Which I believe was the word intended.
yes, it gives labs edge and leads to self-recursive improvement loops.
also i was myself able to finish 7th in a later competition with 2-3 other approaches which are variants of the method discussed in this blog.
in general, having a harness as thin as possible with some problem specific instructions while controlling for context rot is the key.
point i am trying to make is there are a lot of optimisation surface areas possible.
You can't use Claude for this sort of thing if the goal is to make better AI systems. Anthropic finetunes Claude to dissuade people and the agent from using research that actually works. Anything that they use internally in their own models is poisoned, to protect their moat.
By proxy, that also means any openweights model that was distilled from Claude is equally useless for this purpose.
Thankfully, I don't believe OpenAI does this - they are far more honest and seem to care about their reputation. Anthropic is evil though.
Bro. Sam Altman?