I think if you’re human-reviewing all the output of AI, then you’re going to hit the human comprehension bottleneck.

The key is to have clear specs and clear architecture, and then have agents enforce this.

I devote most of my time to specs and much more of my time to e2e and integration tests.

I find a lot of value, even more value than before, in strictly hexagonal designs and even a large does of DDD.

Following these principles, it’s relatively easy to design systems of systems that decompose to domains that decompose into use cases / ports / adapters.

By the time you’ve decomposed to this level, AI is very capable and it’s easy to review or verify by tests. I am very comfortable with AI verifying if a basic CRUD port is functional, for example, because at this point each operation becomes less than a dozen lines of code.

Stop thinking of yourself as a programmer and start thinking of yourself as an architect.

The key rule is that decomposition of a problem into smaller problems is what wins. This was always true, extremely true before AI and extremely true with AI.

Focus your individual effort on the top-level decompositions and let AI handle the lower-level decompositions. Trust AI to test the lower-level and make sure you test the higher levels.