I think a lot of people are underestimating how expensive unreliable agents are

not in API cost in human attention I had a workflow recently that technically “worked” it completed tasks returned outputs didn’t crash but every few hours I’d still check it manually because I didn’t fully trust it and eventually I realized: if I’m constantly monitoring the system, then part of my brain is still doing the work that hidden cognitive overhead adds up fast I think this is why so many agent demos feel impressive but don’t survive real daily usage. reliability isn’t just about accuracy. it’s about whether a human feels safe ignoring the system for long periods of time the agents that actually became useful for me weren’t the smartest ones. they were the ones with: * predictable behavior * tight boundaries * validation before actions * stable inputs honestly a lot of my “AI problems” ended up being environment problems too. especially with web-based tasks. flaky page loads, inconsistent data, expired sessions. the agent would just adapt badly to whatever it saw once I made that layer more stable, using more controlled browser setups and experimenting with things like Browser Use and hyperbrowser, the same workflows suddenly felt way more trustworthy without changing the model much curious if others feel this too at what point does an agent actually become trustworthy enough to stop checking constantly?