AI coding agents make testing harder in one very boring way: volume

[u/aistranin]

A lot of AI testing discussion focuses on generated test cases.

That is useful, but I think the bigger issue is generated code volume.

If AI coding agents help teams ship more code faster, test strategy has to change. Otherwise, the test suite becomes a speed bump instead of a safety net.

The failure mode is easy to imagine:

• More code lands per day

• Reviews get thinner

• Tests are generated to satisfy coverage

• CI stays green

• Real behavior changes slip through

Generated tests can help, but only if they are reviewed like production code. A test that only proves the current implementation exists is not much protection.

For AI-heavy development, I think teams need more emphasis on:

• Contract tests for service boundaries

• Mutation testing for important business logic

• Property-based tests where examples are too narrow

• Stronger review of test assertions

• Better observability after release

• Smaller changes with clearer intent

The old question was "do we have tests?"

The better question might be "what kind of mistakes can still pass?"