A random mix from the whole library. Shuffle for a new set.
He had the AI transcribe more than 70,000 images of old documents in two days, for $380 in total. The handwriting and worn pages hurt the quality and it did worse in Portuguese than in English, but the AI handled the whole run.
He wanted to type into a remote tmux session from his phone. The AI wrote a script that finds the pane, watches for his messages, and injects the text as keystrokes, and it works.
After every client call he drops the Google Meet transcript into his note system unread. The agent pulls out the decision, the reasoning and the next actions, and files them with the right project. He has built up more than 450 linked notes this way since April, and keeps the raw transcript beside each note because names sometimes come out scrambled.
Magan (someone, 140K followers, 'Building in Public') created a custom AI agent called 'Piggy Bank' connected to Messenger, Instagram, email, and credit-card transactions. It scans sources to find all subscriptions (which she can cancel), reads Instagram DM chat history to track brand-deal payments, and generates a ledger showing how much she's owed, plus spending insights and payment reminders.
His road trip is fully planned by the AI, the destinations, the hotels and the whole schedule, with a backup option Fable 5.1 found in case the Badlands roads are rough. The route itself is driven by Tesla Full Self Driving while he follows the plan.
A user had the AI apply TurboQuant skills to optimise a Qwen3.5-9B model running locally via MLX on Apple Silicon. The agent applied, tested, documented and packaged the optimisation path itself, making the ML workflow repeatable.
LLM audited about 100k lines of tests, deleted about 60k useless lines, wrote broader scenario tests, and caught and fixed bugs, in about 2 hours.
When the tool he wanted was not on the AI’s connector list, he had the AI build the link itself. The AI took his Linear API key into secure storage, built a connector that can list teams, search and create issues and update their status, then checked it worked with an identity check. He says the same route works for any service with an API.
The AI automated porting business software from QuickBASIC on DOS to Tcl on Linux, usually right first try, to add features management needed.
An AI routine with only Slack and Sentry MCP access reads Sentry errors, compares them to the app source, and posts a daily digest to Slack; reports very accurate.
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.