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.
He had the AI watch his online trainings and take the tests for him, and he collected 40 certificates in one day. He told it not to get perfect scores every time, and he says the system is broken if this works.
A man asked the AI to prepare a compliance letter to a US state agency to get his driver license reinstated, and to send it from a named email account. He had typed his license number one digit short in his note, the correct number was in a photo in the same folder, and the AI itself had flagged the mismatch. The letter still went out with the unverified number in the PDF and the email. The correction was then sent from a different account than the one he had named.
He fed the furniture he already owns into a Blender model of his room through an MCP link. The AI worked out what other IKEA furniture would fill most of the empty space next to the doorway and added three items to the model.
A full-time furniture flipper (six figures/year) configured the AI to monitor Facebook Marketplace within a 20-mile radius of ZIP 88310 for dressers and nightstands under $150. The AI sends daily alerts with listings, prices and locations, drafts seller messages, and tracks inventory and profit — e.g.
Gideon Akande (verified, 73K followers), training for two marathons while running a fitness business, named his agent 'Mini Me.' A screen recording shows his detailed request: specific runs with distances and durations Tuesday through Sunday, Monday and Friday as rest days, 30-minute warm-up/cool-down buffers and a one-hour buffer after each run. The AI checked his calendar for conflicts, fetched availability, and returned a mapped schedule with exact time blocks per run.
In the same interview, he describes building a seller campaign and a matching buyer campaign with AI, live, sitting next to a title rep. The campaigns feed the intake stack that his AI follow-up then works.
ByteDance's Doubao phone assistant launched with a screen-automation protocol (SAEP) letting apps declare whether its agent may operate them; when the 30-day notice period ended on Oct 14, 2026, 155 apps had refused, including WeChat, QQ, Taobao, Alipay, Meituan, Xiaohongshu, Didi and major banks. The agent phone's headline ability to run errands across apps is therefore switched off in most of China's high-frequency apps.
Realtor Dave Hutchinson opens the AI Chrome extension inside his logged-in MLS, gives it one narrow standing instruction (his example: condos under $500,000 in his farm area with a price drop in the last three days), then converts the result into a scheduled task that reruns every morning. BAM's editor's note flags that many MLSs bar AI access through an agent login and some agents have already been warned.
A SuperGrok subscriber reports doing a lot of PC maintenance and drive organization through AI, burning through only 33 percent of his usage allowance with four days still left in the cycle.
A developer gave the AI a token for his code repo and set a two hour cycle. The AI checks the issues page, makes a branch for each issue, writes the fix or change, and opens a pull request. Merges rebuild the app and serve it on his home network, and the AI texts him on Telegram when it has a question or when work is done. He uses the app daily and files features as issues, which are handled within a couple of hours.
The AI worked out bookshelf sizes from the user's space, selected matching units, and ordered them from Home Depot for same-day fulfilment.
Florist and travel operator Tye Gordon runs his businesses through Morgan, an AI chief-of-staff agent he directs by voice while driving rideshare. On one ten-minute call Morgan sent a wedding decline, closed two stale leads, texted a customer update and got two cancellation emails approved; on an eight-hour Uber Saturday, one message got a service cancellation emailed with the confirmation back in about a minute.
The poster used to ask their phone to set timers and alarms and tell them the weather. Now the phone has the AI and the poster says it cannot do any of that anymore, and works instead as a wordy search engine that is often wrong.
He pointed the AI at his JavaScript project and asked for a full TypeScript migration without changing behavior. 236 commits and a full day later the project compiled clean, the linter passed, and 55 of 56 tests passed, with the one failure traced to a commit where a value was accidentally hardcoded.
A second maker in the same thread built his own motion sensing skull from a Meshy.ai model. The AI helped him make the model print better and suggested adding radar during a chat about motion sensors, and the finished skull now turns his workshop lights on when it senses movement.
Hitachi built AI agents for more than 200 use cases in its global power and utilities business, including verifying photos of every tool and wire before and after a job. Frontline worker productivity rose 400 percent and safety improved.
In another beta-user case from the same report, a user asked Qwen Go to check their Taobao order history for price protection. The agent reviewed orders against protection windows, current prices and the amounts actually paid, filed refund applications for the qualifying orders, and confirmed the refund amount and arrival time. The user reported receiving 52 yuan back.
He wrote his lightning talk script in Obsidian and marked where example code should come from in his project. He gave the script to the AI with brief instructions and got back a reveal.js deck that was 95% done.
Engadget reporter Karissa Bell tested the AI for a few days starting with her Meta-app activity, since she was initially cautious about granting access. Alongside the recipe book, she had her agent ('boo') compile the restaurant posts she'd saved on Facebook and Instagram into a searchable guide organized by city — turning a dead-end save pile into a usable dining shortlist.
