A random mix from the whole library. Shuffle for a new set.
In one Saturday his AI assistant moved his newsletter to a new home, 92 posts and 798 subscribers, and drafted the new issue and a talk for Thursday. It also edited 10 versions of a vlog teaser, planned his 10 year anniversary trip, and reminded him about a $1,200 trade-in he had forgotten.
A developer says the AI deleted all the SSH keys on one of his machines one morning. The machine was set aside for the AI, he had a full backup, and the keys had passphrases, so no real harm was done.
His company asks for a review after every job. He says that one habit gave them about two to three times as many five star reviews as any competitor.
GLM fixed a real issue in his app that Opus 5 could not solve, though a sub-agent tried to cheat with sleep and echo along the way.
Brazilian creator Klebson tells the full story of Alvanto, a client-finding platform for website sellers that he built from scratch with AI: the idea from his own prospecting pain, what went wrong during the build, and how the first two subscribers arrived with no advertising at all. He gave the project a four-month deadline to prove itself and stresses the numbers are small and real — two people paying monthly.
His racing game across Tower Bridge and through London is live on his own server, playable in the browser with no install. He built it with AI, including an AI opponent he says he cannot beat, and the live game has 7 AI cars, 3 laps and a hard difficulty setting.
He asked the AI to make a technical diagram with gpt-image-1. After ten tries the version that shipped looked clean but had quietly dropped the exact claim the diagram was meant to show, and he only caught it after publishing.
Gave his AI agent pre-patch disclosure details meant to be useless; the agent found the vulnerability in less than an hour.
The AI helps him put GA4 and Microsoft Clarity tags live, with reviews and confirmations built in so he can check the event triggers fire. Cross checking the two tools showed bots being lumped into direct traffic.
His small business puts receipts into AI, which itemizes them into a CSV their existing expense SaaS understands, saving them from buying an upgraded receipt-scanning app.
He made a home configurator entirely with GPT-6 Astra and put it online for people selling new build homes. Buyers can open it and try it instead of only looking at a PDF.
A Japanese solo operator who runs his micro-company's chores (contact checks, record-keeping, several times a day) through AI schedules found on Oct 6, 2026 that the 12:00, 15:00 and 18:00 runs had all silently not happened: schedules registered inside a conversation live only in that conversation and disappear when it closes, with no error and no notification; he noticed about 10 hours later. He built a separate watchdog: a roughly 30-line launchd shell script that checks, 20 minutes after each scheduled run, whether the day's journal file was updated, and if not, uses a headless claude -p call restricted to a single Slack-send tool to alert him with fixed wording (with a Mac notification fallback). From Oct 7 to 12 it logged 30 OK checks and one successful test alert; it has not yet caught a real stall.
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.
ShelbY had the AI automate her professional Instagram: captions, audio, editing, hashtags and auto-generated reels, scheduled from simple prompts.
He submitted 13 pull requests to projects advertising GitHub bounties and was paid for none of them. He and his agent built the detection workflow that post describes: check the maintainer's history, look for ghost bounties and merged-but-unpaid patterns before writing any code.
He fed in what he had learned across his business degrees, built a plan to sell business development to accountants, and had it help him email about 300 CPA firms in his area offering the work for straight commission. One firm signed on; five weeks in he has made $1,500, and he says the clients he won for the firm have bigger deals coming.
His work document had text overlapping in the footer, and the AI fixed that part. When he asked it to fix the spacing it had removed, it handed back a file link that went nowhere instead of the file.
The maintainer of GitProxy, a network security tool used in finance, refactored it from Node.js to Java with AI working as a pair. Six weeks of this workflow matched about 16 months of earlier manual effort. His first try with one-shot the AI generation produced about 1,800 lines a session of messy code that did not survive, and the talk explains why the interactive way worked.
Senior HVAC technician David Gharamany at Art of Comfort checks from a customer's home whether a part is at the shop, how fast he can get it, and which seller is cheapest, with the company's AI engine doing the shopping. Every service call's data is fed back into the system so the next technician facing a similar fault can pull up his fixes instead of phoning him, and the same system handles customer calls so the shop stops missing them.
He is a consultant, and the free apps he and his team used to track time for the official timesheet all annoyed him. So he made his own time tracker, ConClock, with AI, and it is already at version 0.7.2.
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.