Using AI coding agents on a Java team without losing quality

AI coding agents are now good enough to write most of a Spring Boot feature. That does not make them senior engineers. The value comes from pairing their speed with the judgment of someone who knows what production looks like.

What gets faster

• Boilerplate and glue code: DTOs, mappers, controllers, configuration.
• Tests: agents are excellent at enumerating edge cases once you describe the behavior.
• Reading unfamiliar code: asking an agent to trace a request through a legacy codebase saves hours.

What still needs a human

• Boundaries: transaction scope, module ownership, what belongs in which service.
• Failure modes: retries, idempotency, timeouts, what happens when Kafka is down.
• Review: every generated change is read like a pull request from a new colleague.

Guardrails that work

1. Small, focused tasks with a clear definition of done.
2. A fast test suite the agent must keep green.
3. Static analysis and formatting in CI, so style debates never reach review.

Used this way, AI does not replace the engineer. It removes the parts of the job that were never the point.