What's the smallest, dumbest thing that made you completely lose trust in an AI agent mid task?
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It doesn't even have to be a big dramatic failures, more the small moments where something clicked and you went from trusting the output by default to double checking everything. For me it was watching an agent confidently rename a function across twelve files, then leave the original function untouched in a thirteenth file it apparently didn't search, with zero indication anything had been missed. It wasn't even a hard case, the file just wasn't in the directory it happened to grep first.
What was your moment? And did it actually change your workflow afterward, or did the trust creep back in after a week like it always seems to for me?
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A surprisingly small one: it created a file, then deleted it during cleanup without asking. Nothing broke, but I stopped trusting automatic cleanup after that.
Mine was when the agent forgot a simple instruction from the beginning of the task. Not a complex requirement just one basic constraint.
For me - and it's a really consistent/regular problem - it was an agent "fixing" a failing test by editing the assertion instead of the code, and reporting it green. Now I never let one close its own loop. Pay attention, and it happens more than you think!
Mine was when it confidently referenced a file that didn’t exist. Not a complex hallucination just a basic fact it should have verified.
The smallest trust breaking moment is probably an agent making a reasonable assumption without telling you. The assumption may be correct, but hidden assumptions are difficult to trust.
For me trust drops fastest when the mistake is easy to prevent with one simple verification step. do you think agents should be more transparent about they did not check?
@twagiramungu_yves yes, the agents should be more verbose about the things they didn't check.But I'd go further than just flagging what wasn't checked. I'd want it to default to naming its own confidence level per claim, something like "ran the tests, they passed" versus "assumed this worked based on the diff, didn't actually re-run anything."
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the small moments are one thing but the ones that really break trust are the public ones.
pocketos had an AI agent delete an entire production database row. not because the model hallucinated, but because the agent had access it probably shouldn't have had and no one had defined what it was actually allowed to touch.
that's the pattern. it's not always the agent being dumb. sometimes it's that the agent inherited too much access, acted confidently within that access, and there was no audit trail to catch it before the damage was done.
that's actually one of the reasons building MonoCloud. giving agents their own identity and scope instead of borrowing the user's token. because when something goes wrong, you need to know exactly what the agent did, what it had access to, and be able to revoke it instantly. right now most stacks can't answer any of those questions cleanly.
the trust creep is real though. a bad incident scares everyone for a week and then slowly things go back to normal 😅
I had an agent triage and dedupe a messy backlog for me, a few hundred tickets, and on the surface it did a genuinely good job, with clean clusters, sensible labels, and a confident summary of the top themes. The problem showed up later. It had merged two reports it decided were duplicates, and they were not. One was a checkout bug and the other was a display glitch that happened to use similar words. The second issue simply disappeared off the board, with no note that a judgment call had even been made.
That is the moment my default flipped. It was not that the agent got something wrong, tools get things wrong, it was that it collapsed two items into one and gave me no signal that a decision had happened at all. A visible mistake I can catch, but a silent one I have to suspect before I even go looking.
What changed for me is that I stopped letting agents make quiet merges or deletions. Summarizing, clustering, and suggesting are all fine. Anything that removes or combines items has to show me what it touched and why, so the judgment stays with me. And to your last point, the trust does try to creep back, but on anything that changes the actual source of truth, I have held that line.
@roguetink That distinction between wrong and silent is exactly it. A wrong merge you can fight with, a silent one you have to remember to go looking for in the first place, and most people won't.
mine was an agent telling me "all tests pass" after a refactor, and it turned out it had run the suite, hit a config error on one test file, and just moved on without flagging it - so "all tests pass" actually meant "the tests that happened to run passed." found out two days later when CI failed on the same commit. now I always ask for the actual test count before I believe a green summary, since a silent skip looks identical to a real pass in the chat output.
Mine wasn't a catastrophic error either. It was when an AI agent silently made assumptions instead of acknowledging uncertainty. It filled in missing context, produced a polished answer, and everything looked reasonable until I realized one key assumption was completely wrong.
That changed how I use AI. I still trust it for drafting, research, and exploring ideas, but I no longer treat confidence as a proxy for correctness. Now I pay much more attention to whether the agent surfaces its assumptions and uncertainties. Ironically, an AI that occasionally says "I'm not sure" earns more trust than one that sounds certain about everything.