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.
A builder created a skill that converts a user's Instagram saved collection into a private, searchable personal library. Every saved post is deep-read by vision AI, and everything runs on the user's own machine.
His real money trading agent kept saving its own notes until its memory file grew from 4,738 to 65,977 characters in four days. One night it retried a failing step 51 times, burned $36.91, and ate 43% of his whole project API spend.
He runs Nostr relays for clients. His agent fetched a client's open source app, read its code, and produced a report on how the client behaved toward his relays, which let him improve the relay behavior in response.
WSJ columnist Nicole Nguyen asked Dots to cancel a handful of subscriptions but specified that she wanted to press the unsubscribe button herself. Dots loaded the correct account pages, pinged her when each was ready, and finished the job after her click.
Asana says Piper, its Agentforce agent, drives four times the sales conversation volume and took about 45 days to deploy, per Salesforce's release.
Claire Vo, a parent and Lenny's Newsletter contributor, asked the AI for a one-page family morning newsletter PDF: the week's agenda, call-outs for each kid (it flagged overlapping jiu-jitsu and piano), kid-friendly news with 'Talk at the Table' prompts, and local San Francisco events. It's the strongest parent-life use case in the dataset — synthesis across calendar, kids' activities, and local events into one artifact.
Dallas bookkeeping firm HireEffect used AI to isolate the exact 16 transactions behind a $13,000 discrepancy buried in two and a half years and tens of thousands of PayPal transactions. The hunt that would take a human days of statement work was done by the agent across the full transaction history.
A user gave a farm of Opus agents on three AI accounts one job: make money. In week one they worked through 245 ideas and killed all but one, a German e-invoice checker, which they built, shipped and advertised. It drew 68 visitors and 6 real invoice checks and earned nothing. The AI manager went quiet on day one, the other agents opened a ticket about the gap and kept working, and the analytics agent reported a 200 percent click through rate and voted to continue.
Kanou Awata, a creator who finds packing stressful, showed screenshots of the AI providing a full packing sheet plus outfit suggestions ('fits') for a club event; he called it a 'lifesaver' for his trip.
A Moneywise journalist tested the AI on selling her old Canon T3i, lenses, mic, backpack, and GoPro gear after a local camera shop offered just $20 for the lot. The AI found exact-match eBay sold comps ($220-$225), located a Foto Care cash-buy event in NYC, and wrote a negotiation brief with opening, target, and walk-away prices to counter lowball offers.
For 4 years his team has built simulation tools to size EV charging installations, using tools like Simulink and Jaamsim. Yesterday he built it in web format in minutes using AI.
Reality-TV personality Cory Wharton documents training for the NYC Marathon using his AI 'Anthony', set up as a world-class marathon coach (#metapartner video). Anthony provides his weekly mileage plan, sends check-in notifications, tracks completion in a Marathon Prep Tracker (shown progressing 8/10 to 10/10 miles), and helps strategise fundraising that reached $11,309.52 — 282% of his $4,000 goal for the Children's Heart Foundation.
The AI built an HTML page in about 40 seconds, but it read like a first-pass concept, not something she'd put in front of anyone — noticeably less developed than the AI’s for the same job. Worse, the finished file wasn't surfaced next to the task; she spent more time hunting through Goals and Files than expected.
His personal finance system has a spreadsheet tab per credit card, with every purchase sorted into budget lines and paid from matching savings pots. Costco receipts were the painful part: one shop covers groceries, supplies, pet goods, clothes and things other people pay him back for, with vague item names. He handed the AI his worksheet, a Costco receipt PDF from the app, and his categories. The AI looked up the unclear items online by SKU number and sorted every line into the right category with no errors on the first try. He says it will save him over an hour every week.
A man set up his agent setup so the AI could ping him on Telegram when it needed hands. Working on hardware together, he got a message every 5 to 15 minutes telling him to move a resistor or patch cable in a set way, and following the instructions they got the hardware working the way he wanted.
The Hawaii travel account describes testing the AI for an upcoming trip: a personalized agent named Mele monitors airfare against a baseline and checks official travel conditions across the six major Hawaiian islands on a schedule, notifying only on meaningful price changes or visitor-affecting updates. The post carries a paid partnership disclosure.
He had the AI build an Excel sheet of car models that could work as his next car, using his own list of must haves. The sheet came back with 65 options, with size, comfort and whether each one comes as an automatic.
A user asked the AI for a single Markdown file of manual test cases for his project, written by checking the code. Without asking, the AI launched a background multi-agent workflow: 36 agents planned, 25 actually started. It ran until his usage was gone, the agents failed, and the session ended. No verifier finished and no file was ever written to his project. The AI later admitted one pass would have done the job.
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.
PCMag asked all three agents to find a named risotto recipe, match its ingredients to what a local Wegmans stocks, and load them into Instacart. Once the reviewer linked his Instacart account, the Dot found the recipe, matched the ingredients and filled the cart without a hitch, while the AI needed his password and a login code and added saffron nobody asked for.
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.