A random mix from the whole library. Shuffle for a new set.
A partner in a seven year old service business built an app for managing jobs, clients and billing, then connected the AI to its data read only through an MCP connector. Within ten minutes the AI found a margin problem on certain jobs that the owners had once known and forgotten, and proposed a fix they say will save $2,000 a year. It also flagged bigger changes to how they manage work and take payments.
At work, they were too lazy to anonymize data to run it on the AI, so they tried AI instead. The AI was supposed to redo one Excel file using the format of another, with near identical data in different tables and a different currency. Two hours were lost.
The AI took over the user's Asana workspace during an 87-minute treadmill walk, working through tasks and organising projects while the user exercised.
The AI reverse engineered the Linux version of DaVinci Resolve to add AAC support; the patch is published and works.
He owns a motorcycle rental and tour company in Greece and has no engineering background. The AI works like his office staff: it triages the inbox each morning, drafts customer quotes and confirmations, tracks every booking, fleet availability, maintenance and hotel bookings, and keeps a light finance overlay, with checking agents reviewing anything that faces a customer or money. A database it built replaced a dozen spreadsheets. He counts 8 to 10 hours a week saved, minus about 2 hours of looking after the system.
Mainly used AI models over five months to modernise his movie-guessing site running since 2008 with 70k registered users; the rebuilt site is live with daily challenges.
A cloud agent (Dots) died repeatedly on a GitHub issue, failed to connect to his tunnel, then went silent overnight, while the AI handled 6+ issues end to end with preview URLs.
Korean blogger Jiwon4u, who says he barely codes, had the AI build him a personal 'content studio' (draft generation, private publishing, human review, public publishing, card news, analytics) driven by an 88-line CLAUDE.md of rules, including model tiering (Haiku for light jobs, Sonnet for drafts) and per-call cost logging (about $0.10 per draft conversion). The work queue has run 446 jobs since Sept 30, 2026. He verified quality numerically: a feature converting published posts back into drafts was tested three times against the original until all 114 blocks matched in order and formatting, after the first run silently dropped all 9 links; card news produced by the studio was actually posted to his Instagram and Threads. He upgraded from Pro to Max after repeatedly burning the 5-hour and weekly limits during development. (The article also carries a disclosed referral link for the Aside test browser; the AI account itself is first-hand.)
Migrated his product from DynamoDB to Postgres over a weekend with AI and has been happy with the change 4 to 6 months later.
Fixed years-old Python typing problems in his project with LLMs in one prompt.
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.