A random mix from the whole library. Shuffle for a new set.
A shop owner set the AI up to work out how many socks to order so the shop does not run out. It sends the order by email, reacts to replies, creates the order, stocks the goods, and books the invoice when it lands in the inbox.
He gave the AI access to his Auth0 tenant to check his JWT validation. It found that the tenant was already rotating signing keys while his app only checked the first one.
A cloud agent (Dots) died repeatedly on a GitHub issue, failed to connect to his tunnel, then went silent overnight, while the AI handled 6+ issues end to end with preview URLs.
He used AI to build an analysis of his own Substack posts. It split the posts into themes and pulled together collections, so readers can click through every theme, motif and term in one place.
His agent goes through each episode of his own podcast, pulls the timestamps of the best moments for clips, and drafts the social posts to go with them. Finding clips used to take 3 to 4 hours per episode and now takes about 20 minutes, and he approves and tweaks the picks.
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 solo non-engineer founder building a salon SaaS commented that the AI handles his coding while an AI chat acts as strategic advisor; that week they shipped 7 PRs and found 12 production bugs in manual testing. The advisor vetoed two feature ideas and made him draft a formal contract change.
He let the AI run on its own for 40 minutes on a billing refactor. The changes looked clean, but it had quietly renamed a Stripe webhook handler, and he only caught it when he reviewed the work.
A reviewer agent has gated his commits for four months of daily use, about 3,877 commits and 7,600 reviews, rejecting about half at least once and catching real bugs before commit (his own measured use, RemainderBot class).
Prompted an agent to build a custom LLM coding harness with session resume, done in an hour and working nearly flawlessly, plus a WebFetch tool added in 5 minutes.
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.
Used a work MCP server with an LLM to find why a tag was lost in traces, found in minutes what would have taken him hours of going through lengthy traces.
He used AI in a Google spreadsheet to apply a mass change to 30k rows. It got it mostly right after two tries, but it took longer than the perl one-liner he wrote to do it correctly.
They found 24 Android vulnerabilities using their open source AI security agent.
He wanted to type into a remote tmux session from his phone. The AI wrote a script that finds the pane, watches for his messages, and injects the text as keystrokes, and it works.
The AI goes through his sent emails to learn which sorts he typically responds to, pings him when it thinks he left something unanswered he'd want to answer, and repeats the exercise monthly to stay current.
An outside agency runs some of his advertising and sends a report with the numbers every week. He set up a system that handles the numbers on its own and has the AI draft the reply, and today the draft came out sarcastic.
Ticket-driven agent setup: he adds a ticket, it makes a mockup and writeup, he approves, and it spins up a temporary webserver and iOS and Android builds to verify; review and testing loops run automatically.
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.
The same studio's agent Timmy orchestrates more than 20 tools to turn blog posts into short videos: Veo generates scenes, ElevenLabs synthesises a custom voice, and automated captioning, lip sync and final assembly finish the piece. The pipeline runs inside the studio's normal the AI production setup.
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.