X user someone (Charlie) gave the AI inbox access at the start of a deep personal-data experiment. In one of the standout moments, the agent surfaced an important message he had missed, drafted a response, co-edited it with him, and sent it — an agentic loop (find, draft, revise, send) rather than a one-shot draft.
Eleanor Konik writes that she hates requesting books through the county library website, so she told the AI to find books about chess aimed at a bright 6-year-old; the AI picked titles and requested them using her library account. A few days later the county emailed that the books were available, and she picked them up (her post also shares an AI invite code).
Unite.AI reports Anthropic's October 16 research post: The AI Mythos 5, working in a closed loop with an automated evaluator and no human input between rounds, designed quantum circuits improving on the best published designs across eight computational primitives. One run took 53 hours to produce a new reversible modular-inversion approach using 17x fewer gates; a companion paper was submitted to arXiv on October 15.
Scheduled the AI connected to his calendar and inbox notices email that should change the schedule, tells him, and automatically schedules and reschedules items emailed to himself.
A Halloween fan fitted two small screens and a radar chip into a Home Depot skull so the eyes follow people as they walk past. The AI wrote the code for the ESP32 board, and he posted the parts list and the code so anyone can build the same thing.
An agent he had not yet set up with proper governance or skills refunded $8,000 of orders. It did ask 'You sure?' before acting, but he blanked on the confirmation and approved it. He puts the fault on his own setup more than on the agent.
$8,000one time
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Asked what else it should do, Kicker used a team-meeting transcript to draft the follow-up meeting agenda and created a prep document for a panel Newton was moderating that weekend. Both artifacts were produced proactively from existing context.
An engineer at Sumasate writes that his team connected the AI Tag to GitHub, Sentry, their database, log tools and Notion, and let it do the first look at every alert in Slack. After three months, fixes finished inside alert handling went from about 2 of 38 alerts a month (5.3 percent) to about 7 of 44 (15.9 percent).