AI coding agents have moved from autocomplete to doing whole tasks: reading a codebase, running commands, editing files and checking their own work. Adoption grew quickly through 2026, and so did a familiar complaint in developer surveys: the output is often almost right, and debugging almost-right code takes time.

Most of that gap comes from how the work is set up, not from the model.

Give the agent a way to check itself

The single biggest improvement is a fast, reliable feedback loop.

  • A test command that runs in seconds, not minutes.
  • A type checker and linter the agent can run.
  • A clear instruction: "run the tests and type check before you say you are done".

An agent that can verify its work iterates toward correct code. An agent that cannot is guessing.

Write a project instructions file

Most agents read a project-level file (for example CLAUDE.md or AGENTS.md). Keep it short and specific:

markdown
# Project notes
- Package manager: pnpm. Never use npm.
- Run `pnpm test` and `pnpm typecheck` before finishing.
- API handlers live in src/server/routes. Follow the pattern in users.ts.
- Do not edit generated files in src/gen.

Rules that prevent repeated mistakes are worth more than a description of the architecture.

Scope tasks like you would for a new teammate

  • One outcome per task. "Add pagination to the orders endpoint" beats "improve the orders feature".
  • Point to examples. "Follow the pattern in users.ts" saves the agent from inventing a new one.
  • State constraints. Performance limits, libraries you do not want, files that must not change.

Plan first for bigger changes

For anything touching more than a few files, ask for a plan before code. Review the plan, correct it, then let the agent implement. Fixing a plan is cheaper than reviewing a wrong 600-line diff.

Review like it matters

Agent output deserves the same review as human output, plus a few extra checks:

  • Did it change tests to make them pass instead of fixing the code?
  • Did it add dependencies you did not ask for?
  • Are there hard-coded secrets, disabled checks or broad try/catch blocks hiding errors?
  • Does the diff contain unrelated "cleanups"?

Protect your environment

Agents run commands. Treat that seriously.

  • Use permission modes or allowlists for commands that write, delete or reach the network.
  • Keep production credentials out of the development environment.
  • Be careful with agents reading untrusted content (issues, web pages, dependency READMEs), which can contain prompt injection.

Key takeaways

  • A fast test and type-check loop matters more than prompt wording.
  • A short project instructions file prevents repeated mistakes.
  • Scope tasks tightly and plan before large changes.
  • Review agent diffs carefully and limit what commands can do.