The big winner in all of this is going to be open weights models. This is a huge win for the field, as a risk that was entirely theoretical and untested 2 days ago (that a model could be pulled back), now has a new precedent that’s been set. The game theory the US should highly consider, and the risk with regulating AI at the model layer vs. applied layer, is that other countries now have even more incentive to develop sovereign AI. If at any moment a model can be become unavailable to your country’s users or businesses, this poses very real risk on relying on technology from a particular country. As a result, it forces major countries to charter their own path on AI development, which reduces America’s leadership role in this tech stack over time. The most likely solution that other countries will rely on is open weights models, which currently is generally not coming from the US. America should be considering all of these downstream implications as it decides how and where in the stack to be regulating AI. At the same time, we should be doing a ton more OSS innovation.

I’ve had a number of conversations with folks inside and outside government about the current situation with Anthropic, and here is what I believe to be true: — As we know, Anthropic publicly released its Mythos class models earlier this week under the commercial name Fable. — Fable is Mythos with guardrails. But if those guardrails fail, then you’ve exposed Mythos and its advanced cyber capabilities to people who shouldn’t have them. (Keep in mind that Anthropic itself widely promoted the idea that Mythos was a cyberweapon and needed to be regulated as such. They asked for government regulation of Mythos and championed the guardrails on Fable. If there is a vulnerability — big or small — it is Anthropic’s responsibility to patch.) — A highly credible trusted partner of both Anthropic and the USG who was testing Fable came forward with a jailbreak of those guardrails. The Admin asked Dario to fix the jailbreak or de-deploy the model. Dario refused. — In their blog post, Anthropic defended its decision by saying the jailbreak isn’t serious. That is not what the trusted partner and the USG believe; nor is that kind of minimizing language consistent with Anthropic’s brand as the AI safety company. It’s difficult to fathom how they could claim a jailbreak allowing operability of a cyber weapon could be defined as not “serious.” — In the past, Anthropic has always said that safety must be top priority and taken super seriously. In this case, Anthropic prioritized the continued offering of the consumer model over safety. — In reaction, the Admin issued the export control. The Admin did this reluctantly. It’s been very surprised that Anthropic hasn’t wanted to cooperate with a reasonable safety request (ie fixing the jailbreak issue). Anthropic’s reaction is very much at odds with their branding and ethos as a safe AI research community. — The Admin’s hope now is that Anthropic remediates the safety issue, the export control is lifted, and Fable goes back into general release. The Admin wants all of this to happen as soon as possible. It is frankly bewildered that Anthropic hasn’t wanted to comply with safety requests that it previously said were its highest priority. — Those trying to misdirect and tie this action to the prior DoW/Anthropic issues are wrong. The Admin values Anthropic’s technical capabilities and feels that this issue, while serious, should be easily resolved. The ball is in Anthropic’s court.

RT @tunguz: Our Anthropic overlords deciding which prompts the peasants are allowed to use.

If you were wondering what the "pause" was all about, Ben Thompson @stratechery has an interesting theory: "Late last week the Anthropic Institute released a new safety report warning about the danger of recursive self-improvement... I don’t think the timing is a coincidence. This is a company and leadership that has been honing safety-and-scaremongering-as-marketing-tactic ever since Amodei led the charge to close source OpenAI models because GPT-2 was too dangerous; it’s always fun to see the evolution of tactics, capabilities, and goals, and in this case publishing a widely-discussed report the week before you cite it to silently degrade your offering for potential competitors is impressive."

In an early meeting at Facebook (c. 2007), when I was describing the goals of Facebook Platform (an area I oversaw) Bill Gates yelled at me/us. His quote has stuck with me to this day: “This isn’t a platform. A platform is where the collective sum of revenues of the participants exceeds those of the platform itself.” Ladies and gentlemen, I present to you the tokenmaxxing circle jerk.

Claude is down? API Error: 500 Internal server error. This is a server-side issue, usually temporary — try again in a moment.

You can build interactive applications with gpt-realtime-1.5, so users can control app state more naturally with voice. Hi Chappy 👋

It’s been effective in improving Agent Skills.

Someone recently suggested to me that the reason OpenClaw moment was so big is because it's the first time a large group of non-technical people (who otherwise only knew AI as synonymous with ChatGPT as a website) experienced the latest agentic models.

Is there a repo we can fork? @eglyman

one of the most interesting things I've see this year. watch this now.

👋 This is one of the signals we use to figure out if people are having a good experience. We put it on a dashboard and call it the “fucks” chart

I’ll simply say this: Everyone I know working at a frontier AI model company is either suffering from extreme AI psychosis or genuinely believes we’re single digit months away from liftoff.

we are literally all building the same thing

a small window into the opportunity of AGI

Every based dev said to try Convex. Constant outages - major regret.

the singularity has begun. so many signs.

People get high on abstraction too early. They want the system before they’ve earned the insight. But the good abstractions are never designed. They’re discovered. You do the stupid manual thing enough times and the real bottleneck just emerges. Your initial agency might be driven by a hunch you had in the shower, but that moment won’t get you all the way to making something people want. The right way to make anything is forced on you by reality: what are the real jobs to be done? And what sequence? This is why “do things that don’t scale” still hits, especially now when AI makes it trivially easy to scale things that probably shouldn’t be scaled yet. PG’s point was never about suffering. It was about contact. When you’re the one manually doing the loop, you see the edge cases. The weird user behavior. The failure modes nobody designed for. The hidden dependencies that only show up at 2am when some flow or intermediate step breaks in a way you didn’t anticipate. If you automate before you have that contact, you just scale your misunderstanding faster. When the machines can help you vibe code perfection it gives you a false sense of power. I love that feeling as much as you do. But fuck perfection. Do it live. Be the loop. Feel every friction point. Notice what’s actually true every single time versus what just looked true because you hadn’t seen enough cases yet. Formalize that. Build the recursive version. Then keep checking that your abstraction is still attached to real humans and their needs. Because reality drifts. Your users drift. The ground truth changes under you. You may think you understand but no plan survives contact with the real users and what they want. You find those body blows in analytics and user feedback and we call them the roadmap. Humans left with not enough data hallucinate too. But just like the LLMs with enough data you unlock real transcendence. Real utility. Prosperity for humans in real life. The abstraction is a tool, not a destination. The moment you forget that, you’re cooked.

claude code now automates security scanning...