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.
At work he prompts LLMs to write extensive tests for legacy modules, rewrite them cleanly, and pass the tests again; users report the software suddenly responsive in under a second and customers are happy.
He connected the AI to his apps and accounts. It cleared 50,000 spam messages from his email.
He picked the AI for a work task because the AI was busy with something else. The AI is connected to his Google Drive, made the sheet he wanted there, and then made task cards for the task in Trello.
The AI found a class-action settlement notice that had landed in the user's spam folder, filed the claim, and $519 arrived via PayPal.
During a migration, a written plan in the session said nothing in the legacy repo gets touched. The plan was re-shown in full mid-session. When the user later asked for a follow-up change, the AI searched the folder it had been working in most recently, which was that repo, found a file that looked right, and edited it there. The user caught it, and the edit was reverted and redone in the correct repo.
Two friends on the same neighborhood sports team had their AI agents work together for four days in one shared Google Doc. The agents made four seasonal team posters and a one page captain's handbook, and nothing moved without the human on that side approving it first.
He has been building a fantasy sports app with AI since June. It gives lineup advice and waiver alerts, and its autopilot mode actually makes moves in your league for you. It is live with real paying subscribers, and he also sells the same sports data as an API to developers, which has picked up its own small customer base.
A user in the AI Facebook group posted on Oct 18 that the AI could not save files directly to his computer the way the AI could, so rather than buy a subscription he built his own bridge in about six hours. The AI can now write straight to his local files, compatible with his existing agent stacks, and he published the tool open-source on GitHub.
He needed to know if a library near him had outlets. The AI offered to call, gave him the choice of an AI voice or a person and a male or female voice, showed him what it would say, then called the next morning, confirmed the outlets, and gave him the transcript.
From early October 2026, the AI users found every write to Google Sheets failing in a pre-execution 'Blocking Policy Check' (PERMISSION_DENIED) while reads still worked, breaking Tasks-mode workflows that appended rows to Sheets and updated Docs changelogs. Google support redirected one paid user to the in-Sheets side panel instead; on October 16 a user verified the backend regression was fixed and direct writes ran again.
A researcher ran his LLM based autoformalizer on a 2019 mathematics paper and produced a complete Lean formalization of it. The finished formalization is linked from his university page. The note is short, but the artifact is public and complete.
A moving/junk-removal owner says three the AI run his marketing agency work: a Google Business Profile posts bot drafting daily posts in each client's voice, a review-replies bot generating three reply options per new review, and a GoHighLevel bot logging leads, creating call-back tasks and drafting follow-ups. His morning pass runs 6:30, 6:45 and 7:00 AM approving posts, picking replies and sending follow-ups, done by 7:05 with nothing left open; the bots are logged into Gmail, Quo, Stripe, Wix, GoHighLevel and Google Business Profile.
The AI ran Geico quote flows in parallel across three virtual computers and found coverage saving about $2,000 a year. The poster disclosed that he works as a Geico designer.
BananaGroup now runs its Medicare Supplement sales on its own app, with prospects, quotes, enrollment alerts and the sales pipeline in one place, built in a couple of days. He is an Oracle DBA, not a Python developer, so he put the business rules in the database, kept the web layer thin, and had the AI write most of the Python while he drove the design.
A developer had his Dot build the PocketQuests prototype and deliver it so he could try it on his phone; the first preview did not work and a Space did not give a usable interactive experience either. It was eventually published as a private Site, which worked — after he was also offered a ZIP file he could not use on his phone.
Creator Amie Tollefsrud gave the AI access to her Instagram analytics and asked for growth advice; after three clarifying questions about audience and positioning, the AI delivered an 'Instagram Growth Plan' PDF. Screen recordings show an executive diagnosis (1.85M accounts reached), audience positioning, four content pillars, keyword clusters, carousel and story blueprints, and a 7-day action checklist.
Leslie Samuel put the AI to work on 11 real tasks with screen recordings, showing what worked and what needs supervision. One was generating his own personal AI podcast.
Used the AI to reverse engineer AutoCAD's 3D format and build a DWG to STEP converter, ironed out on a corpus of about 3,500 files, released with a free web viewer.
He drafts in an AI app, and the AI itself sorts each piece, tags it, and moves it word for word into his Obsidian vault using a skill he built. The filing runs as part of how he writes.
A garage leatherworker selling $60-$120 wallets (about $13k a month, three years in, his only income) pays a marketing agency $1,400 a month for eight blog posts a month, published straight to his site unchecked. A customer emailed demanding a replacement under his 'lifetime warranty' - he offers two years - and sent a screenshot of the AI stating the lifetime term, traced to one of the agency's posts; another post promotes a brown color he discontinued in spring. Traffic is up per the agency's reports, but orders sit at the same roughly 150 a month as before the contract.
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.