The AI built a board-game engine and trained a bot that beats the best open bot
The AI fully vibed a fast Splendor engine and trained a playable bot that decisively beats the best open-weights Splendor bot he could find.
Real things everyday people got it to do, and how to try them yourself.
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The AI fully vibed a fast Splendor engine and trained a playable bot that decisively beats the best open-weights Splendor bot he could find.
His team is replacing a client's 15 year old system. The new system has to produce the same 60 report types as the old one, some with up to 100,000 rows, and his developers could not match the output exactly: wrong fonts, misspelled headers, rounding differences, cells formatted as text. He gave Fable 5.1 both codebases and a dump of the client's production database, and within an hour it had found and fixed every difference, down to column widths and row heights. Matching the reports by hand would have taken weeks.
He gave an agent his favorite meals, his dietary limits and the food he has on hand. It makes a weekly food plan and a full grocery list, and he tells it over the week which meals he liked.
Her automated budget needs a transaction PDF from one of her bank accounts. Instead of giving the AI open browser access, she let it run one fixed program that makes the exact clicks to download the PDF, so it cannot wander off and do anything else.
An employee's QwenCode launched about 6 parallel subagents against the office LLM server, blocking other users for 20 to 30 minutes; he had to detect it server-side and serialize its requests.
The AI worked through data-broker removal requests for the user and got four broker listings about them suppressed.
He works in environmental health. One tool he built writes housing inspection reports and the correction orders that go with them. Another reviews septic system plans by arguing against his own review. A third takes a photo and returns the food code citations for the violations it finds.
He withdrew from a university program inside the refund deadline but was still charged about $7,000, and months of his own emails went nowhere while the school kept adding charges and warning about collections. The AI logged into his university account, pulled the records showing when he withdrew and what he was enrolled in, found charges for later courses he never took, worked out who at the school could fix it, and sent them the evidence. The balance was removed.
A dedicated segment of the same session shows the AI auto-dubbing his videos into English, opening his Urdu-language lessons to an English-speaking audience.
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.
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.