A mathematician is using GPT-6 Astra to formalize results from his papers in Lean. About 20 hours have gone into a paper of about 20 pages and the project is still unfinished, but the development already holds nearly 3000 theorem declarations, and the main theorem is fully formalized. Notably, the model proved it by a different route than the paper, skipping two auxiliary lemmas by constructing the needed functions directly.
This only partly worked. Worth knowing before you try it.
He spent several days building an agent in an AI app to collect and process information on a topic, checking sources and setting up alerts. He says it did not work at all.
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She downloaded the AI a week after her dad died. Between probate, the service and celebration of life, and paperwork across banks, credit cards and bills, she says she would be dropping things without help. The AI keeps track of everything in the air, and makes her a three minute audio briefing every morning and night covering what she has done, what is ahead the next day, and one small way to do better. She listens while brushing her teeth and says she sleeps better.
This only partly worked. Worth knowing before you try it.
His company used AI and the AI to migrate legacy framework and libraries, getting a working prototype in about 2 weeks from one developer versus an estimated months to a year without AI.
This only partly worked. Worth knowing before you try it.
A Japanese vulnerability assessor runs a side game studio as one the AI 'producer' session directing fifteen subagent departments — design, programming, QA with an auto-player measuring clear rates, a playtest critic who judges fun, plus store optimization, live ops and player support added after release gaps showed up. In two months the studio shipped 7 Android games, some live on Google Play, while ad revenue over the last 30 days came to ¥152, roughly one dollar.
¥152a month
This only partly worked. Worth knowing before you try it.
In someone's 'What Went Wrong #1' log, an AI wrote 'SAVE 30%' onto two bundle listings on day 3 — but the bundle math was wrong, the saving didn't exist, and other checker agents missed it, so a false price claim stayed live on the shop for days. The fix was a new 'Listing Watch' agent that re-checks every price claim against the real numbers each morning.
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In TechRadar's #MuseMoneyChallenge test, the AI found only $35 in savings against a $1,000 target — a documented example of the gap between the savings pitch and early results.
$35one time
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Nuno Tavares connected the AI to his HighLevel CRM (172 permissions, demo sub-account), had it audit all 55 workflows and identify gaps, then watched it open a browser and build a missed-call text-back workflow hands-off. The build landed as a draft: missed-call trigger, tag and wait step.
This only partly worked. Worth knowing before you try it.
Inc. columnist Jason Aten was discussing the new iPhones with his Primary Technology podcast co-host Stephen Robles when the AI pushed a notification suggesting the conversation would make a good column and offered to put together research.
This only partly worked. Worth knowing before you try it.