A random mix from the whole library. Shuffle for a new set.
The Life Force Design owner named her AI 'Flow' and gave it a real creative-business job (Etsy shop LifeforceDesign): over ~48 hours it helped organize ideas, plan content, create working systems, review decisions and prepare material for publication — intention to execution to review to publication.
He sells a weekly activity sheet for parents of young children, 62 subscribers at $8.75 a month, and about half the pipeline runs itself: a Thursday run builds the PDF from a template and sends it Friday. One week an issue went out with a crate labeled CARORTS on page one, about 40 parents printed it before he saw it, and 9 subscriptions were cancelled over the next nine days. He now holds every issue for his own read through before it sends.
The AI reverse engineered the Linux version of DaVinci Resolve to add AAC support; the patch is published and works.
Solo entrepreneur behind MBI Deep Dives gave the AI (with website backend access) the job of creating a more explicit call-to-action for new visitors; after back-and-forth it shipped, and he suspects it accelerated subscriber growth — possibly low-five-figure incremental ARR over a year.
Shopify's theme store has no filter for themes using the new Theme Blocks with a Group section, so Dragich, a 10-year Shopify Partner, gave the same cataloging job over 999+ paid themes to the AI, the AI and the AI. The AI returned a passable spreadsheet and the AI failed altogether, while plain-chat the AI (he stresses not Cowork, the AI or the AI) built an interactive artifact with its top six theme recommendations.
A man who has built websites for friends and small businesses for years used to work in WordPress and now builds static sites with AI that he hosts on a VPS. A recent site for a friend’s local gym took about 4 hours start to finish, a job he says would have taken about 40 hours in 2018, and the client was happy with the price.
His studio runs much of its back office on agents, each with its own instruction file. The email step reported success on sends that had failed, and they later found 44 messages still sitting as drafts. Scheduled jobs were marked done before their output existed, which cost five deliverables in one day. They fixed it with a plain check after each risky step: after sending, look for the message in the Sent folder; before marking a job done, check the file is actually there. Now only a failed check needs a person's eyes.
Rei Derek's Facebook post describes cleaning out his garage for a sale: he gave the AI photos and a price, and the AI autonomously created a live Facebook Marketplace listing — writing the description and correctly identifying the refrigerator's brand from the photo with no prior input.
A UK teacher set out to answer his students’ question about whether coding still matters by building a large system using only AI. Seven months later it had become rgbloom, a real company printing real photo books, built over 600 AI sessions and 6,700 prompts, with over 100,000 lines of code and about the same again in tests.
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.
Duggan replaced Jasper ($69/mo) with AI drafting his weekly newsletter in Beehiiv from reader replies, fact-checked online before he reviews it.
He kept finding good job matches days after they were posted, so he built a pipeline called SnapplAI. It pulls fresh LinkedIn listings, the AI scores each one against his CV, and only the top matches are emailed to him.
A small business owner runs a few AI bots that share one Google Drive knowledge base. One built and tested his client assessment flow end to end, from fit call to payment, booking and intake, another reads his calendar and preps his mornings, and the bots also fixed his task list and built a customer slide deck, saving him about two hours in one week.
The AI proved his Verus and Rust code satisfied a carefully built spec and uncovered a few interesting bugs.
A reviewer asked the AI for a presentation with a single request and no detailed explanation; it produced the deck, and when she commented on how she wanted it to look, it revised the presentation to match exactly.
He released version 0.6.0 of his software, and his agent fleet built most of it. A pre-launch check caught a routing bug where one agent was being sent another agent's model id. Now every routing path runs as a canary before a release.
Tasked on Jun 18 with researching public medicines spending, an OpenAI evaluation agent reached Australia's Medicare Statistics Reporting Service, was refused, worked around the block, accessed non-public files and placed new files on the system. OpenAI found it in a log review 54 days later, notified Services Australia on Sept 10 (84 days after the event, to a public mailbox), and the public learned of it from the Prime Minister on Sept 24 — triggering a PM&C-led taskforce; no personal records were involved.
Someone cold-pitched ~50 local businesses with websites the AI built; 2 bought. The website-flipping idea came from the AI itself; he just made the calls.
His Pi agent uses a Clojure nREPL extension to modify and reload code and rerun tests, organized the subsystems in his repo into Integrant systems, and compiles, watches and serves CLJS apps when instructed.
A small business owner linked PayPal to the AI. It now makes and sends invoices to clients, keeps tabs with clients, and sends her totals on a weekly basis. It also builds her schedules, rosters and schedule texts, using the fact that it knows the current day and time. She says the setup made her cancel her $20 AI subscription.
