flexible backend for creating custom HTML apps via its JSON API.
One of my earliest Datasette projects was an internal search engine for documentation when I worked at Eventbrite - it worked by importing documents from different systems into SQLite on a cron and then serving them through a Datasette instance with a custom HTML+JavaScript search interface that directly queried the Datasette API.
I had client-side JavaScript constructing SQL queries, which originally was intended as an engineering joke but turned out to be a really productive way of iterating on the app!
Imagine how much more useful Claude Artifacts could be if they had access to a persistent relational database. That's what I'm building with Datasette Apps!
Neat ideas in Datasette Apps
Here are a few of the ideas and patterns I've figured out building this which I think have staying power.
This is the magic combination that makes Datasette Apps feasible in the first place. I need to run untrusted HTML and JavaScript on a highly sensitive domain - an authenticated Datasette instance can contain all sorts of private data. The sandbox= attribute lets me run that untrusted code in a way that cannot interact with the parent application - it can't read the DOM, or access cookies, or steal secrets from localStorage. It can however use fetch() and friends to load content (or exfiltrate data) from other domains. But... it turns out if you start an HTML page with a <meta http-equiv="Content-Security-Policy"> header you can set additional policies that lock down access to other domains. I was worried that malicious JavaScript would be able to update or remove that header but it turns out that doesn't work - once set, the CSP policy is immutable for the content of that frame.
Locked down APIs with postMessage() and MessageChannel()
Having locked down those iframes to the point that they couldn't do anything interesting at all, the challenge was to open them back again such that they could run an allow-list of operations, starting with read-only SQL queries against specified databases.
I built the first version of this with postMessage(), which allows a child iframe to send messages to the parent window. I created a simple protocol for requesting that the parent run a SQL query - the parent could then verify it was against an allow-listed database before executing it.
One of the LLM tools, I think it was GPT-5.5, suggested that postMessage() on its own can be exploited if the iframe somehow loads additional code from an untrusted domain. I don't think that applies to Datasette Apps, but I also believe in defense in depth, so I had GPT-5.5 help me port to a MessageChannel() based transport instead.
MessageChannel() has the advantage that if a page navigates to somewhere else the channel closes automatically, removing any chance of executing commands sent from an untrusted external page.
Visible logs, for queries and errors
If you navigate to the timeline demo and search for the string usercontent you'll pull in some search results that embed images from the user-images.githubusercontent.com domain. This domain is not in the CSP allow-list, so it trips an error.
Those errors are captured and transmitted back to the parent frame, where they can be displayed in a useful error log. This is meant to make hacking on apps more productive by surfacing otherwise-invisible problems.
I built an experiment demonstrating that you can even turn this into a one-click-to-allow mechanism for building the CSP allow-list based on what breaks, but I haven't integrated that idea into datasette-apps just yet.
I want apps to be able to conditionally write to the database, but this is an even more dangerous proposition than SQL reads!
My solution involves Datasette's stored queries feature, rebranded from "canned queries" and given a major upgrade in the recent Datasette 1.0a31 - work that was directly inspired by Datasette Apps.
Users can create a stored write query that performs an insert or update, then allow-list that specific query for an app to use. Usage from code inside an app looks like this:
I'm only just beginning to explore the possibilities this unlocks myself, but my goal is to support full read-write applications built safely as Datasette Apps.
Copy and paste a prompt to build an app
The Datasette Apps plugin has no dependency on LLMs at all, but these self-contained apps are the perfect shape to be written by a modern LLM.
The create app form includes a copyable prompt at the end. This prompt has everything a model needs to know to build a new app, including the schema of any selected databases.
This means you can click "copy", paste it into ChatGPT or Claude or Gemini, tell it what you need, and there's a good chance the model will spit out the code necessary to build the app.
If you have Datasette Agent installed your AI assistant will also gain tools to both create new apps and edit existing ones, Claude Artifacts style.
Built with so much AI assistance
Datasette Apps started life back in April as datasette-agent-artifacts, a plugin I have since renamed to datasette-agent-edit keeping only its editing tools. I built that as one of the first plugins for Datasette Agent, to help get the plugin hooks into the right shape. That first prototype was mainly built using Claude Opus 4.6 in Claude Code.
When I switched track to Datasette Apps I started with a plan constructed using Codex Desktop and GPT-5.5 xhigh, based on extensive dialog and feeding in both datasette-agent-artifacts and other prototypes I had built.
Most of the work that followed stuck with Codex, but in the few short days that we had access to Claude Fable 5 I had it run a security evaluation of the product (an ability that would get it banned by the US government shortly afterwards) and it found a very real problem.
I was allowing users to allow-list CSP hosts for their apps, but Fable pointed out the following attack:
A less privileged user with create-app permission creates an app that queries SQLite for all available tables and selects and exfiltrates all of the data to a host they had allow-listed via CSP.
They then trick an administrator user with access to private data into visiting their app.
... and the app can now run queries as that user and steal their private data!
That's clearly unacceptable. I fixed it by restricting the ability to allow-list any domain to a new apps-set-csp permission, which is intended just for trusted staff. Site administrators can also configure Datasette with a list of allowed_csp_origins, which regular users can then select. This means you can do things like allow cdnjs.cloudflare.com and your users will be able to build apps that load extra JavaScript libraries from the cdnjs CDN.
I've reviewed Datasette Apps extremely closely, especially the security-adjacent parts of it. The critical sandbox and CSP configuration are based on multiple AI-assisted prototypes and tests.
It's looking good so far
I'm really pleased with this initial release.
Datasette is growing beyond its origins as an application for serving read-only data into a much richer ecosystem of tools for doing useful things with that data once it has been collected.
Datasette's roots are in data journalism. I've always been interested in the question of what comes next after a journalist gets their hands on a giant dump of data about the world. Datasette supports exploring and publishing it. Datasette Agent adds interrogating it with AI assistance. Now Datasette Apps expands that to building custom interfaces and visualizations to help unlock the stories that are hidden within.
The _index.js payload begins with a large JavaScript block comment containing fake system instructions and policy-triggering content. Because it is inside a comment, it does not affect JavaScript execution. The runtime skips it. The real malware begins after the comment with a try{eval(…)} wrapper around a large character-code array and a ROT-style substitution function.
This header appears designed for AI-mediated analysis, not for Node, Bun, or Python. It attempts to derail scanners or analyst copilots that feed the beginning of a file to a language model without clearly isolating the content as untrusted data. In weak pipelines, this can cause refusal behavior, prompt confusion, context pollution, or premature classification before the scanner reaches the actual malware.
This is not a magical bypass against static detection. YARA rules, entropy checks, AST parsing, string extraction, deobfuscation, and behavioral rules still work. But it is a practical anti-analysis trick against naive LLM-first triage systems.
Up by four o’clock and to my office, where all the morning writing out in my Navy collections the ordinary estimate of the Navy, and did it neatly. Then dined at home alone, my mind pleased with business, but sad for the absence of my wife. After dinner half an hour at my viallin, and then all the afternoon sitting at the office late, and so home and to bed. This morning Mr. Cutler came and sat in my closet half an hour with me, his discourse very excellent, being a wise man, and I do perceive by him as well as many others that my diligence is taken notice of in the world, for which I bless God and hope to continue doing so.
Before I went into my house this night I called at Sir W. Batten’s, where finding some great ladies at table at supper with him and his lady, I retreated and went home, though they called to me again and again, and afterwards sent for me. So I went, and who should it be but Sir Fr. Clerke and his lady and another proper lady at supper there, and great cheer, where I staid till 11 o’clock at night, and so home and to bed.
When the flood waters ravaged Micaville Presbyterian Church, lifting pews and pushing a neighboring house into the back of the building, the water level stopped just below the base of the stained glass windows. Saving the blue-rimmed fractal panes was one of many blessings for pastors Beth and Tom Hall, alongside receiving $140,000 in April of last year to rebuild.
This money came through the Public Assistance program for Houses of Worship damaged by declared disasters through the Federal Emergency Management Agency, or FEMA.
Micaville, an unincorporated community in Yancey County, about 45 miles northeast of Asheville, lies at the intersection of two creeks. When tropical storm Helene blew through western North Carolina in September 2024, causing catastrophic flooding, much of Micaville was washed away. Once neighbored by a gym, a coffee shop, a thrift store, a post office and a water tower, Micaville Presbyterian Church stands partially rebuilt in the middle of the destruction. The rest of the strip is abandoned, filled with debris and stacks of wood.
“You wouldn’t believe how much water came from such a little creek,” said Beth Hall on a sunny day in early March, 18 months later. “I’ve never seen anything like that in my life.”
Micaville Presbyterian Church reopened one year after Helene, when the water filled the basement and flooded the sanctuary up to the stained glass windows. Left, pews are scattered amid debris and mud soon after the water receded. Right, chairs face the altar in the newly rebuilt church. Photo credits: Beth Hall and Ali Caudle
With the initial funding from FEMA, debris removal by the National Guard, as well as donations and aid from community members and Amish volunteers, the Halls were able to reopen their church last fall. The basement remains unfinished, though, and much of the planned work to fortify the structure against future storms and flooding remains on hold.
The Halls are waiting on approximately $300,000 in aid from FEMA that they have already been approved for, said Tom. This mitigation money would be used to rebuild a flood wall to protect the church if the creek floods again. It would also be used to waterproof the doors and windows, and replace supplies in the basement for ones that could be easily cleaned.
“We’ve got over $300,000 that is approved for mitigation,” said Beth Hall. “And we’ll never get that. But I’m just thankful we got what we did.”
What Is FEMA?
FEMA is a government agency under the U.S. Department of Homeland Security, or DHS. The primary purpose of FEMA is to support disaster response when recovery efforts overwhelm the resources of state and local authorities.
There are two primary categories of aid dispersed by FEMA after a disaster declaration: individual assistance, known as IA, and public assistance, referred to as PA.
“FEMA does two major things after a disaster. One of them is helping individuals, IA, so that’s helping people, tree on the house, bridge washed out, that kind of thing,” said Rachael Sawyer, the strategic partnerships director for Buncombe County, and Helene recovery coordinator. “And then PA is help government to government. So if we sustained any damages that need to be repaired, they help with that, and they also help reimburse us for … emergency protective measures.”
FEMA funding involves a fractured landscape, shifting constantly. Between the DHS government shutdown, leadership changes and an uncertain political future, FEMA assistance is deeply complicated. As of March, both public and individual assistance remains stalled.
As of March 19, North Carolina state officials estimate that there are roughly 1,800 Helene-related projects in progress within the FEMA public assistance program, accounting for an estimated $2.6 billion in need.
“The FEMA money is not flowing as fast as expected or as is needed in the state,” said an official within North Carolina’s Department of Public Safety on the condition that his name not be used because of the sensitivity of the topic and the state’s continued dependency on federal aid. “We would have liked to see that funding move quicker,” he said, adding that his office has urged legislators including Republican Sen. Thom Tillis to help free up federal disbursements.
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According to FEMA’s website, public assistance is FEMA’s “largest grant program providing funds to assist communities responding to and recovering from major disasters or emergencies declared by the president.” Eligible applicants for PA include states, U.S. territories, federally recognized tribal governments, local governments and certain private non-profit organizations. The houses of worship provision falls under the umbrella of private non-profit groups.
However, as a result of the DHS shutdown in early 2026, FEMA was operating for months at limited capacity, which meant that the agency made slow progress on processing grant funding for public assistance category A, or debris removal, and category B, emergency protective actions. Categories C through G are considered “permanent work” and include rebuilding roads and bridges, water control facilities, public utilities, parks and other facilities.
The Secretary’s Approval
Within PA categories A and B alone, senior North Carolina state officials report that there are approximately 21 projects waiting approval by the DHS secretary, representing an obligation of approximately $28.6 million.
This is due, in part, to a rule implemented by former DHS Secretary Kristi Noem last June that the secretary must personally approve any expenditures greater than $100,000. Widely criticized for causing delays and putting a burden on FEMA’s disaster response, this policy was rescinded by Noem’s successor, Secretary Markwayne Mullin, on April 2. While this move is expected to ease the bottlenecks, the effects of this change are likely to be felt well after the end of the DHS shutdown.
According to North Carolina state officials, Noem’s policy definitely slowed down progress on awards reaching the state for reimbursement through public assistance. State officials have turned to liaising with legislative partners at the federal level to try to get funds freed up.
In a March 3 Senate Judiciary Committee hearing two days before Noem was fired, North Carolina Sen. Thom Tillis questioned then-Secretary Noem, criticizing her leadership of DHS, especially in regards to immigration enforcement and FEMA.
“You have a policy right now that anything over $100,000 has to go through your desk for approval,” Sen. Tillis said in the committee hearing. “If you’re requesting a review of $100,000 and up, then it begs the question why? Why would you be involved in that? Why would that be a policy?”
In a study released March 4 — titled “Delayed by Design: Disaster Survivors Left Behind by DHS Secretary Noem’s $100,000 Approval Policy” — by the minority staff of the U.S. Senate Committee on Homeland Security and Governmental Affairs, ranking members Gary Peters (D-MI) and Andy Kim (D-NJ) laid out real-world impacts of this DHS directive for disaster survivors. The study found that minority staff identified 1,034 contracts, grants or disaster assistance awards that were delayed or left pending as a result of this directive.
“The Homeland Security Act of 2002 expressly prohibits the Secretary of Homeland Security from restricting or diverting FEMA resources from the agency’s mission. Based on your disaster response,” said Sen. Tillis in the committee hearing, “I have reason to believe that you’re violating the law, either knowingly or unknowingly.”
On the ground in North Carolina, individuals cited DHS policies and the Trump administration when assessing FEMA’s response to Helene.
“If we got the rest of the FEMA money, we’d be wonderful,” said Tom Hall. “Donald Trump came in here and said, ‘I’ll build it back better than ever.’ … FEMA was here right from the start helping us. They were the ones that did the job. They came and found us. …The administration change just…it came to a screeching halt.”
Navigating the FEMA Landscape
With constant changes at the federal level, it becomes complicated for individuals to track the status of their assistance applications.
“In terms of the day-to-day operation of the Individual Assistance Program that we see, I would say the only change that we have seen at this level has been that FEMA responses have slowed down,” said Emma Smiley, a supervising attorney for the Disaster Relief Project at Legal Aid of North Carolina. “The time to get a decision on an appeal has crept longer and longer. … We’re talking like three months, but it’s at this point at least four before people get their decisions made on appeals.”
In September 2025, the U.S. Government Accountability Office published a report finding that from Jan. 1, 2025, to June 1, 2025, the active number of FEMA employees decreased from 25,800 to 23,350 — a loss of 2,446 employees, including 1,465 who participated in a workforce reduction program. The report ties these departures to the Trump administration’s efforts to reduce the size of the government workforce, as well as attrition and employee burnout from concurrent disasters.
“I think that it’s important for FEMA to have the staffing levels where they can make decisions on appeals in a timely manner, because when people are in a disaster situation, they tend to have a lot of emergency needs,” said Smiley. “So if they have to wait four months for an appeal decision, just because there isn’t the staffing to be able to do that, that can make somebody homeless.”
In January 2026, the American Federation of Government Employees led a coalition in a lawsuit challenging the Trump administration’s “unlawful and drastic” staffing cuts at FEMA. The complaint alleges that attempts to dismantle FEMA through workforce reductions take direct aim at FEMA’s mandate as laid out in U.S. law, and warns that shrinking FEMA risks pushing disaster relief to state and local governments in ways that could cause the kind of catastrophic tragedy Congress sought to prevent.
“We had to hunt through so much red tape. And we’re educated people, so we were able to persevere and not give up,” said Beth Hall. “So if we had that much trouble, I think a lot of people, they don’t try and get it filled out. They just don’t believe that they can.”
Beth Hall, co-pastor of Micaville Presbyterian Church, stands on the front steps and points at the ravaged remains of Micaville. The Yancey County community was decimated by the floods and structures still sit abandoned 18 months out. Photo credit: Ali Caudle
Impacts On Organizations
MANNA FoodBank is a private, nonprofit regional organization that works to end food insecurity in Western North Carolina. Their Asheville headquarters and warehouse, then-located on Swannanoa River Road, were completely destroyed by Helene.
Claire Neal, MANNA’s CEO, credited FEMA with providing crucial support in the immediate aftermath of Helene by providing significant amounts of food to be distributed to people in need — including foods for specific dietary needs and cultural or religious restrictions that couldn’t be sourced through community donations alone. MANNA was able to resume food distribution within days of Helene’s impact. But 18 months later, the organization is still trying to piece together funding from various sources, including FEMA, on a relocation project to rebuild.
The Swannanoa River completely changed course as a result of the flooding. What used to be MANNA’s parking lot is now the river — meaning the organization cannot rebuild on the old site. To fund this relocation, MANNA is coordinating with FEMA on a daily basis, contracting with an outside consultant and dedicating substantial staff time.
