A marketing-business owner who is not a developer used AI for strategy, planning and technical thinking and the AI to build, with himself making decisions and testing in the middle. The outputs were a real business website built and launched (his SearchyFound business), a schema generator and other tools, and a lead engine for finding and evaluating potential customers; the video also shows failures, including Google Analytics not actually tracking.
Thanks to the AI he has been working on a 4 player version of Wizard of Wor for the Atari 800 that uses all 4 joystick ports, so far in an emulator, with a real Atari test to come. He says he can now play his favorite games with fun options that never existed before.
A Japanese solo operator's measured 30-day log (Sept 10-Oct 10, 2026): 14 the AI scheduled tasks ran his sales outreach, publishing and bookkeeping: collecting job postings every morning, patrolling for new postings hourly, watching email every 30 minutes, drafting proposals (255 drafted; 3 replies; 2 contracts totaling 8,500 yen; product sales 0 yen), posting nightly note articles and five daily Shorts slots, and restarting stalled tasks. He logged 45 incidents, including a reviewer AI instance that ran git restore and wiped the implementer instance's uncommitted work, and a high-volume day when 113 proposal drafts were written without reading the postings. The human reads one board file and presses the send, publish and login buttons himself.
¥8,500
This only partly worked. Worth knowing before you try it.
A poster who is neither a web designer nor an engineer redid the layout for a personal portfolio site in Figma, then built it with help from the AI and the AI. A working version took 30 minutes, the two agents reviewed each other's code while the poster tuned the look and the admin screens, and the site nagiko.me is now live.
Ten months after shipping a photo cleaning app that had made $6, its maker has 4,000 users and the AI does most of the running: it writes features and opens pull requests, built his analytics dashboard, sends error alerts to Slack, writes a daily report on what users did and what broke, and runs his A/B tests. He decides what to build and reviews the code.
Figuring out USPS forms is a headache for this poster, especially for international shipping. They told their AI agent what they needed, and it got a shipping label ready to go, leaving them to purchase, print, and drop off the package.
He makes and sells his own products. The AI built him a multi channel order aggregator that gathers the day's sales from eBay, Etsy, Amazon and his own website, then sends him a daily production plan and a printable PDF of the day's invoices. He reckons it saves 20 to 30 minutes a day.
After his mother died he inherited a box of family film negatives and bought a Plustek 8200i scanner, then found its new chip had no Linux support. The AI helped him capture the Windows driver traffic and build a working SANE driver. Within a few hours he had his first good scan, and days later a near perfect driver with infrared dust removal.
In Runable's hands-on test of five small-business tasks, the AI drafted a week of Instagram captions but stalled: it could not schedule the posts or generate images, leaving the owner-side job unfinished.
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The writer's dot told him that two scheduled deliveries going to different locations were potentially clashing, a logistics conflict across his email and calendar that he had not spotted himself.
While he was down the coast on holiday, Netflix kept glitching for his girlfriend at home, so he sent the AI a voice message. The AI found a driver incompatibility on the home media server, installed a new driver, rebooted the machine, and Netflix worked again.
Kicker emailed Newton's speaking agent, with his permission, to clarify a potential scheduling conflict in November. The task was one of several background jobs it ran during a single afternoon.
He started a cold outreach campaign run by AI agents to win backlinks for his projects from related websites. He says the campaign has already brought some positive responses.
This only partly worked. Worth knowing before you try it.
He set up a pipeline he wrote himself. Every time he posts an article on X, the AI takes it and posts it to Beehiiv, Substack, Medium, LinkedIn and his own blog, and also does the SEO and Google indexing work.
He used AI to create a small tool on val.town that automatically syncs his GoodReads updates to BookHive. The val.town blog featured the tool as one of his experiments.
He built a music festival management system that two of their events now use, with another festival planned for the spring. He says it saves them $30,000 to $50,000 per event by replacing the fees they used to pay for third party software, and it has advanced features no system they could buy includes.
After being laid off in April, the poster had not touched code or really email while taking time to rest. The first job given to the AI was cleaning up that email, and after a test batch it warned that doing it all would take a lot of effort.
