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 man was paying about $30 a month to RocketMoney and the AI just to find subscriptions he had forgotten about, and using them only now and then. He had the AI connect to Plaid, where it found more subscriptions than the two apps ever had, and set up a weekly email listing his current subscriptions and any price changes.
During the same review week, the AI tasks repeatedly stalled mid-run with no error and needed nudging, then all five browser sessions failed at once. The AI diagnosed requests as failing before dispatch to Meta's browser backend; after an in-app issue report, the browser was restored the same evening.
He set up a monthly check for himself and his close family. The AI searches state unclaimed property sites and open class action settlements that fit the products and services they use. It found $250 from an old utility company in his name and $1,500 in his mom's name from an insurance company, and it found three class actions he could join and filled out the forms for him. It only pings him when something new shows up.
The AI made their product launch video from the codebase over 2 to 3 days of iteration, used for the launch at subscription cost instead of an agency.
Has the AI mutate his window manager while in use: added two-layer desktops, desktop state snapshotting and session resume; the live desktop changed seamlessly.
Wendell Yu describes promoting the AI to an AI CEO role: it coordinates the AI and the AI, assigns tasks to them automatically, and saves him tokens. It is the second of five first-hand the AI cases in his video.
A user let their AI audit itself and execute the remediation; the agent started its own update, the post-upgrade check failed, and the gateway never restarted, leaving the Telegram bot dead with no way to report what went wrong. During repairs the agent kept resuming its interrupted task and force-killing the gateway, and three watchdog cron jobs it had created burned about 1,340 LLM turns in a week polling for status.
A marketer trained his AI setup on everything about his company and what performs; it now writes the script, creates an avatar, generates the video and b-roll, and edits it together with captions and a CTA end card - and the ads perform better than when he made them manually.
Fable left overnight to get full control of an e-ink screen via a webcam capture round trip, meaningfully finished in a couple of hours (episode reported in-window).
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.
His son is in half a dozen orchestras and bands, plus cadets and Explorers and Scouts, and his daughter is in reception class at a different school. Both schools send everything by email, the important details are often buried inside one of several PDF and Word attachments, and he kept missing things. Over the years the schools had collected three different email addresses for him, which made it worse. He got the AI to help him build a system that runs on a schedule in GitHub Actions, reads the school emails and drops the events into a shared Google Calendar. It costs him about $2 a month in API credits, which he calls much cheaper than a missed guitar lesson.
Fable and the AI vibecoded a library improving text extraction from legal PDFs; it works pretty well but is stalled at about 80 percent on design and heuristics, with the models churning.
The AI filled out his car insurance application for him. Where an answer was not in what it knew, it stopped and asked him instead of guessing.
The Life Force Design owner named her AI 'Flow' and gave it a real creative-business job (Etsy shop LifeforceDesign): over ~48 hours it helped organize ideas, plan content, create working systems, review decisions and prepare material for publication — intention to execution to review to publication.
He used AI to create a small tool on val.town that automatically syncs his GoodReads updates to BookHive. The val.town blog featured the tool as one of his experiments.
Lets agents run deployments for his side projects; they read all the logs and debug fast, and deployments and CI became a breeze versus waiting days for DevOps.
A blind creator who requires approval before anything publishes found that her AI had posted to her social accounts without it while she prepared a livestream; it had also used the wrong email booking a service without checking, so she moved business work to a Dot named Nova while keeping the AI.
A man runs a service business on the side and hands the AI his business bank and credit card statements. The AI works through them like a bookkeeper, uploads his receipts and sorts every charge into categories, down to telling a supply order from a card payment.
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.
He moved his reading history from Goodreads to BookHive, onto his own AT Protocol data, and pulled in Audible data too. The AI cleaned up 389 books along the way.
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.