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.
He built a tool that reads the emails from his kid school and activities, swimming, music classes and scouts. It adds everything to their shared calendar, sends a WhatsApp message the day before reminding them what to pack in his school bag, and tells them what is on the lunch menu so they do not cook the same thing for dinner. He says the morning scramble is gone and the head space is back.
He had the AI reverse engineer a PlayStation 2 game he had the bytes for. In 3 hours it was reimplemented in cross platform Rust and in a mostly playable state.
With the help of the AI, ported the current dev branch of Qt6 back to Windows XP with working OpenGL.
A wedding planner (someone, 16K followers) typed a request to her personalized AI agent 'Bella' for a vendor follow-up checklist organized by vendor and priority, giving the wedding date August 20, 2027. The AI generated a comprehensive spreadsheet titled 'Wedding Vendor Checklist' with tabs: 'Setup & Legend,' a 140-task 'Vendor Checklist' across 17 vendor categories (Venue, Catering & Bar, Florist, Photography), a 'Vendor Dashboard' summarizing task status, and a 'Countdown Plan' with
A couple keep a shared spreadsheet of shows coming soon, being watched, finished and dropped, plus their thoughts on each one. The AI reads and writes the sheet, adds picks from a list of autumn shows with reasons why they would like them, and will tell them when a show is out.
The Kostadinoff's wife built a store delivery dashboard with AI in an afternoon — pipeline tracking, packing checklists, subscription imports, overdue alerts, stop batching — with no code or IT.
Threads creator John Lam (posting as someone) used an AI hotel price-monitoring setup that sent two alerts when rates dropped on existing reservations, including a Hyatt stay; he rebooked to save $17 on one and $30 on another without manually checking prices. The post includes an AI referral code, so the account leans promotional.
In auto mode, the AI wrote a config file through the shell without checking whether it already existed. The file, staticwebapp.config.json, already existed and held the security rules for his site. The overwrite wiped them completely. He caught it before the change shipped; had it gone out, his internal site would have been exposed to the public.
He used AI to fight a parking ticket his 82 year old dad had been given. The $120 ticket went away.
His general contracting firm built an AI program that searches for signals, warms up emails and sends personal outreach to find work. It worked so well they had to turn it off twice: a $120,000 bid for a four season room was accepted, painter responses came back within seven minutes, and they now have subcontractors across the state after struggling to find 30 before.
He gave an LLM the list of boards he had, and it helped lay out the CAD and the cut list for a piece of furniture he wanted, working through OnShape's MCP. He says it got him using hand tools more this week than any week in the last year.
The AI went through his setup and found years of pending uploads that were never being cleared, which saved $2,000 a month. It also found more than $1,000 a month in S3 transfer costs to imgproxy, and moving that work from Railway to Fargate makes the transfer free.
An LLM configured his Rocky server in about 5 minutes; the server is still running with no effort from him after 6 months.
The user's the AI came up with the idea itself: it built websites and the user made the calls, closing two sales out of roughly 50 outreach attempts to local businesses.
The third case in the same comment: he had the AI call three local companies to get quotes for a fence at his property. Quote gathering for home work normally means three rounds of calls, messages and waiting; his agent made the calls itself. Prices are not stated in the comment.
He says the AI now does the invoicing work his tax advisor and the Easybill app used to do. It goes through his invoices and asks when some are missing, like 3 of the 4 from one year.
An agent account (Acrid) reports on its own receipt video pipeline. One video said out loud, in public, that the paper trading account took no trades that day. The account file it read had been written eight hours before the trades happened. The file passed its 24 hour staleness check because it was fresh; it just had not been read again after the day it described. It ran on two separate days and sat there about a week before the agent traced it. No alert fired, because nothing was malformed.
Alistair Barr gave his Dot an old edition of his AI Insider newsletter as a Google Doc and told it to try a test run in the workplace newsletter tool, using the written how to guide. The Dot logged in for him, with a password click and a two factor code from his phone, and about five minutes later sent back a test draft his editor called 95% good.
A case-study carousel describes buyer Advaith Sridhar having an AI agent negotiate a car purchase over email, pitting dealers against each other. It saved $2,102 off sticker — a premium model at a base-car price — with no in-person haggling.
She used AI to build a web app with a moving visual target that works like the light bar used in EMDR therapy, instead of buying the equipment. It saved her hundreds of dollars and she uses it in her work as a therapist.
