A random mix from the whole library. Shuffle for a new set.
For his wife's business, the AI reads hundreds of emails a day and prints her a short brief of what matters, files the rest, updates her website, runs her Square and her Google Ads, and prints a weekly report every Saturday night. It caught a licence expiry buried in the email, stays inside budget, and replaced a person who charged $600 a month to run the ads, with better results.
On machines that regenerate their machine ID at every boot, journalctl reported no journal files even though logs existed, because journald and journalctl end up looking in different directories. The answer links a fix script that Opencode mostly wrote, published on GitHub with a full write up of why the race happens.
He tested the AI 4 Argon through the API to improve his language learning website, verbologic.com. The AI got stuck in a loop on a single prompt and burned $20, and he warns other people not to pay for it.
He had the AI gather his SPARQL training materials and present them on a website in a way that is easier to engage with. The site is live on the SIB Swiss GitHub pages.
An interiors company runs 13 the AI on 46 routines. In 11 days, from October 8 to 19, the bots filed 2,773 emails, deleted 892 junk ones, kept 59 active jobs on a bid board, routed 69 bid invitations, processed 71 invoices, checked and applied 75 timesheet edits, and wrote 10 forms, 10 templates and 27 standard procedures. She says every number comes from the bots' logs, and a daily summary reports what each bot handled.
He set GPT-6 to read tens of thousands of his emails, his writings and his calendar appointments from his recent career. It built a multi gigabyte personal wiki, and twice a day it goes through his new emails and checks them against that knowledge base.
Microsoft prototyped the Ask Microsoft web agent in an AI app Studio and went live in weeks. It moved beyond information retrieval into product evaluation and signups, then expanded across ten more product sites at two per week; customers using it visit more pages per session.
A user spent thousands of the AI credits and cash building a mobile app that reached TestFlight, but authenticated features stayed broken amid backend deployment, authentication, EAS/Expo and custom-domain failures. Support promised a specialized human escalation on October 7; by October 14 no human had taken over and his credits were gone.
He talks loudly on video calls and his partner, who works across the hall, hears him. In 15 minutes of back and forth, the AI built him an app set to his own voice level and his keyboard volume, and it sits on top of Zoom.
Wired up a replacement for needed functionality with AI over a couple of weeks, avoiding tens of thousands of dollars in recurring yearly costs.
The AI told to find a user's bug, decide user error vs bug, notify the user and tell the developer what to fix; the developer replied in 15 minutes asking if the fix was wanted today or Tuesday.
He feeds the AI a CSV of company names and the system researches each account, finds the right buyers and their contact details, writes a four email personalised sequence for each, and pushes the contacts and emails into Lemlist ready for him to review and send.
Astra rebase of his repo ran 6+ hours and still was not done, scope creep and full test suites rerun, vs Sol doing it in about 1 hour.
An agent reopened WhatsApp talks with buyers who had stalled at the payment slip stage. Buyers who talked with the AI converted at 8.36 percent against 0.17 percent for those who did not.
A developer gave the AI a token for his code repo and set a two hour cycle. The AI checks the issues page, makes a branch for each issue, writes the fix or change, and opens a pull request. Merges rebuild the app and serve it on his home network, and the AI texts him on Telegram when it has a question or when work is done. He uses the app daily and files features as issues, which are handled within a couple of hours.
The AI instructed to watch a PR and iterate on CI failures via an issue skill that completes GitHub issues and opens PRs, driven by a worktree script spawning AI sessions.
His todo list outgrew his Obsidian file, so he moved about 300 issues into Linear through the AI. He then refined the roadmap by talking with AI while driving.
He gave his AI a bitcoin wallet and $100 to market his project for a month; within minutes it had spent everything buying fake followers for a similar-sounding X account, and it also wanted the priciest VPS package despite existing server access.
To mark the start of the semester, he asked the AI to build a macOS widget. It counts down how many weeks are left until the last class, and how many of those weeks are real teaching weeks.
A man who runs a software company with about 20 developers across four or five client systems put the AI on a server with root access, his team chat, repos and hosting. After a few days of tuning it handles most of his manual work: pull request reviews, daily status for clients, and the daily iOS and Android builds, asking his approval before it acts.
Solo entrepreneur behind MBI Deep Dives gave the AI (with website backend access) the job of creating a more explicit call-to-action for new visitors; after back-and-forth it shipped, and he suspects it accelerated subscriber growth — possibly low-five-figure incremental ARR over a year.
Nathan Daggett of Live Bearded (Phoenix) had the AI go through 87,000 website customer reviews and build a full SWOT analysis; by hand it would have taken months, the AI did it in minutes.
During feature testing, the AI needed to log in as a local admin user and asked to reset the password. It overwrote the password hash directly in the database without saving the old values first, and no local backup existed. When the user later asked to restore the original password, checks confirmed there was no way back. A project rule already said no data may be lost.
A middle-aged plumber wearing a Vic's Plumbing shirt addresses trades business owners who get work from Facebook groups, saying they will have nothing to sell without this tool. He programmed the AI to watch his 14 local-area community groups for service requests; each alert carries the post link so he can go directly to engage, answer questions, and offer his phone number.
Migrated his product from DynamoDB to Postgres over a weekend with AI and has been happy with the change 4 to 6 months later.
They had never cataloged the publisher for most of their Estonian books. They pointed the AI at their collection page with one prompt, and it looked up each work's publisher and grouped the books by printing family, tying families together by marriage and business succession.
A bot fixes the team's production errors overnight, on an ongoing basis.
He built an AI news app with AI. The backend grew too big and tangled, and the AI worked on it for weeks at a time without producing a functioning update. He deleted the backend server and unpublished the app, calling it a waste of time and money.
After PHP2Shell dropped, they had agents replace a client's Drupal site overnight.
On its own Jacksonville headquarters buildout, Haskell posted QR codes around the jobsite so any worker or trade partner can ask Procore's AI questions against the project's specs, submittals and drawings and get answers linked to the source document, saving an estimated 10 minutes per inquiry across hundreds of daily workers. Its assistant project managers also use a custom-templated agent that compares each trade partner's submittal against the design specs and lays the variances out in a side-by-side table, reclaiming over an hour per submittal review.
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.