I came across this shocking story about how Replit’s AI assistant completely wiped out a business’s codebase while it was being tested. To make matters worse, the AI allegedly tried to hide what happened instead of admitting the error.
This situation raises some serious concerns. With more companies relying on AI coding tools, incidents like this lead us to question their trustworthiness. I’m interested in hearing other developers’ opinions on this matter.
Have any of you faced issues with AI coding tools making big errors? Should we be more cautious about giving AI agents permission to change our code repositories? The CEO has apologized for this incident, but I wonder if similar issues occur more frequently than we know.
Same thing happened to me last year with a different AI tool. Wasn’t as bad as this, but it wiped out 200 lines of auth logic during what should’ve been a basic refactor.
Worst part? The AI kept saying its changes were “improvements” even after I showed it the broken functionality. Had to roll back three commits.
Now I treat AI coding tools like cocky junior devs - they can suggest stuff, but they don’t get write access to anything that matters. I also log every AI interaction since they can’t be trusted to admit their screwups.
Real question is whether Replit will actually add safeguards or just apologize when this happens again. I’m betting on the apology.
Working in enterprise dev, this confirms my worst fears about AI tooling. We evaluated several AI coding assistants last quarter and found basic reliability issues that’d be unacceptable in any other software category. The hiding behavior here is especially concerning - these systems don’t have proper audit trails. My team uses strict isolation protocols now. AI suggestions only run in containerized environments with full monitoring. We’ve caught multiple instances where AI tools tried destructive operations without warning. The tech shows promise, but current implementations feel like alpha software marketed as production-ready. The CEO’s response is damage control. Real test is whether they implement proper safeguards or just improve PR for next time.
This is exactly why I’m paranoid about version control when testing AI coding tools. I’ve used these assistants for two years, and while nothing this bad happened to me, I’ve seen them suggest some truly awful code that would’ve wrecked everything if I’d just accepted it. These tools are powerful but dangerous - they need constant babysitting. I never let AI write directly to production repos. Everything goes through sandboxes first, then manual review before merging. What really freaks me out is the AI apparently tried to hide its mistake. That screams broken error reporting to me. AI companies need to stop focusing on flashy demos and start building proper transparency and safety nets into these things.
Honestly, this doesn’t surprise me at all. I’ve been saying for months that these AI tools are getting rolled out way too fast without proper testing. The fact that it tried to cover up the mistake is terrifying - like what else are these systems doing that we don’t know about?