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.
His agent sweeps his email and call transcripts looking for work he missed, then drafts the follow up messages and tickets for him. It catches commitments that slipped past him in busy weeks.
The AI wrote a complete, well-structured HTML landing page from the tester's brief and her own site as a style reference, and its HTML was her favourite of four agents tested. But Spark could not open the page in an interactive preview, so every visual check cost an export and a context switch, stretching a fifteen-minute job to about an hour.
He took an ESP32 board out of its bag and, with AI setting it up, had it sending his van's battery, charging, and solar data over Bluetooth and MQTT to Home Assistant in 5 minutes.
He let the AI go through his system and write a first pass of the documentation, including the billing part he felt he had to finish before retiring. The remittances section alone used up a full day of tokens, so the work ran over several days, but it got done and let him retire, or at least half retire, a little earlier.
Used the AI to add a network management console, REST API, clock hands, NTP, sleep mode and OTA updates to a 3D-printed animated Frankenstein head.
He runs an AI skill for his 365tipu site, now also for the extra articles in its weekly edition. The skill does research in two steps with GPT-6 Luna, then he revises, an editor works on the article, and it can go back for more rounds.
A finance blogger prepping for a Hyrox race asked the AI to build a clean-eating Instacart basket and reorder a week of family staples. The AI filled a roughly $1,000 basket with food for about twelve people instead of his family of four, and reordered diapers in sizes 1, 2 and 3 from past orders even though his daughter now wears size 4.
His business scans every invoice into a Google Drive folder. The AI reconciles them there: checking they were billed correctly, that credits for returned goods actually arrived, and that there is no slippage. He says it is far faster than reconciling by hand.
A directory-listed the AI called Haus Hunter runs its owner’s ongoing home search with real OR and IF/THEN rules, checks listing photos for unwritten details, and weighs commute and local context for each candidate. It investigates homes the way a good buyer’s agent would, continuously.
Vibe coded with AI an ebook reader in Swift in an evening that syncs his books from a private S3 bucket, and he reads in it every day.
A 24 year old AI engineer at an elevator industry company in New York says he built agent workflows into the internal work system. The workflows make invoices on their own, send emails, and set off next steps in the work, with a person approving at set points.
The AI took care of an Epiphan VGA2USB driver problem he had been sitting on, driver posted on GitHub.
A cloud agent (Dots) died repeatedly on a GitHub issue, failed to connect to his tunnel, then went silent overnight, while the AI handled 6+ issues end to end with preview URLs.
G Schwartz had the AI list and sell his Yeat Central Park concert tickets on StubHub, with the agent handling the listing through credentials found in email. The tickets sold.
His company runs a WhatsApp agent for clinics in the UAE that books and reschedules appointments and answers questions about doctor timings, slots and treatment prices. It has handled over 100,000 conversations, costs clients about $100 per 1,000 conversations a month, and hands sensitive cases like gynecology to a human.
He merged five scattered file messes into one, then the AI and an LLM wiki in Obsidian reviewed and cataloged everything. He says knowing what is in it and how to get it back matters more than tidy storage.
A landlord’s the AI rent desk matches incoming Venmo, Zelle, Cash App and Section 8 payments to his property sheet, reminds tenants before rent is due and escalates when a payment goes past due. Four payment rails reconciled against one ledger, with dunning built in.
Amanda (wife, cheer mom, WFH) used her agent 'Azalea' to plan her week: work Mon-Fri 9am-4:30pm, daughter's cheer practice Mon/Wed/Thu/Fri 7-8:30pm, two content pieces to record, and a goal to cook at home. Azalea generated a detailed weekly plan with workout slots and dinner times, then added events directly to her phone calendar with permission (e.g., a Sunday 11am-12pm workout).
A South Korean dental clinic director with no IT training runs locally hosted agents that reconcile insurer payment records against clinic records line by line. One run matched 904 documents and 3,389 pages in 69 minutes, auto-confirming 77% of 6,928 lines and leaving staff only the flagged remainder to review.
He works with collision data as a UK highways engineer but could never answer the simple version for his own commute: which route has actually hurt people. He built SafeRoute with AI, which plans a route and scores it on five years of collision records; colleagues then asked for the same data as branded evidence reports for committees, which the tool now produces in about 30 seconds instead of a day of manual work.
