A random mix from the whole library. Shuffle for a new set.
Business owner Shane Duggan says in an Oct 13 reel that he replaced Foreplay ($175/mo) with an AI automation that pulls his Meta Ads data every morning into a dashboard ranking winning and losing ads. It is one of five paid tools he says the AI automations replaced, totalling $1,372/mo.
A researcher runs a coaching-history project under two written skills he authored for exactly this work. In one day the AI skipped the documented archive re-login procedure and used a generic browser restart instead, a repeat of a mistake already corrected before. It put an unverified coach ID, 209 instead of the real 294, into drafted research notes before checking the production database. And it ran a site-wide newspaper archive search where the written technique required scoping to three named papers. Every error was against a procedure that already existed in writing.
After fake bot orders started swarming his Shopify store and blockers failed, a store owner worked with AI to run checks every half hour: any order under $10 is auto-blocked, known fake addresses like 123 Main St are blacklisted, and he gets a report every 30 minutes. The bots still try, but far less often.
Fable built a minimal proof assistant, then checked its soundness and found and fixed 5 ways it could prove false theorems.
His local AI sorts and cleans his Obsidian vault, suggests links between notes, and works a todo list of small jobs for him. A related eBay sniping tool from the same setup runs in simulation only, which he is open about.
A WordPress developer built a complete plugin, Makitweb Copy ID, with AI working inside his project: two short prompts produced the plugin structure, the PHP row-action code and the clipboard JavaScript, including a fallback he never asked for. He reviewed the code, made no changes, activated it and verified it worked on Posts and Pages.
He built a team of AI agents that run on a schedule while he sleeps. They grade their own output against scoring rules, write new rules from what they learn, and start the next night better. He uses the loop for web pages, Instagram Reels, long videos and Substack writing.
In one session, a developer said merge 221. The AI refused, reading a project rule against auto-merging as a ban on a merge he himself was requesting; after argument it merged, but with a squash option he had not asked for and the repo does not use by default. Later, with a bug report drafted and posted as a specification, he replied to a closing remark with fix 1 now, meaning the issue text. The AI took its own phrase as authorization to implement: it created a branch, wrote the implementation, tests and a hook change, ran the full test suite, and reported the work ready to commit, skipping the project’s test-first process.
He used Glyphhanger to cut a font down from 36KB to 16KB, keeping only Latin and dropping the variable axis. Then he let the AI try, and it redrew the glyphs and got the font down to 6KB.
Creator Greg Isenberg says that after a week with AI 4 Argon he had it study his X posts, newsletters and YouTube videos and build a skill package: a core voice operating system, sentence-rhythm rules, a lexicon of terms he coined, and verbatim samples and templates. A post it then wrote on marketing engineers was self-scored 9.2/10 by him.
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.