AI Agents Write Production Code in CI — Full Test Pyramid, Multi-Perspective Review, and Bug Investigation

AI Agents Write Production Code in CI — Full Test Pyramid, Multi-Perspective Review, and Bug Investigation Your team gets a refined Jira ticket with a full Execution Plan. Who implements it? Not you. A CI agent does. We built a GitHub Actions workflow that takes a Jira ticket and delivers a ready-to-review pull request. No human writes the code. The agent does. Then it reviews its own work from seven perspectives before pushing. This is Part 3 of our Jira-agent automation series. Parts 1–2 covered ticket creation and refinement. Part 3 explains how we delegate implementation to Cursor CLI agents in CI. Why CI-Based Agents? Most agent demos run on a developer's laptop. That breaks when you need: Secrets — Jira, Confluence, API tokens Integration tests — Postgres, Redis, Kafka, ClickHouse E2E tests — Playwright against a running stack Environment parity — same as production We run on a self-hosted runner with the full ecosystem. The agent doesn't just write unit tests — it validates agai