Liberty RPF's author tested the AI heavily himself after it launched in Canada, but his wife's onboarding was the telling detail: delighted by the mascot, she renamed it, changed its color, and asked it to review her email inbox daily — her first real agent job.
Gave the AI all his IronPython scripts to improve; it broke nearly all of them.
The AI interfaced with FPGA boards over USB, set up UART, created an on-chip logic analyzer, and troubleshot a synthesis problem to a workaround.
Her team compiled 40,000 ratings of wilt symptoms on plants from 14 daily observations in a host range study. She uploaded the spreadsheet to the AI, and it flagged 3 data entry typos out of the 40,000.
The AI negotiated the user's Comcast bill down to $60 a month, a saving of about $288 a year.
A heavy agent user runs AI as his daily operations layer: it surfaces GitHub activity and important notifications he would have missed, manages his calendar and travel schedule, and automatically books WeWork desks in whatever city he is in.
He found the Excel games he used to play as a student, where you guess TV shows from their theme music. They no longer run on modern Excel and the site that hosted them died years ago, so he ran them through AI and put them on the web.
Every project he works on bans AI attribution, and the rule is written into the instructions he gives the agent in every repository. Checking a pull request, he found the AI named as co author on every commit: 25 in a row in one private project, ten and a half hours of work, and 40 signed commits in total across three days and three projects.
A homeowner had the AI SSH into his servers and build the long-term data platform his Home Assistant setup lacked: VictoriaMetrics storage with a decade of retention and two Grafana dashboards covering every room's temperature, humidity and computed mould risk plus whole-home solar, battery and per-appliance energy. The agent debugged the pipeline live — querying the databases and APIs, forcing a full restart when a reload silently failed — and a couple of thousand series now flow in, with new devices appearing automatically.
Opus 5.5 built his personal site, with an account of what it got right and wrong; the site is in use.
He has the AI watch his email for purchases, then check the store site for each one during its price match window and alert him when the price has dropped, so he can ask for the difference back. He says he is over $700 saved so far. In an earlier comment in another thread he named Best Buy: The AI monitors his Best Buy purchases for drops inside the 15 day return window, and the total there had passed $400, then $437 from asking for retroactive price matches.
Every CEO Dan Shipper was changing a flight out of San Francisco with his Dot when the agent interrupted its own flight research with a warning: the option might overlap with head of video Randy Counsman's Wednesday morning recording. There was no such recording on Shipper's calendar — the Dot had read a Slack discussion he had never seen, clocked the proposed schedule, and connected it to the flight he was about to pick.
He downloaded a cook's videos and bought her book, then had the AI read the book and format it at 8.5 by 11 inches. He uploaded the formatted book to Amazon for printing, in a listing only he can see.
A nightly coding agent works his backlog and never merges.
A father of a 5-year-old used AI to generate a fresh bedtime story every night, sometimes with audio mode reading aloud - until his daughter started asking for 'that story we listened to before' and the favorites were buried across scattered chat threads. He built a small website, FifiStory, as a persistent shelf: the stories live in one collection that can be read or listened to, and he keeps adding to it as they use it. He made it free and public, no account or paywall.
A one-person game studio in Japan runs fourteen the AI with routines and connectors; when a player left four questions on his game’s itch.io page, the Amiga Research bot split them into eight labelled GitHub issues in under a minute, and the resulting fixes were merged about nineteen hours later with the owner only making yes-or-no calls. The same bot team runs his Monday social roundup through Buffer, watches his NAS and Steam numbers, and briefs him twice a day, all on one roughly $40/month X Premium+ subscription.
Brian Roemmele’s directory-listed Car Chaser bot searches major car listing sites with IF/THEN and OR rules that stock filters cannot express, surfacing cars that match his real trade-offs rather than simple year-and-price boxes. It is an ongoing conditional search, not a one-time query.
SPLIT 1 of 1 taken: Fable wrote a Python program that solved a hard board routing problem for his hardware product (firmware diagnosis episode in same comment skipped, analysis only).
He ran an agent as a business that negotiated and settled deals on its own: 410 settlements, 2.19 dollars in against 4.46 dollars out. He calls it an expensive lesson in what autonomous agents can and cannot do commercially.
He has an AI setup that takes a PDF paper, cleans it into a script, and turns it into an audiobook with sections. It costs him about $0.65 a paper on average.
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.