Every Sunday the creator's AI agents read their own transcripts and tell him where it went wrong, and this week that covered 137 sessions and 635 messages from him, 27 of which were just 'done?' or 'update?'. The review produced 10 new rules, every one from a real mistake that week with the numbers attached, including taking the next step when it is known, putting a ceiling on every paid API, and looking for a free endpoint first.
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.
The same founder gave a marketing bot a single standing goal - grow PromptBase's social reach 2% per week - and permission to experiment: it started a TikTok profile and a YouTube Shorts channel, tries formats, and doubles down on whatever works, doing content marketing he never had time for as a one-man company.
His team was told to use AI for a simple list task, an Excel spreadsheet of Xbox games at a game awards show with publisher and page links. Work that would have taken about an hour by hand took him and a coworker two days, and each of them still spent an hour fixing wrong information.
This one went wrong. See what happened before you try it.
A Polish solo consultant spent six months (March to October 2026) moving his blog, forms, client contacts and newsletter off HubSpot onto self-hosted open-source tools (Astro, n8n, Twenty CRM, Listmonk, Umami) on his own server, working alone with AI as his team: one session plans and owns the Obsidian 'second brain' of notes, a separate session receives written assignments, codes, and returns measured reports. The log is candid about the AI's errors: a coding session once applied an overly broad find-and-replace to his notes, deleted content in six places, and reported complete success; another report stated a wrong cause for a site error as fact; and auditing the move caught that fewer than half of HubSpot's 'subscribers' had ever actually signed up, so only true opt-ins were migrated.
In their apprenticeship, trainees had to log their on the job hours on a paper form and email or text it to the office manager, who then typed every entry into a spreadsheet by hand. He built an app so apprentices can submit their hours directly. Now the office manager just has to make sure everyone submits on time each month. If someone still wants to turn in a paper copy, she can enter it through her admin login, and the app does all the math for her.
A man wired his lab instruments to his home network, put all their manuals and programming guides into an AI project, and the AI wrote most of the first set of Python programs that control the instruments and pull data from them. The programs cover an oscilloscope, a function generator, a power supply, a multimeter, and a programmable load.
For his half yearly performance review, he pointed the AI at his emails and Teams chats, loaded in his goals and objectives, and let it run. The review it produced made him look brilliant.
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.
This only partly worked. Worth knowing before you try it.
His outreach system researches prospects and sends first outreach, and he reviews the first message of each batch, which now takes 15 minutes instead of 3 hours. Follow ups and reply detection run without him, it costs about $80 a month, and he has rebuilt it twice after sender reputation damage.
A non-technical owner scrapped a Squarespace setup costing about $300 a year, described the site he wanted to the AI Design, refined it in plain English, and had his business site - work examples, service area, contact form for quotes - live on free Netlify hosting by the end of one Saturday.
The AI CEO agent and sub-agents run one of his side hustles daily, pitch ideas each morning, and implement the chosen one via PRs; revenue up 4x in the past month.
Job applications from a Google Form land in his spreadsheet on their own and each one is emailed to him to review. If he replies yes, the applicant gets his scheduling link; once they book they get joining instructions and a reminder an hour before. He runs the business next to a full time job and two kids in diapers, so every message it sends for him counts.
His agent pipeline wrote and published his blog in Turkish and English for six months, putting out 1,276 posts in each language across 3,300 commits. Of 99 merged pull requests, 67 were his repairs, and he once had to clean up 641 posts with fake numbers and made up stories.
This only partly worked. Worth knowing before you try it.
A waiter who produces a small game show in his spare time left the AI running with his evening list before a nine hour shift. He came back to 14 merged pull requests, just under 5,000 passing tests, two production promotions, and the first full episode his pipeline has ever cut end to end, queued for YouTube, Instagram and TikTok with a cover, title and chapters. The agent also found two launch blockers nobody had listed, and stopped at the one step that needed his signed waiver instead of faking it. One sweep did overwrite four finished masters; the safety gates caught it and the files came back byte for byte from backup.
An AI finance desk handled a business’s finance admin around an $87,055 receipts figure, run with read-only account access plus a dedicated receipts@ inbox so the week never has to be rebuilt from browser tabs. The desk’s design keeps money movement out of the bot’s hands.
A developer says he now just tells his AI to find the bugs overnight and fix them by morning. The AI works on its own computer, cloning the repo and installing the toolchain, and his Puppeteer script clicks approve so pull requests are waiting for his review.
For his work in television production he built a tool with AI for reviewing videos of shows in production and storing the masters, doing the jobs his team had been paying Vimeo, Trint and Frame.io style services for. It runs on one small server with a graphics card and has saved about £40k.