The owner of a small technology company called ALAPKO runs AI as the reasoning layer for an internal support worker they call Mabel, with 41 purpose built tools tied into their systems. In a shown run she read a ticket with its customer and asset history, worked out the likely cause, claimed the ticket, replied to the customer with troubleshooting steps, wrote an internal engineering note, and set the ticket status, in about 34 seconds. Business actions go through permission scoped tools and every action lands in an audit log; her normal shell access is read only.
A perpetual the AI thread in his llama.cpp checkout periodically sweeps PRs and research, rebuilds llama.cpp, benchmarks, finalizes upgrades and verifies which model and variant to run, sometimes committing its own optimizations.
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.
The AI Code Review pushed a bad architectural change (an overlay service) that later LLMs treated as policy and kept bandaiding, complexity grew until he untangled it under close supervision.
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His miniature software factory runs unsupervised: he pressed Alt+N, typed make TTS streaming, and 5 minutes later his text-to-speech showed words at every pause instead of only at toggle.
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.
Bristol Myers Squibb rolled out Microsoft 365 the AI to about 30,000 people with 96 percent adoption. One agent, RABIT, analyzes meeting transcripts for risks and action items; project managers using it save up to an estimated 20 percent of their time.