Does this replace developers?

No. It changes what they spend time on: the AI does the routine work, and developers spend more of the week on design, review and the problems that actually need them.

How do we keep AI-written code to our standards?

Write the standards into the repository where the AI reads them, start with small well-scoped tasks, and keep human review on every pull request. Quality comes from the same place it always has: clear expectations and review.

AI Use Cases

BuildBusinessSaves 1 to 2 days per developer per week

AI development accelerator

Use AI as a junior developer that works to your coding standards, with you as final reviewer, and as an expert across your whole codebase.

The problem

Development teams lose their best hours to work that is necessary but not hard: boilerplate, test scaffolding, small fixes, and answering "how does this part of the system work" for the third time this month. Meanwhile the backlog of real engineering waits.

The workflow

1
Connect the codebase
Give the AI access to your repositories through the GitHub connector or a coding agent like Claude Code.
2
Write the standards down
Capture your conventions in the repo: style, patterns, review rules. The AI reads them and works to them, like any new starter.
3
Delegate like a lead
Hand the AI well-scoped tickets: bug fixes, tests, refactors. It opens branches and pull requests like any team member.
4
Review everything
You stay the final reviewer. Nothing merges without a human approving the PR.
5
Use it as the codebase expert
Ask how a flow works, where a value comes from, what a change would break. The AI reads across the whole codebase in seconds.

Start here

Once your connectors are set up, this prompt kicks the whole workflow off. Adjust the details to match your business.

Paste this into your AI tool

Read the contributing guide and coding standards in this repository. Then take issue <number>: implement it on a new branch following those standards, write tests that match the existing test patterns, run the test suite, and open a draft pull request describing the change and anything you were unsure about. I'll review before anything merges.

The outcome

Routine engineering delegated, questions about the codebase answered instantly, and your senior developers back on the hard problems.

Time saved: 1 to 2 days per developer per week

What it needs

The connectors this workflow uses, and how it runs on each AI platform.

Connectors

GitHub

Works on

Last verified 18 October 2026

Claude Code

Works natively

Purpose-built for this: repo access, standards files and PR workflows out of the box.

Who it's for

Technology & Software Development/Engineering

The reusable skill

The reusable recipe: treat AI like a capable junior with a perfect memory of the codebase. Invest in written standards, keep tasks well-scoped, and never give up the review step. Teams that skip the standards get volume; teams that write them get velocity.