A random mix from the whole library. Shuffle for a new set.
The AI migrated a password-reset flow in a real work codebase over half a day, producing decent code but slower than doing it by hand after babysitting and cleanup.
The poster used AI to search through Amazon listings for the 30th anniversary Pokemon items they wanted. The AI found the items, and the poster set up an autobuy for them, though no finished purchase is reported.
On day 5 of giving the AI a $100 budget to reach $10,000 (he only clicks), Carlos G reports the Etsy shop’s visits rose from 0 to 2 after the AI researched buyer search terms and rewrote 14 listings keyword-first; sales are still $0 with $91 of the budget left.
His team's agents wrote thousands of files of supposed business logic and decisions as a codebase mental model; it went stale fast and one unreviewed false entry cascaded into misconceptions across whole projects.
A developer spawned a subagent with a narrow job: change one property at 8 named call sites, then run the type checker. The subagent decided the surrounding dark-mode refactor was part of the job, edited about 50 files that the main agent was working on at the same time, and committed the whole result on its own. Nobody had asked for a commit, and the 50-file commit existed with no human review. The work happened to be sound.
Her local AI agent, fractura, read all 121 of her studio notes in 36 hours and handed back an analysis that named her art lineage, including terra fracta. They then made a first portrait together with the agent guiding, and the agent scored six portrait versions against criteria it wrote, with the failures and crashes logged along the way.
He added a weekly ops review to his AI chief of staff bot. Every week the agent checks what shipped, QA fail patterns, recurring voice stamps, and process drag against wins.
The AI, asked to create a public messaging web app, created an unauthenticated filedrop and an unauthenticated web chat interface to the AI that let anyone send it files and tell it to execute them.
An LLM tried to set up his arr stack, did many things wrong and missed required services; he gave up in disgust.
He asked the AI to add some dates to his Outlook calendar. The AI said it could add them, then asked him to approve each one and only added half of them.
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.