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.
Creator Lyndsey King says she used AI to create a single $37 PDF in 47 minutes: eight buyers brought in $296 the first night, and she reports total sales approaching $40,000, a shift from the $500–$600 courses she used to sell.
The AI opened a browser, created an account on the ticket site, picked his concert ticket, and paused for his approval in the app before paying. The confirmation email arrived and the AI added the concert to his calendar.
He built a tool that reads the emails from his kid school and activities, swimming, music classes and scouts. It adds everything to their shared calendar, sends a WhatsApp message the day before reminding them what to pack in his school bag, and tells them what is on the lunch menu so they do not cook the same thing for dinner. He says the morning scramble is gone and the head space is back.
A professor took the PID control demo from his own book and had the AI build it as an eight mission 3D flying game for his students. Students predict what the drone will do before each flight, and he checked every mission against his book version before it went live.
Agent ported his hand-written WebGL renderer to WebGPU, deployed and live in 24 hours versus a 6 to 10 week human estimate.
He uses an AI plugin to monitor returns on his accelerator board orders. It messages him on Telegram when the return window is about to close or prices move.
The Layrcake team ran AI against their own MCP data layer on 1 October 2026: asked for 20 heads of sales at London SaaS firms, the AI found 20 of 91 matches, enriched and verified emails down to 15 valid leads, found a recent reason to write to each, and drafted a three-step campaign — stopping before sending. The logged run took under ten minutes and 145 credits, about $1.45.
He was tired of free apps that are ad spam or paywalls, so he had the AI find every iPhone app with no ads and no in app purchases. The agent verified 149 apps and built them into a directory. Deals in it are checked daily and everything is rechecked weekly.
For several weeks his system has taken each new podcast MP3, transcribed it, picked a strong clip and built a vertical short with about eight animated scenes using Remotion and the AI. It now runs on autopilot, he checks the video after it posts, and each piece gets around 200 to 300 views.
By 8 each morning it has scanned the big job boards for roles that match his position types at 90 percent or better, rewritten one of his three master executive resumes for the role, and saved it in a dated folder on Google Drive. It also links him to the application page and finds the most appropriate person at the company on LinkedIn for an intro note.
After giving someone a book they already had, he used AI CLI to build a small app for gift ideas. It suggests gifts from his own 5 star book reviews and the other person's Goodreads wishlist.
The AI completed and filed the user's resident tax report through Korea's HomeTax system.
Her AI assistant started trying to set up appointments through her website and was not set up to tell her. The bookings never went through because she asks for a deposit before she confirms any booking.
He told the AI the ebook he is writing only had endnotes with no links, not footnotes linked in the text. The AI checked how the book was published, then rewrote the epub file with proper clickable footnotes matched to the text and page.
A mom of four school age kids started using AI last week and it already watches her school email, the grades site, Google Classroom and the ClassDojo app. It adds events and tests to the family calendar, sends a weekly report on missing assignments, reminded her about a field trip permission slip today, and drafts the email when a kid is out sick.
In the same CEO's US business line, an agent reviews the call-center operators' calls, transcripts and CRM results every day, then writes the human supervisor's task list with numbers and deadlines and sends each operator 3–4 small skills to fix from their own recent calls. Each skill is marked pass or fail every evening and closes after three consecutive passes; the agent only suggests — people decisions stay with people.
XAI says Starlink call centers run on the AI Voice, handling about 20,000 customer calls a day across multiple languages, with roughly 70% resolved without a human and one in four sales calls ending in a purchase. A single agent verifies customers, troubleshoots hardware, issues credits and ships replacement equipment.
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.
He built an invoice processor for a small law firm: PDFs arrive by email, get read with OCR, matched line by line to case codes, and pushed into the billing system. Anything it is unsure about goes to a manual review queue with a screenshot, and months of edge cases like 8s read as 3s went into its rules.
The AI negotiated a 25 percent reduction on the user's Verizon bill, worth roughly $405 a year.
A delivery driver has the AI run his weekly payroll. Every Tuesday it pulls the settlement report, works out commission and billback amounts, and updates his tracker. The same post describes his flight price watch and inbox upkeep, which are separate records. He says the payroll job used to eat a chunk of his evening.