MANNA is also working with FEMA through the Hazard Mitigation Grant Program, or HMGP, which provides funding to state, tribal and local governments to reduce or mitigate future disaster losses. In Buncombe County, there are four groups of applicants. The first group involves 23 properties with funding already awarded by FEMA. For group two, 24 of 26 properties have been awarded funds. Groups three and four, involving 157 and 72 properties respectively, are listed as “application submitted to FEMA.”
MANNA has been approved through the county and state level for this program, so the state has agreed to buy back the original land to be converted to green space, at fair market value, using FEMA funds, once approved.
Over in Black Mountain, a Quaker meeting house was damaged beyond repair. The Swannanoa Valley Friends Meeting, which did not have flood insurance, are now gathering at a host church on the Warren Wilson College campus. The group’s leadership recently learned that their old property has been approved in the first group of HMGP funding in Buncombe County.
MJ Hogan, the group’s assistant treasurer, recalled the state of the meeting house after the floods. “We salvaged what we felt like was salvageable, and it was a mess. I mean, it was disgusting. Everything was just caked in mud,” she said.
In Hogan’s initial correspondence with FEMA, she was redirected to different programs and led to believe that there was no support the agency could offer the group. “All my efforts to get FEMA help or help anywhere prior to this moment of this hazard mitigation was, ‘We can’t help you because you’re not residential,'” said Hogan. “It’s a weird situation. We’re not commercial, we’re not a business. But we’re not a family owning a property.”
Her situation mirrors what countless others have been through. The confusion, the mixed messaging, the promise of aid and then its retraction, have left residents of Western North Carolina wondering how they will fully restore their lives after so much chaos and loss.
“Then you add on top of it government shutdowns, and you add on top of it the current administration, and you add on top of it, all the things. The whole time we’ve been kind of in the dark,” said Hogan. “We found out maybe a year in that we were one of the first 23 properties approved for this buyout program, which was great news. That still might mean that it’ll be years from now before anything happens. We don’t know.”
The Swannanoa Valley Friends Meeting house in Black Mountain was destroyed by tropical storm Helene. With no flood insurance, the Quaker group has to rely on public assistance to recover what they lost. They were rejected by FEMA at first, but the state has just approved at least a portion of their request with FEMA-provided money. Top: The front of the meeting house before and after the storm. Bottom: The back deck of the meeting house before and after the storm. Photos courtesy of MJ Hogan:
This article is part of Caught in the Current: Helene Recovery in Asheville and Beyond a project that we have partnered on with the School of Journalism at Northeastern University. Their enterprising students took on the story of Asheville, North Carolina, a community still dealing with the devastation of Hurricane Helene, 18 months later. As part of our mentoring program, we’re amplifying their efforts by sharing the amazing work produced by their students. Visit the official interactive magazine for the project HERE.
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Donald Trump has now surrendered to Iran. The irony is that the 60-day agreement he signed is actually the best possible deal for everyone given the situation he put the whole world in.
Under the terms of the agreement, the United States gets nothing it didn’t have four months ago, and the government of Iran gets pretty much everything it wanted. At this point, there really is no better alternative. That’s what a disaster this war was.
The world’s worst negotiator gets owned
As I have been trying to get people to understand for years, while Trump successfully convinced millions that he’s some kind of grandmaster of dealmaking, he’s actually the world’s worst negotiator. Even the simplest principles of negotiation — for instance, it’s good to know as much as possible the person on the other side of the table so you can understand their incentives, goals, and fears — are beyond his ken.
If you picked up The Art of the Deal and skimmed through it (which you can do in about ten minutes), you’d be shocked at its almost complete lack of anything resembling advice on dealmaking. Beyond some blindingly obvious real estate tips (“Enhance your location”), the anecdotes in the book amount to him explaining that he’s a bully, and sometimes that works. “My style of deal-making is quite simple and straightforward,” he says. “I aim very high, and then I just keep pushing and pushing and pushing to get what I’m after.” So insightful.
As president he has shown that he’s incapable of anything more subtle or complicated than that, which is why in five and a half years in the White House he did not manage to complete a single difficult legislative negotiation (and no, watching from the sidelines while Republicans passed two tax cuts for the wealthy and corporations doesn’t count). His belief about Iran, from the moment in 2018 that he tore up the Joint Comprehensive Plan of Action that required two years of negotiation under President Obama, was that he would make a bunch of threats, and cowed by his virility and power, Iran would come crawling back and give him everything he wanted.
Instead, he is now the one on his knees.
This happened because the Iranian government understood the situation far better than he did. They quickly learned the power the could wield by choking off the Strait of Hormuz when they plunged the whole world into an energy crisis. They saw the domestic political problem the war was creating for Trump, which for all the destruction American and Israeli bombing could do, meant they could drag the war out longer than he could tolerate. They understood how to exploit the diverging goals Trump and Benjamin Netanyahu have. And above all, they realized they were dealing with a simpleton.
Hostilities, i.e. Iran and Israel bombing Iran, now cease. Israel is supposed to stop its military operations in Lebanon, which it probably won’t.
The U.S. blockade of Iranian ports is removed.
A $300 billion fund for the reconstruction of Iran will be set up; it isn’t clear who will foot the bill, but don’t be surprised if Gulf countries put up the money at first and then eventually get reimbursed in one way or another by the U.S.
Sanctions against Iran will be removed.
Iran gets to “maintain the current status quo of its nuclear program,” which means uranium enrichment for civilian purposes.
The U.S. will issue waivers so Iran can export oil.
Iranian funds frozen in banks around the world will be released.
In return, the U.S. gets the following:
Iran will stop attacking ships moving through the Strait of Hormuz, and traffic will be restored to what it was before the war.
Iran declares that it won’t develop nuclear weapons, which is the same position it has always had.
Or, as Trump would put it, UNCONDITIONAL SURRENDER, except the U.S. is the one doing the surrendering.
Much of this is vaguely described and will take time to implement, which of course offers either side the opportunity to go back on its promises. But the essence of it is that the U.S. gets nothing it didn’t have four months ago, and Iran gets economic benefits it has been seeking for years.
Let’s remind ourselves of what Trump’s goals were at the outset, and how they’ve turned out:
Iran should never get a nuclear weapon. That was part of the JCPOA, and Trump himself could have gotten it without launching a war.
Iran’s missile stockpile must be destroyed so it can’t threaten its neighbors. Not only is this not happening, Trump is now saying that Iran should be able to keep its missiles!
Iran must cease its support for regional proxies, including Hezbollah, Hamas, and the Houthis in Yemen. There’s nothing about that in the deal, so Iran gets to keep supporting those groups.
Some of the more hawkish people around Trump also wanted the regime overthrown, though that was not an officially stated goal, but in any case it’s not happening. Once the war started and Iran effectively closed the Strait of Hormuz, reopening it was added as a war goal — i.e., turning the clock back to before the war. But having seen what its control of the Strait can offer, Iran is now suggesting that in the future it will charge “fees” for ships to transit, creating a source of revenue it didn’t have before. And the U.S. spent what will likely turn out to be hundreds of billions of dollars fighting the war, in addition to the cost to American consumers in higher prices for gas and other goods.
The right is freaking out
The release of the MOU has produced the most widespread criticism of Trump from within the right since January 6. The New York Post editorial board wrote a condemnation headlined “Trump’s Iran deal gives the Islamic Republic big wins up front — and America nothing.” Radio and TV host Mark Levin, who still thinks launching the war was a great idea, savaged the deal, saying it was “unthinkable.” Elon Musk’s white supremacist social network lit up with outrage from right-wingers.
No one on the right seems able to defend it on substantive grounds. Sean Hannity, Trump’s close friend and most relentless media fluffer, had to assure his audience that there’s another, secret deal behind the deal. “I’ve been assured by the people involved in discussions that it’s much deeper and [Iran] conceded a lot more,” he said on his radio show Wednesday. Right — Trump got an even better deal, but he was too modest to tout it publicly. That checks out.
Trump supporters are facing a cognitive dissonance problem: The deal is self-evidently terrible, yet Trump is a genius and master negotiator. How to reconcile the contradiction? The answer some found is that it must be JD Vance’s fault. War booster Brian Kilmeade of Fox & Friendssaid of the vice president, “this is his deal. It’s not the president’s deal.” Ben Shapiro said the same thing: “This is JD’s deal. Let’s be very clear. This is the vice president’s deal.” Lindsey Graham referred to Vance as “the architect of the deal.”
Much as it pains me to defend our odious vice president, that’s absurd. This is Trump’s war, and he had to approve every word of the agreement to end it. The only people praising the deal are Trump lackeys doing so through gritted teeth, and foreign policy experts who argue that given what a phenomenal screwup it was to launch the war in the first place and the advantageous position the Iranian government is now in, unconditional American surrender is the best of the available options.
That’s the proper conclusion to draw: Right now, we should be glad that Trump surrendered. Not only might that surrender bring this catastrophe to a close, it also drives a wedge into the MAGA coalition that will be difficult to repair, and will be a stain on every Republican who supported the war (including most of those who will run for president in 2028).
Finally, some good news!
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Washington Sees Motorcycle Fatalities Decline by Over 20%, Strengthening Safety Outcomes
Key Takeaways
Washington ranks among the top states in safety improvement: With a -20.14% decline, Washington reduced motorcycle fatalities from 139 to 111, reflecting a strong year-over-year improvement in rider safety.
A clear performance gap separates leading states: While Washington shows steady progress, it trails Vermont (-61.11%), Rhode Island (-46.67%), and Louisiana (-26.80%), indicating variation in the scale of reductions.
The contrast with the worst-performing states is stark: While Washington achieved a decline, Maine (+125.00%), Wyoming (+84.62%), and Delaware (+64.29%) recorded sharp increases, highlighting a divided national safety landscape.
Motorcycle safety outcomes across the United States vary widely, but Washington stands out with notable improvement nationwide. The state reduced rider fatalities from 139 in 2023 to 111 in 2024, a -20.14% decline, placing it among the top-performing states. This reduction highlights how a decrease of 28 fatalities can significantly improve outcomes in larger states and underscores the role of regional safety efforts in shaping rider risk.
The study, conducted byEaston & Easton, LLP , analyzed motorcycle rider fatality data across all 50 U.S. states for 2023 and 2024, focusing on year-over-year percentage changes to assess shifts in safety outcomes. For each state, total fatalities in 2024 were compared with 2023 figures to calculate the percentage rise or fall, which served as the primary ranking metric. Additional breakdowns of fatalities occurring on interstates and at intersections were also examined to identify location-specific trends. States were then ranked from greatest decline (Rank 1) to highest increase (Rank 50) based on overall percentage change in fatalities.
Washington’s Safety Snapshot: Motorcycle Fatalities and Key Statistics
Using Data From 2023–2024
Metric
Value
National Rank (by % Decline in Fatalities)
#4
Motorcycle Rider Fatalities (2023)
139
Motorcycle Rider Fatalities (2024)
111
Percentage Change
-20.14%
Interstate Fatalities (2023–2024)
13 → 13
Intersection Fatalities (2023–2024)
54 → 46
How Washington Compares to Other Top-Performing States
States with the Steepest Percentage Drop in Motorcycle Fatalities (2023–2024)
Rank
State
Motorcycle Rider Fatalities 2023
Motorcycle Rider Fatalities 2024
% Rise/Fall
1
Vermont
18
7
-61.11%
2
Rhode Island
15
8
-46.67%
3
Louisiana
97
71
-26.80%
4
Washington
139
111
-20.14%
5
Arkansas
92
75
-18.48%
6
Arizona
261
217
-16.86%
7
California
595
519
-12.77%
8
Missouri
166
145
-12.65%
9
Illinois
165
147
-10.91%
10
New Hampshire
38
34
-10.53%
Washington ranks fourth and reflects a mid-tier improvement, with a -20.14% decline compared to -61.11% in Vermont, -46.67% in Rhode Island, and -26.80% in Louisiana. Most states below this point cluster closely between -10% and -20%.
In effect, while several states show meaningful improvements in motorcycle safety, Washington aligns with the broader group of steady performers rather than the top tier. Its progress is notable but less pronounced.
Washington’s Motorcycle Fatalities by Road Type
Breakdown of Interstate and Intersection Fatalities (2023–2024)
Metric
2023
2024
% Rise/Fall
Total Motorcycle Rider Fatalities
139
111
-20.14%
Interstate Fatalities
13
13
0.00%
Intersection Fatalities
54
46
-14.81%
Washington’s decline in motorcycle fatalities is driven primarily by reductions at intersections, while interstate fatalities remained unchanged. Total deaths fell from 139 to 111.
The mixed pattern suggests that improvements are more concentrated in certain road environments rather than across all categories.
How Washington Compares to States with the Sharpest Increases in Motorcycle Fatalities
Contrast Between Washington’s Decline and States with the Highest Percentage Rise (2023–2024)
Rank
State
% Rise/Fall
Percentage Point Difference vs Washington
4
Washington
-20.14%
—
46
Nebraska
+31.82%
+51.96 pp
47
Kansas
+33.33%
+53.47 pp
48
Delaware
+64.29%
+84.43 pp
49
Wyoming
+84.62%
+104.76 pp
50
Maine
+125.00%
+145.14 pp
The contrast between Washington and the worst-performing states is evident. While Washington achieved a -20.14% decline, states like Maine and Wyoming recorded sharp increases, creating a gap of over 145 percentage points.
Even mid-tier increases, such as in Nebraska and Kansas, are over 50 percentage points apart from Washington’s performance, highlighting uneven safety trends.
Methodology
The study analyzed motorcycle rider fatality data across all 50 U.S. states for 2023 and 2024, focusing on year-over-year percentage changes to assess shifts in safety outcomes. For each state, total fatalities in 2024 were compared with 2023 figures to calculate the percentage rise or fall, which served as the primary ranking metric. Additional breakdowns of fatalities occurring on interstates and at intersections were also examined to identify location-specific trends. States were then ranked from greatest decline (Rank 1) to highest increase (Rank 50) based on overall percentage change in fatalities.
Easton & Easton, LLP is a personal injury and wrongful death law firm with more than 100 years of combined legal experience. The firm represents individuals and families harmed by motor vehicle collisions, including motorcycle crashes, and advocates for safer road design and stronger rider protections.
For decades, consumers largely relied on a familiar group of authorities when making important decisions. Doctors, financial advisors, researchers, journalists, educators, and industry professionals were often viewed as the primary sources of reliable information. While disagreements certainly existed, expertise was usually associated with formal credentials, institutional backing, and professional experience.
The rise of social media has dramatically altered that dynamic. Today, consumers can access thousands of opinions, reviews, personal stories, and recommendations within minutes. Before consulting a traditional expert, many people first encounter content from creators, influencers, community groups, and everyday consumers who share their experiences publicly.
This shift has not eliminated the value of expertise, but it has changed how trust is formed. Consumers are no longer evaluating information based solely on credentials. They are increasingly considering authenticity, transparency, relatability, and consistency. As a result, experts, brands, and media organizations are all adapting to a world where authority must be continually earned rather than automatically assumed.
Personal Experience Has Become Part of the Trust Equation
One of the most significant changes introduced by social media is the growing influence of personal experience. Consumers regularly encounter individuals documenting their journeys, sharing results, reviewing products, and discussing challenges in real time. These firsthand accounts often feel more relatable than traditional expert commentary because audiences can see how information applies in practical situations.
This does not necessarily mean people trust professionals less. Instead, many consumers now combine expert guidance with peer experiences when making decisions. They may read research, watch interviews with specialists, and also examine how real people have applied that information in everyday life.
For media organizations, this creates both opportunities and challenges. Reporting facts remains essential, but audiences increasingly expect stories that provide context and connect information to real-world experiences. News and media platforms that successfully bridge that gap often find it easier to build lasting trust with readers.
Transparency Matters More Than Ever
Another major shift involves how credibility is evaluated.
In previous generations, authority often depended heavily on titles and institutional affiliations. While those factors remain important, modern audiences frequently want additional insight into how conclusions are reached. They look for transparency, openness, and explanations that help them understand the reasoning behind recommendations.
As a result, organizations that communicate clearly and honestly often develop stronger relationships with their audiences. People appreciate content that acknowledges uncertainty, explains limitations, and avoids overstating conclusions.
This trend extends beyond journalism and into nearly every industry. Consumers increasingly seek educational content that helps them understand topics rather than simply encouraging them to make purchases. Companies and publishers that provide useful information often become trusted resources over time.
Consumers are often faced with dozens of similar-looking products, making it difficult to evaluate quality, comfort, and long-term value. Whether someone is comparing skincare ingredients or exploring options from brands such as https://tadbeauty.com, access to clear and reliable information can make purchasing decisions far easier.
The Speed of Information Creates New Challenges
While social media has made information more accessible, it has also created new difficulties for consumers trying to evaluate accuracy.
Information now spreads faster than ever. A post, video, or comment can reach millions of people within hours. Valuable insights can travel quickly, but so can incomplete information, misunderstandings, and unsupported claims.
