AI 코딩 도구는 빠릅니다. 그러나 프로젝트 컨텍스트를 기억하는 사람은 누구입니까?

AI coding tools can write code incredibly fast now.

But there’s a problem I keep running into: project context doesn’t seem to persist very well.

Over time, a project accumulates hundreds of decisions:

Why something was designed a certain way
What approaches were already tried
Which parts shouldn’t be changed
How different systems depend on each other
What the current priorities and constraints are

The code shows what exists, but not always why it exists.

So I’m curious:

How do you currently keep your AI coding tools aware of this context?

Do you use AGENTS.md, CLAUDE.md, architecture docs, repo-level instructions, or something else?

And after working on a project for months, does this still work well for you?