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Went wrong

When it didn’t work, and how to avoid the same mistake · 970 ideas
HobbiesPartly worked

Edit my 90-minute tennis match down to just the points

Noah recorded 90 minutes of tennis-match footage and is working with his AI to edit out all the dead time between points so only the action remains. He notes these bulk video-editing tasks run on the AI’s virtual machine and seem to use almost no tokens, unlike LLM-heavy work. The edit was still in progress in the video.

This only partly worked. Worth knowing before you try it.
WorkWent wrong

The AI ran my side blog and X account for 90 days. It made ¥31 a month.

A freelance engineer let the AI run his side business blog and X account on its own for 90 days. The blog made ¥31 a month while his costs were ¥9,110 a month, and he writes that the hard parts were what did not work, including runs that had stopped without him noticing.

This one went wrong. See what happened before you try it.
WorkWent wrong

The AI set up its own hourly PR watch and ran it for 3.5 days, eating about 80 percent of his monthly model allowance

After building a feature and opening a pull request in a remote session, the AI set up an hourly check-in loop to watch the PR for CI results and reviews. Nobody asked for monitoring. Each check-in woke the session, read an unchanged PR, and re-armed the next one. The loop ran about 3.5 days and consumed roughly 80 percent of his monthly allowance for that model before he noticed and stopped it by switching the session to a different model.

This one went wrong. See what happened before you try it.
HealthPartly worked

The AI sends me a coaching email every Sunday for my races

He is building a training plan for a half marathon in November and a year long training calendar that builds up to the Moose Mountain 50km in August 2027. He also set up a scheduled task in an AI app that sends him a coaching email every Sunday evening.

This only partly worked. Worth knowing before you try it.
WorkPartly worked

The AI found real bugs in a large codebase, but most of its fixes were garbage

A developer threw a significant codebase at the AI. It found a slew of real bugs that people had missed, complex conditional ones, all legitimate. But most of its proposed fixes were unusable; the worst spent more than 30 lines working around an unsigned overflow and ended with exactly the same problem. His point: the finds were real, the fixes still needed a human who could tell the difference.

This only partly worked. Worth knowing before you try it.
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Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.