That was Anthropic.

End of day, output and results are top target of measurements, token consumption is the obvious number that they would like to disclose for their own business benefits and a simple metrics that correlate with the output.

Rest assured, capitalist appears irrational in wasting money, but they certainly care more about profit.

my stack in a sentence: refine the docs/prompts/skills often, that's your biggest job, use both frontier labs models reviewing each other, don't solve individual problems only the systemic ones (set standards strategically, don't define tactics)

If I had that many tokens/dollars I would be running canaries and adversarial verification in prod based on e.g. traffic replay, live fuzzing, all kinds of things to build confidence without direct human line-by-line review. If I had $100k to spend next month I could probably get through it, I'm running $2500+-api-equivalent a week at this point and I feel very token limited. Will be time for a 2nd or 3rd subscription soon for both labs I think.

Fable was a revolution, still learning how best to use it, 5.1 felt like a notable upgrade. At this point I launch a workflow with 10-20 minutes of interactive setup (and even that I feel might be too much), it runs for hours, and the PR is trivially mergeable (I still review every line, but 95% are just merge, maybe 4% are feedback needed, 1% are thrown away and regenerated, which implies I'm being insufficiently ambitious)

Yes, because no employee with million-dollar comp has ever been untrustworthy in the history of business.

Imagine if one of the humans at OpenAI was misaligned! We should get the AI to research this possibility once they've been aligned.

I'm currently running two 24/7 semi-autonomous AI research projects using Fable 5.1. It's on track to burn through my weekly quota in about 3 days. I check progress in the morning and in the evening, and provide some light steering.

My only experience in >24h agents is with economically sane models (one of GLM5.2, 5.3-flash for orchestration, DSV4-flash for implementation, and glm5.3|sol|kimi3 agents + subagents reviewing at the end)

Over 24h my token spend is <30$. Excluding tokens for review it's <10$. With the absurdly gigantic subscription subsidies and a reasonable workflow I suspect one could run parallel agents.

I'm not sure what the point would be though unless working on some kind of optimization problem -- it takes me days to review <24h of the agent's output. It's almost always near enough to correct to be shippable; though I do give it feedback and iterate until it's better than the code I would have written.

/loop ?