Comment by NichoPaolucci
3 hours ago
This is a recurring issue for us. Very small team. We move fast and pretty loose.
Dev + AI spend 3-4 hours on a project plan, there's a "wait a minute" moment, and finally they spend another hour dialing it back to a solution that could have been built, tested, and deployed in 2 hours.
Example: Someone was setting up a dev environment with multiple DB migrations from different branches - AI planned this wild 8 phase solution with a pretty fancy cutover event.
In review I essentially said... "Wait, isn't this a dev environment? It doesn't need 0 downtime, why not just destroy and recreate the DB" and it turned into a <1000LOC script.
Technically the original plan would have worked, it would have been more robust, but it would have taken a good deal more time to implement.
Some of this falls on the devs to know what fits our team well, what's realistic, what's obviously overengineered, etc... But some of it feels like AI just defaults to the most complex version of a thing. I catch it SUPER frequently. (And unfortunately some devs think that more complexity means it's a better solution)
Thanks for posting this!
I feel like I’m going crazy, using all of the best models, spending time to have excellent prompts, configuring tools and skills… and still getting overly complex solutions with mediocre results.
Like it’s still impressive how far we’ve come, and undoubtably cool technology. It’s made a bunch of personal projects possible that I never would’ve started.
But for a business I’m struggling to see the ROI. Sometimes there’s a big benefit and sometimes it’s net negative. Not saying we won’t get there but I’m trying to stay grounded in the reality of today rather than the hopes of where the technology could get to