I'd say AI code review is a good starting point. For instance, having one thing review code for CVEs, I've found that very useful. Another review agent for looking at typical things like static analysis violations, or not adhering to DRY, or 10,000 lines of code in one class, whatever makes the code less maintainable and more expensive technical debt wise. Then you still need a human in the loop to validate what the reviewers (agents) are recommending and what the agent that wrote the code did as well (if the agent submitted the PR, even if a human did it I'd still have a human review it). It can augment what reviewers typically do day-to-day but definitely doesn't replace them. Here's why: if the system breaks at 3 am and you're losing millions of dollars a minute because it's down, you can't email / call the agent and say, "fix the broken code you allowed into the repo". (at least not yet).

nothing wrong with worrying about that part specifically, and I don't think it's the same situation as a senior using AI at all. a senior supervising AI is applying judgment they already built the hard way, years of hitting walls, debugging blind, being wrong and finding out why. that judgment is an asset and AI just makes it faster to deploy. a junior using AI the same way skips where that judgment gets built in the first place. reps that used to force comprehension, writing it yourself, staring at a stack trace with no idea what's wrong, are exactly the reps AI removes. so yeah, I think juniors are at real risk here, but from using it the same way seniors do. the solution isn't avoiding AI (obviously) but using it deliberately in a way that still forces the struggle. write your own first attempt before you ask AI anything. when it hands you a fix, don't move on until you can explain why the bug happened, not just that it's fixed. that's slower than just trusting the output, but it's the only way the comprehension actually gets built instead of borrowed. you still need to train yourself!

Let me know if I’m wrong but, The way that sounds is you push for AI to be kind of like the programmer. And you are the supervisor making sure it fits its i’s and crosses its t’s. The new skill is not going to be programming but prompt engineering basically. How to effectively make the AI do what I want the AI to do. I get melancholy about a future where we are just typing into a chatbot to write a program for me. It’s like paying for gems in a game to speed up a chest. Feelings aside lol, do you really think AI is at that point that the skilled who can use it correctly will become better engineers as a result? I guess another question I never mentioned was what about being able to understand what you’re working on? I get why a senior dev would have no issue using AI and being the final check but I am a recent graduate. Isn’t AI also going to affect developers comprehension of problems? Even if it’s just about spotting those errors, junior devs I feel will struggle disproportionally more.