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.
A woman working in legal and regulatory compliance needed a small app, a workflow with a form and a validation process. Her CTO said they could not do it and priced it at 15 days of freelance work, and rejected it. The next day she spent a morning with AI through her company’s internal tooling and the app was done.
A man connected his local agent to Monarch Money through an open source MCP project, with some AI help on the login. The agent can now pull his transactions and look at spending patterns, and the AI generates a daily report from it.
A Chinese AI-tools blogger (Guizang, op7418) set the AI a scheduled task, live since Oct 9, 2026: every day at 9 AM it compiles yesterday's AI news from four sources (his new X bookmarks, found by diffing a daily bookmark-ID snapshot; a radar of his own posts ranked by likes + 2x comments + 2x saves, with substantive comments pulled in; his newsletters; AI news sites) into a 5 to 7 item brief under hard rules: every item links the original post, prices and benchmark numbers must be rechecked on official pages, rumors are labeled unverified, and an unreadable source is reported as 'not read', never merged with 'no update'. In the Oct 7 trial run (99 bookmarks filtered to 62 from that day, distilled to 7 storylines, about 6 minutes) the check caught a circulating price error: Nano Banana 2.1's 4K price was $0.113 on Google's pricing page, not the widely shared $0.076. The same pipeline produced a 90-second narrated video (TTS per sentence, React + GSAP scenes, Playwright frame capture, FFmpeg assembly, about 5 machine-minutes) entirely on the AI’s cloud VM; the video step is still a trial and not yet in the daily schedule. He published the full reusable prompt and his three open-source skills.
The AI wrote the tooling to annotate historic map tiles and a CV model ran across the rest for an exhaustive study of unlisted formal gardens in Ireland; a decade-planned project done in a weekend.
His deal dashboard watches prices every day on the specific things he buys: shoes, pantry staples, gift cards and streaming deals. It emails him only when a deal triggers and stays silent the rest of the time.
He built a home dashboard with AI that pulls a dozen sources into one wall screen for the whole family. It shows the shared calendar, weather warnings, solar and battery levels, car charge and bin days, and it only brings things up when they matter, like bins out tonight or a frost warning.
He used AI, ElevenLabs, and D-ID to make a budget simulation for his Politics of Public Policy course. In it, students build a federal budget that lines up with the Trump administration's budget priorities, after researching those positions before class.
Angela customized her avatar 'Mimi' and asked for a kids-friendly meal plan for a family of five: no pork, at least one high-protein meal, under $125 total. The AI returned a PDF titled 'Busy-week meals, minus the scramble' with seven dinners organized by ingredient loop at about $110.
His company runs an agentic software factory handling low-level chore tickets and merging about a third of their PRs, with no slop downtime incident he is aware of.
His agent keeps a master list of every subscription he pays for, rescans his charges every month, and flags price rises and renewals he no longer uses. He says he has cancelled several subscriptions because of it. In a comment on the same post he adds that his bank and card transactions come through Plaid's read only connector, so the AI pulls them live when it needs 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.