But, in context learning could be better. One important thing here also is the ability to align on what to more/less pay attention to — no matter the Knowledge Base. These are the highest leverage points that need to be exposed to a human to think and reason over. Constrained/Guardrailed development tasks work fine*, But exploration new direction — vs exploiting local minimas — is still an achiles-heel, even with all these knowledge unless there is sufficient steering and exploration the minima-seeking "tries" hard to win.
* With Claude's 1-million context window I have been doing some slightly longer range tasks — ~1-3 days of work — with RPI/QRSPI frameworks(see last few days of comments else where on HN) in one context window. They involve a grill-me session with 20-60 sometimes more questions for tasks to get alignment which produces the design and the plan in one window.
> They involve a grill-me session with 20-60 sometimes more questions for tasks to get alignment which produces the design and the plan in one window.
My experience with this has been that it front-loads a lot of the LLM interactions, which can be exhausting without a reward (i.e. output.) And then, when I get the output, it's so large as to be hard to review/grok.
In other words, it feels a bit like when my coworker delivers me a month's worth of work in a single PR.