Comment by staticassertion
10 hours ago
TBH I don't think it's worth the context space to do this. I'm skeptical that this would have any meaningful benefits vs just investing in targeted docs, skills, etc.
I already keep a "benchmarks.md" file to track commits and benchmark results + what did/ did not work. I think that's far more concise and helpful than the massive context that was used to get there. And it's useful for a human to read, which I think is good. I prefer things remain maximally beneficial to both humans and AI - disconnects seem to be problematic.
Might not be worth it now, but might be in future. Not just for future LLMs, but future AI architectures.
I don't think the current transformers architecture is the final stop in the architectural breakthroughs we need for "AGI" that mimics human thought process. We've gone through RNN, LSTM, Mamba, Transformers, with an exponentially increasing amounts of data over the years. If we want to use similar "copy human sequences" approaches all the way to AGI, we need to continuously record human thoughts, so to speak (and yes, that makes me really queasy).
So, persisting the session, that's already available in a convenient form for AI, is also about capturing the human reasoning process during the session, and the sometimes inherent heuristics therein. I agree that it's not really useful for humans to read.
I just don't really see the point in hedging like that tbh. I think you could justify almost anything on "it could be useful", but why pay the cost now? Eh.