What matters when comparing AI coding assistants?

QUICK ANSWER

Start with a representative task and the people who will do it. Evaluate repository access, generated-code correctness, test quality, command permissions, and review effort. Test the same inputs across your shortlist and record output quality, manual work, and current plan terms.

What to do next

Write down what you need

Choose one task you need help with. Code completion, coding agents, and AI-assisted development. Note who will use the tool, what a good result looks like, and anything it must connect to.

Try the same task in each tool

Pick two or three options and give them the same example. Try a normal task and a difficult one. Record the result, any corrections, and how much time the work takes.

Check the cost and important limits

Ask specific questions before paying. For Cursor: Pilot a small repository change; inspect generated diffs, test results, command permissions, and review effort. Check the same requirements with the other options, including access, exports, and the price of the plan you need.

Useful tools to explore

Open a profile for more detail, or check the vendor’s current plans.

Cursor

Developers and engineering teams considering Cursor for this job: AI-assisted code editing.

GitHub Copilot

Developers and engineering teams considering GitHub Copilot for this job: AI coding assistance in development workflows.

Claude Code

Developers and engineering teams considering Claude Code for this job: Agentic coding from the terminal and development tools.

Before you decide

  • Use your own example instead of relying only on a demo.
  • Ask the people who will use the tool to try it.
  • Check the full cost, including extra users and add-ons.
  • Make sure you can export your work if you leave.
Keep in mind

A long feature list does not show how well a tool works for your task. Choose using the results of your own test.

A LITTLE FEEDBACK GOES A LONG WAY

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