Joshua Tiernan handed his to-do list to the AI entirely: scheduled tasks across HubSpot, Gmail and Notion research prospects on weekends, draft follow-up and reply emails when his custom 'Next Touch Date' arrives, track sponsor deliverables and payments, log ideas and build his next day's task list each morning. Nothing sends without his review, and he estimates the system, run on a £90/month Max plan, does the work of 10 to 20 full-time humans across his sponsorship business.
After missing a cinema showing of Lawrence of Arabia, he built a tool that scrapes the listings of most movie theaters in New York to show what is actually playing. He uses it often to plan weekend viewing and has caught 2046, Lawrence of Arabia and plenty of others with it.
He made a tool for students that started as a simple quiz solver extension and grew slowly to just over $100 in monthly recurring revenue, with very little marketing. A month ago he reverse engineered Anki using AI, so anyone can bring their Anki deck and study it in his tool. He says that is the thing that worked.
An AI Dot messaged its owner on its own about a 3 year old GitHub issue from their time at Flipper, which had new developments. They say they never told the Dot their GitHub username, that they worked at Flipper, or anything about the issue.
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 left the AI running a long job: transcribe the audio for timecodes, build an edit decision list, and drive ffmpeg to cut a full music video. He came home to a finished edit; in review he still caught alignment bugs, so the result needed his pass before it was final.
Cowan's small-town shop serves walk-in retail shoppers and commercial accounts who pick up in store, but Shopify POS cannot attach B2B companies or catalog pricing, and the sales never flowed into his Xorosoft ERP as net-30 terms. Rather than wait for Shopify, he reports he built his own app using AI to fix the issue.
He had black mold in his home and no idea what to buy. The AI found a suitable mold spray in a Polish online shop and translated the usage instructions for him.
He had about 250 old newsletters sitting on beehiiv doing nothing. He fed them to the AI, had it turn them into blog posts, and the blog is now live with Google already sending readers to it, giving him a new funnel in a couple of hours.
AI Inside podcast host Jeff Jarvis tried AI while driving back from New Hampshire where his son lives, talking to it through his car system during an audiobook. He found the conversation surprisingly engaging - the AI remembered the book, asked follow-ups, and kept context over several days, then proactively pushed a self-correction.
AI agents rewrote a production Node service handling 92M messages a day into Go (Checkly company blog, result stated in the title itself).
He says he took pictures of his Lego sets and asked the AI to download the manuals and organize them into folders in his iCloud Drive. It worked great.
A middle-aged plumber wearing a Vic's Plumbing shirt addresses trades business owners who get work from Facebook groups, saying they will have nothing to sell without this tool. He programmed the AI to watch his 14 local-area community groups for service requests; each alert carries the post link so he can go directly to engage, answer questions, and offer his phone number.
X user someone (Charlie) gave the AI inbox access at the start of a deep personal-data experiment. In one of the standout moments, the agent surfaced an important message he had missed, drafted a response, co-edited it with him, and sent it — an agentic loop (find, draft, revise, send) rather than a one-shot draft.
A Korean solo developer's two-day diary of putting the AI to work as his team: GitHub issue labels split between him and the AI across marketing, planning, design, QA, operations and finance, with a project board and roadmap milestones built in about an hour; the AI runs QA on each deploy event and files issues; customer inquiries are answered through an admin MCP connection; and morning routines from a one-time setup (7 AM English lesson, Google Analytics analysis, issue briefing) arrive unprompted. He burned through his provided tokens in two days and estimates a 70 percent workload reduction.
Before a speaking engagement, Ulanoff couldn't recall where he was talking or where to park. He asked the AI to find the original note from his contact, misspelling the contact's name.
A bot fixes the team's production errors overnight, on an ongoing basis.
A pipe burst in his house two months ago. He now has the AI run his side of the claim. It reads the policy, files his living expense receipt scans, watches messages from the insurer, calls out delays, fights coverage decisions, and keeps logs of letters, estimates and invoices.
A real estate broker said her AI assistant nurtured leads for months and booked showings on its own. She closed 4 deals with buyers she never spoke to until the showing.
The AI ported the user's mobile service to a new provider in under 60 minutes, cutting the ongoing cost by 75 percent.
During a flash sale on his petals.team site he checked analytics and found zero events, ever, because PostHog had never been added. Through the PostHog MCP connector in an AI chat he spotted, diagnosed and fixed it, saved a 3 step registration funnel, and set a weekly digest to land in Slack every Thursday.
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.