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 pointed the AI at his JavaScript project and asked for a full TypeScript migration without changing behavior. 236 commits and a full day later the project compiled clean, the linter passed, and 55 of 56 tests passed, with the one failure traced to a commit where a value was accidentally hardcoded.
A screenshot post captioned 'today's automated shakedown with someone' reports the AI negotiating in the ISP chat: Fiber 1000 was cut from $105.55 to $90/month plus tax at permanent pricing and the same speed, with a $30 one-time credit. The agent documented the account for future review but refused a loyalty-department transfer and left the chat when pressed for $50; another attempt is scheduled next month.
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.
Amanda Robinson ('The Digital Gal', 3.5K followers) got a notification that the AI wanted to book 'Beeside Del Mar' for 5:30 PM for 3 via OpenTable. The chat showed detailed criteria — seafood-focused, mocktail/cocktail variety, ~$50 per person, cool vibe, Instagrammable but not trendy.
He gets 215 GitHub notifications a day, so he built a bot to triage them.
His invoice agent processed 688 documents in 30 days at about $0.11 per document and made 3 errors, with no retry storms. He is open that a document marked completed does not prove every field was read right, so the numbers count finished documents, not verified ones.
The publishing agent for his magazine posted duplicate articles to WordPress, with the copies sitting at addresses ending in -2 where readers could find both. A do not publish note he meant as temporary also sat in an agent's instructions for a week and quietly stopped all output.
Had the AI build a minimal OTel agent sending VM metrics to a collector plus iOS and macOS apps to query it regularly; works with his existing setup at no extra cost.
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.
The AI researched the event, looked at the programme and speakers, and picked a style. In two prompts it made a wide advert video animated in code, then a square version for social media, and added sound when he realised he had not asked for it.
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.