AI agents fail in ways nobody writes about. Here's what I've actually seen.

Not theory. Things that broke on me running real workflows. Context bleed. Agent carries memory from a previous task into the next one. Outputs start drifting. By step 6 of 10, it's confidently wrong in ways that are hard to catch. Confident wrong answers. Agents don't say "I don't know." They fill gaps. In outreach automation this means sometimes writing a personalised message that references something that doesn't exist. The model just invented a plausible detail. This is the one that costs the most with clients. The human review queue nobody designed for. You build 90% autonomous.