A random mix from the whole library. Shuffle for a new set.
A researcher wrote the Lean statement of a theorem himself, then fed the published paper to the AI and had it write the proof. It finished in a couple of hours, and the Lean kernel verified the proof.
An LLM performance-tuned his Godot voxel game over 3 days, taking it from 12 fps to 60 fps with diagnostics and render changes.
Amanda (wife, cheer mom, WFH) used her agent 'Azalea' to plan her week: work Mon-Fri 9am-4:30pm, daughter's cheer practice Mon/Wed/Thu/Fri 7-8:30pm, two content pieces to record, and a goal to cook at home. Azalea generated a detailed weekly plan with workout slots and dinner times, then added events directly to her phone calendar with permission (e.g., a Sunday 11am-12pm workout).
A professor took the PID control demo from his own book and had the AI build it as an eight mission 3D flying game for his students. Students predict what the drone will do before each flight, and he checked every mission against his book version before it went live.
Keeps his Namecheap API key on his server so every time he buys a domain he tells his AI agent to SSH in and set everything up.
His Ubiquiti access points are full of firmware bugs. Scripts from the AI collected dozens of gigabytes of logs for his support cases, and Ubiquiti's engineers confirmed the bugs, but six months later they still cannot fix them and he only gets weekly updates.
Agents found sources, produced summaries, and helped build murder-stones.org, a catalogue site for his own historical research.
A man built a chat copilot inside Blender in a day, at a total cost of $7.18, then gave it 5 sentences. In 15 minutes and 52 tool calls it built a spaceship with swept wings, a glass canopy, 4 sets of steering thrusters, and 22 exhaust flames, with a full flight animation. On its own it checked every thruster, found the rear ones firing into the side of the ship, moved them to the wingtips angled outward, and checked them again.
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.
Had an AI go through a book of 200 year old religious records and pick out references to possible ancestors.
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.