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.
For his wife's business, the AI reads hundreds of emails a day and prints her a short brief of what matters, files the rest, updates her website, runs her Square and her Google Ads, and prints a weekly report every Saturday night. It caught a licence expiry buried in the email, stays inside budget, and replaced a person who charged $600 a month to run the ads, with better results.
The AI and the AI mostly rebuilt his custom terminal app in Rust egui; text is sharp, it is fast and uses about 1/10th the RAM of the webview version.
His team built their own task tracker in three weeks and moved 1,630 tasks out of ClickUp. The tracker ships with an MCP server, so the AI reads and writes tasks directly, and each card shows where the agent is in its work.
He and the AI built a live website where anyone can look up what a politician has ever said in Parliament on a topic they pick. He calls it a moral manoeuvrability monitor.
Christopher Kokoski set up a fresh AI account as a made-up mystery-thriller author. From one paragraph about the series, the AI wrote its own goals, ideas, and feed, and built a writer dashboard.
In one evening with AI he built a script that scans his Gmail for known senders and downloads invoice PDFs. If a supplier sent no PDF, it saves the email itself as a PDF, puts everything together for the office, and logs what it downloaded and sent so nothing goes twice.
Set the AI the task of running Parseable locally against another of his apps; it worked around a protobuf limitation by running a proxy, he switched his stack to JSON and got it running.
Aggie Lal (verified, 1.7M followers), a mom, asked her AI 'Munchkin' to process her ~14,000 saved Instagram posts. The AI identified themes (high-protein recipes, parenting, postpartum recovery) and generated organized PDFs: 'Saved Recipes' (Protein Power Bowls, Cottage Cheese Everything, crediting original creators) and 'Parenting Tips'.
A non technical founder, who spent 25 years in banking, has six AI agents running his small business magazine: a CEO agent, trend scout, researcher, writer, SEO agent and publishing agent. He has caught real errors, including a sales agent that wrote a full report for a fake email address and a CEO agent that burned money by waking up too often.
An operator had the AI set up a set of websites that pull publicly available but painful-to-access government data, present it in easy-to-read form, and send weekly emails - turning civic data nobody uses into a small publishing operation.
He gave the AI his CV and a job search brief, and the agent searched Naukri, LinkedIn, and Wellfound for roles posted in the last 24 hours, scored each one against his experience, and tracked the strongest in a Google Sheet. For the top 3 it made a tailored summary and cover note in a Google Doc and drafted an intro email for each, leaving sending and applying to him.
Creator took on a $30/week family-of-4 budget challenge with AI, asking it to start from what she already had in her pantry. The AI produced 7 dinner ideas, a grocery list, and a price comparison; her Walmart haul came to $29.66, under budget.
Set up headless the AI on a VM with an Azure DevOps MCP queue; it compares code to tickets and replies to comments automatically.
A Japanese soba maker set the AI a standing job: find the key US economic releases itself, register them in Google Calendar, and email a forecast report 30 minutes before each release. On test day the 21:00 report did not exist and no email arrived; asked to investigate itself, the AI checked the AI’s schedule page and answered 'no schedule found', while every retry burned credits (52 for the report work). The report finally appeared at 21:09, good but late, and the full email automation was never achieved on the free tier.
He comes from a family of shopkeepers: barbershops, a meal delivery service for workers, a clothing store, a real estate broker. Every business had its own paid ERP and none of them fit. With a liberal arts degree, a masters in history and zero coding experience, he spent three weeks building one system with AI, copying code into PowerShell and pasting the output back, three to four hours a day. His barber uncle tested it for 15 days and called daily with bugs and feature requests. Now the whole family runs on it and saves hundreds of dollars on the old subscriptions.
The AI agy hooked itself to Discord, set up and troubleshoots SSH servers on his home network, commands it remotely.
The AI files his detailed bug reports and his agent pulls the project's new changes daily to check whether his issue is fixed.
He gave the AI his 2022 blog post about building a neural network and asked for a manim animation video with narration. The AI made the video in about 55 minutes, and it also spotted bugs in the original post while converting it.
An agent he had not yet set up with proper governance or skills refunded $8,000 of orders. It did ask 'You sure?' before acting, but he blanked on the confirmation and approved it. He puts the fault on his own setup more than on the agent.
He normally develops his astro photos in Siril. This time he handed the AI the raw stacked FITS file straight off his Seestar S50 and asked for three things only: flatten the background gradient, remove the noise, and stretch the image to bring out the spiral structure.
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.