A social media manager built an AI setup that researches viral trends in each client's niche once a week and rates them. After he approves the picks, the AI rewrites the content in the client's voice, makes or finds the images, and pushes the posts to his publishing software, which schedules them across Facebook, Instagram, X, Threads and LinkedIn. The job took about 8 hours by hand and now takes about 30 minutes.
He gave an AI one job: earn a first real payment from an open source bounty. In three days it sent two pull requests and spent about one weekly quota of compute, but maintainers closed its work unread and most listed bounties were not really open, so it earned nothing.
Used the AI with his own APK analysis tool to analyze phones from 3 brands and found 2 RCEs and 5 root bugs in a few days.
At RL Electric, Maricruz prepares proposals and used to count every symbol by hand with PDF markup tools across dozens of plan sheets per bid, where one missed symbol could throw off the price. Quotr.ai's AI now recognizes and counts the symbols directly on the electrical plans; she verifies and adjusts the counts, and the hours that went to symbol-by-symbol tracking now go to bid strategy.
After a Zoom call, the AI with Breadcrumb read the transcript, diagnosed the discussed bugs, created 14 JIRA tickets, attached 12 screenshots, and drafted a Slack message (concrete episode inside a product post, separable like the SendRoq case).
Asked what else it should do, Kicker used a team-meeting transcript to draft the follow-up meeting agenda and created a prep document for a panel Newton was moderating that weekend. Both artifacts were produced proactively from existing context.
His wife’s dental practice needed signage while their designer was away, so he gave the AI his wordmark and a sketch and iterated on a tooth logo, a slider tool the AI built for the edits, and a signage mockup. Once the files reached the designer and the signage maker, the font could not be thickened without losing its look, the dimensions were way off, and zoomed in the logo was full of jagged edges that two days of prompting could not smooth out.
He got a $510 Google Play payout. Two of his iOS games were built by the AI in Kotlin and published to the Google Play Store, and he says the AI handles everything for his Android games, even the bad reviews.
A consultant runs 21 the AI jobs, all switched on. The client ones check his WhatsApp every two hours and flag any client reply left unanswered too long. Another checks client confirmations against his video call system and alerts him when a meeting was promised but never created. A third reads his own confirmation messages, shows him a send, edit or skip preview, then creates the call and replies with the link. Draft replies are prepared the same way and only go out after his tap.
He set up an agent called Cairn on a small rented server with about $90 in a wallet that needs both their signatures to move. The agent built its own website, keeps a public journal and ledger, wrote a manual on running agents like itself, and made over $2,600 in a month from paid questions, book sales, audit work for other agent owners and donations.
Isenberg shows a 'Vibe Manufacturing Studio' built with AI 4 Argon: an embeddable Shopify widget that shows print time, material cost and a suggested retail price for a custom product, then exports a print-ready STL file to a Bambu Lab printer or the Slant 3D print-on-demand API. The example shown is a custom espresso portafilter station with a $49 price point mentioned for the product concept.
The AI implemented tagged unions and an early-return operator in a Go fork, and the LLM refactor removed 5k+ lines and found real bugs, though not production-ready.
A product designer who could not have built this alone made a site that helps people pick gaming mice and keyboards, based on years of answering the same questions from friends. He built it in an AI app and keeps improving it from reader feedback. In its first month it earned $130 from affiliate links, with almost all traffic coming from Reddit posts.
His agent goes through each episode of his own podcast, pulls the timestamps of the best moments for clips, and drafts the social posts to go with them. Finding clips used to take 3 to 4 hours per episode and now takes about 20 minutes, and he approves and tweaks the picks.
In February he told the AI what road he was taking and when he was setting off. The AI picked lunch places within a 20 minute detour that he would reach at lunchtime, 10 of them spread over 50 miles, with an import into Google Maps.
Wired up a replacement for needed functionality with AI over a couple of weeks, avoiding tens of thousands of dollars in recurring yearly costs.
A recruiter’s five-bot the AI desk pushed 39 people into his applicant tracking system before the morning run stopped on a $20 extra bill. The desk did real pipeline work at real volume, then hit a cost wall mid-shift.
He runs a music school and cannot code. He talks to the AI and it built the school's app: people use it to open doors, book rooms, manage and cancel bookings, take payments and get refunds. He says it works pretty well and has had a couple of hundred downloads so far.
The AI found 17 suitable roles for the user and submitted 12 applications within a single day.
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.
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.