My experience and what I’m concerned about is that eventually more time is spent refactoring to enable new features than writing the features themselves. In my experience this becomes worse with time as the models are reluctant to remove behavior, so the code base will grow to support some version of the old behavior together with the new behavior.
Hats off to my team, they did review the code. And it was embarrassing. I could not answer any questions asked by my team without looking at the diff. It was supposed to be "my changes", as we have agreed to the team. You can do everything with AI, but you own the changes. I did not. Why do we need to remove duplicates and call GraphQL in batches of 25 IDs when it's for 3 items displayed on the page? Did I have that much distrust in our Ops team to not believe that they can choose 3 unique IDs without having duplicates and know the difference between 3 and 25?
Use AI for anything you want but make sure you own the changes. Otherwise, you're just a meat proxy. Don't be a meat proxy like me. Be better. This world needs you more than ever to own it.
I read big claims, no evidence.
"AI code is non-deterministic and has risk. But human code is non-deterministic too, and it has the exact same risk."
No, that's not true. LLM-written code has very different risks, like completely misunderstanding the requirements, adding in hallucinated features, and losing sight of what the codebase actually does (massive tech debt).
I should ask, who writes the unit tests? And how do you write the unit tests beforehand? What if you need to prototype in order to figure out the shape of the API? The setup used here is so far removed from any software safety or software quality concerns, it would be hilarious if it weren't sad.
Stop posting marketing content void of any real information, please.
Kudos•41m ago