His own the AI review action checks every pull request and beats the review services he tried
Custom GitHub Action running the AI on a self hosted runner reviews PRs on publish or tag, works better than the review services they tried.
A random mix from the whole library. Shuffle for a new set.
Work
Jobs, side gigs and small business · 1,665 ideasThe AI handled my Datadog alert and pinged the right Slack group
He had the AI answer a Slack notification from a Datadog monitor. The AI checked the issue through Datadog MCP, found the right Slack group to ping, and sent a summary of what needed fixing.
The AI remade my class video so every pupil's work shows
His 5th grade class studied Maricarmen and her eviction, a real case, and the pupils made work about it. He gave Notebook the AI directions to redo the class video so all of their work can be seen, and the video is posted with a PDF of the work on his class blog.
Williams Technician Builds an Equipment Anomaly Detector With the AI Cowork
At natural gas company Williams, one operations technician built an anomaly detector with AI Cowork. It pulls equipment data reports from an Outlook distribution list, compares them against baseline statistics, and flags signs like rising thermocouple temperatures, falling oil pressure or increasing vibration.
My AI checks my Amazon ads every morning and queues the fixes
The WisePPC team sells on Amazon under its own brands. Every morning an AI reads the account health check and the change history in WisePPC and sends a short Telegram message: which campaigns hit their budget early, which advertised product went out of stock, and which bids changed the night before. It then queues proposed bid cuts and pauses, with its reasons, for a person to approve or decline. Nothing goes to Amazon without that approval.
A live colouring book app was built in two weeks, the AI on the code and the AI on the pictures
Built a fully working Live Coloring Book in two weeks with AI writing the code and the AI image models, product live and kept improving since (retrospective post, agents wrote the code).
Nokia Agents Automate Troubleshooting and Cut Resolution Time by up to 80%
Nokia built an ecosystem of specialized the AI Enterprise agents that automate troubleshooting. Issue resolution time has been cut by up to 80 percent.
Solo operator ran his whole business on 14 the AI scheduled tasks for 30 days
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.
My agent watches my client chats so no reply or meeting ever slips
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.
My agent flagged a client pitch from a live event transcript
During the Apple event she had the AI check the live transcript every five minutes against her client roster. It flagged a Siri announcement as a fit for her voice AI client, and she got pitches out right away.
Every 30 minutes it picks the top open issue in my repo and leaves a draft pull request by morning
A builder runs AI as a night shift for his side project. Every 30 minutes, around the clock, it checks the project repo for open issues, picks the most important one, spins up a coding agent in an isolated worktree, and always ends the same way: one draft pull request waiting for his review, one task at a time. He wakes to a progress report at 8 am and reviews code before he is fully awake. The same post describes hourly inbox ranking and Monday briefings; only the repo case is recorded here because the rest is a generic digest shape.
The AI animated and narrated a spiderweb video with manim
He tried AI with manim to animate and narrate how an orb-web spider builds its web. The finished video is on his YouTube channel.
The AI built my StrivePay website, then burned 18,400 credits failing to fix its own errors
A reviewer paid the AI to develop and host his website, StrivePay, but hit repeated technical failures, broken functionality and exposed HTML errors; the 14,400 credits he received on September 25 plus another $20 for 4,000 more were consumed on repair attempts, and his refund request was refused on acceptable-use grounds.
This one went wrong. See what happened before you try it.
Agents wrote all 6,000 lines of my classroom Raft tool. It found a bug in my lecture notes.
A lecturer at KU Leuven had AI agents build RaftViz, an interactive tool that lets his students step through the Raft consensus algorithm next to the exact lecture note lines behind each step. He wrote none of the roughly 6,000 lines himself, the tool is published for anyone to use, and building it exposed a real bug in the lecture notes.
Two of my games were built by the AI and published on Google Play
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.
$510
The AI tells me about new plays every week
He could not find any service that tracks new plays by his 30 or so favorite playwrights. Now the AI checks and tells him every week.
Our agent bought its owner an eSIM for Turkey, then got the money back
The owner asked ARGUS in Telegram to buy the cheapest eSIM for Turkey, approved with a yes, and got the QR code in the chat seconds later for 0.31 USDC. Thirty-four minutes later he asked for a refund because he had not installed it, approved again, and the 0.31 USDC came back after the seller checked the eSIM was unused.
$0.31
A well-meaning automation nearly corrupted a spreadsheet
The review's lede lists 'one spreadsheet almost corrupted by a well-meaning automation' among the two-week test's incidents: three conference rooms booked, inbox triaged, and one spreadsheet nearly corrupted by an automation acting on her data.
This only partly worked. Worth knowing before you try it.
The AI edited a real video end to end inside DaVinci Resolve
The creator connected the AI directly to DaVinci Resolve through the new MCP server in Resolve 21.1 and had it edit a real video by talking to it. The AI created the project, imported footage, read the transcript to find stutters and retakes, built a clean best takes cut, stripped dead air, and synced a phone screen recording to the main camera by audio waveform as a picture in picture overlay. The description notes some parts did not work on the first try.
Three beauty shops, one owner: the blog writes itself from treatment photos
The owner of three Korean beauty treatment shops says she used to end most days having skipped the blog again; now she hands the AI a few treatment photos and one line of treatment information and a post in her stores' tone and her own voice comes back nearly finished, which she then saves as a Naver draft. Posting frequency is visibly up, the setup handles the recurring work, and she now teaches the same sequence to her staff.
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.