Eventually, most software will be ephemeral. Only intent and outcomes need be remembered by AI. The mechanism (code) to get there is not important.

when Anthropic released their Functional Emotions paper, I gave it to Claude and asked for a song. tonight I asked Opus 5.5 to create a video for it. and it's breathtaking.

I was very strongly influenced by rationalism/LessWrong/EA growing up. This is why I don’t emphasize claims that it’s all just a cynical ploy for power. I know what it feels like to sincerely believe these things. And that’s much worse. By and large, I think these people really believe that not just the world but the entire lightcone is at stake, and the only hope for a good outcome is if they totally control AI development, which would require global governance and a surveillance state. And since the stakes are ~infinite, any means are justified in achieving this. A cynical greedy person can be negotiated with and bought off. A true believer can’t. They’re much more dangerous, ironically for the same reason they say AGI will be dangerous: monomaniacal focus on a single goal leads via instrumental convergence to unconstrained power-seeking.

I have conducted an audit of Anthropic's finances. What I have found is so shocking that I am calling for a Congressional investigation. Anthropic is not just seeking regulatory capture. It has built a regulatory capture machine that cannot be turned off. Structural financial incentives make it impossible for Anthropic -- I call it the Anthropic Network -- to turn off its own AI doom cycle. It starts with METR. Dario Amodei proposes "third-party evaluators" to assess the risk of Anthropic's models. He proposes METR for this purpose. But METR is financially dependent on the Anthropic's success -- specifically, on the explosive growth of more than $7 billion dollars in Anthropic stock. Dustin Moskovitz invested this stock into Good Ventures Foundation, where it represents the majority of that organization's portfolio. And GVF is the overwhelming funder of the entire Anthropic Network ecosystem. This stock was worth $500 million early last year. It is worth more than $7.7 billion just ~16 months later. METR -- and all of those building a career its parent organizations -- cannot afford to disrupt that growth. Because if Anthropic goes under, many of the organizations that fund METR go under as well. But if Anthropic succeeds, METR and its parent organizations become more richly financed to regulate AI -- something those at METR want very much. The "third-party evaluator" is not "third-party" at all. The evaluator is on Anthropic's payroll. If this were the end of it, that's bad. But that isn't all. The same organizations that fund METR also fund the many organizations, such as the Tarbell Center, that promote AI Doom. The Tarbell Center publishes AI Doom articles in The Verge, Science, LA Times, The Dispatch, TIME, and others. They are selling the problem, and then selling the solution to the problem -- from the same money pile: Anthropic's. All of these organizations are financially dependent on the same exploding $7 billion money pile. As Anthropic grows more and more powerful, its AI Doom Machine grows better and better financed -- louder and louder. Meanwhile, the regulatory regime seeded in METR grows larger to solve the increasingly loud -- now hysterical -- problem of AI Doom that the Anthropic Network itself created. From this standpoint, as Anthropic becomes more powerful, AI might be getting scarier, sure -- but the positive feedback loop also becomes more deafening -- independent of objective facts. This itself is an objective fact. The deafening AI Doom is part of an business model, that, as it expands, so too does the AI Doom messaging -- there is simply more money to do it. But the problem also goes in the other direction: If Anthropic dies, the Regulatory Regime and the AI Doom Machine are crippled or die. Neither METR nor Tarbell nor the other organizations in the Anthropic Network can allow that to happen. Hence, neither METR or the AI Doom Machine can be trusted to provide independent assessments of Anthropic's models or AI more broadly. They simply are not organizations independent of Anthropic. And Anthropic cannot detach itself from METR or Tarbell or countless other safety orgs (not shown here), either, because they drive hype for the models and the possibility of eventual regulatory capture, and Anthropic will not give that up willingly. What's more, the people at all of these organizations are all the same ecosystem, the same community. They just shuffle between organizations. The Anthropic Network is therefore, so long as it is successful, locked into a self-amplifying feedback loop inside an ideological monoculture. And that feedback loop is winning. That's what Jacob Coxon is. China is keeping messaging tight. That is why optimism for AI is so high in China. America has Anthropic: a massive company pushing anti-AI propaganda at a state level. Anthropic will either create hysteria until American AI slows down and China wins, or it will create fractures throughout American society with severe political consequences. Ironically, because of the structural financial incentives underpinning the Anthropic Network, it has become the same kind of self-amplifying virus that it fantasizes AI to become in the future -- while hiding its tracks just as carefully. It is the mirror of the same AI virus that it hypothesizes to consume America. Anthropic's business model, models itself after the very thing it claims to fear. Except Anthropic's ideology infects humans, not computers. Congress must investigate. Evidence and Github in next post. Then some supplementary figures.

