Peter Yang gave the AI Duet one short request and a link to his YouTube channel. Duet pulled a year of his published videos and their public data and built a report with charts, which found that personal AI agent videos are his breakout topic and that his solo videos now beat his guest videos unless the guest shows a real demo.
Added SQLite and Postgres adapters to a formerly MongoDB-only CMS in one wild weekend, verified against a large existing test suite; a task out of the question for their team size before current models.
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.
$50at stake
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A developer tired of managing terminal windows one way and other windows another way grew his own replacement with AI over the course of a few months, one that treats graphical apps as part of the session too. He uses it now and says he has never looked back.
Creator Amie Tollefsrud gave the AI access to her Instagram analytics and asked for growth advice; after three clarifying questions about audience and positioning, the AI delivered an 'Instagram Growth Plan' PDF. Screen recordings show an executive diagnosis (1.85M accounts reached), audience positioning, four content pillars, keyword clusters, carousel and story blueprints, and a 7-day action checklist.
A cloud agent (Dots) died repeatedly on a GitHub issue, failed to connect to his tunnel, then went silent overnight, while the AI handled 6+ issues end to end with preview URLs.
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Several parallel AI agent sessions (Opus 5.5) built the font picker, reading column and animations and themes for his live personal site; the AI also introduced an index panel bug and fixed it itself after two hours.
Editing his own audio meant cutting out every breath by hand. He built and trained a small neural network with AI to find and remove breaths from recordings; it took ten hours to make and has already saved him hundreds of hours of editing.