2. If it's the correct solution on a high level
3. Whether it conflicts with or duplicates other parts of the system
4. Whether the comments are actually useful or restating the LLM chat
Also many others but these are the most common IME
The sprawling code comments are becoming the most draining part of code review though, that's really killing me from the inside.
If you don't master this for your own project, what's even the point of your job.
No, none of today's AI would give you enough signal around "should this thing be built in the first place" nor if it's the correct solution on a high level.
They don't understand why you are doing what you are doing, and even if you explain it, they still don't actually understand the motivation and lots of other things.
You'll get them to do guesses and pretend they actually know how to prioritize and will tell you it makes lots of sense, whatever they come up with. But try following it blindly and you'll see where you end up.
This is why "one agent + one good developer" beats "thousands of agents working in a swarm" still today.
> What really important things are human reviews catching in your org?
Another person said:
> 1. Whether the thing should be done in the first place
And you replied:
> All of these are angles an AI reviewer can test for as well, and will (IME) mostly catch mistakes correctly
Which as I noted, is very far from the truth. I neither claimed that you said "agent reviews are a panacea", but when you claim "AI can solve all those things" and two of the first items cannot be addressed by AI (today), then I'm rebuking those specific things, not some other general point you implicitly made.
Where "mostly" means kind of what it says but also not really.