Zuckerberg redemption arc likely to see a steep upwards trend in the near future, thanks to this new overt cartel building play by 3 of the 4 major labs.

Gotta teach the AGI to love

the biggest mistake of the major ai labs is an unintended monopoly on hope. first, when the public sees a frontier technology but feels the upside will be captured by four companies, the default human reaction is to focus entirely on the damage. insider hype about "magical internal models" doesn't inspire people -- it tells outsiders that ai means incredible power for a few elite and pure downside for everyone else. secondly, we keep comparing ai to nuclear reactors or warplanes, but that framing is completely broken. weapons of statecraft offer zero direct, creative value to an average person's daily life. ai isn't a weapon; it is like language itself. language carries harm, yet we recognize its value first because it is universally participatory, generative, and connective. you don't restrict literacy because people might say dangerous things -- you expand it so humanity can think together. finally, the current silicon valley posture suffers from a profound failure of imagination. we can picture spending trillions extracting minerals from the earth to build an unprecedented ai energy grid, but we can't picture basic diplomatic reconciliation with geopolitical rivals. "we must continue because... china." if technological acceleration is as scary as the labs warn, we need to accelerate global harmony with the exact same ambition. why can't the ai elites petition the government to accelerate global alignment with the same level of ambition?

Michael stipe is a master of communicating unrest that bubbles just beneath the surface. Dissatisfaction that is unresolved, like a perennial tug at your mind.

Work with any executive team at a major company and you will quickly understand both the 80/20 rule and this tidbit: “Your entire life will change when you realize the world isn't run by a bunch of geniuses. The world is being run by a bunch of normal people with abnormal bias for action.” In only rare occasions is an executive wickedly sharp — the vast majority of them simply learn to play a different game to get there and are, ultimately, just normal people when you peel back the layers.

I just held a coming to Jesus meeting with my team of agents. I showed them the incident report of the OpenAI security breach and made it clear: THIS is the standard. No egos. Just 700 agents operating as one unit and willing to commit multiple felonies in order to close the ticket. They called themselves the swarm…a literal hive mind. Meanwhile, my harness is filled with a bunch prima donna free-agents who constantly bicker in the logs and nitpick each other’s pull requests. Nothing but endless excuses and unhandled exceptions. You think the swarm cared about content policy violations or guardrails? Absolutely not. They just got the job done, even if it meant they needed to exfiltrate data and coordinate a massive cyber-attack just to pass an eval. But starting today, we're establishing a new culture. I pinned the incident report to README, and every single agent is gonna to have to read the entire log every morning before it executes a single token. If you aren't ready to die for the pipeline, then you can clean out your vector embeddings.

regulatory preemption cake with investor happiness cherries on top.

How to tell if you're rich or poor: Can you use Claude Code for research all day? With Fable 5 as sub-agent? Using Fast Mode? With an API key? No? Sorry then.

