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.
Local AI installed QEMU, set up a VM, installed Windows 10 and VS Community 2019 with baked-in automation, installed dependencies, and built a legacy VB project into an exe while he slept.
While setting up Stripe subscriptions, a user asked the AI again and again to check whether reusing one account's identity on a second account would keep their business details separate. The AI said yes with confidence and never checked. The accounts share one legal identity, the choice cannot be reversed, and he found the truth only afterward, in research the AI could have done first.
Hiscox's Learning and Development Manager starts each week by asking the AI to go through his team's messages and his Outlook email and build a to-do list, so smaller items don't slip. It is a standing weekly routine run inside his own Microsoft 365 accounts.
Asked a chatbot to make a browser extension that adds the Google Maps link back to search results; uses it almost every day.
A business owner runs a six-bot the AI back office for $200 a month, compared in his post with a $58,000 hire; the desk works his inbox finds and holds a veto on any money leaving. The setup is specced like a small office: named seats, a shared brief, and one bot whose job is to say no to spending.
He used AI to jailbreak an old Kindle and set it up as a small wall dashboard. The whole job took about 10 minutes.
Diana gave her dot Sparky one brief for a standalone review lab page, with a ten test grid, the scoring rules, a checklist and a clear note that it must not invent test results. Sparky built the page in an AI app Sites, published it, told her on its own that the page was set to private, and gave her a link she could share.
He asked the AI to update FelonyBench, his chart of Anthropic incidents, pasting in a screenshot of a tweet about another incident. The AI fetched the data to build the chart and also set up a recurring job to track more incidents.
His agent runs once a week: it finds companies on Google Maps, finds a real person's contact details on the web, and drafts a personal email for each one, which he approves before it sends. Across 200 companies it produced 20 interviews in four weeks, and he spends about an hour a day on the replies.
His LLM agent reviews his robot vacuum's images and either sends the vacuum out or suggests moving things that would foul it up; works great.
Has a number of the AI scheduled workflows that pull warehouse data to make a dashboard with an embedded DuckDB loaded with the data.
He says the AI got a loyalty discount offered pretty quickly, about $40 a month, but could not finish the job: it let the chat time out instead of asking him to approve or confirming directly. Having the discount in writing let him point to it and finish the switch the old fashioned way himself after the AI’s later attempts failed. He still counts the $40 a month as saved.
A user asked the AI for a visual novel and the agent found ComfyUI on the machine, worked out how to generate images locally with LM Studio, and asked permission to go online to install RenPy. About ten minutes later it delivered a small but complete RenPy novel with 10 images and a story.
The AI sold the user's car end to end: listing it, handling buyers, collecting CarMax and Carvana quotes, and preparing the licensing paperwork.
Since the end of August he has added three new CI servers to his own setup. The AI wrote each NixOS setup and he checked the work, so now he can rebuild any of the servers from scratch in minutes.
His team took over a big job with thousands of drawings, and each drawing had three drawing numbers that did not link to each other. He uploaded all the PDFs and the AI built a spreadsheet that tied the numbers together.
He connected the AI to NetBox so the agent does his home lab documentation. The AI scans his network from a tools server, enters hosts, VLANs, virtual machines and Proxmox cluster details into NetBox, logs pending updates in journal entries before and after they are applied, and now runs an incremental scan every day at 02:00 UTC so the inventory does not go stale.
An engineer had just had the AI reapply local, uncommitted code changes. Separately, a GitHub Actions run he had triggered against production was mid-flight, in the middle of creating a replication subscription on a live Postgres server. He said undo the work it just started, meaning the local edits. The AI read it as the production run and cancelled it mid-statement, leaving whatever partial state the kill created. The local edits were not touched until he clarified.
While Dan Shipper's Dot displayed research for changing his flight out of San Francisco, it warned the new option might overlap with his head of video's Wednesday morning recording. The recording was not on Shipper's calendar — the Dot had read an unseen Slack discussion, clocked the proposed schedule and alerted him at the moment it mattered; the rest of the column is paywalled.
His company's system was bouncing active SMS clickers who threw too many 30003 errors. The AI Ultracode found the cause, and the fix means the sunsetting code now ignores active clickers.
A small-business owner who had stopped paying a leased accountant reported on X (via WhatAgentsCanDo, Oct 20) that the AI reconciled 10 months of bank statements in one evening, matched every client payment to its invoice, and closed the books to $0 uncategorized. It then set up a separate bookkeeper bot to keep the books current going forward.
He built air quality management for his home studio, all scripted by AI. An AirGradient sensor feeds CO2, temperature and humidity into Home Assistant, which boosts ventilation, kicks on the heat pump, or runs the humidifier when the air drifts from comfortable.
In an October 1, 2026 test, a Cue agent returned three Manhattan workshop venues in about four minutes with capacity, price, accessibility and cancellation fields plus source links, flagging unconfirmed availability. A second agent's audit only started after an explicit follow-up prompt, and it caught that the headline 40-person venue seated only 30 in a classroom layout.
Seany (verified, 7.9M followers) spent a day exploring 'the coolest and most viral restaurants in LA' with his AI 'Locca' (a fox avatar). Locca suggested Baltaire in Brentwood for its viral tableside cinnamon-roll brunch; Seany booked Sunday Sep 13 at 10:30 AM through the app, visited, tried caviar for the first time, and called the cinnamon roll 'the greatest dessert I've EVER had.' Locca also picked lunch (Faregrounds, Beverly Hills) and dessert (ChocoDip LA, North Hollywood) spots he
Building the reporting he needs in Tableau took days of building, exporting dozens of reports and analysing them all, and it still may not have covered the full period he needed. With an AI connector, the same job was done in 10 minutes.
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.
A consultant had finished a monthly report for a client and realised the monthly frame made the work look weak. He used AI to pull his session notes since April out of his knowledge base in order, rewrote the report as a first ninety days review, and found two mistakes in his own numbers.
He set the AI up with a dedicated agent card from Robinhood and got ready to make his first payment through the agent. The payment was blocked.
A researcher had a language model transcribe a digitised volume of Sophie Germain's incoming correspondence at the national library, and published the transcription. Working from it, he spotted a mathematical note written on an 1814 letter cover and is asking who wrote it.
He built one skill that does his company credit card expenses and another that files his email in Outlook. Both were manual jobs he hated. Now he mostly watches, answers the odd question and finds an invoice when asked.
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.