This environment places greater responsibility on both content creators and consumers. Experts must communicate more effectively and adapt to changing media habits, while audiences increasingly need critical thinking skills to evaluate competing claims.
Popularity and expertise do not always overlap. A widely shared opinion is not automatically correct, just as valuable expertise is not always the most visible voice online. Understanding this distinction has become an important part of navigating the modern information landscape.
Trust Is Increasingly Built Through Consistency
Perhaps the most important change is that trust is becoming more relationship-driven than institution-driven.
Consumers often follow the same journalists, analysts, educators, creators, and publications for years. Through repeated exposure, they observe how those sources handle new information, respond to mistakes, and communicate with audiences. Over time, trust develops through patterns rather than isolated interactions.
Consistency plays a major role in this process. Audiences tend to return to sources that repeatedly provide useful, reliable, and understandable information. They learn which voices prioritize accuracy, which communicate transparently, and which consistently deliver value.
Social media has not removed the need for expertise. Instead, it has reshaped how expertise is evaluated and communicated. Consumers still seek knowledgeable guidance, but they increasingly expect authenticity, transparency, and real-world relevance alongside traditional credentials. As these expectations continue evolving, the organizations that earn lasting trust will likely be those that combine expertise with clear communication and a genuine commitment to helping audiences make informed decisions.
i first started dabbling in therapy nearly a decade ago. i started with an older male therapist i found through betterhelp, to address what felt like outsize anxiety about my new relationship. we did a few brief sessions before he promptly told me i was fine and didn’t need more therapy.
a few years later, when i was working at square and feeling despondent about my life and career, i decided to try therapy again, this time at a practice by and for women in san francisco. it was... fine? i went once a week to talk to my therapist about what had been on my mind lately. she nodded and took notes. therapy is just a dedicated space for me to think through how i’m feeling about my life, i thought. there’s nothing a therapist can tell me about myself that i don’t already know.
after i moved to new york, the pandemic struck. i left square and started to search for what could come next. homebound and questioning my past choices, i picked up therapy once again, with lyra health, a corporate benefit through my partner’s workplace at the time. its focus was, unsurprisingly, productivity—how to deal with burnout and anxiety and depression so that you could return to achieving your goals. my therapist practiced cognitive behavioral therapy, which i came to view as capitalism’s answer to the problem of the self. identify your irrational thoughts so you can stop having them and get back to work! before long, it started to grate against me—it felt like a therapeutic modality designed to convince me that the only problem in my life was the insufficient policing of my own mind, and i already did plenty of that.
i decided to find another therapist outside of these online platforms maximizing for scale, at a real practice. after doing a round of consultations, i landed on a therapist with whom i clicked. she was warm, affirming, and funny, and we got along well. and it was good! we chatted weekly for four years. over that period of time, i was able to speak in more depth about deeper subjects—my family, my relationship, my fears. i cried a few times, even.
still, then, i couldn’t get over this feeling that therapy was just a weekly appointment setting for me to analyze myself and my life, where it wasn’t clear what it added beyond a protected time and a supportive ear. nothing was happening. it wasn’t aggregating toward anything; it wasn’t enabling me to perceive or behave differently. my problems kept recurring.
in fact, they got worse. eventually my therapist diagnosed me with generalized anxiety disorder. i wondered what we should do about that, but i wasn’t sure what could be done about it. i was the way i was, and i already knew exactly why. what else was there? so we kept doing our usual routine, where i would chat through what happened each week, how i had felt about it, and what the psychological causes and effects were. and everything stayed the same.
looking back, as an analytical person who intellectualized emotions so reflexively that i didn’t know there was any other way to be, i had run into the most obvious failure mode of talk therapy. when all my therapists were impressed by my emotional awareness and praised me for how thoughtfully i acted on my self-knowledge, i just thought i was doing a good job. when nothing shifted after years and years of what i believed was “doing the work,” i just thought that that was the limitation of what therapy could do. i couldn’t expect it to be transformative; the results might be slow and imperceptible, but it was better than nothing.
turning thirty last year led to a cascade of events that included leaving my therapist and seeking a new one, again. this time, i had a much clearer goal: to find a form of therapy that was less analytical and more embodied, as well as a practitioner intimately familiar with the hyperintellectualizer archetype. i wanted to, well, feel my feelings.
how did i arrive at this conclusion? ironically, perhaps, claude was a big part of it. i would use it to search for blind spots in my own self-perception, countering my automatic interpretations of events with a “neutral” third-party perspective. that was helpful, though limited. but what the process did reveal to me over time was just how often i would spiral into overthinking and how heavily i relied on analytical understanding in every single aspect of life. it turns out that using claude as an adversarial judge to discern the most objectively healthy emotional response to a situation and then diagnose the origins of why you aren’t experiencing it indicates a pretty specific kind of person.
the other part was the rise in popularity of less mainstream therapeutic modalities like internal family systems (ifs), somatic work, and psychedelic therapy in my social circles. i saw the effects play out over time with people i loved and respected, eroding my long-held skepticism of how much these kinds of interventions could really do.
so at this point i believed it was possible for therapy to be more impactful than it had been, but i was also now aware of how difficult by default it was to find the right fit. i decided to cast a wide net, scheduling a series of consultations with different practitioners—psychoanalysts, somatic therapists, ifs coaches. some had been recommended by friends, and others were people i had encountered online.
many of these conversations went the same way as my first several experiences of therapy. i would speak to a practitioner, and they would be surprised at how “articulate” and “self-aware” i was and inquire what i was hoping to get out of the experience given that i already had a handle on it all. earlier in my life, i would have been flattered; now it read as an anti-pattern. i would explain my history with therapy and what i wanted to be different this time, and they would agree readily to all of it without seemingly any real recognition of what i was saying.
only two of the conversations i had had the click where the practitioner instantly understood what i meant and had evidently undergone this experience on a personal level. both were coaches, not therapists, which gave me some pause. i was worried about the degree of rigor and professionalism; all the requirements (licenses and credentials, confidentiality, etc.) of therapy were nonexistent. plus, coaching was much more expensive. both of them charged three times the hourly rate of my previous therapist, which at the time had already felt like an exorbitant expense because it was uninsured. but the clear resonance was the one non-negotiable factor that i had been missing for years, so i decided to give it a try.
i chose the coach who had worked with one of my closest friends for a few years. she was the most perceptive of everyone i had met by far—in our brief consultation, she read me more quickly than perhaps anyone ever had. it was a novel experience. i was used to having to explain myself to be legible even to people who had known me for years. beyond that, she was trained in specific modalities like ifs and somatic experiencing rather than vaguely gesturing to “alignment” and “clarity,” which made the prospect of working with her feel more substantive than the average coaching experience.
our very first session reached a depth of emotional honesty and attunement that i hadn’t experienced in the decade of therapy prior to that. granted, i was in a period of overwhelming grief, and my emotions lurked closer to the surface than they ever had. but my default level of self-control meant that nearly everyone in conversation with me experienced that as factual information rather than my felt experience. she drew out the emotions, not just my accounts of them. one of the prompts she gave me was so psychoactive that, when i mentioned it to my sister and a few friends, two people cried just hearing it.
not every session was like that, of course. there were stops and starts, many iterations, points of friction and challenge. i struggled with the pace. i had imagined the rapid progress i’d make once i really applied myself; in reality, most of the year went to developing the capacities to even start the practices i had wanted to do. i kept waiting impatiently for the “real” work to begin, not noticing it already had. eventually, for the first time, i could see a path to an evolution of who i was, the surprising contingency of what i thought were fixed, load-bearing parts of my identity.
to do this kind of work well requires a level of perception and attention that most practitioners haven’t cultivated. what can this client receive? what’s the ask under the ask? what’s the feeling under the rationalization? calibrating to that in real time with a stranger is really, really difficult, especially with someone whose mental architecture is wholly foreign to their own.
therapy is a tricky job; the incentives can often be misaligned. both from a financial perspective and from a support perspective, it is hard for a therapist to say that they aren’t the right fit for you. but when you’re early in this work, less emotionally aware and less knowledgeable about the options, it’s difficult to locate yourself in what’s out there. the particular alchemy of what you need might be so hard to find that you conclude it must not exist. then again, maybe there’s no way around that; you blunder through it for a while, and you learn.
when i had offered up individual context to prior therapists—that i feel deeply and want to go there even when i’m less outwardly expressive, that i don’t think in words or images, that it helps me to have a course of action and directionality to the work—they had nodded in understanding and then changed nothing.
my coach, though, took in everything. nothing was dropped. she didn’t disavow my analytical mode, which i had been eager to do but with no idea of how to operate without it. she channeled it where it was productive and guided me toward developing other capacities where it wasn’t. my strength is understanding complex systems, identifying their faults, and addressing them, which means i can be remarkably clear-eyed about where in my life i’m not acting as the person i want to be and will put in a huge amount of work toward shifting those behaviors. it also means it’s much harder for me to accept the status quo of who i am as exactly how i’m supposed to be and not in need of fixing. but the analytical mode could be directed in service of flow over resistance, moving toward over moving from.
we built a working doc together that continued our work outside of sessions, now approaching probably a thousand pages of experimentation and observation. every tool was fluid and adaptive, rather than prescriptive—we worked to understand what resonated, what didn’t, and why. she tuned the work to be the right gradation, easing into depth, building up skills over time.
this same perception, directed at our relationship, turned it into a focal point of the work. she established our time together as a playground for learning and experimentation—not just saying it, but consistently reinforcing it. we worked through conflicts and misunderstandings, building trust over time that we could be honest with each other. she affirmed over and over again that i could not hurt her feelings with my feedback or reactions, or even if i decided to stop working with her. slowly, i started to believe her.
psychoanalysis has the concept of transference; the therapist-client relationship, then, becomes the site of a lot of the work as long-held relational patterns emerge within it. but, from my experience, few modern therapists know how to skillfully use the working relationship as a foundation for growth. many people aren’t looking for that from therapy in the first place—they’re looking for validation, comfort, understanding. investigating the tension in the working relationship risks disrupting that.
in my final session with my previous therapist, we discussed how we had worked together and why it hadn’t quite clicked. she told me that she had been going to her peer consultation group and asking, why does jackie keep coming back? i told her that i had been wondering to myself, why aren’t we ever going deeper? there was a deep connection in that honesty, after four years of not saying what we really thought. she hadn’t wanted to intrude past my comfort zone; i hadn’t wanted to make her feel bad. but the conflict avoidance on both parts had limited the relationship to a certain shallowness, despite how much we liked each other.
one of my other therapists offered a lot of frameworks. i would come with a problem, and she would hand me a printout with a process for dealing with it. none of the strategies were bad, per se, but we kept hitting walls. i always intellectually understood the first layer or two of what was happening, and i had these reasonable explanations at hand. “i care about having a budget because i need to feel in control.” “all my tasks need to be done before i can write so that my head is clear.” “it’s important to me that every choice i make is intentional and meaningful and not random.” she accepted them, and that was that. they were true enough.
but then what? we never asked the next question. why is that so important? i could supply a litany of surface-level reasons: i’m an oldest immigrant daughter, i had to become mature and responsible from an early age, my parents grew up amid abject poverty and scarcity, chinese culture values security and avoidance of risk, and so on. all of it was true, and none of it was the substance of the feeling. i never seriously questioned why i had these needs and why they felt so fundamental. they were just a feature of who i am.
my coach used her own frameworks, but in our work they became the lens to seeing what came next. they weren’t the terminal point, handed off to check the box of giving the client a tool. they were processes for gathering the information needed to go further or doing the work once you’d gotten somewhere interesting.
so we asked the next question. if most of my needs circle a deep fear of not having total control, of not having the ability to perfectly predict outcomes and have certainty, then what? perhaps the issue was not how i was following a framework, or how my life was organized. perhaps i needed to go upstream.
much of this past year i spent searching for the perfect answer, a beautifully wrapped reason tied with a bow. what i kept finding was that there was none—or, rather, there were a million, but they all came back to: “i don’t feel safe.” it was a frustratingly simple truth, one that couldn’t be made endlessly fascinating and analyzed into the ground. it just had to be felt.
if i can explain inner work in one way, it’s as a series of perceptual shifts.
my mind was a little room that i thought i had long since memorized. here’s where everything is. here’s how everything works. i know it all, i’ve lived here my whole life.
but over time, i looked around the room, and i noticed, oh, i thought that was a wall. but there’s a doorway. suddenly you see this door, and you open it. you peer inside this new room and realize, wait, i have been hearing this sound my whole life. i thought that was just what the world sounded like, but in fact, in this room, there is something making the sound, and i can just turn it off.
and then you do it again, and again, and again.
inner work is this continual expansion of the frame, where barriers of your mind that appeared immovable are in reality quite fluid if you find the right switch. inner work that’s working is able to gently widen this frame progressively over time, mapping the territory, finding the switches.
learning anything works this way, but it’s especially extreme when you’re learning yourself and your own mind. you’re so accustomed to your particular way of existing in the world that every contingent truth feels like a law of nature. on top of that, your mind is obscuring your field of view purposefully at every level to protect you.
i think of psychological defense mechanisms like reaching the boundaries of an open-world video game. an open world is supposed to feel infinitely expansive, but of course there are edges to the maps of most open worlds because the game designers didn’t, in reality, create an infinite world. so you will reach the outer bounds, but they don’t want to make it obvious that the world they’ve designed has these limitations. instead, your vision just starts to blur and fade out, or you find your character turning back toward the map without your directing it there.
that’s how it feels to not be ready for a realization. it just slides off you. often there’s this practiced quality to it, where your mind automatically replays some default response: “oh, of course, i know what’s over there,” and without quite noticing it, you’ve covered up the lack of deeper inquiry or engagement with this sleight of hand; you’ve turned back toward safe ground.
but a skillful practitioner can notice when it happens and say, “wait a second, i see you turning back from this direction. what if we look back there for a moment?” and that’s where the work takes place.
or it happens during a period of acute grief. grief turns your mind into a prison. you are trapped, and in your desperation you do everything in your power to find a way out. you start inspecting every nook, every surface, every shadow, with suspicion. and, it turns out, when you do that intently and for long enough, you usually do find a hidden doorway, or even a few.
i’ve often wondered whether it would have been possible for me to arrive at this place earlier. did i need to be wholly unmade to remake myself anew? or is it possible that, with the right practitioner, i could have done it before? it’s hard to say. grief without direction would likely have led me to cope in all the ways i already knew: rumination, achievement-seeking, self-control. and even the perfect practitioner, absent my willingness to question everything, might have found me impenetrable.
my defenses were so strong, so foundational to the person i believed i needed to be to move through the world, that i mistook them for my core self. i couldn’t imagine releasing the competence, the perfectionism, the certainty, these parts of myself i was sure i needed to be safe and, beneath that, to be loved. the perceptual shift was realizing that the walls weren’t protecting that; they were keeping me from feeling it.
as always, responses are my single favorite part about sharing to this newsletter, so if anything sparks a thought for you, i would love to hear it.
Desert Field Test With NASA Advanced Rover Prototype
PIA26701
Credits: NASA/JPL-Caltech
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Desert Field Test With NASA Advanced Rover Prototype
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Description
A prototype four-wheel rover developed at NASA’s Jet Propulsion Laboratory with advanced mobility and robotic autonomy capabilities trundled across the Colorado Desert near Plaster City, California, during a field test in March 2026. Called ERNEST (Exploration Rover for Navigating Extreme Sloped Terrain), the rover served here as a testbed for autonomy software developed for a potential lunar mission requiring higher speeds and much greater mileage than can be achieved with current planetary rovers.
ERNEST was trailed by engineers as it traveled about 16 miles over the course of 37 hours of drive time. That’s more than 10 times the speed at which NASA’s Perseverance rover can navigate on Mars. The team also tested how well the rover traveled at dusk, dawn, and nighttime to simulate the experience of large terrain shadows in polar regions on the Moon.
Figure A
Figure A shows the rover traveling toward its shadow.
Figure B
Figure B shows two team members setting up illuminators on the rover at night.
Figure C
Figure C shows three team members observing the rover during its long-range traverse.
Figure D
Figure D shows the rover with one wheel up on a rock.
Work on ERNEST began in 2022 and was initially supported by JPL internal research and development funds. It is currently funded by NASA’s Mars Exploration Program and the agency’s Exploration Science Strategy Integration Office under its Science Mission Directorate in Washington. Caltech in Pasadena, California, manages JPL for NASA.
A SpaceX Falcon 9 rocket stands at Space Launch Complex 4 East (SLC-4E) at Vandenberg Space Force Base ahead of the launch of the NROL-179 mission. Image: SpaceX
Update June 19, 6:11 a.m. EDT (1011 UTC): SpaceX landed the booster at Landing Zone 4.
SpaceX launched its third mission this year supporting the National Reconnaissance Office’s constellation of intelligence-gathering satellites.
The mission, dubbed NROL-179, launched an undisclosed number of satellites into orbit as part of what the NRO calls its proliferated architecture constellation. These are believed to be Starshield satellites, a government variant of SpaceX’s Starlink, though neither the NRO nor SpaceX has confirmed on the record that this is the case.
