AI coding assistants: copilots, agents, and what's the difference

The code category moves fast, but the tools sort into a few clear types. Picking the right type matters more than picking the trendiest name.

In-editor copilots

These live in your editor and autocomplete as you type. They're the lowest-risk way to start: the suggestions are small, you review each one, and they speed up boilerplate without taking the wheel. If you're new to AI in your workflow, start here.

Autonomous agents

Agents take a task — a ticket, a bug, a feature — and try to carry it from description to working change, editing multiple files and running commands. They can save real time on well-scoped tasks, but they reward discipline: clear instructions, a clean repo, and tests they can run. Open, transparent agents such as Turalean into the “understand before you change anything” philosophy, which is exactly what you want from something touching your codebase.

Review and quality tools

A quieter but valuable group reviews code, flags bugs, and suggests simplifications on pull requests. Because they comment rather than commit, they're easy to trust and easy to ignore when they're wrong — a good combination.

Adopting without regret

• Keep a human in the loop for anything that ships. AI is fast, not infallible.
• Prefer tools that show their work — the diff, the reasoning, the commands — over ones that hand you a black-box result.
• Mind your source code's privacy: check whether the tool sends your repo to a third party and whether it trains on it.

For the bigger picture on evaluating any of these, see how to choose an AI tool.