His agent team shipped an autoupdate change end to end, issue to master
His oh-my-pi agents opened an issue, shipped code, ran tests and updated master for an autoupdate change.
Real things everyday people got it to do, and how to try them yourself.
A random mix from the whole library. Shuffle for a new set.
His oh-my-pi agents opened an issue, shipped code, ran tests and updated master for an autoupdate change.
An AI-designed split keyboard, built and now on his desk.
Abraham Gerving runs two small gyms on a key card model, staffed only part of the day. About a year ago he put an AI agent on member messages and calls: it schedules tours, books consultations, and points new members toward personal training, and some people who started out chatting with it became long term training clients.
The AI ported about 7 classic 68k Mac games, writing its own 68k disassembly tools.
With the help of the AI, ported the current dev branch of Qt6 back to Windows XP with working OpenGL.
Michelle Solomon (recipes/homemaking, 9.5K) typed her weekly meal plan for four into AI, which returned a consolidated grocery list organized by produce, meat/seafood, etc., keeping the total under $200 using store-brand picks. She approved the AI logging into her grocery account; the groceries arrived and she cooked glazed chicken breasts.
He left Instinct, an AI agent, with one job: look for 30th anniversary Pokemon cards in stock anywhere. It sits in the background and alerts him to places that have stock.
He ran an extensive audit of his Datasette software using AI Fable 5.1, GPT-5.6 Sol and GPT-6 Astra, then fixed a range of bugs the audit found. The fixes went out as the Datasette 1.0a39 and 0.65.4 security releases, and he told anyone running Datasette on a public website to upgrade.
A solo founder runs his game key store with about a dozen AI sessions, one each for code, pricing, copy, bookkeeping and suppliers. They stay in sync through a shared record where facts are only ever added, each fact says whether a session confirmed it or just read it somewhere, and his decisions go into a numbered ledger the sessions look up instead of asking him again.
Used nit-picking history-teacher agents to evaluate a few hundred generated stories for accuracy, and pointed the AI at HN comments to aggregate issues and fix them with his OK; reported issues mostly fixed.
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.