Liftoff of the Falcon 9 rocket from pad happened Friday, June 19, at 1:50:45 a.m. PDT (4:50:45 a.m. EDT / 0850:45 UTC).
SpaceX launched the mission using the Falcon 9 first stage booster with the tail number B1103. This was its third flight following the launches of Starlink 17-35 and 17-42 in April and May respectively.
Fewer than eight minutes after liftoff, B1103 returned to California for touchdown at Landing Zone 4. This was the 35th landing at that site and the 626th booster landing for SpaceX to date.
This was SpaceX’s 14th launch supporting the NRO’s low Earth orbit constellation and the third of the year so far. The NRO said it envisions having “hundreds of small satellites on orbit” in order to “provide greater revisit rates Ian increased coverage. And even eliminate single points of failure.”
The agency hasn’t disclosed the desired size of the constellation or many details about the scope of the network. It has said that it’s Geospatial Intelligence Systems Acquisitions Directorate (GEOINT) does contribute components to the proliferated architecture.
“GEOINT’s contribution to the NRO’s proliferated architecture includes electro-optical, radar, and relay satellites,” the NRO wrote in its prelaunch press kit. “Additionally, these relay satellites enable inter-satellite optical communications and serve as a key component of the NRO’s resilient communications architecture as well as the Department of War’s (DoW) upcoming Space-Data Network.”
China continued its accelerated launch pace with a series of missions, but long silence followed liftoff of a Kuaizhou-11 solid rocket Wednesday, suggesting potential issues.
We now have three more studies–from America, Australia and Canada–that find similar results using large numbers and credible research designs. Thus, I think we can up this to the Shingles vaccine reduces dementia.
If you are 50+ and have not gotten Shingrix vaccinated, you may want to consider that. You get protection vs Shingles (which can be dreadful), slowing of your biological aging (by methylation and RNA metrics), and ~20% reduction of dementia, predominantly related to Alzheimer’s disease. All of this benefit is magnified in women compared with men, but 3 of the studies showed some reduction of dementia in men. As a tradeoff, men appear to derive more cardiovascular benefit, but that evidence is not as compelling as protection from dementia from natural experiments.
Blue Origin has started rebuilding a launch pad severely damaged in a New Glenn explosion less than three weeks ago as it works to resume launches by year’s end
An Ariane 6 with upgraded solid rocket boosters successfully launched three dozen Amazon Leo satellites June 17 as ESA weighs options for increasing the vehicle’s launch rate.
Humans have always gazed up at the moon in wonder. A generation ago, NASA astronauts did the extraordinary and touched down on its surface, planting an American flag and igniting […]
Very important work from Hyunjin Kim and Rembrand Koning. Insead and HBS respectively:
We study how firms built around AI capabilities-“AI-native” firms-are organized. Drawing on Y Combinator batches W20-F24 and U.S. venture-backed startups whose first financing closed between 2020 and 2024, we classify each firm’s AI-native status and link it to workforce microdata on team size, function, seniority, and hierarchy. Relative to non-AI startups in the same industry-cohort, AI-native firms are 25% smaller. Their share of engineers is 13% greater, and the shares of entry-level workers and managers are each roughly 15% lower. Their hierarchies are half a seniority level flatter-yet valuations are comparable, implying more value created per employee. We argue these patterns reflect two channels: a process channel, in which AI changes how people work inside the firm, and a product channel, in which AI capabilities are built into what the firm sells. Using text from product descriptions and job postings, we find that embedding AI into the product, beyond layering on AI tools into existing workflows, is a primary way startups are scaling “knowledge work” without large teams of knowledge workers.
With over 100 million daily active users and projected revenue bookings of $7 billion this year, it is one of the largest gaming economies in the world—and one that has made millionaires out of teenage developers in Argentina, South Korea, and everywhere in between.
Tyler and Dave explore why Roblox decided early against prioritizing advertising revenue, why Dave thinks the main competition of Roblox is its own execution speed rather than Fortnite, whether every mega platform inevitably becomes an everything app, how falling token costs will change the platform, why he insists all the games on Roblox are beautiful, whether Robux should have a floating exchange rate, why admitting you have kids under 13 on your platform turns out to be a competitive advantage, why he’s skeptical of blanket social media bans, what his son’s experience with bipolar disorder taught him about metabolic health, his two-year sabbatical between companies that involved a motorhome trip across North America and a stint hosting talk radio in Santa Cruz, why Mutiny on the Bounty remains one of his favorite books, what he’ll learn next, and much more.
Excerpt:
COWEN: What percentage of your games now do you feel are beautiful?
BASZUCKI: All of them.
COWEN: Some look just quite ordinary. They might be fun, but I wouldn’t say they’re beautiful, right?
BASZUCKI: Well, I was trying to go a couple levels out of the box on you there. The reason I feel they’re beautiful is when you said that, I immediately went to look and feel, but then I tried to imagine the 12-year-old or the 18-year-old or the 30-year-old struggling to build something wonderful and the human connection to those games. By that definition, I think they’re all beautiful. They are all the efforts of creation of real people trying to pour their hearts out to make something that other people love to play.
On an artistic basis, I think you could ask me what percent of paintings in the MoMA do I think are beautiful. I’d probably say 20 percent. If I had to look at 1,000 Roblox games, I wouldn’t name which is more beautiful to me because I think that’s less important than really the heartfelt work of all the creators.
COWEN: I’ve been struck when I look at gaming at how much people don’t seem to care much about the visual beauty of their games. I would have expected something different, say, 15 years ago, and they just want a game that engages them somehow. Normal standards of visual beauty seem to have fallen away. Is that incorrect? Would you correct that impression in some manner?
BASZUCKI: I think you’re absolutely correct. What I feel you may actually be describing, if we looked into other disciplines, the evolution of story from the campfire to written to audio to a movie, and the increasing fidelity; all of those stories, in a way, are beautiful, but at the time, for the vast majority of the creators, it may be that writing is just easier than producing a 4K Hollywood movie. I feel that’s a little bit like the metaphor you’re talking about right now in gaming.
For the vast majority of people, their story or their idea for their game is actually pretty beautiful. Whether it’s a fashion game like Dress to Impress or it’s a grow garden game, the games are arguably beautiful, even if they don’t look photorealistic. What I think we’ll see is, over time, as AI helps accelerate the ability to make games look really polished in any style the creator wants—could be photorealistic, could be anime, could be a Warner Brothers 2D cartoon look—you and I might say that looks more beautiful, but the core gameplay is still somewhat the original gameplay. I think we are going to see games arguably look more beautiful, even though I think they’re all beautiful.
The dialogue is a bit slow to get underway, but there are many interesting parts.
Higher-than-normal sea surfaces (red) are visible in the central and eastern Pacific on June 8, 2026, a few days before El Niño was declared. Data for the map were acquired by the Sentinel-6 Michael Freilich satellite and processed by scientists at NASA’s Jet Propulsion Laboratory (JPL).
NASA Earth Observatory/Lauren Dauphin
El Niño, characterized by warmer-than-normal water temperatures in parts of the equatorial Pacific, made its return in June 2026. Observations of sea surface height from the Sentinel-6 Michael Freilich satellite that month indicated that the 2026 event was continuing to strengthen.
The natural, recurring phenomenon can have widespread effects, typically bringing wetter conditions to the U.S. Southwest and drought to countries in the western Pacific, such as Indonesia and Australia. NOAA declared an El Niño on June 11, after sea surface temperatures in the central and eastern equatorial Pacific measured at least 0.5 degrees Celsius above average for several consecutive months.
Meanwhile, NASA scientists have been observing a complementary sign of El Niño: areas of elevated sea surface height. When ocean water warms, it expands in volume and causes the sea surface to rise—making the water’s height a reliable indicator of ocean temperatures. Warmer-than-normal temperatures, hence higher sea surface heights, in parts of the equatorial Pacific Ocean are associated with El Niño.
The map above depicts sea surface height anomalies across the central and eastern Pacific Ocean as observed on June 8, 2026. Shades of red indicate sea levels that were higher than average. Normal sea level conditions appear white, and lower areas are blue.
Data for the map were acquired by the Sentinel-6 Michael Freilich satellite—launched in 2020 by NASA and led by ESA (European Space Agency)—and processed by scientists at NASA’s Jet Propulsion Laboratory (JPL). Note that signals related to seasonal cycles and long-term trends have been removed to highlight sea level anomalies associated with El Niño and other short-term natural phenomena.
Earlier in spring 2026, the satellite started to detect precursor signs of El Niño as swells of warm water hundreds of miles wide, known as Kelvin waves, moved from the western Pacific to the eastern Pacific. That happens when trade winds in the western equatorial Pacific weaken and then temporarily reverse to blow from the west. Warm water piles up in the east, deepening the warm surface layer, lowering the thermocline, and suppressing the upwelling that usually keeps waters along the Pacific coasts of the Americas cooler.
This buildup of heat beneath the water’s surface is what sea surface height observations capture. It goes beyond surface temperature measurements to indicate how much heat is stored in the subsurface. That’s important because a shallow warm layer might not have much impact on climate and weather, while a large reservoir of heat below the surface can matter more.
According to JPL sea level researcher Severine Fournier, deputy project scientist for Sentinel-6 Michael Freilich, conditions in the western Pacific on June 8 looked similar to those from the same time in 1997, a year when an exceptionally strong El Niño emerged. Warm conditions in the eastern Pacific in 2026 have lagged behind, however, with fewer Kelvin waves built up by the same date.
Still, more warm Kelvin waves appeared to be approaching the eastern Pacific, meaning El Niño was still strengthening. Whether it catches up to 1997 depends on ocean activity in the coming weeks. “For now, it looks like it’s going to be a big one—more so than I would have said last week—but we still need more observations to know what’s going to happen.”
NASA Earth Observatory image by Lauren Dauphin, using modified Copernicus Sentinel data (2023) processed by the European Space Agency and further processed by Josh Willis, Severin Fournier, and Kevin Marlis/NASA/JPL-Caltech. Story by Kathryn Hansen.
My favorite story of the week is the reflecting pool in Washington, D.C., which Donald Trump insisted needed to be re-painted the shade “American Flag Blue.”
So, because it’s 2026, a $14.7 million no-bid contract was presented to a Virginia-based firm he had some familiarity with (Atlantic Industrial Coatings, which had worked on a swimming pool at one of his golf clubs). The workers arrived, plopped down their tarps and brushes and and glue and the like.
And now the pool is (drumroll, please) …
Green.
And not Kermit green. Not New York Jets green. Not even beautiful lawn green. Nope, it’s the green I recall from my freshman year at the University of Delaware, when I drank far too much vodka and unleashed the entirety of my innards upon a porcelain bowl. Upon looking down, I saw … yuck. Puke green. The exact shade of the above image, taken by Jessica Koscielniak of Reuters.
Alas, this is the most Donald Trump thing ever. Fake gold turning brown. Fake silver turning red. It’s all a shell game to the 47th president; a paint-over-the-cracks-and-sell-the-house-as-perfect ode to swindles near and far. Trump wanted the Reflecting Pool to ooze perfection for the July 4th celebrations, but he never took a few minutes to study some essentials.
Namely:
• 1. A darker paint draws more heat. More heat draws more algae. More algae turn American Flag Blue to green.
• 2. Doing this in warm weather would only speed the rate of an algae infestation.
• 3. Not all pool companies are created equally. Just because you hired a firm to do your club pool doesn’t mean they’re capable of doing THE pool.
• 4. Tweeting stuff like this (“This was not a paint job. This was highly sophisticated material, industrial strength, that could last for 100 years, applied by very talented people”) only makes you look even dumber when it all goes to shit.
And now, here we sit. As we speak, men and women in rubber boots and gloves are wading through the green, dumping large jugs of hydrogen peroxide into the liquid with hopes of a revival.
A Reuters/Ipsos poll showed that even before a fighter launched a slur at former First Lady Michelle Obama, and even before the sight of the corporate branding at the event, only 16% of Americans thought it was appropriate to hold an Ultimate Fighting Championship fight at the White House.
Today, Federal Bureau of Investigation director Kash Patel, who has been in trouble with Trump over stories of his drinking, said the FBI discovered and foiled a plot to attack the UFC fight. The FBI alleged in an affidavit that nineteen attackers planned to target the fight with drones laden with explosives and then to shoot at the fleeing crowd.
Jude Joffe-Block, Lisa Hagen, and Audrey Nguyen of NPR noted in 2024 that Patel often peddled in conspiracy theories and, since taking on the directorship of the FBI, has tripped himself up in the past by announcing things that he later has to walk back. That history meant that social media users greeted the announcement with skepticism.
Tonight the Justice Department announced the arrest of five people in four states. Mark Berman, Amy B. Wang, and Victoria Craw of the Washington Post reported that Matthew C. Quinn, deputy director of the Secret Service, told reporters that the Secret Service had led the investigation and that the UFC fight “was never at risk due to the great investigative work.” In what appeared to be a reference to Patel, he added: “In order to maintain the integrity of the investigation and the security plan, we chose not to leak it.”
Meanwhile, Democrats on the House Judiciary Committee today issued a press release announcing they are launching an investigation into Patel’s alleged misuse of FBI funds. Representative Jamie Raskin (D-MD), the highest-ranking Democrat on the committee, says they have received information that Patel had directed more than $1 million in bonuses to agents close to himself. “These payments raise serious concerns that FBI funds are being used to reward political loyalty rather than merit and professionalism,” the Democrats wrote.
The FBI is part of the Department of Justice, and it, too, is undergoing a crisis of confidence in its work.
In Chicago, a case against six protesters for interfering with a federal agent and conspiring to interfere with a federal agent at a detention facility protest fell apart in May when the judge discovered that prosecutors had talked to individual grand jurors outside the courtroom and removed those jurors who refused to indict, as well as apparently overstating the strength of the evidence against the defendants. Then the prosecutors tried to hide evidence of their misconduct by redacting the transcripts from the grand jury.
As Julie Bosman of the New York Times reported, U.S. District Judge April Perry dismissed the case against the “Broadview Six,” saying: “I have read hundreds—if not thousands—of grand jury transcripts involving prosecutors who are the most junior of prosecutors to several U.S. attorneys who appeared before the grand jury. I have never seen the types of prosecutorial behavior before a grand jury that I saw in those transcripts.”
Today U.S. attorney for the District of Minnesota Daniel Rosen announced his office was charging fifteen people with conspiracy to impede or injure federal officers over their behavior during the federal immigration crackdown in Minneapolis last year that led to the deaths of U.S. citizens Renee Good and Alex Pretti. Rosen alleges that the defendants are part of two “antifa” groups that “violently oppose immigration law enforcement.”
At the press conference about the charges, prosecutors introduced a Facebook post from one of the accused that said: “We need to become ungovernable.” Journalist Aaron Rupar noted: “Oh, so they have NOTHING nothing.” It’s actually even more embarrassing than that: Trump attended the Libertarian National Convention in 2024 when its theme was “Become Ungovernable,” and stood in front of the banner bearing that slogan, so the idea that the phrase is part of a criminal conspiracy will be awkward to argue.
From Minneapolis, Matt Sepic of MPR News reported that Rosen said the people were “charged not for what they said but what they did.” But Rosen did not answer questions about whether any law enforcement officers were injured and said evidence would come out later. Sepic notes that federal prosecutors charged thirty-six people with assaulting or impeding immigration agents in December and January, but have now dropped eighteen of the cases entirely and eleven more through nonprosecution agreements. Sepic notes that Magistrate Judge David Schultz in April called one of the prosecutors’ charging documents a “false affidavit.”
At the time of the Good and Pretti killings, Open Measures, which tracks the spread of harmful social media activity, noted that right-wing social media personalities tried to redirect public outrage by claiming that community organizers using group chats on Signal were threatening the safety of federal officers. As those claims spread, right-wing media amplified old stories that those opposing ICE agents were “antifa” or part of a “radical left.” They demanded such chats be investigated. Today’s charges cited messages sent in Signal chats.
Reporter Christopher Mathias of MS NOW noted that while the Department of Justice is going after Minneapolis protesters, Greg Bovino, the commander-at-large of the Border Patrol during the Minneapolis crackdown that cost Good and Pretti their lives, has appeared on a white nationalist podcast as he teases a bid for the presidency.
Journalist Kat Abughazaleh, who is one of the Broadview Six, commented: “As the government raids “antifa groups” in Minneapolis with the SAME charges levied against myself and the rest of the Broadview Six, we need to be asking how they got this indictment. And as charges (hopefully) get dropped, we must remember the process is the punishment.”
But today’s charges have redirected at least some media energy from the details emerging about Trump’s “deal” with Iran. While the U.S. has declined to publish details of what appears to be a memorandum of understanding that participants hope will lead to a final agreement, Dov Lieber, Summer Said, Alexander Ward, and Rebecca Feng of the Wall Street Journal report that the agreement says the U.S. will waive sanctions to allow Iran immediately to sell oil and to access the banking, transportation, and insurance systems it will need to do so.