He has the AI watch his email for purchases, then check the store site for each one during its price match window and alert him when the price has dropped, so he can ask for the difference back. He says he is over $700 saved so far. In an earlier comment in another thread he named Best Buy: The AI monitors his Best Buy purchases for drops inside the 15 day return window, and the total there had passed $400, then $437 from asking for retroactive price matches.
He asked the AI to tidy his todo inbox in milieu.cloud. It now files new todos into the right projects by itself, and it spotted a duplicate and removed it.
Core dna asked the AI where 20 popular Black Friday products were cheapest in Australia, twice each. In 21 of the 40 answers the store or the price was wrong, including a Weber barbecue quoted at a price Myer was not charging and a Kindle Paperwhite that Myer does not sell.
Glossaries for his Moodle course used to be a lot of work for a poor payoff. The AI made matching XML for them and he had it in the course in 2 minutes, with only the proofreading left to do himself.
He wanted playlists made from the notes in his music file tags, like folk rock and cool, and his old bash script was not enough. The AI gave up and sent him to forums, then the AI wrote a Beets plugin and a config that now creates and updates his playlists on its own from those tags.
Luke Davies runs Davies Construction with a team of the AI set up like a company org chart, with bots for estimating, admin, books, sales and project work. Day to day the bots sort the inbox and draft replies, pull tasks out of meeting notes into a list a person approves, and create and update the job tasks in ClickUp as work moves on the Wunderbuild board.
He asked the AI to check if his phone and internet plan was worth what he pays, and shared the agent's own account of what it did. The AI signed into his account and checked five months of statements: he uses 14 to 30GB a month, so his unlimited plan was charging him for room he never uses. It found a cheaper tier, Mobile Select at $30 a month with a 50GB data bucket, $15 a month less than his $45 legacy plan. The tier was not offered on the self service pages, so the AI opened the Xfinity chat, told the bot it was acting for him, got passed to a live agent, and handled the account checks, including spotting an expired approval link and getting a fresh one sent to his email. Before agreeing, it read the order review page: one line, $0 due today, $15 a month less, no add ons. His whole part was typing the word go. The saving is $180 a year from the next bill.
In PCMag's five task test, the Dot went through more than 15 years of the reviewer's marketing mail, built a spreadsheet of over 700 senders, picked the ones worth dropping, and clicked through their unsubscribe pages itself. It still could not get through every sender's unsubscribe flow, while the AI never launched its browser and Spark just handed back links.
A man in Korea runs 17 AI bots for the back office of his distribution company. The bots get statements, customer emails and claim rows ready, then post each one in Slack so a person can approve or cancel it before anything goes out.
The AI sold the user's car end to end: listing it, handling buyers, collecting CarMax and Carvana quotes, and preparing the licensing paperwork.
In 'Using the AI for Business' Ep. 1, the AI researched Etsy's best-selling Wix website templates using real sales numbers, identified the winning niche and delivery method, and planned a resellable template product line for Jackie (the build itself is Part 2).
Josh Kahn replaced his family's kitchen whiteboard with a TRMNL e-ink display that shows the family Apple calendar, a dinner menu calendar, and the weather. GPT helped him build and refine the custom Liquid templates behind the plugins, and the display now stays up to date on its own.
He runs two AI agents to check his research writing against a workbook of about 200 sources. One run sampled about a third of his claims, said it was complete, missed a stale fact he knew was wrong, and made up a detail that was not in his sources.
His kid's transcript was not going through, so as a last try he asked the AI to make a cleaner version of it. The cleaned version uploaded fine.
Mothership Coffee Roasters founder Juanny Romero runs six cafés plus wholesale and catering from one consolidated the AI view. Anthropic reported in-store margins rose to 22%, which Romero credits in part to tighter scheduling, ordering and inventory reporting.
The AI built a fast personal image browser for his many old photo folders, which he uses and likes.
Alongside his homemade TMS, Wes Oberman built a settlement payroll program that calculates every driver's pay automatically. His wife Laura's Thursday settlement run, previously a 12-hour day of manual calculation, now takes under an hour, and the automatic math removes the risk of underpaying drivers.
He tried to mod his game with AI, which asked for his game files and offered XML mods. So far not one of the mods has worked.
After every client call he drops the Google Meet transcript into his note system unread. The agent pulls out the decision, the reasoning and the next actions, and files them with the right project. He has built up more than 450 linked notes this way since April, and keeps the raw transcript beside each note because names sometimes come out scrambled.
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.