A coding agent (Claude Code, Cursor, Copilot, and the like) is an agent tuned for work with your project: it reads files, writes code, runs tests, walks the repository. The difference between people it speeds up several times over and people whose agent "writes nonsense" isn't the model — it's how they work with it. It's a skill, and it has a basic loop.

Give context and a goal, not an order

The most common beginner mistake is to throw the agent a short command and wait for a miracle. The agent works with exactly what's in its context and knows exactly what you gave it. A productive session starts with three things:

  • The goal — what should come out and how to know it's done. "Add a cancel-order endpoint; after it the status in the database is cancelled, the test passes."
  • The context — which files, rules, and constraints relate to the task. Not "the whole project", but the relevant.
  • The boundaries — what not to touch, what style to write in, which approaches are forbidden.

The clearer the input, the better the output. This is a direct consequence of how models work: a vague prompt → a vague result.

Work in iterations, not one big go

Don't try to get everything in one huge request. A large task in one turn almost always gives a result that's easier to throw away than to untangle. It's more productive to go in small, verifiable steps:

  1. Break the task into pieces, each of which can be checked (build, run a test).
  2. Do one piece → check → lock it in → the next.
  3. If it went the wrong way — roll back to the last good step, not fix the snowball.

Small steps matter also because an agent's errors accumulate: the longer the uncontrolled series, the further the result drifts.

Keep steps verifiable

An agent is strong when it has an objective criterion: a test, compilation, a run. Give it something to check itself against — the tests that should pass, the build command, the expected result. Then the agent sees its own error and fixes it, and you get a result about which something is already known.

Without a verifiable criterion the agent "thinks it's done", while in reality it's plausible but wrong.

Don't let go of control

The agent is an amplifier, not a replacement for judgment. You remain the one who:

  • reads the diff rather than accepting it blindly — especially at seams, in edge cases, in deletions;
  • decides architectural forks yourself, rather than asking "which is better?" of a model that will answer plausibly;
  • verifies the result (accepting AI output) before it goes into action.

The speed from the agent is real, but it turns into debt if you accept everything without looking.

What this means in practice

Working with an agent isn't "ask and receive" — it's a controlled loop: a clear goal and context → a small verifiable step → a check → locking in → the next step, with your judgment at the forks. A product engineer treats the agent like a very fast junior: gives a clear task, gives something to check against, reads the result, and keeps the wheel.

What's next

Next — concrete scenarios of this loop: how to use the agent to understand an unfamiliar codebase, develop features through plans and brainstorming, find and fix bugs, review and test code, and how to configure the agent for your project.