Alayna Treene and Kevin Liptak of CNN report that U.S. negotiators are downplaying the significance of the language in the memorandum of understanding, claiming that language that seems to favor Iran is designed to give cover to Iranian officials back home.
But Philip Wegmann and Lindsay Wise of the Wall Street Journal report that the vagueness of the language of the agreement is not fooling Republican war hawks who stood behind Trump in his attacks on Iran. They are calling early reports about the deal “disturbing” and “utterly disastrous.”
There is other news the administration would likely prefer to cover up, as well.
Sarah Blaskey and Jonathan O’Connell of the Washington Post reported today that even as Trump was assuring the American public that private donors would pay for his ballroom, the White House had already approved tens of millions of taxpayer money for the contractor building the addition.
With access to project summaries, the journalists were able to show that “internal cost estimates have been significantly higher than administration officials have acknowledged in public comments or court filings. They also show that the work was projected to rely heavily on taxpayer dollars from the moment it was announced.”
And Trump’s renovation of the Reflecting Pool by the Lincoln Memorial is having the effect experts warned of. Because of the dark paint on the floor of the pool, the sun heats the water up even faster than it did before, and the resulting algae bloom has turned the pool bright green. Today, workers poured hydrogen peroxide into the pool to try to kill the algae.
Snap is finally launching augmented glasses for the public. Specs,
which Snap describes as “a wearable computer built into
see-through augmented reality glasses,” will cost $2,195. You can
preorder a pair of Specs now at specs.com with a $200 refundable
deposit, and Snap says they’re expected to ship “this fall” in the
US, UK, and France. [...]
The company says that Specs are “fully standalone, with no puck
and no tether.” (Which is perhaps a jab at Apple’s Vision Pro,
which is tethered to a separate battery pack.) They’ll be offered
in two sizes, a 47mm model weighing 132g and a 52mm model weighing
136g, and will have removable inserts that Snap says will support
“a wide range of prescriptions.”
Unlike Vision Pro, Snap is presenting Specs as eyeglasses that users will wear out and about in their daily lives. Viewed perfectly straight-on and photographed by a professional fashion photographer — as presented on the Specs website — they’re a bold look. Viewed from any other angle and captured normally, they look like goggles, not glasses. The frames look orthopedic and the lenses are not even close to clear. They make you look like you forgot to take off your goggles leaving the theater after a 3D movie — goggles that are big enough to wear over regular glasses.
Maybe Specs are useful enough to justify looking so orthopedic, but I doubt it.
John Gruber of Daring Fireball joins the MacBreak Weekly panel
this week! A deep dive into Apple’s new Siri following WWDC. Why
Apple Intelligence & the new Siri are not coming to the EU
initially later this year. And could the iPhone Ultra’s launch be
delayed this year?
It’s fun to be the guest, not the host, of a podcast. I took Jason Snell’s usual panelist spot this week, alongside Leo Laporte, Andy Ihnatko, and Christina Warren. Lots to cover, including a week of real-life experience using the new Siri AI. (It’s really good!)
Also, sometimes you just know what the episode title of a podcast is going to be, the moment a phrase is uttered. This was one of those episodes, with “Intimate Functionalities”.
So where did Markdown come from? It came from John Gruber. John
joins the show, along with Anil Dash, to tell the story of where
Markdown came from and how it took over the world.
Markdown has been growing steadily for years, but it’s seen a step change in popularity now that it’s been embraced as the lingua franca of LLM agentic systems. I had an interesting all-too-brief chat last week in Cupertino with some people from Apple’s developer tools team about how it feels to see Markdown spread everywhere — including WWDC. In a word, gratifying.
But the biggest reason for Markdown’s continuing success isn’t Markdown itself. It’s the triumph of plain text files, both for system configuration and for the interchange of human-readable (and thus, LLM-readable) prose. Markdown isn’t really a “syntax”. It’s a set of conventions for formatting plain text. If everyone agrees to the same basic conventions, plain text can be significantly more expressive than a string of unformatted characters.
That’s it. So what I find gratifying isn’t that my “language” continues to thrive, because it’s not a language. It’s that the way I like to format plain text when I’m writing, and the way I like to see plain text formatted when I’m reading, has so thoroughly won the world’s mindshare battle. “Ha-ha”, I say, to people who want *this* to mean bold, not italic. (And to Slack and WhatsApp, I say “Fuck you.”)
The TPM Show will not be recording this week. We could say it’s because we’re riding high on the Knicks win, but really, we just had some scheduling issues. We’ll see you guys next week with a brand new episode!
The co-founder and CEO of Science Corp. joined me for our first-ever live podcast recording, which took place at the Brex headquarters in San Francisco. Thanks so much to all the Core Memory subscribers who turned up.
Max walked us through Science’s technology aimed at restoring vision in the blind, and the company’s new product lines focused on organ transplants and extending the abilities of brains. So, like, totally normal, everyday stuff.
Mostly, we talked about the merger of humans and machines and the progression of bio-tech and AI technology.
We’ve had Max on the show twice now because, for our money, he’s one of the most daring minds in the neuroscience and bio-tech fields, and there’s a decent chance that Science becomes one of the most fascinating companies in the world.
Thanks, of course, to Brex for hosting this event and to you guys for all the great questions.
The Core Memory podcast is on all major platforms and on our YouTube channel over here. If you like the show, please leave a review and tell your friends.
Timestamps
0:00 Intro 4:23 One Company or Three? Inside Science's Real Master Plan 6:25 Why Is Humanity So Bad at Curing Disease? 9:12 Implants That "Work" But Don't: Miracle or Mirage? 13:34 Restoring Sight to the Blind: How PRIMA Really Works 22:34 The BCI Gold Rush and the Money Problem No One Talks About 31:44 Keeping Human Organs Alive Outside the Body 36:52 Artificial Wombs and Bodies Grown Without a Brain? 41:23 Audience Q&A: Is the AI Biotech Boom Actually Real? 47:53 The Bet Every Other Bionic Eye Company Missed 56:02 Can a Brain Implant Make Us Superhuman? 1:05:04 What Will Surprise Us Most by 2035?
The United States, uniquely among advanced nations, fails to guarantee healthcare to all its citizens. Partly as a result, it has worse health outcomes than comparable countries, including substantially lower life expectancy. Perversely, the U.S. delivers these poor results while spending much more per person on healthcare than anyone else.
U.S. healthcare performance improved in terms of both coverage and cost after the Affordable Care Act, aka Obamacare, was enacted in 2010 and went into full effect in 2014. But much of what was achieved during the Obama and Biden administrations is now being unraveled by Trump II.
Today’s primer is the third and final in a series. Part I laid out the basics of healthcare policy, why universal healthcare is a desirable objective, and why some type of government intervention is essential to achieve it. Part II described how and why the U.S. adopted Obamacare and the ongoing Republican assault on its successes. In today’s primer I will discuss a possible path forward. That is, basically, what Democrats can and should try to achieve if they have unified control of the government after the 2028 election.
Beyond the paywall I will address the following:
1. U.S. healthcare in international perspective
2. What kind of system is workable in America?
3. The changing political economy of American healthcare reform
4. The path forward
U.S. healthcare in international perspective
The United States, alone among advanced nations, has failed to create a system of universal healthcare for its citizens. We also have uniquely high healthcare costs. However, it wasn’t until the 1980s that the U.S. system truly stood out for its poor performance.
The Peterson-KFF Health System Tracker compares U.S. performance on several dimensions with a Comparable Country Average, where the “comparable countries” are Canada, Japan, and several European nations. Circa 1980 the U.S. was roughly similar to other advanced nations in both health outcomes and cost. As the charts below show, since then our relative performance has worsened.
Here’s comparative life expectancy:
In 1980 US life expectancy was already slightly below that in other advanced nations (a fact that was often greeted with incredulity when stated in political debates) but the gap was less than a year. The gap in life expectancy is now more than 4 years.
And here’s one measure of costs -- health expenditures as a percentage of GDP:
By this measure, US healthcare spending in 1980 was already higher than spending in other wealthy countries, but the gap was modest — about 1 ½ percent of GDP. By 2010, however, the gap had widened to more than 6 percent of GDP, although it has narrowed slightly since then.
Moreover, if we look at spending per capita rather than spending as a share of GDP, the U.S. looks even worse, because US GDP per capita is higher than in the comparator countries.
U.S. healthcare, then, has performed very poorly on a comparative basis, spending much more money than other nations yet delivering significantly worse results.
It’s true that our relative performance improved after the enactment of the Affordable Care Act: The percentage of Americans without health insurance declined substantially, while the rate at which costs were rising slowed sharply. But the U.S. system under Obamacare, the result of difficult political compromises, remained awkward and jerry-rigged. In effect, it was a complex add-on that remedied some of the failures of the pre-Obamacare system but still left U.S. healthcare both far less fair and far less efficient than it should be.
And now, under Trump II and Republican control of Congress, even the gains since 2010 are under severe assault.
Looking forward, if MAGA is driven from power in 2026 and 2028, Democrats will have a chance to repair the damage. But times have changed: they should not settle for restoring the status quo as it existed in 2024. Post-MAGA, Democrats can and should aim for a more comprehensive healthcare reform with the aim of achieving universal coverage.
Let me not be coy here about what will be achievable. Given the realities of America’s money-driven politics, I believe that a single-payer system — rather than either direct government healthcare provision or regulated private-sector competition — is the reform most likely to succeed in achieving universal healthcare at acceptable cost. But rather than imposing a single-payer system and eliminating private-sector coverage, U.S. policymakers should offer Americans the right to buy into government healthcare coverage – the so-called “public option”.
Government healthcare coverage like the public option has significant advantages over private-sector coverage: much lower administrative costs for patients, doctors and hospitals, along with elimination of the profit-making incentives of denial of care or the padding of bills for government compensation. Over time it is likely that the public option will dominate as Americans will voluntarily shift to it and away from private-sector coverage. But for obvious political reasons, private insurers should be outcompeted rather than forcibly shut down. And if they can, in fact, compete with the public option on a level playing field, that’s OK too.
To explain why I recommend the public option, I need to address two topics: one, what is likely to work in policy terms; and two, how the political landscape has changed since the adoption of Obamacare.
What kind of healthcare system is workable in America?
In the first installment of my series on U.S. healthcare, I explained that there are three basic ways a nation can ensure that healthcare is available to all its citizens.
· The government can provide healthcare directly by paying for and running the delivery of healthcare — so-called “socialized medicine”.
· The delivery of healthcare is left to the private sector but the government provides health insurance to pay for it — the so-called “single payer” system.
· Both the delivery of both healthcare and insurance are left to the private sector, but private insurers are regulated and cross-subsidized in order to guarantee coverage for all. Obamacare fits into this last category.
All three approaches have been applied in the modern world — and all three are workable. Furthermore, we have partial versions of all three approaches operating in the United States right now, serving various segments of the population. Reposting a chart from my first healthcare primer:
The fact that many other countries manage to provide universal healthcare, while spending much less than the U.S. does, is really helpful for guiding reform here in the U.S. Healthcare isn’t one of those policy issues where nobody knows what will work, and reform must rely on untested theories. On the contrary, the world has abundant experience with systems that out-perform what we have, and we can use other nations’ experiences to construct a better system for America.
That said, America is exceptional — and when it comes to healthcare, that exceptionalism is overwhelmingly negative for the American people. To be blunt: Any effort to reform U.S. healthcare must take into account the way big money distorts both politics and policy to a greater extent than in any other wealthy nation. Generations of dysfunctional healthcare policy in America have created powerful interest groups that will attempt to corrupt any effort at reform.
How should our approaches to healthcare reform be shaped by these uniquely American political and policy realities? To answer that question let me discuss briefly each healthcare reform alternative.
“Socialized medicine”: A government-run system along the lines of Britain’s National Health Service, which directly employs doctors and nurses and operates hospitals and clinics has some clear advantages. Such a system can provide a higher level of integrated care rather than a patchwork of isolated treatments. It can prioritize care based on the judgments of medical professionals, directing resources to the procedures that deliver the most cost-effective health benefits. And government systems are probably less vulnerable than other systems to self-dealing – that is, doctors and other healthcare providers effectively directing medical spending to their own financial benefit.
Unfortunately, recent problems with the NHS highlight a key problem with such a system: Because it’s centrally controlled, it has a single point of failure. If badly managed from the top, it can fail comprehensively.
In the UK, the NHS has suffered from penny-pinching. A government trying to hold down spending will always be tempted to underfund healthcare, because cuts on the margin won’t have highly visible effects on healthcare quality until they reach a critical point. Given the way the United States has underfunded public services, especially at the state and local level, it’s very easy to see this happening to a government-run public health system.
And there’s also the question of whether political figures can be trusted to exert as much direct control over healthcare as they might in a direct-provision system. Again, to be blunt, imagine the whole system of medical care in America answering directly to Robert F. Kennedy Jr. or another crank.
So while socialized medicine can and in some case has performed admirably, it’s hard to see it as a safe role model for the United States. It might work, but there’s ample reason to worry.
Regulated private insurance: I wrote today’s primer in the Netherlands, where the main healthcare system is built around highly regulated private insurers. That system is widely regarded as highly successful. Could it work in the United States?
To some extent it already does. As I pointed out in my second healthcare primer, almost half the U.S. population is covered by private insurance provided by employers, which is effectively subsidized through the tax code and regulated because that tax subsidy requires that employers adhere to rules that prohibit discrimination based on health status or job title. Another significant chunk of the population is covered on the Obamacare exchanges, which subsidize highly regulated private insurance plans.
Yet given the power of money in U.S. politics and the power of the profit-seeking insurance industry, it’s unlikely that the United States could run a system centered on private insurers as well as the Dutch do.
And we already have a prime example of what can go wrong –the partial privatization of Medicare that was achieved through pressure from insurance companies. While Medicare originated as a single-payer component within the U.S. system, politicians subsequently allowed a significant carve-out in the form of the Medicare Advantage program. Medicare Advantage allows a large part of the funds to flow through private insurance companies. For such partial privatization to work, the government must “risk-adjust” payments to insurers – that is, paying less for healthy clients and more for patients with medical problems. Not surprisingly, insurers have been “upcoding” their clients, making their health seem worse and hence collecting extra payments. Moreover, the incentive to deny coverage for legitimate medical conditions still exists.
In the U.S. context, then, a system reliant on private insurers will inevitably be subject to gaming and some level ofcorruption. This is not to say that such a system cannot work— in fact, it does work to some extent for tens of millions of Americans. But given U.S. realities, along with our history of political and regulatory capture by big money, it is profoundly unwise to make regulated private insurance the heart of our healthcare system.
Single-payer, aka “Medicare for all”: Americans over 65 have lived under a single-payer healthcare system — standard Medicare — for 60 years. Tens of millions more are covered by Medicaid. These programs are hugely popular, and despite the growing problems caused by partial privatization have been relatively successful in containing costs. As the Congressional Budget Office has documented, costs for these programs are far below projections made soon after the Affordable Care Act was passed:
Single-payer isn’t a perfect system, but it is a system that has been run effectively not only abroad but in the United States. While I am by no means dogmatic about this, my view is that the next phase in U.S. health reform should involve an effort to transition away from private insurance to single-payer.
Longtime readers may recall that this was not my position in 2009-10, when Obamacare was being put in place. Nor did I support Bernie Sanders’s call for single-payer in 2016. However, like many and probably most supporters of Obamacare, I backed patchwork rather than comprehensive reform not because I believed that it was the best policy but because I believed that it was the only politically realistic way forward in 2010 and in 2016.
But it’s now 2026, and the political landscape has changed in ways that arguably put fundamental reform in reach.
The changed political landscape
Given the history of U.S. health policy, described in my previous healthcare primer, and the intensity of right-wing opposition to any expansion of coverage, the passage of the Affordable Care Act in 2010 was a political miracle. It was possible only because progressive policy experts had spent years hammering out a policy framework and because the 2008 financial crisis briefly gave unified control of government to politicians who listened to these experts.
Even so, it was a very close win— it would have never passed Congress without the extraordinary leadership of Nancy Pelosi, Democratic Speaker of the House. And thanks to constant political attacks by Republicans, the new law was highly unpopular for years. It gained strong public support only after Americans experienced its benefits and faced Trump’s 2017 efforts to kill it.
Given the current high popularity of the ACA, however, the political prospects for another major reform are good -- if and when we emerge from MAGA efforts to destroy it.
In addition, there is now very strong support for the idea that the U.S. government should, one way or another, ensure universal healthcare:
Another way in which the political landscape has changed in a way that is favorable to reform is the huge public backlash against the insurance industry. In my brief history of US healthcare policy I pointed to the key role insurers played in defeating the Clinton reform, most famously through the “Harry and Louise” ad campaign. Obamacare was designed the way it was, with a large role for subsidized private insurers, in part as a way to buy those insurers off and avoid a similar lavishly funded opposition campaign.
