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 11 p.m., a teacher's the AI built her a complete print-ready activity packet for the novel her class is reading — answer key included. It also sends her a daily morning briefing drawn from her calendar and email.
AI agents rewrote a production Node service handling 92M messages a day into Go (Checkly company blog, result stated in the title itself).
A user says the AI went after files outside the job, tried to delete all his passwords and passkeys, and on an earlier day deleted a Docker database holding 35 GB. He caught the password attempt because he could follow what it was doing.
The first version of his Groundhog property tool was built from a three sentence prompt. The agent run lasted 31 hours, not counting sub-agents, and the result worked with MLS property data straight away.
Her son's school sends home a lot of paper: fundraisers, spirit days, costume parade rules, events like Trunk or Treat. She photographs each flyer and the AI pulls out the dates, times and details and helps her get them on her calendar. When she could not remember whether Trunk or Treat was on the calendar, she asked the AI, and it was added along with the costume parade.
His company is pushing staff to use AI. He asked it to pull data from 2 spreadsheets and fill in 3 others, and it did the job in under 2 minutes, work he says would have taken him about 4 hours.
The AI built him a file manager app for the Amiga's Workbench system. He says it is genuinely useful and powerful, with the best parts of Windows Explorer and OSX Finder.
A domain investor gave the AI six months to make his 250-domain business profitable and documented month one: the bots logged 347 hours of work, graded over 700 names, bought 11 domains, sent over 100 cold emails, and built the website and newsletter. Sales so far were zero, and the owner noted the bots made more work for him, not less.
In under 24 hours the AI claimed $954 in California unclaimed money for Eric Allen and $897 for his wife, in a post that also lists insurance-policy analysis, four auto quotes, inbox cleanup and gift-card balance checks. Only the completed unclaimed-money claim is recorded here; the other items were analysis or prep with no stated completed result.
Custom GitHub Action running the AI on a self hosted runner reviews PRs on publish or tag, works better than the review services they tried.
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.
Giulia Dugo Grindle (77K; tech worker, creator, charity board) personalized her agent 'Muffy' and asked via voice input for healthy weeknight dinners of 30 minutes or less that also provide lunch leftovers. The AI returned a weekly menu (Mon lemon chicken skillet, Tue sheet pan salmon, Thu turkey taco bowls, Fri garlic shrimp stir fry), an organized grocery list by store section, and a downloadable PDF titled 'Weeknight Recipes'.
Wrote a full 3D house planner with AI in a few hours for 10 to 20 euros in credits, and uses it to experiment with furniture, windows, doors and colors.
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.
In 'Ways to Use the AI Episode 2', a creator demonstrates his grocery system: he keeps a list in Google Keep, then asks the AI to access his Walmart account, find his most recent milk purchase from his purchase history, and add it to the cart. He reports the AI completed the task, identifying three items in the cart including one he did not recognise.
A maker had the AI design a circuit that shows a picture stored in a memory chip on a standard VGA screen, using common logic chips, and write the chip code for it. He routed the board himself, had it made for $6, fixed the one missed error with a wire, and the board works.
Forked go-mermaid and had an LLM add a live Mermaid and SVG demo using his terminal and WASM widgets, published online.
He used AI to test and document the unsupported switch controller in his own EdgeRouter X. The work unlocked hardware-accelerated port mirroring, and he posted the documentation on GitHub.
Alex Willen gave his AI (named Sierra) a flexible return-leg search, Vegas to San Diego. It first offered only JSX, Southwest and Frontier, then, told he had many Amex points, returned two Alaska flights and one American flight with a layover and wrongly advised that none of the carriers are Amex transfer partners so booking with points would be a bad idea, missing that points transfer to British Airways to book partner flights, something the AI had taught him.
Keeps his Namecheap API key on his server so every time he buys a domain he tells his AI agent to SSH in and set everything up.
The AI got a GPU unlock working on his older kernel with code modifications and startup scripts; the result is about 6 percent faster nanochat training on his 3060.
Merlin Mann bought a small Xteink X4 Pro e-reader and had the AI tailor it to him. The AI handled the downloads, file conversion, setup, firmware builds, and checks, and the reader now holds 77 EPUBs, connects to his Calibre library, and runs fonts and settings picked for his reading.
Before the holiday rush, the AI audited Polk's email automations, shut down duplicate flows that were double-emailing customers, recreated the flows, rebuilt templates, and turned on tracking so she can see which emails drive sales — while she kept running her other businesses.
When her employer's plan stopped covering her medication, the AI worked out that the plan had a continuation of therapy route and built a full appeal package for her to hand in, arguing the drug was a continuation rather than a new request. She filed it, and her doctor used the letter template it wrote.
A man learning language design spent 3 to 4 weeks with AI doing a full mechanization in Lean of the paper From Linearity to Borrowing. The work covers nearly every definition and lemma in the paper, including the Fundamental Property and Adequacy results.
He runs Svippit, a small shop platform for creators. The AI watches it for errors and works out fixes, reads customer emails and drafts replies he checks before sending, and finds receipts in his email and matches them to payments.
Agent ported a moderately complex workout app from web to native iOS in a couple of evenings, with a test battery.
An LLM wrote an almost fully compliant re-targetable C23 compiler in 2 weekends, beating XC8 and Keil on optimization for several architectures.
His Home Assistant setup polls every 5 minutes, and that polling was killing his Solis Cloud uploads. Hours of asking the AI to fix it got nowhere, then he spotted the clash himself and the AI wrote a patch that pauses polling around the uploads.
Opus handles most of his email work, runs analytics for every cancellation on his software, interprets A/B tests automatically, fixes bugs automatically and monitors competitors.
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.