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Continuous integration for AI agents

What a sensible CI pipeline looks like when the artefact under test is a prompt, a model version and a tool set.

24 June 20266 min read

Agents deserve the same pipeline discipline as the services they call.

Pipeline stages

  • Smoke suite on every commit, 10-15 scenarios, under a minute.
  • Full suite on pull requests, the complete scenario set plus regressions.
  • Comparison against the current production version, with a verdict.
  • Block the merge on any failing release-blocker case.

Handling flakiness

Seed everything. If a case is genuinely non-deterministic, fix the case or the agent, do not add retries until it passes, which is how suites lose their meaning.

Reporting where people look

Post the delta as a pull request comment: fixed, new, and blocked. Nobody opens a dashboard during review.

What to take from this

  • Two tiers: fast smoke, full suite on PR.
  • Never paper over flakiness with retries.
  • Put the verdict in the pull request.

See it on your own agent

Connect an endpoint and run twenty scenarios. The first run usually finds something.

Start testing

Keep reading

  • Claimed, not executed

    The most expensive agent failure is a confident sentence about something that never happened, and a transcript cannot see it.

  • Not verified is not a pass

    A test suite that quietly passes the checks it could not perform is worse than no suite at all.