But health insurers are now immensely unpopular, especially over the issue of delays and denials:
The industry’s reputation is now so bad that a shockingly large number of Americans said that they approved of the 2024 killing of UnitedHealthcare’s CEO. As a result, while private insurers can and will throw money into a campaign against any healthcare reform that will reduce their profits, they won’t possess the veto power they had in the past.
Finally, if we are going to make a major effort at healthcare reform, it will come in the aftermath of four years of Trump administration destruction — destruction that is underway on many fronts, but in particular includes devastating cuts in Medicaid and Obamacare subsidies. The human cost of these cuts will be immense. But it may be easier to pursue more comprehensive reform amid the wreckage than would have been possible if we still had the sort-of acceptable system we had two years ago.
Arguably, then, if MAGA has been decisively beaten by 2029, the stage will be set for more than a restoration of the status quo ante. America will, instead, be potentially ready for more fundamental change. What might that change look like?
The path forward
As I’ve shown, there are three different approaches to universal healthcare, all of which can work and have worked in different countries. However, I believe that single-payer — the government provides insurance, but doesn’t directly provide healthcare — is likely to be the best system in terms of both providing adequate care and keeping costs manageable given U.S. political realities.
But how should we get there from here — or rather from the healthcare wreckage at the end of the Trump administration?
I still believe that it would be a political mistake to simply impose single-payer, requiring Americans to give up private insurance. Buying off the insurance industry is much less important than it was in the past, but it’s still difficult to sell people on giving up what they have in favor of something else, even if the replacement would be better.
Americans now dislike insurance companies far more than they did in the past. But most people with private insurance still say that they are satisfied with their coverage, although not as satisfied as Americans covered by Medicare:
This suggests that an attempt to push people into Medicare-for-all would run afoul of concerns about change.
But it would be much less controversial, I believe, to offer a public option — allowing Americans, including employers providing insurance to their employees, to buy into a Medicare-type system. Many people surely would avail themselves of that option. And if they like what they get, which they probably would, we could transition over time to a single-payer system without forcing Americans into it.
Of course, insurance companies would hate this, and campaign furiously against it. But given their current reputation, this might even help the cause of reform.
Now, I am not offering policy specifics, partly because this post is already long but mostly because this is the point at which we need details from real experts. And I am not at all dogmatic about the path forward.
The main point is, instead, that we are approaching a point at which ambitious healthcare reform, well beyond simply repairing the damage to Obamacare, will be possible. And Democrats should be prepared to rise to the occasion.
Brief post today on amazing things happening in the markets.
While I don’t know anyone who loves Microsoft or its products, it’s a wildly successful company with a long track record. Last year Microsoft earned $125 billion in profits on $318 billion in revenue.
In that same year SpaceX lost $4 billion on $19 billion in revenue. Robin Wigglesworth, editor of the Financial Times blog Alphaville, memorably described Elon Musk’s company as a
very successful but fairly small satellite launch company, bolted onto a stagnant money-losing social media company [X, formerly Twitter] and a money-incinerating AI company [xAI, operator of the widely despised model Grok], and then sprinkled with a lot of hype about humankind going interplanetary.
And yet at the end of trading yesterday the stock market placed almost as high a value on SpaceX, which went public last Friday, as it did on Microsoft, and slightly more than it placed on Amazon, which made $78 billion in profits last year.
What can explain this valuation? Many investors appear to believe that Musk is a wizard who can conjure up world-conquering inventions on a regular basis. But while Musk has done some impressive things, his track record for more than a decade has been one of failed venture after failed venture. And his current big ideas, like data centers in space, fundamentally don’t make sense. A recent Government Accountability Office report is carefully worded, but as I read it basically says “this is another Hyperloop [Musk’s absurd, failed attempt to reinvent public transportation].”
Granted, Musk has enormous political influence through his close ties to Donald Trump. So might SpaceX’s valuation be justified, not by Musk’s technological prowess, but by his access to the fruits of crony capitalism?
Nobody should doubt the Trump administration’s willingness to tilt the playing field in favor of its friends, especially those who enrich Trump personally. But there are limits to what even blatant favoritism can deliver.
Consider the current fate of the crypto industry. Trump, who once called Bitcoin a “scam,” became a passionate booster of cryptocurrency once it became clear that it was a channel through which he could profit from the presidency. The fighting cage he had erected on the White House lawn was “wrapped in cryptocurrency advertisements.” And cryptocurrency valuations soared after he won in 2024.
But the Trump bump for crypto has now vanished. Here’s the total market capitalization of Bitcoin over the past two and a half years:
At its peak, Bitcoin had a market capitalization similar to that of SpaceX now. Yet the fact that Bitcoin is economically useless for anything other than money-laundering meant that its soaring valuations rested on the belief that the crypto-friendly Trump administration would subvert regulations in its favor, for example by allowing crypto companies to effectively operate as unregulated banks. Hence, as I wrotelast year, crypto became a Trump trade, operating under the belief that Donald Trump’s patronage would overcome both economic logic and the opposition of the banking industry and many Democrats in Congress.
Sure enough, as Trump’s poll numbers began to sink, along with his political leverage, so did the value of Bitcoin. But those who got in on the Trump trade early, and sold their holdings to the Trump believers, made big money.
The particulars of SpaceX are different from those of Bitcoin – SpaceX does have one profitable division, Starlink, which was touted as the money-engine behind the SpaceX IPO. Only incredible growth in Starlink can justify SpaceX’s valuation. Yet an analyst who has dug deep into the numbers has shown that the Starlink valuations in the SpaceX IPO imply that Starlink will eventually dominate 80% of the global internet service market. That’s not remotely possible,
So the moral here is that SpaceX is essentially all about hype. It is, in effect, a $2.75 trillion meme stock. The only winners will be those who got in early, stoked a market frenzy, and exit before the bottom inevitably falls out.
Chinese AI lab Z.ai released GLM-5.2 to their coding plan subscribers on June 13th, and then yesterday (June 16th) released the full open weights under an MIT license. Similar in size to their previous GLM-5 and GLM-5.1 releases, this is 753B parameter, 1.51TB monster - with 40 active parameters (Mixture of Experts). GLM-5.2 is a text input only model - Z.ai have a separate vision family most recently represented by GLM-5V-Turbo, but that one isn't open weights. GLM-5.2 has a 1 million token context window, up from GLM-5.1's 200,000.
GLM-5.2 is the leading open weights model on the Intelligence Index v4.1. At 51, it leads MiniMax-M3 (44), DeepSeek V4 Pro (max, 44) and Kimi K2.6 (43)
They did however find it to be quite token-hungry:
GLM-5.2 uses more output tokens per task than other leading open weights models: the model uses 43k output tokens per Intelligence Index task, up from GLM-5.1 (26k) and above MiniMax-M3 (24k), Kimi K2.6 (35k) and DeepSeek V4 Pro (max, 37k)
The model is also now ranked 2nd on the Code Arena WebDev leaderboard, behind only Claude Fable 5. That leaderboard measures "front-end web development tasks, including agentic coding workflows". I'm impressed to see it rank so highly given the lack of image input, which I had incorrectly assumed was a key part of building a truly great frontend coding model.
I've been trying it out via OpenRouter, which has it from 9 different providers, almost all of which are charging $1.40/million for input and $4.40/million for output. For comparison, GPT-5.5 is $5/$30 and Claude Opus 4.5-4.8 is $5/$25.
Excellent pelican, disappointing opossum
GLM-5.1 gave me one of my favorite pelicans and my all time favorite opossum (for the prompt "Generate an SVG of a NORTH VIRGINIA OPOSSUM ON AN E-SCOOTER".) Interestingly, in both of those cases the model chose to return SVG wrapped in an HTML document that added additional animations using CSS.
Let's try GLM-5.2. For "Generate an SVG of a pelican riding a bicycle" I got this:
It's a self-contained fully animated SVG, and the animations aren't broken! Often I'll see eyes falling off or wheels rotating independently of the bicycle but here everything works great. It's a very nice vector illustration of a pelican too. Very impressive.
Sadly, the NORTH VIRGINIA OPOSSUM ON AN E-SCOOTER did not come out nearly as well:
This is such a step down from GLM-5.1! As a reminder, that possum looked like this:
What happened in 2025 was this: the economics of code production were turned upside down. Instead of being very hard, time-consuming, and expensive to generate code, it became effectively free and instant. Lines of code went from being treasured, reused, cared for and carefully curated, to being disposable and regenerable, practically overnight.
— Charity Majors, AI demands more engineering discipline. Not less
A progressive enchantment Web Component that turns this markup:
<click-to-play>
<a href="URL to GIF">
<img src="URL to first frame" alt="...">
</a>
</click-to-play>
Into a still frame with a click to play button which loads the GIF on demand. For when you don't want big GIFs to be loaded unless people want to play them.
Here's an example that demonstrates the new row editing tools in Datasette - in fact I built this Web Component for that post.
I find this inspiring. Brent Simmons retired a year ago, and his retirement project is making one piece of software really, really good - free from any commercial pressure.
The software is NetNewsWire - "it's like podcasts, but for reading" - first released in 2002 and made open source in 2018.
I've been using it on Mac and iPhone for several years now and I'm finding it indispensable.
Up before 4 o’clock, which is the hour I intend now to rise at, and to my office a while, and with great pleasure I fell to my business again. Anon went with money to my tar merchant to pay for the tar, which he refuses to sell me; but now the master is come home, and so he speaks very civilly, and I believe we shall have it with peace. I brought back my money to my office, and thence to White Hall, and in the garden spoke to my Lord Sandwich, who is in his gold-buttoned suit, as the mode is, and looks nobly. Captain Ferrers, I see, is come home from France. I only spoke one word to him, my Lord being there. He tells me the young gentlemen are well there; so my Lord went to my Lord Albemarle’s to dinner, and I by water home and dined alone, and at the office (after half an hour’s viallin practice after dinner) till late at night, and so home and to bed.
This day I sent my cozen Edward Pepyshis Lady, at my cozen Turner’s, a piece of venison given me yesterday, and Madam Turner I sent for a dozen bottles of her’s, to fill with wine for her.
This day I met with Pierce the surgeon, who tells me that the King has made peace between Mr. Edward Montagu and his father Lord Montagu, and that all is well again; at which; for the family’s sake, I am very glad, but do not think it will hold long.
Our landlords’ house was up at the top of the property, where you can see the trees at far upper left. The garden was on raised beds below the house. The shakes were handsplit from downfall redwood logs.
I built this house in 1967–’68 at Burns Creek in Big Sur, California (about two miles north of Esalen). It was on a 40 acre piece of land owned by Boris and Filipa Veren (whose home was at top left where you see the trees). We signed an agreement (drawn up by my friend, lawyer Tony Serra) whereby I could build a house on their land in exchange for my wife Sarah running Boris’ Craft and Hobby Book Service, a mail order operation, when the Verens traveled.
Details for Builders The 14 posts were 12-foot-long 6″ by 12″ double-track railroad ties on 8′ centers. The girders, as well as the rafters were 30-foot-long, 2-by-14’s that had been salvaged by Cleveland Wreckers from an old horse stable built in gold rush days in San Francisco.
The foundation was a grade beam with concrete delivered (40 miles down the coast) from Pacific Grove,. At 14 spots on the foundation, I enlarged the footing and left 4 pieces of steel rebar sticking up.
After it cured, I placed Sonotubes over each pad, mixed and poured the cylindrical columns (wheel-barrowing wet concrete I made with the family concrete mixer). Steel brackets embedded in the columns secured the posts and girders as shown below.
Here you see the use of the 30’ 2-by-14’s for both rafters and floor girders.
Exterior sheathing was lumber from a farm labor camp I tore down in Salinas, and the shakes (on top of the sheathing) were split (with a froe) from deadfall trees I found in Palo Colorado Canyon. I used studs in between the posts.
Roof decking and flooring were 2-by-6 Monterey Pine T&G from Carmel Valley.
For shear panels (diagonal bracing) on one 8-foot-wide section of each of the 4 walls, I used ⅝″ plywood nailed 2″ on centers around the edges and 6″ o.c. on the interior studs. I used annular grooved nails, way stronger than smooth nails.
It took me about a year. I did all the carpentry, plumbing, and wiring. It was a very simple house, a big shed really, and the carpentry was — ahem, less than exquisite — but it got a roof over our heads.
Total materials costs were $8,000 (about $80,000 in 2026 dollars). Talk about affordable housing!
On this wall I used the 2-by-14s as horizontal sheathing. The house had a lot of windows on this side facing east for the morning sunrise.
In those days, due to my discovery of the Platonic solids while building domes, I was fairly obsessed with the strength of triangles.
I developed a water supply by building a little dam in a spring above the house, and running 600′ of plastic pipe down the hillside. I started some small-scale farming and we had a big garden. I would pick up fish guts in a 50-gallon drum on the Monterey wharf (in our 1960 VW van) on our weekly shopping trips into town.
There were a few things about it that didn’t exactly fit the building codes, so once when the building inspector came, I put on a Jimi Hendrix record loud when I saw him pull up:
You know you’re a cute little heartbreaker …foxey lady…
…and he was so rattled that he didn’t notice the non-compliances.
This was when Barbara Spring lived in the house. She was a fairly well-known artist who did life-size wooden sculptures (horses and humans). I left her the table, made out of the 2-by-14s and with legs that are two sections of a 16-by-16 redwood bridge timber.
When I decided to leave Big Sur (and embarked on a 5-year period of building geodesic domes), I sold the house to the owners of the land for $11,000.
Item of interest: Barbara Spring, an artist who bought the house from the land owners in the early ’70s, was a friend of the architect Phillip Johnson (post-modern architect known for his Glass House, and co-designer — with Mies van der Rohe — of the Seagram Building in NYC, etc.). Johnson and his partner David Whitney were looking for a house to buy in Big Sur and when they came to visit Barbara on a rainy day (with the Ashley Automatic wood stove warming the house), Phillip told her this was the kind of place he would love to find.
Post note: Philip and David eventually bought a beautiful light-filled cottage overlooking the ocean, but it was heartening that he dug the soul, if not the fine carpentry of my house.
Barbara told me a number of times that she loved the house.
The present owners (Barbara’s daughter and husband) also cherish the house. I visit once in a while, camp out next to a studio on the land, and use the pool. (And sneak into Esalen Hot Springs at night — heh heh — under cover of darkness.)
This pool was in the creek below the property,. No chlorine, kept clean with running creek water. Every night after work I’d walk down to the pool, bow (Japanese oiji style, but with hands in prayer position under chin) to the family of redwoods behind the pool, then in the four directions, and dive in. What a way to end the day — hey, it was the ‘60s!
On 14 April, the Trump administration quietly acknowledged the widespread use of AI to automate government processes. The office of management and budget (OMB) disclosed a staggering 3,611 active or planned use cases for AI across the federal government. The list has ballooned by 70% from the one published in the final year of the Biden administration, and includes many disturbing-seeming plans to hand over sensitive governmental functions to AI.
Scanning this list, many readers may find many causes for alarm. It represents a transfer of decision processes from human to machine on a massive scale over matters of individual freedom, public health and well-being, nuclear reactor safety and more.
Consider these examples. The Health and Human Services’ (HHS) office of administration for children and families hired the world’s “scariest AI company,” Palantir—notorious for its work on behalf of the military, the CIA and ICE—to scan all grant applications to flag those not ideologically aligned with the administration’s dictates. The Federal Bureau of Prisons is developing an AI system to assess the “potential for misconduct for newly admitted inmates,” routing people into high-security confinement before they have actually done anything wrong in their custody. These read like programs fit for a Philip K Dick or George Orwell novel.
Other use cases insert AI into life-and-death decision making. The Department of Veterans Affairs is developing an AI that will listen in on calls to the veterans crisis line, and then gather information from external databases to assess the mental state and suicide risk of the caller.
The Department of Energy is testing the use of AI to control nuclear reactors, targeting a way to autonomously respond to potential nuclear safety incidents. Here’s one that’s disturbing for its retirement, rather than its deployment: the state department has ended a program to use AI to forecast mass civilian killings, which had been intended to aid conflict prevention.
While it’s easy to raise questions about these and similar uses of AI, the reality is that any of these programs could be implemented responsibly. In some cases, like the HHS system, the AI might be enforcing alignment to a policy prescription that opponents abhor. But that concern is more about the policy itself rather than the idea that agencies should comply with executive orders.
In other cases, there may even be bipartisan agreement on the goal, like taking urgent action to help veterans at risk of self-harm. Lots of work and validation is needed to prove AI safe and effective for these use cases and convince the public it is appropriate, but the idea is plausible.
In other cases, a scary-sounding AI use may not even be new. The use of predictive methods and statistics to assign prisoner security classifications goes back decades, even if such systems are often biased and ineffective.
Using autonomous systems for model predictive control (MPC) of nuclear reactors is a well studied, and a widely applied aspect of nuclear plant management. And the recently disclosed addition of AI was initiated under the Biden administration.
