He had a few Windows machines left alongside his Macs, Linux machines and a large NAS. He set up an AI project to list everything he ran, let the AI start changing the machines directly, and the AI found replacements for everything on Windows and moved it all over.
Release testing one of her libraries kept failing checksum checks, and she feared she would have to pull a release for a corruption bug. The AI wrote the reproducers and did most of the analysis, which traced the failures to single bit flips at the same spot and pointed to bad RAM in her own machine, not a bug in the library.
Fable reverse engineered the Satisfactory blueprint file format and wrote a reader, a graph auditing tool, and a website; work that would have taken a couple of weeks by hand.
The reviewer set up a scheduled daily AI-news briefing in an AI app as a two-host podcast saved in the app's Library, with an RSS feed for following in a podcast app. It worked, though the newest episode shown was dated two days earlier, flagging a freshness caveat on daily generation.
Author Matt Deitke fed an entire book to the AI and had it generate a chapter-by-chapter podcast website, with subagents handling chapters in parallel. The output was a finished multi-episode podcast series derived from the book.
He is not a programmer, but he used AI to trace a bug through localization files, tech scripts and the game's internal category system. The AI hotfixed a deprecated modifier key in his Clausewitz engine mod, and he shipped a working patch in 30 minutes.
A home server owner had the AI study his running server and turn the setup into Ansible files, which they refined together until it worked. The AI also wrote a small tool that unlocks the server encrypted disk from another machine, which he now uses.