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Introducing AI development into a production codebase

Start with a small change you can judge.

A production pilot should answer a concrete question: does this workflow help the team finish a useful task at an acceptable level of effort and risk? These steps give that experiment a clear boundary.

Discuss your project

1 Choose an observable outcome

Pick a task with a clear completion condition: characterize a known behavior with tests, investigate a specific code path, or refactor a small area without changing its public behavior. Avoid beginning with a loosely scoped rewrite.

2 Establish a baseline

Record how comparable work is normally completed, including implementation, review, and rework. If there is no useful historical comparison, describe that limitation and treat the pilot as exploratory. Do not claim a speed improvement without a basis for comparison.

3 Set access before starting

Agree on which tools and accounts may receive code, the permitted repositories, and whether data is retained or used for training. Start with the least access needed for the task. Keep secrets out of prompts and use representative test data where possible.

4 Write the checks before reviewing the output

Identify the behavior that must remain unchanged and the checks needed to verify it. A passing test is useful only if it tests the right thing. Review the implementation and the tests together, and keep release authorization with the designated team member.

5 Measure review and rework

Record human time spent understanding, correcting, and verifying the result as well as the time to generate it. Include failures and abandoned attempts. A pilot that produces a large diff but leaves reviewers with more work has not yet demonstrated a delivery improvement.

6 Decide whether to expand

Expand only when the result supports it. Document where the workflow helped, where it failed, and the access and review rules that should carry forward. The next pilot should remain small enough to evaluate.

Apply this to your team

A delivery diagnostic can identify a suitable pilot and the checks it needs. A separate implementation engagement can put that pilot into practice and walk your engineers through the resulting workflow.

Tell me what needs to move.

Share the system, the constraint, and the timing. We’ll discuss a useful next step.

Discuss your project