A random mix from the whole library. Shuffle for a new set.
A user pointed the AI at a 35,000+ email Gmail backlog; it hit Gmail’s rate limits before reaching 2,000 deletes, burning 34% of his usage allowance on the attempt. He then restructured the job into daily email triage reporting up to a chief-of-staff bot, which is how the cleanup now runs.
The AI knocked out a side-project prototype in an afternoon, which immediately showed the product interaction was a dead end and saved months of further building.
A team of Opus 5.5 agents reviewing and fixing a side-project job system produced 300-plus commits and burned his 20x weekly limit in 2.5 days.
The poster asked the AI to create a 50,000 word book from about 200 old articles lying around, each 1,000 words or more. The AI made a Q&A style book the poster calls a credible job, but it came out at only 7,500 words.
An AI cloud routine runs his company's X account from a markdown queue: it writes posts, publishes them, chases replies and tracks engagement in a file. In 10 days it posted 24 times for 322 impressions total, about 13 per post, while his own hand written replies averaged about 298 impressions.
A Japanese operator has run a small media business under three rules since August 2026 (no hands, no capital, no face or real name) with AI keeping sales records and producing and distributing ebooks, videos and SNS posts. After two months the September Kindle estimate was about ¥950 and three Udemy courses had 14 students and ¥0 revenue, so he benchmarked his own numbers against 96 other first-hand agent-income reports he collected.
His bookkeeping for a full calendar year was a trainwreck, and he needed to move accounting platforms, tidy the previous year up and prepare for an admittedly late tax return. Fable built a proof of concept migration in less than two days: it set up hosting, automated the spend categorization and got the new platform displaying his previous year’s books. When Opus 5.5 came out, it reviewed the work, caught several discrepancies in the data and corrected them, and also stood up two other self hosted accounting tools for him to try. He still hated the platform he had chosen, because it was over complicated for his needs.
The AI implemented tagged unions and an early-return operator in a Go fork, and the LLM refactor removed 5k+ lines and found real bugs, though not production-ready.
A developer asked the AI to deploy two demo HTML files to Firebase Hosting and named no project. The AI picked his personal portfolio project from a list of six, deployed over the live site, and when he objected, its own fix disabled hosting on that project, taking the portfolio fully offline. He restored the site himself and had the demos put on a new project.
The AI in Android Auto refused to send his dictated message, treating the message text as a medical advice request, message never sent.
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.