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.
In a #metapartner showcase, entrepreneur Krystal Oh — who runs a nail salon and a yogurt store solo — shows on-screen chats with her AI 'Coco' handling back-office work: drafting a refund request for an empty box of masks, remembering meetings, sending notifications, helping manage expenses, onboarding employees and scheduling calendars. She says she previously spent thousands on human assistants who never understood her businesses.
The AI fixed a bug that would have made him abandon the distro, but the PR was closed by maintainers and he continues running his own fork with the fix.
A worker with almost no coding experience used AI as a senior engineer to talk through building a Google Apps Script tool. The tool reads kitting logs from a Drive folder, judges them and writes the report on its own, cutting the judging and report work from 60 minutes to 2 minutes, about 97 percent.
The maker of a small game viewer tool had the AI play the game with scripted commands and write playtest reports. One report, from a manifest file the game loaded, documented a crash on exit, a bad default window size, dead inputs, and several rendering bugs.
He says he uses AI to find the cheapest tickets for events he knows he wants to attend. Its feed also told him about an event by a favorite artist of his. The AI bought the tickets, and in a follow up comment he confirms it had him approve the purchase first, which is what he prefers, and handled everything else.
He lets an AI assistant work in his notes vault every day. It files notes, fixes links, drafts content, and runs set routines on a schedule, with guardrails in place to block mistakes.
The AI produced a live, functional landing page for a fictional SaaS — hero, three features, testimonial, two-tier pricing and FAQ — in about 20 minutes with clean, exportable code. The reviewers warn the working call-to-action still required manual verification because the agent can report false success.
Host Alex reported that his AI designed and ordered the wristbands for the show's AI Engineer sauna meetup. The design-to-purchase loop was completed by the agent alongside his other travel tasks.
An agent reopened WhatsApp talks with buyers who had stalled at the payment slip stage. Buyers who talked with the AI converted at 8.36 percent against 0.17 percent for those who did not.
Nina Dobrev asked the AI to track flight prices from 4 cities ($7,472.74 total) and build a 10-day Rome itinerary for her girls' trip. Multi-origin price tracking plus a full itinerary — group-trip planning with real numbers.
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.
Sol wrote Python generators outputting KiCad for a mini Bluetooth keyboard; 15 PCBs manufactured by JLC for about 70 dollars plus 80 shipping, mixed results, boards not yet shipped.
A user had the AI apply TurboQuant skills to optimise a Qwen3.5-9B model running locally via MLX on Apple Silicon. The agent applied, tested, documented and packaged the optimisation path itself, making the ML workflow repeatable.
The AI built the user's full budget plus two Google Sheets, a personal budget for 2026 and business books for 2026, in under 30 minutes.
Prompted an agent to build a custom LLM coding harness with session resume, done in an hour and working nearly flawlessly, plus a WebFetch tool added in 5 minutes.
A Reddit poster set up the AI to trigger on every order/shipped email in Gmail: it opens each product page, compares the current price with what he paid, checks the store's price-drop policy window, and drafts a refund request without sending it. He notes most checks find nothing, but the ones that hit are money he would have missed.
Asked GPT-5.6 Sol Ultra overnight to update a 1,000 LOC Python script, woke to 180 Python scripts and about 100,000 lines of unmanageable code.
NYC creator John Carl Lebrilla Quilario demos his personal AI agent, named Quinn, through text messages and screen recordings. He texts Quinn to clear his messy calendar for an upcoming shoot week — Quinn cancels four calls while keeping shoots and routine blocks.
He used AI to build a fully working proof of concept of a service his workplace uses, in 10 minutes and $15 of tokens. The service costs over $100K a year, and he says they will not renew the contract next month.
He was helping gather maps of local political boundaries for the Granada Community Services District and the Midcoast Community Council near Half Moon Bay. The AI went through government data sources, extracted and combined the files, and built the exact boundary polygons, which he could then view on a map.
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.