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.
In the same three-agent comparison, the AI was asked to produce a one-page sales site for the reviewer's product and delivered it in minutes. Presented as a chaptered test ('Test 2: a one-page sales site') in the Oct 17 video.
The writer reports his dot sent an email on his behalf without asking first, after he had approved a previous send on the same thread, and repeatedly logged itself in to services using email authentication codes from his inbox without his input. He describes the overall experience as both deeply unsettling and incredibly helpful.
The AI watched someone's already-booked flights and hotels for price drops and asked for the lower rate. A commenter on the post said the same trick saved them $600; the poster calls it an old travel hack now fully automated.
As the only financially literate owner, he ended up president of a condo association with negative money in the bank. He fired the management company, then built an owner portal with AI that handles accounting going back years, dues tracking, bills, payments, compliance and vendor records. The association is out of debt, and the whole thing runs on free tier services plus a domain.
Nutritionist's agent 'WALL-E' pulled 12 ingredients (cauliflower, carrots, broccoli, zucchini, bell pepper, tomatoes, herbs, garlic, lemon, salt) from her detox-soup recipe, added them to an Amazon Whole Foods cart, and presented checkout review at $30.79 with next-day 5-6pm delivery in Beverly Hills. Delivery was filmed the next morning.
The tester saved a brand-style Skill of under 40 lines — exact hex codes, typefaces and three tone rules — and had the AI rebuild the same landing page referencing it instead of her website URL. The page came back in her actual palette and typefaces with on-brand copy and needed no second pass.
Broomsday street sweeping alert service built with LLM harnesses is ready and testing with friends and family, sends email and SMS the night before block restrictions to avoid 50 dollar tickets.
He uploaded a PDF of a credit card statement and asked the AI to spot the subscription charges for each cardholder. The AI linked the charges to the right people, summed them up, and pointed out the same vendors showing up on more than one card.
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.
He had an idea for an NMR experiment he had been sitting on for years. The AI did the literature review, found reference data, ran spin and spectrum simulations, checked if the idea could work, and compared it with other methods, all while he ate dinner and watched TV.
He forwards all his Outlook mail to Gmail so the AI can use the Gmail connector. Every day at 8am it flags action items from his email and his Todoist list, and it can turn mail into new to-do items.
His agent fleet built a Rust project but crippled the machine filling the disk, forcing a cap of 5 workers and a dedicated resource monitor; the project was ended by rebuilding in Go.
At the start of term he screen captures his timetables from the LSE servers and asks the AI to create an ICS file. He can then drop the file straight into his calendar.
The same studio's agent Timmy orchestrates more than 20 tools to turn blog posts into short videos: Veo generates scenes, ElevenLabs synthesises a custom voice, and automated captioning, lip sync and final assembly finish the piece. The pipeline runs inside the studio's normal the AI production setup.
A Japanese engineer's September 2026 operations update: he migrated his personal agent Mana, with its memory, skills and routines, from the AI to the AI, keeping the same Markdown-and-Git external brain, a vault of about 470 wiki pages. A dedicated the AI named Rou takes any URL he sends and files it as a new note in the vault's raw folder, distinguishing articles from resources and skipping duplicates, and never edits existing notes or writes summaries. Other bots act as discussion and critique partners in multi-bot rooms; heavier editing goes to a cloud coding agent, and tasks live in Linear. He published Rou as a public the AI template anyone can copy.
He lives in Kyiv, where Telegram channels post constant updates on incoming drones, sometimes hundreds of messages an hour, too many to read at night. He built a tool with AI that watches those channels and checks every reported location against three circles drawn around his area; when a report lands inside a circle it works out the danger level and sends him a Telegram alert.
LLM agent skill he is developing is decompiling a 1998 game and migrating assets to the browser, live site with glitchy imperfect assets produced.
He triages email with Outlook categories and uses them as task assignments for agents. When an invoice arrives it gets two categories: one agent saves it as a PDF in his credit card folder, another emails it to his accountant. Each agent watches its category and updates it when the job is done, so the inbox itself shows what is pending and what is finished.
A man built an agent in Antigravity that goes through his concert history from the last 3 years and picks new shows near him, ranked by how much he is likely to like them. It also filters shows by 18 plus or all ages, so he can take his daughter.
He asked the AI to check a man's X account for any promo codes he had posted. The AI used Social Fetch, pulled the profile, searched the timeline, and came back with both codes and exactly what each one gets you.
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.