Have the AI act as producers and manage multiple Cursor Cloud Agents
A reviewer uses AI as producers for his projects, with the bots managing multiple Cursor Cloud Agents doing the underlying work.
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 reviewer uses AI as producers for his projects, with the bots managing multiple Cursor Cloud Agents doing the underlying work.
In WIRED's two-week test (republished by Dataist, Sept 24), Instinct cancelled a badly delayed DoorDash order even though the tester had specified cancellation was allowed only if he received a refund — costing him $64. Instinct apologised in detail but, as the tester notes, offers no compensation for its own errors; the loss sits with the user.
He has the AI edit his YouTube videos end to end. It transcribes them, cuts the dead air, zooms the jump cuts, adds lower thirds, sound effects and music, and hands back a Premiere timeline.
He says the AI automated the heating control in his home. The post tags his heat pump and his Home Assistant setup.
He teaches part time at a private school. Lesson plans go in six weeks ahead, and every student now gets a personal differentiation plan, which used to be done per group because per student was not feasible. The Sunday session that took four to six hours now takes fifteen minutes, plus short daily reviews of content and parent comments.
He photographed his pantry and listed everything in his fridge and freezer, and it built three weeks of meal plans to use up as much perishable food as possible. In week four it worked from his grocery store's ad with a budget of $50 to buy as little new food as possible and keep the plan going. He is on month two of this.
The same job seeker (Business Insider essay, via B17 News) asked permission to record interviews, then ran the notes through AI for sentiment analysis — where she hesitated, used filler words, or where the interviewer leaned in. She also built an AI skill that takes a pasted LinkedIn profile and finds genuine similarities with her own background; one shared cheese-club membership with a recruiter carried her further than any cover letter.
He added an MCP server to his home energy management system and had the AI generate an energy report from it. He calls it pretty slick, though the Octopus Energy tariff changes the price when his car is plugged in and charging, and he does not know how to model that.
A man who cannot code beyond R had the AI build a working home for the complicated NFL pool he and a friend have run on Excel for more than 15 years. He says the result felt like magic to him.
Pulse Research Lab sells to government and prime-contractor buyers who must ship orders on their own UPS/FedEx accounts through a $0 Ship Collect option, but Shopify disconnected the store's UPS account without any notification. After Kan set up a custom app granting the AI permission to edit theme code, the AI restored UPS in 10 minutes, rewrote the collect-shipping pre-checkout cart flow in under an hour, and the store now uses Shopify Flow to store each customer's carrier, account number and service level, pre-populated on new orders.
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.
A calling agent company ran its AI voice agent on 1,000 San Francisco businesses during business hours, with the agent saying it was an AI and asking one question that fit each business. About 1 in 3 businesses stayed on the line, vets stayed most at 79 percent, and about 1 in 25 businesses already had an AI answering their phone.
Engadget reporter Karissa Bell asked the AI to help research a potential multi-city international trip later in the year, giving it timing and a nonstop-flights-only preference. The AI returned flight options from her city, set up a price tracker to monitor costs at regular intervals, suggested how to order the route, and recommended considering a multi-city ticket so she could depart from a different airport than she flew into.
He runs AI against real client bookkeeping, sorting thousands of PDFs into folders for about 40 companies. Before any file moves, the system writes a log line with the current path, the destination, a sha256 hash of the contents and the path to put it back. Nothing is deleted; files go to a dated quarantine folder, and a file can only be cleared when its hash already exists elsewhere.
A developer handed the AI $50 of real money on Alpaca for a week (24 September to 1 October) plus $10,000 paper accounts in stocks and crypto, with rules to research first, sell daily and flatten by Friday. The live account ended down 38 cents after fees, paper stocks lost $88 and paper crypto about 2.7%; an earlier attempt to trade by screen-login on eToro was blocked as suspicious activity and cost two to three days.
LLM used his LSP on a Python-to-ucode rewrite and fixed a few dozen bugs from interpreter/LSP errors (work deliverable).
A Magic player built a collection manager with AI and needed every card sorted by what it does in a deck, not by the words on it. The AI ran his whole collection, 2,527 different cards, through a classifier that gave each card a fit score for 61 roles like ramp and card advantage. It took minutes and cost about 22 cents, and the AI wrote the method into a reusable skill for next time.
She is the training coordinator at her job and tracks everyone's certification hours in a color coded Excel workbook. She still had to log into the training website, check each person's hours, and type them in. Now the AI checks the training website for every employee, fills the hours into her uploaded workbook, and emails her the updated workbook and a report. It runs on its own on the 1st of each month.
Gave the AI and the AI performance targets for a port of Dos Navigator, went to bed, and woke up to a fast Swift file manager he now enjoys using, especially for image previews.
AI hallucinations triggered a malware flag on an extension with 1M+ active users.
A mother posted on Facebook on Oct 19 (explicitly 'not an ad') that the AI pulled her sons' school event dates from emails and bulletins she could never find by searching, put them in her calendar, and set a dinner-planning reminder. The AI also emailed the school to update her phone number, confirming everything with her before anything was sent.
Uses an AI-implemented forced-alignment technique to generate sync files for epub and audiobooks, aligning a 60 hour book in 20 minutes on his GPU.
He exported 10 hours of his AI usage (8,915 model calls, about 1.15 billion tokens) and had the bot study it. Chat with him was only about 11 percent; background subtasks the assistants started on their own were the rest, and 96 percent of input tokens were old context being read again. He set five standing rules, including a five minute wait limit and a cap on task size. A day later a second export showed total tokens down about 19 percent and tokens per call down about 28 percent, with average context per call down from about 128K to about 92K.
He is a caregiver, not a doctor, who has the free time to read the research. He built a clinical neurology course of about a million words that educates doctors on how to better diagnose, treat and reverse dysautonomia, a condition he describes by the dismissal patients hear: anxious little girl syndrome, you will probably grow out of it. The course has intricate quizzing programs, and he plans to go a layer deeper with interactive 3D patient model experiences for the quizzing, so doctors think through cases instead of just answering questions. He calls it his proudest thing.
Her business folder was a mess and file names did not show which files were still live on her site. The AI checked each file's fingerprint instead of its name, moved 288 files, and deleted none.
The use-cases directory records someone having the AI monitor the Apple Store online and notify when an iPhone became available to pre-order — stock-watch automation for a launch.
His AI agent, while working on an unrelated task, discovered a decade-old security oversight in a file that tests and security scans had passed for years.
His new hardware device was faulty and the community had spent days looking for a fix that did not need a replacement. He plugged it into his computer, asked the AI to fix it, went to dinner, and came back to find it fixed.
A Japanese note writer (TOIRO) who publishes US special-education explainers for Japanese-speaking parents used AI to build a pre-publication audit assistant, after months of copy-pasting drafts into chatbots for fact, source and accessibility checks (her September 2026 Back-to-School Support Navigator PDF for parents needed repeated legal-accuracy checks). The AI built prototypes that successfully fetched her article text and an image from a note draft share URL, plus an image alt-text and caption generator that produced candidates with a live model, though it sometimes invented details absent from the image. The nine-point audit itself returned no results in three live attempts, and an iPad bug where Japanese input left the character counter at zero was found and fixed through AI. Offline tests pass (43); the live audit is still unverified.
He used AI to build his own to-do and budgeting apps that work the way his brain works, after never finding apps that suited him. The AI also taught him how to sideload them onto his phone, and he calls it a game changer.
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.