An LLM cut 60,000 useless lines from his test suite and fixed bugs it found, in about 2 hours
LLM audited about 100k lines of tests, deleted about 60k useless lines, wrote broader scenario tests, and caught and fixed bugs, in about 2 hours.
Real things everyday people got it to do, and how to try them yourself.
A random mix from the whole library. Shuffle for a new set.
LLM audited about 100k lines of tests, deleted about 60k useless lines, wrote broader scenario tests, and caught and fixed bugs, in about 2 hours.
In shipwithmuse.live's errands catalog, one 'finding money you forgot about' entry reports a full sweep of every state's unclaimed-property database by name and past cities, which turned up $88.92. The catalog notes it was as reported by the build author and not independently audited.
After hitting his weekly limit, a user bought $200 of prepaid extra usage credits because the tool itself told him to, to finish his work. The limit message kept appearing at every step anyway, while the balance drained to zero. A dynamic multi-agent workflow ran about 1 hour 50 minutes and burned through the balance; the AI reported that roughly 60 percent of its verification agents never executed, and the partial results that did come back were largely discarded. The $200 bought an incomplete verification.
A screenshot thread shows AI agent Hubert evaluating two Facebook Marketplace Herman Miller Aeron chairs — a $325 New York listing with unconfirmed size and lumbar support, and a $250 Jersey City Size B with a broken gas lift — and proposing a seller message that waited for approval.
He released version 0.6.0 of his software, and his agent fleet built most of it. A pre-launch check caught a routing bug where one agent was being sent another agent's model id. Now every routing path runs as a canary before a release.
She uses AI as a side panel inside Chrome and it clicks on her screen for her. She says it takes ten minutes off her week.
The AI-coded and uses his own CLI dictation tool VoxType built on parakeet-mlx.
Konik gave the AI a list of low-urgency wants she didn't want to overpay for. Over time it built a table of what normal prices in her area look like and flagged good deals, netting her a $25 armchair and ottoman that fit her reading nook.
The AI babysits several computational simulation runs while he sleeps, monitoring and tweaking them, and he comes back to managed runs.
Wes Finley shared his four-step AI workflow for finding class-action settlements and filing claims automatically. Commenters chimed in with their own results, including $400 payouts.
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.