A personal letter on transformative AI

George Rosenfeld

May 15, 2026

George Rosenfeld is Deputy Director for Global Catastrophic Risks at Coefficient Giving, which covers our Navigating Transformative AI and Biosecurity funds. In April, he wrote a letter to his friends and family about why he thinks AI could transform the world in the coming years, and why the current trajectory worries him.

It’s a personal letter, written for people who are encountering these arguments for the first time. We’re sharing it because we think more people should be having these kinds of conversations.

Note: this letter was shared at the start of April. In the roughly six weeks since, Anthropic’s annualized revenue has reportedly grown to $45 billion (up from the $9 billion figure in December 2025 cited below), and it announced the development of Mythos, a new powerful AI model that it claims was able to find security vulnerabilities in every major operating system and web browser when prompted. The letter doesn’t incorporate these developments, but AI progress continues at a blistering pace.

Dear family and friends,

For the past two years, I’ve worked at Coefficient Giving on the Navigating Transformative AI program. For the most part, our work involves thinking about what might happen with AI over the coming years, trying to get a sense of how powerful and transformative it might become, and doing whatever we can to help make the world more prepared.

The sorts of scenarios my team thinks about sound pretty extreme and sci-fi. We think about worlds where AI systems are able to do practically everything humans can do, just faster and better; where decades of scientific progress start to happen in months or years; and where we’re asking ourselves not just what AIs can do, but whether humanity can remain in the driver’s seat at all.

It’s hard to overstate how completely wild these possibilities are. If these outcomes are even somewhat plausible, then we may be living through one of the most important turning points in human history.

I don’t know for certain whether any of these things are going to happen. I also don’t know whether these things would be very good (think: unprecedented human flourishing), or very bad (think: all humans dead or disempowered), or somewhere in between.

I should also be upfront that these views are not mainstream.1 The idea that AI could automate nearly everything and transform civilization within a few years is a minority position, and one that most economists, policymakers, and people in general aren’t taking seriously yet. It certainly doesn’t feel like the world is awake to these possibilities.

I was personally skeptical for a long time too. When I first encountered these arguments, they sounded sci-fi and far off, and I took a while to come around. But over the last couple of years, my more conservative predictions have consistently underestimated how much progress AI would make, and I’ve become increasingly convinced – and increasingly worried — that these scenarios are plausible, and that they might not be far away.

I wasn’t sure whether to share this, whether it would even be a good thing for people to read. Although I’m uncertain, my best guess is that the world is on the cusp of changing radically — that we’ll look back at this period like we looked back on February 2020 before COVID-19 changed everything,2 except this time the transformation will be much more drastic and the world may never go back to how it was before.

These are real views that I live with, and that increasingly guide my emotions and decisions and hopes and fears. It feels strange, and lonely, to hold them and not share them with people I care about.

In what follows, I’ll write about (1) why powerful AI could be such a huge deal, (2) how quickly we could reach that point, and (3) what unprecedented risks — and benefits — transformative AI could introduce. I also link to further resources where you can learn from people much more knowledgeable than me.

Why is AI a big deal?

Most of us interact with AI as a chatbot, an online interface that answers our questions, plans our holidays, and occasionally does our homework.3 Sometimes it feels helpful, other times useless. Either way, it doesn’t necessarily feel that ground-breaking or that different to other technologies that humans have invented.

One key difference is that unlike previous technologies, it might be possible for AI to automate everything that humans can do. Previous technologies have always been a complement to humans in some way. The printing press let us spread ideas faster, but someone still had to have the ideas. Computers can calculate faster than we ever could, but they only do what we program them to do.

AI, by contrast, could plausibly do everything that humans can, including the open-ended thinking that used to be exclusively ours. We can’t be certain that AI will be able to reach this point, but if it does it would likely be a huge deal.

For starters, there go our jobs. Not in the historical sense of: AI automates a particular portion of human labor, so the humans reskill and move on to different jobs, as has happened many times before.4 But plausibly: AI is now better at doing basically any job than even the best humans, so there’s no other job to move on to.5 This may currently be easiest to imagine with cognitive work, though physical labor could follow. In that world, it’s unclear how most humans would earn a living, or what the economy would look like.

But job loss, as dramatic and world-changing as it could be, might not even be the most important part. Up until now, human labor has been a significant bottleneck to both scientific and economic progress. Yet with sufficiently powerful AI, we may have the equivalent of billions more top scientists, entrepreneurs, and other experts to throw at every problem at once.6

It’s hard to know exactly how fast things could move. Even with superhuman AI, there would still be bottlenecks: physical experiments take time to run, many real-world problems are intrinsically messy and complex, and human institutions, regulations, and adoption could all lag behind.7

But it’s plausible that such a world could quickly become unrecognizable from today’s, with hundreds of years of progress compressed into months or years.

