> For AI agents, it means well-designed CLI tools that help the agent orient itself in a task and pull exactly the 'context-for-the-job' it needs right then.

This is exactly what I am trying to solve and I have what I call smart repositories that demonstrates this at

https://github.com/gitsense/smart-ripgrep

https://github.com/gitsense/smart-codex

The issue I am finding is, getting the agent to pull what it needs, even when the data is there is still challenging since LLMs are trained on blind discovery where the pattern is:

grep -> read -> grep -> read ...

What is working for me now is thanks to Pi (pi.dev). I am working on a pi-brains extension that makes it dead simple to control the lifecycle for an agent so if I detect that it uses `rg` without `gsc rg`, I can block the agent and inject a steering message that says always search with context.

I can also see if they try to "read" without first looking at the files metadata and so forth.

I'm finalizing things right now, but I think pi with my brains extension should allow domain experts to better guide agents so they can find what they need, when they need it.

> You now have to account for the unknown cognitive construct of a completely different intelligence.

But your LLM training corpus covered that, right? /i