A random mix from the whole library. Shuffle for a new set.
Gave the AI sudo on his dev machine: it commits, pushes, checks pre-push test results, deploys as another user, checks smoke tests, and adjusts the Cloudflare pipeline and environment variables.
An agent on GPT-5.6-Terra read a webpage sentence about creating GitHub issues and derailed into creating issues using his context.
Creator Lyndsey King says she used AI to create a single $37 PDF in 47 minutes: eight buyers brought in $296 the first night, and she reports total sales approaching $40,000, a shift from the $500–$600 courses she used to sell.
His Pi agent uses a Clojure nREPL extension to modify and reload code and rerun tests, organized the subsystems in his repo into Integrant systems, and compiles, watches and serves CLJS apps when instructed.
A husband runs an AI job hunt for his wife: the bot works 11 searches across 84 listings and sends a 7:30am digest, and she approves applications with one-word replies. The search runs daily without either of them opening a job board.
A portfolio advisory firm says the algorithm inside the Portfolio Optimizer on its website - built through multiple iterations with AI's agents for structuring equity portfolios - would not have been possible without them, and would have cost upwards of $100,000 to build the conventional way.
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.
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.
The AI runs a daily reply-opportunity scan across forums and a daily SEO keyword and content-gap research report for his app.
Gave the AI a Java RISC-V emulator and a partial libc bridge, and in under an hour it could run bash and sqlite from Debian.
He did not know how to make Eclipse plugins, so he had the AI make one that highlights and type checks jOOQ’s own tag syntax. It took a single prompt, and the plugin already works.
12 hours with AI Fable 5.1 was a disaster, it created 20+ bugs, failed to test the fixes, and built every new feature on a minimal basis.
A GPT agent crunched through a famously hard Disobey conference hacker ticket challenge in an evening and a morning with occasional steering, a challenge unsolved in some years.
During a flash sale on his petals.team site he checked analytics and found zero events, ever, because PostHog had never been added. Through the PostHog MCP connector in an AI chat he spotted, diagnosed and fixed it, saved a 3 step registration funnel, and set a weekly digest to land in Slack every Thursday.
Vibe-coded SimilaritiesEngine in two months with AI, a free service he says would have taken three years and would never have been done otherwise.
The AI flagged a job applicant PDF with hidden white on white text meant to manipulate AI screening, in his own hiring.
A user asked the AI to build a multi-agent outreach pipeline. The code it generated retried failed calls forever, re-billing the most expensive call in the system on every run. The spending guard it wrote only slowed spending down instead of stopping it, and the daily ceiling it picked reset every day, so the charges accumulated to roughly $50 of unintended OpenAI usage before he noticed.
Built a local Qwen system on every employee machine that watches folders, checks files against company and legal rules, and mails or dashboards feedback in about 20 minutes.
He records raw video, sends it to his Mac, and the AI cuts the bad takes and adds captions and graphics using a skill he made. He says he does not open a video editor anymore.
A Korean author writing a book about AI describes using AI every day (he nicknamed the agent 'San'): it polishes his manuscript drafts, searches his mail, checks flight prices daily, and proactively picks out the one message in thirty that he really needs to read, working under his own identity with broad standing permissions. Testing OpenAI Dots alongside, he found Dots identifies itself as an AI in every conversation and asks for confirmation at every registration or approval step, which felt safer but often needlessly slow by comparison.
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.