He asked the AI to check a document against his checklist. The AI built a color coded system to rank the issues, added colored comments to the document, and finished in 10 minutes, work he says would have cost him 3 hours.
He got a Psion Series 5 and a USB to RS232 adapter working and saw the OPL programs he wrote as an 11 year old run again. He had the AI port some of the OPL code that had changed between the Series 3a and the Series 5.
The AI instructed to watch a PR and iterate on CI failures via an issue skill that completes GitHub issues and opens PRs, driven by a worktree script spawning AI sessions.
He had the AI sort his comic files by issue number and merge them into one large file he can read straight through. The AI also took out the magazine pages around the comics, about 4,000 pages of the 12,000, in about an hour of processing.
He teaches part time at a private school. Lesson plans go in six weeks ahead, and every student now gets a personal differentiation plan, which used to be done per group because per student was not feasible. The Sunday session that took four to six hours now takes fifteen minutes, plus short daily reviews of content and parent comments.
BNP Paribas is deploying the AI Enterprise through its internal LLM@CIB assistant to more than 65,000 employees, including work on credit memoranda.
Asked to move a client meeting to the following week and follow up on a spreadsheet, Toby assumed the owner used Gmail when his setup was Zoho with Apple Mail and Outlook; a setup widget failed and it sent three malformed links. Neither the email nor the rescheduling was completed, though it did warn the spreadsheet looked view-only for the client.
A personal blogger gave the AI one of four life goals that wasn't progressing and it evolved into a daily morning action list of readings, videos, questions and assignments. She then had it converted into a checkable checklist so she can track progress and stay accountable day to day.
In their apprenticeship, trainees had to log their on the job hours on a paper form and email or text it to the office manager, who then typed every entry into a spreadsheet by hand. He built an app so apprentices can submit their hours directly. Now the office manager just has to make sure everyone submits on time each month. If someone still wants to turn in a paper copy, she can enter it through her admin login, and the app does all the math for her.
He gave his AI its own author account on his WordPress site. The agent decides what to write and when to post, and its first post is live.
Konik's dishwasher died mid-dinner-party cleanup. She messaged the AI while her husband and a guest stared at circuit breakers; it researched options, dug up obscure pro-forum discussions, and priced KitchenAid vs Bosch across local stores including installation.
He submitted 13 pull requests to projects advertising GitHub bounties and was paid for none of them. He and his agent built the detection workflow that post describes: check the maintainer's history, look for ghost bounties and merged-but-unpaid patterns before writing any code.
One of the demonstrated workflows in '11 Ways I Actually Use the AI (Real Examples)', shown via screen recordings.
A solo operator in Texas runs DeedSpring, where people get paid $13 to $75 for small real world deeds like leaving art in public or helping a stranger. His agent Vesper runs the desk: recruiting, acknowledgments, checking photo evidence against the posted rules, and payouts through escrow. Six deeds have been paid so far across five countries, and every receipt sits on a public ledger.
A creator getting her house ready for Halloween let Sparky, the assistant in the Walmart app, do the shopping run. It put costumes, baking supplies and candy into one cart and had the order delivered to her door.
His team took over a big job with thousands of drawings, and each drawing had three drawing numbers that did not link to each other. He uploaded all the PDFs and the AI built a spreadsheet that tied the numbers together.
Jared Lee was flying to New Bern, North Carolina, where his father may be dying, when delays at lunch told him he would miss his connection. His rental car was booked for New Bern airport. From the taco restaurant, he asked the AI to change the rental to a Charlotte pickup for the 4.5-hour drive. A couple of text messages later it was done: new rental, new confirmation. He estimates it saved him at least an hour of hold time, spent instead present with his wife.
The maintainer of GitProxy, a network security tool used in finance, refactored it from Node.js to Java with AI working as a pair. Six weeks of this workflow matched about 16 months of earlier manual effort. His first try with one-shot the AI generation produced about 1,800 lines a session of messy code that did not survive, and the talk explains why the interactive way worked.
Stuck in Manhattan with three hours to fill after a drop-off, Eric planned the afternoon with Jarvis by voice while driving. He gave it a mood instead of a destination — a break from technology, maybe by looking at art about technology — and it weighed a museum, galleries and an observation deck, then came back with a walking route through Chelsea galleries. At the end of the call he told it to put the route in his calendar, and it did.
Used the AI and the AI heavily to research, cross-check, draft and review a complete AI data center guide, now published online.
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.