How to give AI context about your code — so it stops guessing

The most common beginner complaint: "the AI writes some nonsense that doesn't fit my project." And here's the twist — it's almost never dumb. It just can't see your code. It guesses in a vacuum because you never showed it what you're working with.

Good news: context is given once, in a file — and the quality of answers jumps. Here's how, step by step.

1. Understand what the AI genuinely doesn't know

First, accept a simple thing: the model only sees what you gave it in this request. It doesn't "remember" your project and doesn't crawl your folders on its own. Anything outside the context window doesn't exist for it.

So your job isn't to make the AI "understand" — it's to lay the right things in front of it. Here's exactly how.

2. Create a context file in your project root

Create a text file in the root of your repo where you gather everything essential about the project. Popular AI editors have standard names for this: CLAUDE.md, AGENTS.md, and the universal option — a plain README.md.

The trick: editor agents (Cursor, Claude Code and others) read that file themselves before working. Write it once and it gets mixed into every request without you lifting a finger.

3. Describe the stack and structure in two paragraphs

First up — what the project is and what it's built on. Keep it short:

A notes app. Frontend — React, backend — Supabase (Postgres). Styling — Tailwind. src/components is the UI, src/lib is the database layer.

Don't write a novel. Three or four sentences answering "what is it, on what, where things live". That's enough to stop the AI from suggesting a stack you don't use.

4. Set the rules and conventions

Next — the thing the model will never guess: your unwritten rules.

• Style: "write in TypeScript, no any".
• Boundaries: "don't touch the legacy/ folder, it's being removed".
• Conventions: "all database calls go only through src/lib/db.ts".

These lines are exactly what turns "just code" into "code in your style". It's the same move as a good system prompt — you set the role and boundaries up front.

5. Show one real example

One shown function is worth ten descriptions. Paste a short sample of how you write things: a typical component, a typical query. The model copies style from an example beautifully — that's what it's built for.

6. Point to real files, don't paraphrase

When you ask for something, don't retell the code in words — hand over the actual file. "Here's db.ts, add a delete function following the pattern" works far more accurately than a description from memory. Paraphrasing loses details; the source doesn't. That's the essence of context engineering: don't coax the model, put facts in front of it.

7. Keep the file short and update it

Don't turn the context into a junk drawer. Too long a file clogs the window and drowns what matters. The rule: if a line is no longer true — delete it. Changed the stack — fix the paragraph. Stale context lies to the model worse than no context at all.

What you get

You end up with a "project passport" the AI reads before every task. Answers stop being generic: the model suggests your stack, in your style, mindful of your rules. You spend a couple of minutes on the file once — and save dozens of "no, not like that, redo it" every day. On phrasing the requests themselves, see how to write a good prompt.

To make it concrete: without the file, asking "add a logout button" gets you a button in the wrong framework and the wrong style — you redo it three times. With the file, it grabs your React, your Tailwind and your db.ts right away, because it read about them before the task. Same request — one pass instead of five. And a bonus: the context file is a shared language for the team. A new person (or a new AI agent) opens it and gets the project in a minute, instead of asking about everything piece by piece.

Does the file have to be named CLAUDE.md or AGENTS.md?

No. Those names are read automatically by specific tools — handy, but not required. If your editor doesn't support them, just keep a context.md or README.md and paste its contents at the start of your request by hand. The point isn't the name, it's that the context exists.

How much context should I give — the more the better?

No, there's a sweet spot. Too little and the model guesses; too much and it drowns and loses the main thing. Give what the task actually needs: the stack, the rules, a couple of examples, the relevant files. Don't dump the whole project.

Why does the AI sometimes ignore my context file?

Usually because something important drowned in a long text or contradicts itself. Move the key rules to the top, cut the stale bits, shorten it. When an instruction is short and clear, the model holds onto it far better.