I have been thinking a lot about how teams give their AI agents access to real systems, and I would rather hear how people are doing it in practice than in theory. On one end I see teams hand an agent a single API key or service credential that can basically touch everything, because it was the fastest way to ship. On the other end I see people trying to give each agent its own scoped identity, short-lived tokens, and some kind of audit trail, which is a lot more work to stand up. Most teams seem to sit somewhere uncomfortable in the middle. If you are running agents in production today, what does your setup actually look like, how did you land on it, and is there a part of it that quietly worries you when you think about it late at night?
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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