Ship code faster with AI

What it is

Engineering teams and technical marketers can move faster by handing well-scoped coding work to AI: routine changes, tests and documentation. The gain comes from delegating with review, not from accepting large unreviewed changes.

How it works

1. Pick an AI coding agent that works with your repository, such as Cursor, OpenAI Codex, Claude Code or Google Antigravity. All four can work in your editor or terminal, and each also offers agents that keep working in the background.
2. Write task descriptions with acceptance criteria.
3. Let the agent propose changes on a branch and run the tests.
4. Review the pull request and merge.
5. Connect GitHub to other agents if needed. GitHub’s MCP server lets AI tools read repositories and code, manage issues and pull requests, and monitor Actions workflow runs.

Plan names, limits and prices for each agent change often. Check the vendor’s own plan page before you buy, and compare them on which AI platform to use for what.

Benefits

• Faster routine work.
• Better test coverage when you ask for it.
• Backlogs of small issues get done.

Limits and risks

• Insecure or wrong code if review is skipped.
• Shell access needs scoped permissions (see letting an agent act safely).
• Keep secrets out of repositories and prompts.