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Your place, your car and your pets · 265 ideas

My agent called tire shops for swap quotes and brought back transcripts

He needed quotes for a seasonal tire swap, with the winter set already on rims, and did not want a day of phone tag. He connected the AI to a calling service with a script: price with tax, proper lifting pucks for his car, torque to spec at 175 Nm, and openings after mid November. The first call failed because the shop asked where he was and the agent had no answer. The callback with his area in the intro worked: $120 plus tax, pucks and torque confirmed. Other calls came back at $50 tax in for a mobile service and $168 plus tax, and one went to voicemail. Every call produced a full transcript. He then set 18 more shop calls for the next day and updated all of them at once with four facts he had missed the first time.

A physician photographed his whole house into an insurance ready inventory for $6

He is a physician, not a coder. He built a home inventory app where the AI reads each photo and records the item name, brand, model and serial number from labels, then looks up current replacement prices. Photos and receipts back up to the family Google Drive, and the app produces an insurance ready PDF. The whole house cost about $6 in AI charges.

$6one time

Run my living-room lights and fans from an ESP32

A hobbyist says the AI assembled the firmware running his living-room lights and fans: an ESP32 web server driving a radio transmitter. It also built him a Streamlit app to explore the signals, and the code is public on GitHub.

My TV app took 30 seconds to open, so I reverse engineered the TV and built my own

His 2019 LG TV has a great screen, but the official Plex app took about 30 seconds just to show the profile picker, because it is really a web page. There is no public native toolkit for the TV, so he rooted a spare set, read the TVs own software with analysis tools and the AI, and built a native Plex client of his own. On the same TV it shows the profile picker in about 3 seconds.

An AI agent wrote the firmware and CAD for my radar stair light over four weeks

Over four weeks of evenings, an AI agent wrote the firmware, the live web chart, the Node-RED automation and the enclosure CAD for his radar stair light, driving a live Fusion 360 session through its scripting API. He reviewed, printed and measured, and the second half of the video lists what the agent got confidently wrong, including a radome gap that landed on exactly a quarter wavelength.

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Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.