That must be a remarkable model. Smart enough to flawlessly discover everything on its own in every session... but also it just straight up just doesn't obey direction.
Hmmm.
I didn't say give no direction.
I'm saying a lot of devs/engineers little rain dances aren't really bringing the rain.
Keep a basic CLAUDE.md/AGENTS.md that keeps high level details. Have a way to reference other projects/apps/codebases to use as reference architecture.
Don't keep tons of markdown files. Don't keep "decision" documents (these are probably the worst). Don't make skills for every little thing (superpowers are dead these days, stop using them). Oh yeah, don't have the LLM generate docs for reference later... if it can generate the docs it doesn't really need them.
At work it's all Anthropic. I spent a while on Sonnet models but have been pretty consistent about using Opus now. For personal projects I bounce between Sol/Terra and Gemini Flash.
Most of the models are good enough now. You don't need all these documents, memory, plugins, skills, etc. MCPs are good for hooking up to external sources of data (at work we have gitlab mcp, datadog mcp, and our knowledge base mcp... which the knowledge base is mostly worthless now because of all this AI generated documentation, but I digress). I DO still use beads on a lot of projects, but not always. My prompts these days are lazy as fuck: "review this repo, check out this other repo with architectural patterns we should follow and libraries/terraform/etc we should use, <basic desc of goal>. What do you think? Let's review everything and discuss before we start building"
Oh no, I might have to stop the llm agent on occasion, or review what they did and tell them to fix a couple things. Way better use of tokens and my time than creating some rube goldberg machine. Way better than keeping a giant decision file that goes stale and causes context corruption because the llm only saw the OLD decision and not the UPDATED decision.