A new 3D printing fan who did not want to learn the software first had the AI help pick a printer it could drive through its API, then build a small home server between the AI and the machine. He can say find me a phone stand: it searches a model library, slices the file, shows time, grams and cost, and prints only after he says yes. It will not start if the loaded filament does not match the slice, and it sends phone alerts with a first layer photo and buttons to resume or cancel. His partner can request prints through a chat page, which he approves. A firmware update broke the camera setup and the AI found and fixed it.
For a few weeks he has had the AI take over his cursor, open Clip Studio, and put the words on his comics. He still makes small fixes himself, and it saves him real time on the dull part of the work.
A musician in a home studio asked the AI to search his Instagram followers and follows for musicians active in the past year, select two songs per musician, and compile them into a YouTube playlist. The agent succeeded, creating a 6+ hour 'Community Listening' playlist — music mostly new to him from his own network.
Sid Saladi documents a two-week experiment: after a 20-minute sort of his to-do list into DO, DRAFT, REMIND or GOAL, the AI ran it with a morning plan, an evening digest and a Friday sweep — including checking his inbox every morning for a refund email that had sat red for three weeks. In week one, when the list was mostly things the AI could do, it finished 7 items; in week two it finished 0, which he attributes to the list's mix, not the agent.
This only partly worked. Worth knowing before you try it.
A teacher built his own LMS layer on top of Google Classroom using AI and Apps Script (he names the AI and the AI as both able to drive it): far deeper grading features than Classroom offers, a quick-select comment bank where any feedback he writes can be saved for reuse with one click, and on return each student automatically gets a formatted read-only feedback document both emailed to them and attached to the Classroom assignment. Student data never leaves the district's Google ecosystem.
TP-Link has no official way for an agent to control its Tapo devices, so he took the app apart, worked out how it talks to the lights, plugs, sensors and cameras on his home network, and built a connector the AI can use. The AI now runs his house, and even drafts a floor plan from the device names that becomes a live 3D map: doors open in the model when the real sensor opens, and tapping a camera plays its video after a privacy check.
A man who self hosts an XMPP chat server had audio and video calls that worked only sometimes. He gave an agent access to his phone over ADB and to the server logs, and within 30 minutes the problem was clear: a setting for STUN and TURN discovery had been missed in an earlier move, so clients behind home routers could not connect. The fix was deployed.
Jafett Altamirano describes the AI’s actions over two days: one day the AI recovered $60 owed by Google by submitting a claim, audited and corrected a family-tree project (removing errors, adding documents and a generational link), and reduced an unread Gmail inbox from 65,000+ to 700. The author emphasizes all of this was free.
A developer cleared his AI session. Immediately after, a scheduled task left over from earlier testing fired on its own: re-run a camera test scenario on his connected Android phone. With no new instruction from him, the AI found the device tools, force-stopped and relaunched his app, opened the camera, took a real photo, and kept navigating screens until he noticed and stopped it.
This one went wrong. See what happened before you try it.
In the same test, he connected Gmail, Google Sheets, and Google Drive; the AI responded to his emails and performed tasks autonomously on its own server even while his laptop was turned off.