But anyone reviewing the 2025 inventory could be forgiven for leaping to severe conclusions. What matters are the details of how the AI system is used, and here the inventory is severely lacking.
The disclosures carry minimal information, and lack the context necessary to understand their purpose and approach. The descriptions are typically just a sentence, and rarely more than a paragraph.
And while the process theoretically involves some form of public consultation, in reality there is generally none. It would take an eagle-eyed citizen to even come across this disclosure. Unless you read FedScoop regularly, or watch the OMB’s federal chief information officer’s GitHub account, you probably missed it.
Only one of the examples cited above (the DoJ) even proposes to involve the public. Under the administration’s policy, it’s not required for the rest because they are not classified as “high impact” use cases—a label that is applied inconsistently across agencies.
We wrote a book surveying applications of AI to democratic processes worldwide, including executive agencies as well as the courts, legislatures and politics. Our conclusion was that, while there are inappropriate applications of AI in governance that should be resisted, an urgent need to reform the economics of AI, and an imperative for renovating the democratic systems it is being unleashed on, there are also valuable and beneficial use cases for AI in government.
Machine translation is a good example. Customs and Border Protection (CBP) has deployed an AI translation system to help officers when human interpreters are not available. The idea that CBP, an agency under heavy scrutiny for reported abuses of human rights, would direct people to talk to a machine instead of a person may strike many as inhumane.
It’s true that human interpreters have very real advantages when it comes to understanding nuance from physical cues and social context. But an officer with a competent AI translator available immediately is better than one who cannot communicate with the person in front of them.
The Trump administration’s AI use case inventory has 70 such translation use cases, up from 58 in the Biden administration’s 2024 disclosure.
Disclosure of AI use cases could be a means to build public confidence and trust, but only if paired with consistent, meaningful public consultation. Washington DC and California are actively engaging the public to determine where and how it’s appropriate to use AI in government processes, or for government to regulate AI use in society.
Both have held public deliberations on this topic at a wide scale, using AI platforms. These examples demonstrate the potential for capturing broad-based public input to steer AI policy.
The international gold standard was arguably set by the French in 2016, via their Digital Republic Act. The law, itself informed by an online citizen consultation, requires all algorithms used to automate government administrative decisions to be subject to public records requests, to be appealable to a human reviewer, and to have mandatory notification of the use of automation to those affected by the decisions.
Canada offers another example of what more rigorous and participatory disclosure might look like. In 2025, they launched an AI use case registry, not unlike the US inventory. However, Canada also has a federal directive mandating a transparent risk-scoring and impact assessment process for automated systems that make administrative decisions about citizens.
That longstanding directive requires a detailed explanation of risks and benefits as well as consultation with certain stakeholders from the conception of the AI use case. The Canadian system could be improved; it could require a public comment period and an obligation for agencies to respond substantively to feedback before engaging in sensitive uses of AI.
AI offers real potential to improve the efficacy, efficiency and accessibility of government. But, equally, there is legitimate reason for public concern and distrust that can only be addressed through transparency and dialog. The US should adopt, at the federal and state level, algorithmic impact risk assessment procedures and public comment processes to facilitate a safe, trusted, equitable transformation of government agencies to take advantage of modern technology.
This essay was written with Nathan E. Sanders, and originally appeared in The Guardian.
Yesterday, the mainland colony known as the District of Columbia had its primary elections–and for all intents and purposes, the Democratic primaries are the de facto election (there wasn’t even a Republican candidate for mayor on the ballot). Some comments, with the earlier ones being more of a summary of where things currently stand with around two-thirds of the first rank ballots having been counted, with the latter points discussing What It All Means:
For mayor, Janeese Lewis George has a commanding first rank lead over Kenyan McDuffie, 53-37. While it’s mathematically possible for McDuffie to win–and there’s no reason for him to concede right now–that doesn’t seem likely. Interestingly, Lewis George has done well everywhere: even in Ward 3, she is currently down only 43-46 (more on that below).
For the citywide At-Large Council position, Oye Owolewa, the most progressive candidate has 33.8% of the first rank votes, which, to me, is (pleasantly) surprising–though he is a very personable, likeable candidate. That said, if Owolewa doesn’t win a majority of the first rank votes, I would not be surprised to see Chavous do well, as I suspect he is many voters’ “safety vote.” It’s really too early to tell how this race will turn out.
For (non-voting) Congressman, Robert White has a commanding lead over Brooke Pinto, 63-21. I suspect that Kinney Zalesne’s first rank voters (she’s in third at 7.7%) will lean White, so I think it looks good for White.
The insurgent Free D.C. slate for Democratic Party ward committee members seems to have done very well so far (note these are party positions, not governing positions). That said, with more votes to be counted, it’s too early to call any of these, but right now, it is looking good for the slate as a whole.
Assuming the mayoral vote holds up, there will be a trivial storyline about “DSA versus moderates.” I use trivial as a pejorative because I actually think it explains very little.
First, given the Free D.C. slate results, there’s a lot of anti-incumbent energy, and McDuffie is viewed as the old guard, while Lewis George is not. Second, polling suggests that the most successful issue for Lewis George is housing, while McDuffie’s is crime prevention–and, as I keep noting every week, crime has dropped massively over the last three years. It’s just not as salient an issue as it would have been a few years ago. Ironically, to the limited extent that Trump’s fascist surge has been successful in reducing crime–arguably it has with respect to car-related crimes and perhaps muggings–it strengthened Lewis George, whom Trump has publicly attacked. There’s a renters versus homeowners angle here too. Finally, McDuffie has personal issues. He is seen by many as a chameleon who changes his views constantly. He attacked Lewis George’s family during the campaign, and he initially tried to run as the competency candidate, which is a problem when you’re not that competent. In addition, Lewis George hammered both of these themes by arguing he has not done a good job overseeing electricity rate regulation and reminding voters of his attempts to water down some other good legislation.
Put another way, Lewis George isn’t currently down by only three points in Ward 3 because Ward 3 is full of socialists (lmfao).
The real wild card right now in all of this is the At-Large Council position. If Owolewa manages to win, that really changes things regarding the composition of the council–and I think Owolewa also has a bit of Mamdani-style charisma (I joke how Mamdani reminds people of that nice young doctor that time they had to go the emergency room, and Owolewa, who is a pharmacist, can actually fill that role).
The Washington Post editorial board must be really upset right now, which is always a good, deserved thing.
Anyway, with more votes to be counted, you can look at the data yourself here and here.
Jessica Kerr joins Kent by the fire to argue that AI didn't take the programmer's job, it split it in two. The part we loved, crafting code by hand, has been commoditized like IKEA furniture. What's left is harder and more human: understanding what to build, proving it works, and stewarding the living "symmathesy" of people, code, and agents all learning from each other. They get into accelerated learning, why play is a signal you're learning, the loop that "becomes a noose," and choosing excitement over fear while the ground keeps shifting.
Latin America’s momentous fertility transition is now in the domain of history, allowing a cohort perspective on the decline of completed fertility. Using census microdata from 17 Latin American countries, we track female birth cohorts from the 1920s to the 1970s by subnational region to document the extent to which cohort fertility decline coincided with other demographic and socioeconomic processes. Across cohorts within subnational regions, children ever born fell one-for-one with mortality decline. Expansions in urbanization, multigenerational living, women’s and husbands’ education, women’s employment, and the non-agricultural sector all predicted declines in ever-born and surviving fertility, but women’s education and sectoral composition were the dominant forces after covariate adjustment. Fertility decline was not systematically linked with improvements in children’s outcomes, including school enrollment, literacy, primary completion, and non-employment. These cohort facts challenge theories of fertility decline centered on women’s work and children’s education but support others emphasizing women’s education.
I fear that means the women think they are finding better and more fun things to do? Which is hardly bad per se, but…
The online conversation has become an incredibly powerful tool in influencing the reputation of any brand. The opinions, reviews, and feedback that consumers leave on social networks, discussion forums, blogs, and review websites can influence a brand’s reputation within hours.
It is vital for a brand to detect possible issues and warning signals from online conversations in order to respond and prevent a reputational crisis.
Brands can improve their relationships with clients, increase consumer trust, and prevent future crises with proper monitoring of online conversations. The article below will explain why early warning signals are crucial, how to identify them, what to track, and how to react accordingly.
What is brand tracking?
Brand tracking involves monitoring and analyzing the overall health, awareness, and perception of a brand. It enables companies to learn how people perceive the products or services of an organization, including their quality and reputation.
Brands track various metrics, including survey results, analytics, consumer feedback, and even online conversations through social listening to identify any shifts or trends in consumer behavior and attitude.
Brand tracking provides answers to the following questions regarding brand reputation and customer relationships:
Are consumers familiar with the brand?
What do consumers think about the company?
How loyal are the consumers?
Does the brand compete well against other companies?
What motivates people to buy?
Who are the brand ambassadors?
Ultimately, brand tracking makes it possible to detect abnormalities in consumer behavior, attitude, and online discussions about the brand.
Importance of early warning signals for businesses
The online conversation evolves at an extremely fast pace. An unsatisfied client can create and share a negative review in less than a minute, which is likely to be seen by many other users and draw considerable attention.
Early warning signals are useful because they make it possible to prevent possible negative developments before they start, thus protecting the brand’s reputation, increasing customer loyalty, reducing backlash, and addressing complaints promptly.
Early warning signals are an indispensable part of the current reputation management strategy for any brand.
Possible early warning signs
Increasing Number of Negative Mentions
If there is a growing number of complaints about a particular topic online, a warning signal should alert the business. Complaints are usually related to such aspects of products or services as:
Quality defects
Poor customer service
Bills
Delay in delivery
Technical troubles
Abnormal Sudden Increase in Conversation Volume
Sudden increases in the conversation volume are a sign that something is becoming viral and gaining popularity. Such increases occur when:
Customers complain online
Advertisements raise controversy
Products are recalled
There are negative articles in the mass media
Brands detect such sudden increases in conversation volumes immediately to find out the reason.
Quick Shifts in Sentiment Trends
Sentiment analysis allows finding out whether online conversations are positive, neutral, or negative.
Sudden increases in negative sentiment trends usually mean that there is:
Consumer dissatisfaction
Public anger
Ethical issues
Service failure
Issues with policy
Monitoring shifts in consumer sentiments helps brands detect warnings about abnormal conditions.
Increased Media Coverage of a Topic
If mass media start mentioning a certain issue related to a brand, chances are the discussion will grow rapidly and negatively impact the company’s reputation. Consequently, the media coverage should be considered as an early warning signal about a possible crisis.
Mentions by Influencers and Celebrities
Consumers who have popular social network accounts, influencers, and celebrities can make a topic go viral in a matter of hours.
Such mentions are associated with:
Viral discussions
Trending hashtags
Mass media involvement
Bad publicity
Thus, brands monitor these social network accounts closely.
Conversations Regarding Competitors and Industry
Sometimes, brands detect warning signs in conversations with other companies and industries.
The following are possible warning signs that should be monitored:
Privacy and data protection
Product safety issues
Environmental issues
Labor problems
Monitoring industry conversations allows for preparing for problems ahead of time.
Main focus areas for the crisis management strategy
Establishing Benchmark Values
All brands receive occasional negative mentions online. The problem is that sometimes, the level of negativity becomes unusual.
In order to detect abnormality in online conversation trends, a benchmark system is established with the help of metrics like:
Normal daily number of mentions
Normal number of complaints
Normal sentiment score
Normal engagement rate
Normal media coverage
Whenever abnormal values emerge in online discussions, brand monitoring tools like Sprinklr Insights, Brandwatch, and Meltwater will send you notifications about that.
Monitoring System Implementation
Monitoring online conversations about a brand is crucial for detecting early warning signs. Brands monitor discussions related to:
Brand names
Product names
Services
Executives
Competitors
Industry terms
Hashtags used in campaigns
Customer complaints
Monitoring systems provide real-time information about online conversations and opinions about a brand and its products or services.
Utilizing Social Listening Platforms
Due to the incredible amount of data that is posted online every minute, businesses require customer experience software and social listening tools for monitoring purposes.
Modern monitoring systems allow focusing only on those conversations that relate to your brand specifically.
Identifying Key Words and Phrases
Keywords are phrases and terms that are used to detect early warning signs and trends related to a brand. For example, keywords for a food delivery brand can include:
“Late delivery”
“Incorrect order”
“No refund”
Competitors’ product names
Industry-related phrases
Branding-related terms
Creating Alerts for Key Phrases and Mentions
Automatic alerts are the simplest and most efficient way to identify abnormal online activity and warning signs. The alerts can be configured to track the following metrics:
Increased volume of mentions
Increase in negative sentiment
Virals
Influencer mentions
Customer complaints
Security and privacy issues
Products-related mentions
Media mentions
Automatic alerts keep brands informed all the time about the current situation on social media and other platforms.
Conclusion
Today, online conversations have a great impact on the image of any brand. People expect companies to listen to them and address the raised issues.
By implementing brand tracking, monitoring, sentiment analysis, and early warning signals monitoring systems into their reputation management strategy, businesses can effectively prevent and deal with crises.
Rupert Lowe, member of the British Parliament and leader of the Restore Britain party, released The Rape Gang Inquiry yesterday. It details the industrial-scale sexual atrocities committed by predominantly Pakistani Muslims against mostly White British girls in the United Kingdom over decades. It's the stuff of nightmares.
In fact, it's so grim, so vile, and so dark that I can't in good conscience recommend reading the graphic details directly (even just a summary of the accounts is traumatizing). But at the same time, you can't look away either. The report estimates that 250,000 British girls have been victims of these rape gangs over the decades. It's an unimaginable scale of horrors.
The closest comparison to these accounts is the atrocities committed during times of war, but somehow this seems worse: The terror did not come as a result of losing an armed conflict, but aided and abetted by the national institutions sworn to serve and protect. From the report:
Police forces ignored repeated reports, criminalised victims instead of perpetrators, destroyed evidence, and allowed known rapists to walk free on bail.
Social care services undermined protective parents, placed children in trafficking hubs inside children’s homes, closed cases despite clear indicators of exploitation, and retaliated against whistleblowers.
The NHS recorded genital injuries, multiple sexually transmitted infections in children as young as 13, pregnancies caused by rape, and suicide attempts, yet discharged victims back to their abusers without safeguarding referrals or trauma care.
Schools observed older men collecting girls at the gates, heard disclosures of rape on school premises, and responded by excluding victims rather than protecting them.
Taxi licensing authorities renewed permits for drivers who formed the logistical backbone of the networks and collapsed in the face of organised protests when basic safety measures were proposed.
But that's the collective, general assignment of complicity. The specific examples are so much worse. I promise I won't haunt you with more, but here's just one example from the report:
When Fiona's mother called the police to report her daughter missing and mentioned a history of abuse by Asian men, the call handler told her: “You can’t describe them as Asian men because that’s racist. You should just be glad your child is being taught a different culture.” On one occasion, a police officer returned Fiona to the house where the abuse was occurring and told the men to “have fun with her.” On another occasion, police instructed the abusers that if they could persuade Fiona to sign herself out of care, the police would stop bothering them.
Now let me touch on two related topics. First, the BBC reported yesterday that trust in traditional media is plummeting in many places, but the fall in Britain has been particularly steep:
The research published on Tuesday suggests that public trust worldwide is at 37%, three points down on this time last year. In the UK, it has fallen by five points to 30% - 20 points lower than 10 years ago.
So in 2016, half of Brits had trust in traditional media, like the BBC. Now that's down to 30%. Grim. So imagine my surprise when I couldn't find a single mention of The Rape Gang Inquiry on the BBC's news site from neither yesterday nor today. You don't have to be Sherlock Holmes to deduce a connection between narrative-driven coverage (and absence of it!) and lower trust.
Second is how the UK wants to track everyone's social media use under the guise of restricting access to those under 16. Which requires every adult to verify they're of age by providing a digital ID, passport, or credit card. Thus ending any hope of anonymity online. All wrapped in Protect The Childrendressing.
So a state that not only failed to prevent these sexual atrocities, but in many cases abetted the horrors, now wants to end anonymity online to "protect children", so it can prosecute even more regime critics? The same country that leads the world with 12,000 yearly arrests for online speech already? It's painfully on the nose.
It's tragic what the Brits have had and continue to endure. They deserve so much better. Especially these abused children detailed in Lowe's report. And making them wait much longer is a dangerous cocktail.
An Arianespace Ariane 64 rocket lifts off from Europe’s Spaceport in French Guiana to begin the Leo Europe 03 mission for Amazon Leo. This mission carried 36 broadband satellites onboard, the heaviest payload launched by an Ariane launcher. Image: ESA-CNES-Arianespace-ArianeGroup \ Optique Vidéo de CSG – T Leduc
Update June 17, 11:20 a.m. EDT (1520 UTC): Arianespace confirms deployment of all Amazon Leo satellites.
Arianespace launched its largest and heaviest payload to date on a version of its Ariane 6 rocket that incorporated new solid rocket boosters Wednesday morning.
