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.
In a screen-recorded demo, lifestyle creator Jenna Ricciardi's AI agent Glimmer canceled a subscription she had forgotten she was paying for, one of several delegated tasks shown in the reel.
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.
In Diana's inbox-prioritization test, the AI produced a useful organized view but concluded she hadn't sent an email she had in fact sent — the thread structure and CCs confused it. If she'd trusted the first answer, she'd have sent a duplicate email.
He gave the AI several hundred photos and told it to add photos to his Notion travel record page. It picked about 30, added them, and also made a route map from his GPX data.
Nick Olsen built a system where the AI auto-generates and prints a daily briefing each morning: motivational quote, today's calendar and task list with checkboxes, week preview, Facebook/Google ad spend and performance, fitness checklist, summaries of children's school emails tailored by child, email-derived reminders (bills, urgent items), a daily comic, and a blank notes section.
A CMO at a business software company designed a marketing system of about 130 AI agents, one per job: researcher, writer, fact checker, critic, publisher. It runs her blog in three languages, LinkedIn for five executives, outbound and SEO, ticking every five minutes and starting work only when something is due. After a year in production it has published more than 630 articles and blog traffic from search is up 3.9 times. Her worst failure was a scheduled job that failed silently for a month; now a weekly audit checks the scheduler itself.
The AI built him a file manager app for the Amiga's Workbench system. He says it is genuinely useful and powerful, with the best parts of Windows Explorer and OSX Finder.
Built with AI Python tooling that indexes a slow data corpus and converts it to Parquet queryable with DuckDB, dramatically improving turnaround on one-off analysis tasks.
He needed quotes for a seasonal tire swap, with the winter set already on rims, and did not want a day of phone tag. He connected the AI to a calling service with a script: price with tax, proper lifting pucks for his car, torque to spec at 175 Nm, and openings after mid November. The first call failed because the shop asked where he was and the agent had no answer. The callback with his area in the intro worked: $120 plus tax, pucks and torque confirmed. Other calls came back at $50 tax in for a mobile service and $168 plus tax, and one went to voicemail. Every call produced a full transcript. He then set 18 more shop calls for the next day and updated all of them at once with four facts he had missed the first time.
Used the AI to reverse-engineer a neural network accelerator in a Chinese WiFi camera SoC and implement an ONNX compiler and runtime, resulting in a working 20 dollar AI smart camera.
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.