[TomOwens]

Having a bottleneck with AI-generated code is probably a good thing.

Consider before AI. In cases where code was written by a trusted human, you had confidence that they were doing the right stuff - the people understood the context and requirements, the changes were based on those requirements, and tests were updated. You could rely on some basic automated checks to run a linter and static analyzer, execute the tests, and check test coverage. You can defer longer-running tests to a later stage, but people can merge their work in and collaborate. You can have blocking reviews for untrusted outside contributors or new employees and review the rest later.

After AI, the input is a mess. I haven't personally seen the worst of it, but I've read about people generating code before any requirements development or analysis. Code is generated without understanding what it is supposed to do, which also prevents good testing. Even with good requirements, people generate solutions that aren't right, and the generation step may remove failing tests or make unintended changes that aren't covered by tests. So much code is generated from untrusted sources and rubber-stamped. Introducing a bottleneck where a human can slow the process down is a good thing here.

Maybe if we can get people to understand how to use AI tools responsibly and have humans take full accountability for the output and changes, we can get back to the old way. Trusted humans and an AI agent assistant can make changes that are solid enough to merge. Independent control over the pipeline and basic automated checks would give just enough confidence in the change, and delayed review before deploying or enabling the feature would work. But not until trusted humans actually maintain oversight over their tools.