The moment all code is interacted with through agents I cease to care about code quality. The only thing that matters is the quality of the product, cost of maintenance etc. exactly the thing we measure software development orgs against. It could be handy to have these projects deployed to demonstrate their utility and efficacy? Looking at PRs of agents feels a wrong headed, like who cares if agents code is hard to read if agents are managing the code base?

We don't read the binary output of our C compilers because we trust it to be correct almost every time. ("It's a compiler bug" is more of a joke than a real issue)

If AI could reach the point where we actually trusted the output, then we might stop checking it.

You should at least read the tests, to make sure they express your intent. Personally, I'm not going to take responsibility for a piece of code unless I've read every line of it and thought hard about whether it does what I think it does.

AI coding agents are still a huge force-multiplier if you take this approach, though.

> Looking at PRs of agents feels a wrong headed

It would be walking the motorcycle.

This is how we wound up with non-technical "engineering managers." Looks good to me.

You could look at agents as meta-compilers, the problem is that unlike real compilers they aren't verified in any way (neither formally or informally), in fact you never know which particular agent you're running against when you're asking for something; and unlike compilers, you don't just throw away everything and start afresh on each run. I don't think you could test a reasonably complex system to a degree where it really wouldn't matter what runs underneath, and as you're going to (probably) use other agents to write THOSE tests, what makes you certain they offer real coverage? It's turtles all the way down.