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.
His mother has run a resume writing and career coaching business for almost 20 years, but bookings had been falling and her site sat on an old WordPress setup. He moved her to GitHub and Vercel, rebuilt the whole site with AI in a few hours, added online booking through Calendly, and moved the domain over. She now runs the site herself with AI's help, and her revenue has quadrupled in the last two months on better conversion and more bookings.
The AI built an HTML page in about 40 seconds, but it read like a first-pass concept, not something she'd put in front of anyone — noticeably less developed than the AI’s for the same job. Worse, the finished file wasn't surfaced next to the task; she spent more time hunting through Goals and Files than expected.
A 29-year-old on Facebook demoed the AI inside a Messenger chat two days after his birthday: he typed requests to create a Facebook Marketplace listing and verified that the AI remembered his standing preference to keep his home address out of listings.
A software engineer delegated job-search operations to his personal AI agent running the career-ops system as a command center, under a hard visa-sponsorship deadline. Over eight weeks it evaluated roles, tailored CVs, tracked 21 serious applications and prepared interviews, ending in 7 interview processes, 2 offers and an accepted role in Amsterdam.
Tony Xu recalls using AI as his always-on agent in early 2026: he handed it a blog post draft task over Telegram, and the AI cloned his repository, studied his older articles for structure and voice, drafted the post, and he then checked the structure, facts and wording before publishing. He liked the capability but quit over the upkeep: a self-hosted gateway and services he had to run himself.
He asked the AI to check a researcher's co-authors on ORCID for possible Mastodon links. The AI checked 163 co-authors, 120 of whom had ORCID profiles, and found none.
Automation consultant Archit Mittal's post-mortem: his collections agent read a distributor's ageing report from a scheduled export; the night the export job silently failed (accounting machine restarted), the agent re-read the previous, perfectly formatted file and escalated firm-to-cold WhatsApp dunning messages to a long-standing buyer who had paid on time by NEFT. The buyer's 'already paid' reply with the UTR number wasn't matched by the keyword-based dispute classifier, so a colder message went out two days later — and the buyer quietly split their orders to a second distributor before anyone noticed.
His newsletter, close to 9,000 subscribers, is run day to day by four AI agents with set roles: one oversees, one edits and manages, one builds, one dispatches the work. He still approves anything that goes out, and the agents refresh their own context from checkpoints instead of slowly forgetting across days.
Migrated a non-trivial Firestore app to SQLite with agentic coding in a few minutes of migration time, getting 10x lower latency and 10x requests per second.
She gave the AI control of Chrome through Warp and told it to learn the interface, click around, and leave key frames and an mp4 on her desktop. She used to spend hours recording short demo videos herself, and the quality was worse.
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.