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.
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.
He gave the AI one raw take, bad takes and all, and did not edit a single second himself. The AI did the color grade, the titles, and captions on every word.
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.
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.
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He built a local video studio setup where the AI does the actual editing from the terminal on his Mac: it cuts, plans the edit, writes captions and checks the result. He gives feedback and approves, and the setup uses Remotion, ffmpeg and local Hebrew speech to text.
His VP of engineering reviewed two or three strategy tools on the market and they were prohibitively expensive, so he asked if it could be built instead. He built it alone in less than a month: long term objectives broken down into annual objectives, improvement priorities, projects, milestones and tasks, with bowler charts tracking the KPIs, full project management tools, and containerized staging, development and production environments. It cost roughly $1,000 to $2,000 in an AI app credits. The VP then put his own name all over it, and made him replace his own name in the about section with the name of the organization.
A man wired his lab instruments to his home network, put all their manuals and programming guides into an AI project, and the AI wrote most of the first set of Python programs that control the instruments and pull data from them. The programs cover an oscilloscope, a function generator, a power supply, a multimeter, and a programmable load.