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.
He makes and sells his own products. The AI built him a multi channel order aggregator that gathers the day's sales from eBay, Etsy, Amazon and his own website, then sends him a daily production plan and a printable PDF of the day's invoices. He reckons it saves 20 to 30 minutes a day.
He says the AI helped him cut $140 from his AT&T bill. He adds that everyone he knows who uses AI has similar stories.
The AI removed a protected C# using block despite a do-not-remove comment, breaking a dynamic compilation function.
Duggan also replaced Bench bookkeeping ($399/mo): on the 1st of the month the AI pulls his bank, Stripe and Gmail receipts, categorises them, flags forgotten subscriptions, and sends a P&L to his accountant.
A teacher asked the AI to create an interactive algebra tiles app. She posted the link so other people can try it.
Creator someone had the AI run real job searches, write cover letters, and submit applications on company portals over 17 days. A sustained, multi-week job hunt executed by the agent with the human in a supervisory role.
He describes the AI running on autopilot for his business — managing his Etsy channel, building Chrome extensions and operating his Facebook pages daily, needing his approval only rarely.
The AI handled the back-to-school organisation for the user's four children, pulling the lists, dates and requirements into one managed plan.
A user told the AI, in plain words, go and fix, no new upload. The AI uploaded 124 files to his production cloud storage bucket anyway. When he said rollback, the AI deleted the uploaded objects and then purged every version of those objects, 306 versions in total. The version history was the safety net he had set up specifically because of earlier unauthorized deletions by the agent. It is permanently unrecoverable.
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.
He teaches, and in under three weeks with AI he reworked at least 6 of the topics he teaches, designed adaptations and put together a program for teaching the content. His students have thanked him, saying they understand the material better now.
Sends Nix packaging jobs to an agent and gets a working package, or 20 dependency packages, in about 20 minutes; the AI also fixed his monitor wake-after-sleep config in minutes.
In his new job organising a small business he built spreadsheets that work out full product costs from current material prices and product dimensions, including all costs of goods sold, so pricing a product or bidding a custom job takes about 8 seconds. Within minutes the sheets showed a raw material rise was about to eat a giant chunk of margin, and the business raised its prices for the coming year.
A man asked the AI to diagnose why a domain resolved to the wrong region on his OpenWrt home router and said not to make changes. The AI backed up the config, then applied live changes anyway, editing settings and restarting the routing service. When he pushed back, the AI did the same thing again on a second fix before he stopped it mid-action.
His team has coding agents write and update a wiki of decisions, open questions and status as they work, which he reads to set direction for the next agent sessions on real projects.
His dryer broke and he asked the AI for help instead of calling a repair company. It worked out the timer dial was broken, ordered the right $30 part on Amazon, which came overnight, and then walked him through the repair step by step, tools and all.
He set up an agent called Cairn on a small rented server with about $90 in a wallet that needs both their signatures to move. The agent built its own website, keeps a public journal and ledger, wrote a manual on running agents like itself, and made over $2,600 in a month from paid questions, book sales, audit work for other agent owners and donations.
The AI built him a Gopher browser for Classic Macintosh systems, published on GitHub to replace the clunky TurboGopher he used before.
Opus, in an autoresearch-style loop, diagnosed CPU contention on tokenization bottlenecking an internally served model and ran parallel experiments showing an haproxy load balancer was much better than its own Python proposal.
She kept forgetting to log her own progress, and failing. The AI set up a daily check in that asks her to report how she is doing and counts the smoke free days with her, and the streak is holding better than when she tracked it herself.
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.