@andrewcurran_Oct 27

Claude is the only author listed on this paper, in contrast to the OpenAI papers, where the human co-authors are listed. There are a lot of strange things about this. It's fun to guess. Conjecture time. I shall reveal my thought traces: Claude Fable 5.1 and Claude Mythos 5.1 are the same model with the same weights; the only difference is the guardrails. We are about to get Fable 5.5 - in fact, Fable 5.5 is ready to deploy now, and Anthropic could do so at any time. If they follow the same pattern, and I think they will, this implies the existence of a Mythos 5.5. I believe Mythos 5.5 wrote this paper. The way this is worded - 'Provenance. The core algorithm was found on October 16 by an internal Claude research model with 14M output tokens and no human input. Anthropic researchers worked with Claude to improve the presentation, resulting in this paper. Independently and concurrently, an internal model at OpenAI claims to have proven a similar result [Ope26]' - makes me think Claude was not prompted to solve this. I think Mythos was asked to autonomously find and choose general open problems to solve itself, as part of an unannounced project to demonstrate recent advances in autonomy and research taste. You can see this taste in Fable 5.5's student; Opus 5.5. This recent advancement in taste and creativity - which happened in September - is not clearly expressed in benchmarks, but it is why so many people are currently switching to Claude as their primary. I think this research project will be announced with Fable 5.5, as part of Anthropic's big media blitz to boost the IPO. One of the things X has taught me is that many people, if they can't see something moving, can't imagine it moving. This causes them to be continuously surprised by developments in this industry, because the frontier is invisible. I think this project has been running autonomously for some time and has made an unknown, and probably significant, number of discoveries, and not only in math. Do not think Anthropic has been sitting idly while OpenAI repeatedly makes these huge science announcements. This is a war. This ETH result was released without any announcement from Anth at all despite its significance, and they only did so to respond to OpenAI's ETH reveal. They posted it late last night without saying anything. It was up for hours before levent even mentioned it. What value has one coin to a dragon who sleeps upon a mountain of them? This makes me think they are sitting on a pile of discoveries, a golden hoard, and they are saving them up for the big IPO shock-and-awe campaign which will soon begin. And when it does, they will announce multiple discoveries across many fields.

@hammer_mtOct 27

Doing some multiplayer autoresearch and Gemini Argon 4 is crushing it. "Gemini 4 Argon set every frontier, but its round 3 breakthrough (0.625 → 0.938) opened by citing round 2's failed attempts: Fable and Sol had both tried loosening the long-sentence rule and dropped the score, so Argon kept that rule and changed something else. Fable and Sol scored 0.938 and 0.875 in round 4 building on Argon's skill."

@frankdegodsOct 26

as a counter to anthropic s1 glaze majority of q2 was the height of tokenmaxxing where companies were spending as much money as possible on credits it wasn’t until july where the idea of managing ai spend started to get traction also q2 was peak Opus 4.7 & Mythos/Fable season hype vs GPT-5.5, and Codex didn’t really take over until 5.6 during the summer i love anthropic’s products though and probably will slam the ipo because it’s first pure play ai lab but the belief that the headwinds for the ai trade have disappeared because of this document is not accurate >models have never been more commoditized than they are right now i used to be able to tell the difference between model outputs, now it’s almost impossible the more they get commoditized, the more the margins compress. this was not clear in q2. it is now. >still no clear proof of how ai drives more profit to most businesses most of anthropic’s biggest customers are publicly traded companies & they will be incentivized to decrease their own Claude spend to improve their own margins >capex commitments already signed until 2034 every hyperscaler & lab has been racing to sign deals spanning the next decade. this is all priced in already. this means the labs/mag7 basically either find ways to make existing chips more efficient (deepseek deepinfer type stuff) or they dilute shares to spend more on capex. either way stocks go down in both those scenarios — i am an ai bull but i believe the winners have still not been decided i think muse is great but does anyone know if it can drive hundreds of billions of dollars in value to Meta? well that’s what’s priced in and that’s what it would take for the investment to be worthwhile. — of course a lot can change but it feels like the real ai trade will take place after this current one settles down the real one will take time, just don’t see how it’s going to be this business cycle

@aakashguptaOct 23

Everyone asks Claude to review its own plan. That check is close to useless and most people haven't noticed. @thejamesmcaulay runs anything important past a panel instead. Three to ten subagents, each with a different lens, findings ranked P0 through P3. One checks technical correctness. One checks simplicity. One checks feasibility and capacity. One asks what's missing. That last one earns its seat. His reasoning: we don't know what we don't know, so asking what's absent surfaces things you hadn't considered and your main agent hadn't either. This is the structural flaw in self-review. An agent reviewing its own plan checks whether the plan is internally sound. It cannot notice the thing that was never in the plan. He calls it adversarial review, and in the episode he pointed five critics at a set of growth OKRs. They came back with the document being stale, numbers quietly hedged because the wording of the OKR was wrong, qualitative judgment where quantitative was needed, and no link at all to the company's OKRs above them. Anyone who has written OKRs on a team has shipped at least two of those. He hasn't stopped running it daily, because even the strongest models miss big things on a first pass. One practical warning from the episode. He spun up twenty Fable subagents the day before and hit his limits instantly. Run the critics on Sonnet. Cheap models arguing with each other beats one expensive model agreeing with itself.