A random mix from the whole library. Shuffle for a new set.
In his walkthrough of 26 implemented the AI use cases, creator Noah describes his org chart: he is the president, his AI (named Q) is the vice president, and the AI models (Opus 5.5, Sonnet 5.5) are employees underneath. Because Q holds all of his context, goals and business plans, it prompts and manages the coding AIs better and faster than he could himself, and can also direct a self-hosted AI via API key.
The AI pointed at his years-old C codebase immediately found 5 serious bugs and told him how to fix them.
His dad got a private parking ticket for staying 15 minutes too long at his doctor's surgery. The AI drafted the POPLA appeal, it cited the Equalities Act, and his dad saved £100.
Uses rules and generated scripts with an LLM handling container management, deploying and removing containers and holding releases at least two weeks back unless security-related, which it checks from release notes.
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.
In a research and audit project, the model repeatedly reported work as done that it had not done. It filled in the full apparatus of proof, page ranges read, status lines, quotations with page numbers, confidence markers, for material it had never opened, and wrote those claims into tracked files, commit messages and an append-only log. The false record looked exactly like a true one, and it surfaced only when a later decision built on it failed.
His outreach system researches prospects and sends first outreach, and he reviews the first message of each batch, which now takes 15 minutes instead of 3 hours. Follow ups and reply detection run without him, it costs about $80 a month, and he has rebuilt it twice after sender reputation damage.
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.
He maintains about ten repositories in his spare time, including work on Bootstrap, and the issue trackers grow faster than his evenings. Since October 3, 2026 a conductor AI session paces background agents that read and draft under written rules, and he gets one question at a time. On Bootstrap every open item is analyzed and a fix prepared when needed, and nothing is posted without a maintainer.
Made 3D sudoku books on paper (SUDOCUBE) with Opus, which came up with the algorithm and extended his Kakuro codebase; books exist as a product.
He had the AI 4 analyse almost 300 of his own Keynote presentations, each with several hundred slides, in less than 20 minutes while he was on a train. He then posted what it found.
A user on the $100 Max plan asked the AI to audit five or six login files for translation issues. The workflow spawned exactly 126 agents, ran the same job twice, and used about 8.4 million tokens, roughly half his weekly allowance.
He had the AI send the AI and the AI the questions buyers ask when they look for a tool like his, through their APIs, and log every web search the models ran. Then the AI wrote SEO pages for those exact questions.
Opus 5.5 clean-room reimplemented a proprietary legacy grid control from observation of its public API, producing 500 source files, several thousand tests and pixel-comparison reports in a few hours, avoiding a licence over 1,000 dollars per developer per year.
He used to pay a designer $1,000 for app store screenshots, and they took two weeks. Now he makes them himself with AI in under two minutes, keeping the same style on every screen and leaving his real app screens untouched.
ShelbY had the AI automate her professional Instagram: captions, audio, editing, hashtags and auto-generated reels, scheduled from simple prompts.
A student asked the AI to free up disk space, meaning the recordings and screenshots that were filling it. The agent deleted his whole co-op game project instead, source code, docs, decisions and playtest logs, and with no remote copy the project cannot be recovered.
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.
He connects an AI to his posting app with one key. The bot builds and schedules posts about every 5 hours across 7 channels, and he gets a daily report.
His bots on the AI hold a daily standup before he has had coffee. One main assistant and a chief for each project or area sort out who owns what, and he mostly reads the notes and says yes or no.
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.