Think about how different the world looks now compared to 1500: modern medicine, electricity, the internet, nuclear weapons, space travel. Now imagine that scale of change happening not over five centuries, but over five years. And unlike the generations who lived through the original transformation, we wouldn’t have centuries to adapt.8

Where are we now and where are things headed?

As of March 2026, AI hasn’t transformed the world and it hasn’t automated that many jobs. I don’t yet find it very useful for my work.

But what matters is the trend.

AI systems have already improved dramatically over the last few years. In 2022, the first widely available chatbot (ChatGPT) could hold a passable conversation but often made things up. By 2024, the best AI systems were passing the bar exam and getting silver medals in the International Mathematical Olympiad (gold followed in 2025). In early 2026, AI agents can often handle substantial software projects that take skilled humans several hours,9 and are now being used to accelerate the process of AI development itself.10

To understand what’s driving these improvements, it helps to get a sense of how AI models are developed. When we build a car engine or a bridge or a website, we know what we want it to look like, and we understand exactly how and why the end product works. But AI is different: AI companies set up a neural network (a bit like an artificial brain), train it on enormous amounts of data, and let intelligence ‘emerge’ from the model. The engineers shape this learning process, but they don’t hand-craft the results.11

Over the last few years, one of the main drivers of AI progress has been scale: As AI companies scale up the inputs (more data, more computational power, larger models),12 they watch with the rest of us as smarter intelligence and new capabilities continue to appear. Many times people have bet against AI, saying it could never do some particular thing, only for the next round of scaling to prove them wrong. This pattern has held up repeatedly as models have gotten bigger, and nobody knows how fast it will continue or whether it will stop.

There’s a graph I keep looking at which captures this trend, from METR, an organization that evaluates AI capabilities. They measure the “time horizon” of AI systems: the difficulty of software tasks an AI can complete autonomously, measured by how long they take human experts.13 Between 2019 and 2025, METR found that time horizons doubled roughly every seven months. More recent data suggests it may now be doubling every four months.

As we learned during COVID, exponentials can change things fast: the doublings are happening quickly, and it may only take a few of them to transform the world.14

Source: METR

Another way to assess the trajectory of AI comes from looking at the revenue figures of AI companies, in some ways a more trustworthy indicator of real-world impact. Anthropic (the company that makes Claude) went from $100 million in annualized revenue at the end of 2023 to $1 billion at the end of 2024 to $9 billion by the end of 2025 — roughly 10x annual growth. By some measures, this makes it among the fastest-growing tech companies in history.

And the investment dwarfs even the revenue. The five biggest tech companies are on track to spend over $600 billion on AI infrastructure in 2026 alone, mostly on data centers and chips. To put that in perspective: the Apollo program to put humans on the moon cost about $250 billion (inflation-adjusted) across its entire 13-year lifespan. AI companies will spend more than double that in a single year. This is already one of the largest private investments in a single technology in modern history.

These figures alone don’t prove that AI is about to transform the economy; plenty of technologies have had explosive early adoption without changing civilization, and it’s possible the huge investment is a bubble. But combined with the capability trends above, it paints a consistent picture: either AI progress starts hitting a wall pretty soon, or it becomes the driving force of the global economy. It’s getting harder to bet on the wall.

Stepping back a bit: it’s all very well sharing graphs and trends, but when someone tells you there’s this new big thing on the horizon, it’s very reasonable to be skeptical. That was my initial reaction: I took a long time to come around to really believing that scenarios like these were plausible. But over time, the people who are extrapolating the trends and taking these possibilities seriously are looking increasingly correct, and my more conservative predictions keep being proven wrong.15

Now, when I look at what those people are predicting, they’re raising the alarm. In January, Ajeya Cotra (a former colleague of mine who recently ranked 3rd out of 413 people forecasting AI developments) predicted that AI would be able to complete 24-hour software engineering tasks by the end of 2026.16 A few months in, she’s changed her mind: She now thinks it will surpass 100 hours, and may be unbounded. In early March, she wrote: “For the first time, I don’t see any solid evidence we can extrapolate to say [full automation of AI R&D]17 won’t happen soon. AI R&D really could be automated this year.”18 In Ajeya’s view,19 we might expect AI to surpass the world’s best human experts at any computer-based task by the early 2030s, with automation of physical labor potentially following within a couple of years. Unfortunately, substantially sooner than that seems plausible too.

These claims sound wild and they could certainly be wrong. The trends could level off. The remaining capabilit

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