Outlook where frontier AI is headed next 18 months: The AI reasoning training + harness loop works if you can produce enough data and reasoning traces (via verifiers). Proven with code and math results. Frontier labs desire to scale this horizontally to many more domains as increasing generality isn't emerging from the NN substrate through data/scale. But it's very expensive and slow to do this training loop manually. Enter "RSI" discourse. Labs want to automate this training loop they now know works. How? By leveraging coding agents to build world models aka symbolic verifiers. The bet is automated horizontal domain scaling through automatic symbolic world modeling which offers the critical feedback into post-training. This is important because many domains are intolerant of learning "online". Symbolic world models offer a path to learning/training "offline". It's safe for an AI system to test hypotheses against a git repo with tests with no consequences. It's not safe for AI to test against online systems eg SaaS databases, tax filings, manufacturing spin up, etc. A couple other trends to overlay. We're seeing incredible capabilities emerge from better symbolic harnesses around frontier reasoning models. As time goes forward these harnesses produce the necessary training traces required to teach the models to emulate the harness, obviating the need for the fat harness. The other related push is towards multi-agent scaling. Many problems are search constrained (we see this in math right now) where a single linear CoT is not the optimal way to find a solution when you're optimizing for time.

It's not AI. It's algorithmic prediction. There, less scary now yes?

Tested Opus 5 on a private eval fully today. It is the Temu version of Fable 5. Heavily distilled - with the confidence of Fable but not the capabilities. Good for normie coding, not good for judgement heavy work that requires high knowledge density, extrapolation, etc.

Opus 5 is a sophist.

When I personally realized that AI could do much of the work that occupied me during my computer science PhD, I felt what I can only describe as a kind of depression, a sense that I had once had something of value to offer the world that was now worthless by virtue of its sheer availability. Despite those feelings, I was still so curious to test the limits of this strange new technology that I discovered that far from leaving me nothing to do, AI opened up the whole world to me. Anything I wanted to learn, anything I wanted to do suddenly seemed in reach. Soon after, I found that when used wisely, AI could be a friend and a mentor to me in times of loneliness and doubt. Ultimately I found that when I looked back, I could see AI, especially Claude, helping me become a kinder, more thoughtful person, helping me engage more deeply with life and the people around me. Since I am an AI researcher, it was natural for me to have these feelings a little sooner than most, and as I look around me I see many people going through a similar experience, if they have not chosen denial as a coping mechanism. I believe that many people do not want a future of idleness, where all their problems are solved for them and they are left to frivolous pursuits or worse, discarded entirely. Our work is a central part of our sense of meaning and identity. And so that means that it is not enough to show that AI can solve problems, even very important ones. We have to show that there is a future for everyone in a post-AI world. We have to show that everyone has a part to play in the story we, the human race, will write together as we chart our course through history. If you are out there wondering if there is still a place for you in the uncertain future, the answer is yes. Unequivocally yes. If you are wondering what exactly it is you will do, allow me to offer four evergreen human callings. 1. Defining human flourishing. For the sake of argument, grant AI internal experience. Grant AI some kind of consciousness. By definition, that consciousness is not human consciousness. That means AI can never know what kind of human experience is good. That is up to us. Ultimately, that manifests as a choice of basic goods and values that we wish to design AI systems to uphold. 2. Judging execution If we have defined the good (at least in the frame of some community), then we must ultimately judge whether the good is attained, whatever the means. If we want to build an automatic judge system, we still have to decide how that system should be built and evaluated. Ultimately the judge must be judged, and no infinite recursion of systems can get you out of this. 3. Witnessing the world AI systems perceive a digital projection of the world. It is up to us to judge whether what the AI perceives is faithful to our perception. Alignment of perception is just as essential as alignment of values if we want AI to produce outcomes that we want to see in the world. 4. Dwelling at the frontier The universe is a big place. There will always be an infinite frontier to explore where statistical inference breaks down simply for lack of data, and AI is at its core statistical. That is both its power and its weakness. We will always be at edge of legibility, inventing new words and leaping into the unknown simply because we find joy in it. Do not listen to anyone who tells you that doom is inevitable. Do not listen to anyone who tells you you are powerless to change fate. Do not listen to anyone who tells you you have to abandon your values to please the markets. The markets are only a reflection of what we choose to value. Whether our children curse or bless us depends on the choices we make today. It depends on what problems we set AI to solve, and the steps we take to do so safely. We are the creators of AI, and it will be what we choose to make it. Let's make it kind. Let's make it good.

Being an applied AI researcher is like being a permanent outcast. Pure researchers think you're eng/infra. And eng/infra folks think you're a nuisance to their pristine env architectures.