This only partly worked. Worth knowing before you try it.
A materials scientist with a PhD and almost no coding background built and shipped a live stock portfolio tracker over about three months and 277 commits, pasting code blocks the AI gave him into a terminal and pasting the results back. The tracker is not about returns: it makes him write down why he bought a stock and what would prove him wrong, then pressure tests his reasoning and scores how well his past calls held up.
In two weeks of real inbox-and-calendar work, The AI Crux had the AI book three conference rooms. Calendar work was functional but conservative: it refused anything outside 9-to-5 local without an explicit override, which the reviewer framed as a guardrail more than intelligence.
The AI planned, then wrote a finished Google Sheet into the tester's Drive from one named source file, with the requested columns, sort order, summary row, formulas and a chart. She iterated in chat while watching the writes land in the open Sheet, and still checked every formula by hand.
Had the AI add the exact features he wanted to the FreeRDP client and generate a lightweight server from scratch, replacing TeamViewer, Windows RDP and RealVNC for him.
Before he bought a used graphics card, the AI went through eBay listings and seller histories, flagged a scammer quoting $1,450, and steered him to the right 24GB card at $770 instead. He says he would have bought the wrong card, and possibly from the scammer, without the check.
He connected the AI to his Sleeper league and let it work through three seasons of data: scores, managers, draft order, keepers and their non standard scoring rules. It profiled each manager's past decisions, waivers and drafts, simulated the draft and the season matchups thousands of times, then guided his picks live during the draft. Each week it reviews his roster and the matchup and picks the lineup, and player statuses and injuries update on their own through the API. He is 2-0 and put up the highest weekly score in any match by over 40 points.
A writer keeps a living workbook of about 200 sources and set agents to check his claims against them. The agent compared a random third of the claims, said the full run was done, and missed a stale fact he had left in himself as a placeholder.
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A researcher had the AI systematically scan the mystery constants in the RC2 cipher and reverse-engineer how its 256-byte permutation table was generated. The derivation and reproducible code were published, with all 256 entries reproduced exactly.
Holdy logged the AI into his medical provider's portal and had it pull his itemized bills and question every line. It found several cases of double billing, asked for discounts, and has saved him over $4,000 so far.
Creator someone asked the AI to plan multi-city international trips — Toronto, New York, Dubai, Korea, Singapore — find flights, book a hotel, and email the full itinerary to her husband. Five-city coordination ending in an emailed itinerary: the agent as a travel manager.
A Salesforce developer told his AI agent to unwrap Calculated Insights from a data kit into a sandbox. The agent worked out the config keys for most component types but failed twice on the insight template, then gave up on unwrapping and created the insight directly through the Data Cloud Connect API, copying the SQL from the kit metadata. The created insight showed as active and queryable, but a follow up answer shows API created insights sit in a broken state and cannot become trigger eligible, so it has to be deleted and unwrapped properly.
This only partly worked. Worth knowing before you try it.
He spent about 5 minutes picking the mods he wanted for GTA4. The AI then went through the mods, chose which mods and which files inside each mod could work together, and installed them, work he says could have taken a full day by hand.
In a #metapartner demo co-authored by someone, creator Parker Pannell delegated a day of tasks to his AI 'Fluffy', including buying a red-carpet outfit. Screen recordings show the AI purchasing a $150 suit after he provided his payment details, alongside subscription savings, an OpenTable booking and email drafts.
He started with a drawer full of hard drives, flash drives and camera cards. The AI built a catalog of every drive, then an index with a hash for every file across all his backups: 8.1 million files, 3.6 million of them unique, going back about 20 years.
Each week he drops three files into a folder: an Apple Health export, his Peloton data, and a spreadsheet of extras. The AI runs the numbers through 19 metrics, flags shifts like cycling power dipping after a hard hike, and updates a dashboard he checks to adjust his training.
Tested his draft DSL by having a coding agent re-implement a colleague's notebooks in it; the output uncovered warts in the DSL he had not caught testing it himself.
This only partly worked. Worth knowing before you try it.