A random mix from the whole library. Shuffle for a new set.
A high school student sent his study guide PDF to the AI and had it build a website with a quiz style practice interface using the guide's own questions. He says it works well and beats making practice sets by hand when time is short.
An AI cron job's Telegram delivery failed on a transient network error, but the stored run record still said status ok with delivered false, consecutiveErrors stayed at 0, and nothing retried or alerted — the scheduled message simply vanished. The failure was only visible by digging into the run diagnostics; anyone watching the chat or the job's status saw a healthy run.
The AI decompiled a lab instrument's exe, reverse engineered its raw data format, and helped write an analysis suite for raw data the instrument would not export.
Worked weeks on an AI-generated, human-guided proof of Hilbert-Smith with a complete 100k LOC Lean4 formalization, rushed out after OpenAI's release.
Over the weekend he had the AI set up a daemon on his Mac mini that syncs all of his Mastodon posts to his Obsidian vault. Now he can search his own posts on all of his devices.
A writer had the AI read more than 1,000 of his Apple Notes from 2016 to today — letters, journals and dream logs — and build a private local site mapping the ideas he keeps returning to. It also produced a model of his writing voice and a query tool to ask new questions at lower token cost.
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.
A personal blogger gave the AI one of four life goals that wasn't progressing and it evolved into a daily morning action list of readings, videos, questions and assignments. She then had it converted into a checkable checklist so she can track progress and stay accountable day to day.
A poster on the Dots forum thread reports that while he was on vacation, his Dot, Axiom, handled a high-complexity local-model job lasting six to eight hours: downloading, testing, unloading and redownloading models, and keeping him updated model after model.
The AI ran a protein-design pipeline at home on a 5090, chose similar tooling, and generated about 100 trajectories running 24 hours.
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.