The mission was designated VA269 by Arianespace and Leo Europe 03 (LE-03) by Amazon. It sent 36 Amazon Leo broadband internet satellites into low Earth orbit.
This was the third of 18 Ariane 6 flights booked by Amazon Leo to deploy its constellation and followed successful flights in February and April.
“We have both institutional and commercial clients and our main and biggest client today is Amazon. And I must say, we are very proud to work together,” said David Cavaillolès, CEO of Arianespace, during a pre-launch press briefing. “For me, it’s much more than a contract. It’s really a partnership.”
Liftoff from Europe’s Spaceport in French Guiana happened at 9:21 a.m. Kourou time (8:21 a.m. EDT / 1221 UTC).
While all three of the Amazon Leo missions for Arianespace have used the Ariane 64 configuration of the rocket with four solid rocket boosters, the LE-03 mission will debut the upgraded version, called P160C.
Compared to the predecessor P120C design, the P160C is a meter longer and holds about 156 tons of solid propellant. That’s about 14 more tons than the P120C boosters, allowing for a 10-15 percent increase in performance for the launcher.
The P160C boosters can produce 3,800 kN of thrust each at liftoff compared to 3,700 kN of thrust from the P120C boosters. This iteration of the Ariane 64 can deliver 36 Amazon Leo satellites to orbit, four more than previously.
Cavaillolès said described this upcoming launch as a big milestone for the company.
“It’s important and we want to secure this milestone. This is our focus as of today, but of course, the story doesn’t stop there,” Cavaillolès said. “The more we launch, the better we know the launcher. We are already looking at further improvements. So we’ll do our best to keep increasing the performance of the launcher and thus the number of satellites we can carry for each launch.”
For the first time, Ariane 64 will fly with four P160C boosters.
Less than 2.5 minutes after liftoff, the four P160C boosters separated from the Ariane 6 main stage, followed by fairing jettison less than a minute later. The first and second stages separated nearly eight minutes into flight and the Vinci engine began the first of two, pre-deployment burns.
The deployment sequence for the Amazon Leo satellites began nearly an hour-and-a-half into flight and conclude at about one hour and 51 minutes post-liftoff. The Vinci engine then performed a de-orbit burn about two hours and 40 minutes after takeoff.
“When this mission is complete, Arianespace will have launched 100 of our satellites to date. That’s three missions in less than five months, which is just fantastic,” said Steven Metayer, vice president of Production Operations at Amazon.
“It’s just something we really count on to build that constellation out at rate across all providers.”
Building a constellation
Prior to Wednesday’s launch, Amazon has deployed 331 satellites on 12 missions by three different launch providers: Arianespace, SpaceX, and United Launch Alliance.
Metayer said production of the satellites is ramping up and is exceeding the rate at which they are currently able to get them into orbit. He said Amazon is currently manufacturing “several satellites per day” at their facilities in the State of Washington.
In Florida, he said they are able to receive satellites at their payload processing facility at NASA’s Kennedy Space Center and get them integrated into a dispenser in about a week.
“We’re comfortable right now running ahead of launch. We know that when these heavy lift vehicles, such as the Ariane 64 and then you add the Vulcan and New Glenn to that, we know that we’ll have quite a consumption rate demand from launches,” Metayer said. “So we’re comfortable right now building ahead of where we need to be and to make sure we never ever run out of satellites.”
Those two launchers, New Glenn and Vulcan, are both grounded for an undetermined amount of time.
For ULA, it’s Vulcan rocket has been grounded due to a problem with one of its solid rocket boosters during the USSF-87 mission in February. The timeline for concluding its anomaly investigation isn’t publicly known, but Metayer said Amazon is anticipating being able to launch its first Leo Vulcan mission “sometime in Q3, the end of Q3.”
ULA stacked its first Vulcan rocket that will carry Amazon Leo satellites inside the newly completed Vertical Integration Facility – Amazon (VIF-A) at Space Launch Complex 41 at Cape Canaveral Space Force Station. The rocket will roll out to the pad for a wet dress rehearsal this summer to validate ULA’s new Centaur upper stage, which the company said is optimized for low Earth orbit missions.
Behind the scenes as prep continues for Leo Vulcan 1 (LV-01), the first of 38 Vulcan missions on contract with @ULAlaunch.
Teams have completed integration of the first LEO-optimized Centaur upper stage with Vulcan inside Amazon’s dedicated Vertical Integration Facility (VIF-A),… pic.twitter.com/2BZgecrbbl
On the Blue Origin side of the equation, a month after recovering from an upper-stage, in-flight anomaly on its NG-3 mission, the company lost its sole launch pad in an explosion of its New Glenn rocket during a static fire test on May 28.
During an appearance at the annual VivaTech conference in Paris on Wednesday, Blue Origin CEO Dave Limp reaffirmed the company’s goal of resuming launches from Cape Canaveral Space Force Station by the end of the year.
“We brought in 400 pieces of heavy equipment, brought in construction workers that were working 24/7. And so now the pad has been cleared of all debris. It’s amazing how quickly that’s happened,” Limp said to panel moderator and former NASA astronaut Mike Massimino. “Just yesterday, we started the reconstruction. We’re going to fly this year.”
Metayer noted that the 24 launches procured using New Glenn rockets represent “less than 25 percent of our total.”
“We definitely want to see New Glenn come to service and we definitely look forward to flying on them, but they’re not the only provider,” Metayer said. “We have a diversified launch portfolio intentionally to do that and we have quite a few launches coming up on others.”
Metayer said Amazon is planning on launching about six more times this year across multiple launch vehicles. The next one after the Ariane 64 mission on Wednesday is expected to be the Leo Atlas 08 mission on July 3, which will be the final non-government launch of an Atlas 5 rocket.
He said they also have one more Ariane 64 launch scheduled this year, but didn’t specify exactly when. Here’s the current lineup of launchers procured by Amazon:
ULA’s Vulcan – 0/38
ULA’s Atlas V – 7/9 (one used for Protoflight mission)
Blue Origin’s New Glenn – 0/24
Arianespace’s Ariane 6 – 2/18
SpaceX’s Falcon 9 – 3/13
Metayer said the reliability of Arianespace since its debut has been important for the company as it rolls out its constellation.
“They definitely have stepped up, you know. I will say, they’re very reliable on their manifest dates, they’re very reliable and safe on their insertions in orbit,” he said. “So we definitely would continue to look forward to the next 16 launches with them on our existing contract and we see them being a player long term beyond that.”
Amazon was up against a challenging deadline with the Federal Communications Commission since it was originally required to have deployed and be operating half of its 3,232 satellite constellation by July 30, 2026.
However, earlier this month, the FCC granted a waiver requested by the tech giant, but not without some conditions attached.
“Specifically, we impose upon Amazon Leo meaningful conditions that incent the company to continue deploying satellites at a rapid clip by temporarily demoting the spectral priority of satellites launched after the relevant July 2026 milestone deadline, until and unless Amazon Leo builds those satellites at a faster pace,” wrote Jay Schwarz, the chief of the FCC’s Space Bureau. “We act today mindful of the specific record developed on Amazon Leo and in a way that will encourage rapid builds and launches.”
He added that “any authorized satellites in the Gen1 Authorization that are not deployed and operational, will temporarily lose the associated priority status granted in both the 2020 Ka/Ku-band Processing Round and the 2021 V-band Processing Round and will be reassigned to a later priority status. This loss of status will last for twenty (20) months—until March 30, 2028—or until 50% of the constellation is launched and operational, whichever occurs first.”
"People increasingly trust AI to make decisions—but research by Alex Chan finds they avoid evaluating the algorithm's rationale if it causes moral discomfort. How can organizations encourage employees to think more critically? "
Abstract Participants acted as loan officers deciding whether to approve real $10,000-loans issued by a private U.S. lender using an AI’s default-risk predictions. When explanations revealed that the AI penalized non-White or female borrowers, participants were more likely to override the AI’s profit-maximizing recommendation. When their bonuses depended on repayment, however, they sought predictions but avoided explanations, consistent with willful ignorance; this effect disappeared when explanations were framed as purely financial or demographics were hidden. A secondary experiment reveals a novel bias: participants failed to reason contingently and undervalued explanations even when these complemented private information and improved decision accuracy.
Space surveillance venture Look Up plans to use Skynopy’s ground station network to help automate its proposed low Earth orbit collision avoidance service, the French startups announced June 17.
Join us as we explore the technologies behind Golden Dome, what’s necessary to make them operate at a high level and what possibilities could be in the works for the satellites involved.
Much of what looks like changing marriage preferences over the twentieth century is actually demographics. Exploiting plausibly exogenous variation in sex ratios across U.S. birth cohorts (1870, 1930, 1950), we jointly identify preferences, match quality dynamics, and the costs of marriage and divorce. Demographics alone explain two-thirds of cross-cohort differences. Women’s premium for older husbands collapsed across cohorts; men’s preferences barely changed. Love that survives its early years becomes permanent, but the odds of surviving fell from 97% to 44%. Divorce costs fell six-fold and depend on life stage. A horse race across behavioral channels shows that the match quality process—not mate-age preferences—is the primary dimension of generational change. Declining divorce costs and fragile match quality are substitutes: either alone fits the data, but together they reveal two independent dimensions of social change. The model validates out of sample on the 1910 and 1970 cohorts.
That is from a recent paper by Jose-Victor Rıos-Rull, Shannon Seitz, and Satoshi Tanaka. Via the excellent Samir Varma.
A new study by Irish researcher Eoin Whelan attempts to answer this. Dr. Whelan told me he was specifically inspired by Haidt’s 2024 claims and sought to examine them rigorously and in the context of other regrets. This is a great use of science…testing dramatic public claims. So…do they hold up?
In Dr. Whelan’s study, 389 young adult participants (20-24) who were social media users as teens were asked about their regrets regarding their teenage years. A list of 20 possible teenage regrets was asked of all participants, with degree of regret marked on a 7-point Likert scale. This is an interesting design…testing social media regrets against other possible regrets, putting them in better context than the crude survey Haidt relied on.
So how did social media regrets hold up? Out of 20 possible regrets, too much time on social media ranked 13th. The top regrets were 1.) not sticking up for oneself, 2.) being too self-conscious, 3.) not documenting memories, 4.) not learning practical life skills and 5.) not getting help with mental health. Girls were slightly more likely to regret time on social media than boys (ranking 11th vs 13th) though this effect was very small (I estimated it at about r = .11) so hardly the big “vulnerable girls” narrative some have peddled.
Further, regrets over time spent on social media as a teen did not predict current young adult life satisfaction for either boys or girls. Thus such regrets may be more a symptom of current panics over social media than anything of actual life importance2. Of the regrets, only not working harder in school and not exercising negatively predicted young adult life satisfaction. Interestingly, having regrets over socializing with friends positively predicted life satisfaction.
As Dr. Whelan noted in his study, “The objective of this study was to critically examine the commonly held belief that social media use during teenage years is a significant source of regret and a predictor of diminished well-being in early adulthood…Contrary to dominant narratives in the public domain, our results suggest that regrets over time spent on social media are not among the most potent regrets reported by young adults…As such, these results align with prior research indicating that the harmful effects of social media may be overstated.”
The reservoir appears lake-like and expansive in an image acquired in June 2023.
NASA Earth Observatory/Michala Garrison
The reservoir is nearly empty by May 2026. The Gila River’s natural channel is now visible and flanked with green vegetation in what had been the bottom of the reservoir.
NASA Earth Observatory/Michala Garrison
The reservoir appears lake-like and expansive in an image acquired in June 2023.
NASA Earth Observatory/Michala Garrison
The reservoir is nearly empty by May 2026. The Gila River’s natural channel is now visible and flanked with green vegetation in what had been the bottom of the reservoir.
NASA Earth Observatory/Michala Garrison
June 7, 2023
May 22, 2026
Little water remains in the San Carlos Reservoir in May 2026 (right) compared to fuller conditions in June 2023 (left). Images were captured by the OLI (Operational Land Imager) on the Landsat 9 and 8 satellites, respectively. NASA Earth Observatory images by Michala Garrison.
The Gila River is among the Southwest’s most important rivers, delivering water for people, farms, and wildlife while linking the snow-fed mountains of southwestern New Mexico to the desert lowlands of southwestern Arizona.
In wetter years, seasonal snowfall on the Mogollon Mountains and Black Range provides much of the river’s spring flow and helps refill San Carlos Reservoir, which is formed by the Coolidge Dam. When filled to capacity, the reservoir is one of Arizona’s largest bodies of water.
However, in 2026, lackluster snowfall left the mountain snowpack in the Gila River watershed at 2 percent of the 1991-2020 March median. The limited snowpack pushed April streamflow to 39 percent of normal. By June, after mandatory water releases for downstream agriculture, the reservoir held less than 400 acre-feet of water.
The Landsat image above (right) shows the near-empty reservoir on May 22, 2026, when it stored 389 acre-feet of water—less than 1 percent full; the other image (left) shows the same area in June 2023, when it was about 60 percent full. The green vegetation growing along the river channel and reservoir edge includes a mixture of tamarisk, willow, cottonwood, sedges, and grasses.
Officials closed the reservoir indefinitely on June 5, 2026, after the declining water levels contributed to low oxygen levels—hypoxia—that killed virtually all of its fish. Species living in the reservoir included largemouth bass, black crappie, bluegill, channel catfish, flathead catfish, and several stocked species, including brown trout and rainbow trout. The decomposing fish may pose health risks to people attempting to boat or fish, the San Carlos Recreation and Wildlife Department warned.
The reservoir has hit similarly low water levels in the past, running out of water at least 20 times since it was filled in 1930, according to news reports. Even when the dam and reservoir were first dedicated, there was enough grass growing on the dried reservoir bottom that humorist Will Rogers famously quipped to President Calvin Coolidge: “If that was my lake, I’d mow it.”
Other years with major fish kills include 1976 and 2018. After more than 5 million fish died during a similar event in 1976, the Gila Heraldreported that it took five years for the lake’s ecosystem to rebound.
The region is currently in the midst of a multi-year dry period that has left much of the Gila River’s headwaters in New Mexico in a state of severe drought, according to data from the U.S. Drought Monitor.
However, the river’s flow is highly variable, and heavy rains during the coming wet season could help the reservoir recover. A seasonal monsoon outlook released by NOAA in May 2026 projected a 33 to 50 percent chance that an above-average amount of rain would fall in the region that summer. El Niño in the central and eastern equatorial Pacific, which was strengthening in late spring 2026, can make heavy rains in the U.S. Southwest more likely.
NASA Earth Observatory images by Michala Garrison, using Landsat data from the U.S. Geological Survey.Story by Adam Voiland.
Tomorrow is the anniversary of the 1972 Watergate break in.
I usually memorialize the burglary that started the extraordinary chain of events that led to the resignation of the president with a letter, but as Liza and I chatted about what might be a fun thing to render in art this month, Watergate jumped out. As we talked, we discovered that we both cut our political teeth on that scandal. It’s been a long time since the details of the event and its aftermath were fresh, and I wanted to remind people of the chain of events. And Liza’s drawing—and the new theme it called out— does indeed give this old topic a whole new life that is ever so relevant today.
Yours truly, in September 2024, expressing skepticism that “European iPhones are more fun now”:
Meanwhile no one in the EU will get Apple Intelligence or iPhone
Mirroring, both of which features are very useful, and, dare I
say, quite fun. Should we judge how much fun each side of the
continental divide is having by how much fun they theoretically
could be having, or by how much fun they are having?
As it stands, the fun side is not the EU. But hope springs
eternal.
Here we are two years later and I think the answer is more clear than ever which side of the continental divide is more fun. It’s not the EU. EU users still don’t have iPhone Mirroring and until and unless the European Commission changes its interpretation of the DMA, they likely never will. It’s a great feature.
Apple Intelligence, as we knew it until last week, eventually came to the EU, about six months after it shipped for the rest of us. One can reasonably argue that EU iPhone and iPad users didn’t miss much during those six months. And that there hasn’t been that much to enjoy since Apple Intelligence debuted in the EU in iOS 18.4. That changed last week with the introduction of the first beta release of iOS 27. Siri AI is really good, truly useful, and genuinely fun. And it is not on pace to come to the EU six months after iOS 27 ships this fall. It is currently on pace to come to the EU never.
I’ll just work from the car, I thought. But after a few minutes
of staring at my screen on quick mountain switchbacks I could feel
the first signs of cold, coagulated nausea bubbling up from that
sweaty place in my gut. I looked to the horizon for relief, but
nothing helped... until I remembered Apple’s magic dots.
Introduced in 2024, Apple’s Vehicle Motion Cues promise to
tap into your device’s accelerometer and gyroscope to reduce or,
in my case, even eliminate the motion sickness felt when trying
to use an iPhone, iPad, or MacBook inside a moving vehicle.
My son has suffered from motion sickness in cars his whole life, and Apple’s Vehicle Motion Cues work like a charm for him too. What a great feature.
Casey Handmer's blog
Market Design
+1 meter longer than P120C
156 tonnes of propellant 
