I now started to us AI to help review my juniors PRs, because I couldn't keep up with the amount of code they ship. It started poorly, but now I have my method: I first read the code and flag the lines I'm not sure about, then ask any frontier model (I like Claude here for analysis, even if I don't use it for the rest) to explain the PR and to put effort on the parts I flagged (basically explain in detail the code, not only the PR), and to search through the libraries. Sometimes it notices something I would have missed (like missing an 'order_by' or off by one errors, because the underlying lib wasn't coded like the original AI pretended it was).
I also changed the way I do review because it has been more than a year and the juniors/new hire are still lost, wether on domain knowledge for the older new hire, or just capabilities for the juniors, and discussing with other departments, it's the same for like 95% of them. Now, rather than correcting the PR or adding a request for change, I add a whole unit/functional test to the PR and let that as an exercise to pass the test. They can use AI but I tell them to try to find what part of the code doesn't work before generating the fix, hopefully they'll take ownership of the code if I keep doing that.
"because the underlying lib wasn't coded like the original AI pretended it was"
So, the models ARE dumb. They just are very good at finding patterns in their training data. I mean, when they code minecraft clones, it is not because they can cook up how to write minecraft clones, rather, their training data includes a lot of minecraft-like games code, and they just reuse that.
Why are you paying them if they insist on remaining meat proxies?
where do u work that even hires juniors lol
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>I tell them to try to find what part of the code doesn't work before generating the fix
this makes me kinda sad. they don't do this on their own? are they not even a little curious