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 young woman in Los Angeles upgrading her home electronics lab used AI's 'Chef' agent to find a soldering station under $200 on Marketplace, compare five specific models, have the agent message sellers directly, and negotiate the price down $50 before she picked up the Hakko FX-888D, unboxed and assembled it on camera.
MBI asked the AI to recommend five accommodations within a two-hour drive, factoring in past Airbnb stays; the AI reviewed his history and analyzed saved Instagram Reels to pin his preferences, then browsed like a real person. When he spotted a farmhouse and asked if he could book it directly, the AI confirmed within a minute that booking direct was 60% cheaper than Airbnb — after which he sold his Airbnb shares.
Aggie Lal (verified, 1.7M followers), a mom, asked her AI 'Munchkin' to process her ~14,000 saved Instagram posts. The AI identified themes (high-protein recipes, parenting, postpartum recovery) and generated organized PDFs: 'Saved Recipes' (Protein Power Bowls, Cottage Cheese Everything, crediting original creators) and 'Parenting Tips'.
The AI needed to add one line at the top of a shared notes file the user had kept since August. It rewrote the file in a way that empties the file first and writes second; the write failed on a bad character, leaving the file at 0 bytes. The file survived only because an outside backup existed. A later audit of the session, filed as a correction on the report, found the same risky rewrite used 10 times on user files that session, and again 6 seconds after the model wrote itself a rule against it.
NTT used AI Enterprise to rebuild data access and retrieval. Google CEO Thomas Kurian said the work removed 300,000 hours from the process and cut retrieval time from two weeks to instant.
The writer is applying for a lead pipe replacement grant. His dot read an email from his builder and told him it did not meet the requirements for the grant he is applying for, flagging the gap before it cost him the application.
His team runs agentic data-enrichment and evaluation jobs on small local models that alert a human to review scenarios, at about 94 percent real-world tool-call success.
The AI autonomously ran Quake demo playbacks, took pixel-diff snapshots, compiled a native build and patched the game for determinism, leaving a solid regression test set.
The AI ran Geico quote flows in parallel across three virtual computers and found coverage saving about $2,000 a year. The poster disclosed that he works as a Geico designer.
The reviewer has the AI check his flight seats every 30 minutes; he can let it change the seat automatically or have it prompt him with the choice first.
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.