Good model. Anybody interested in actually training models or designing agentic systems should be doing this. My company started around working on this problem

Good model. Anybody interested in actually training models or designing agentic systems should be doing this. My company started around working on this problem because it's the basis for how you train programming models/reliably deploy LLMs to do specific tasks. It allowed me to build a much better mental model for LLMs because I saw how weirdly fickle/inconsistent/picky they could actually be outside of a "chat" where it feels like they have a coherent persona or consistent knowledge/capability. Initially I thought of it as a search over prompts for capability at completing specific tasks, but now I think the speed/reliability and operations (eg can I switch models without degrading perforamnce?) benefits are even bigger benefits for most users. A little "secret" since labs are making it harder to even use their models in this way and it's important that it be more widely understood: distribution-aware replay/re-sampling is a key technique in post-training LLMs. But it's also something that allows you to automatically identify the best model for some subset of your tasks, which can save you a lot of money.