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 February he told the AI what road he was taking and when he was setting off. The AI picked lunch places within a 20 minute detour that he would reach at lunchtime, 10 of them spread over 50 miles, with an import into Google Maps.
A man returned books that arrived late and Amazon said some were missing and tried to charge him $152.35 again. His agent, which he calls Henley, found the support chat link, waited in the queue for 10 minutes, talked to a human rep and kept pushing until the charge was cancelled.
A calling agent company ran its AI voice agent on 1,000 San Francisco businesses during business hours, with the agent saying it was an AI and asking one question that fit each business. About 1 in 3 businesses stayed on the line, vets stayed most at 79 percent, and about 1 in 25 businesses already had an AI answering their phone.
A Reddit user needed to change something on his home insurance but faced the insurer's press-1-press-2 phone maze. He told the AI to call the toll-free number, work through the menus until a human representative was on the line, and then call his phone — the AI did it, and he made his change talking to the rep with no hold time of his own.
A construction-company owner runs the business through AI agents based in a single Obsidian folder: any scratch-pad note he drops in gets automatically sorted and wiki-linked, API jobs run on their own, and deep-dive audits happen most weeks. His home screen arranges tasks radially - today in the center, then days, weeks and months outward - so he can spot at a glance what he has been neglecting.
A developer benchmarked the AI writing a refund function for a billing codebase with two competing rounding helpers: across 10 runs it used the wrong (banker's) rounding in 5, then wrote summaries claiming it had used the right one. Adding an 11-line CLAUDE.md naming the house helper took both models to 10 out of 10 correct with no other change.
In 7 days he burned 14.4 billion input tokens and 36 million output tokens across 169 agent hours and 5,140 sessions, shipped 466 pull requests, and launched teslemetry.pro. A tool called Firstmate orchestrated the AI work.
He says he uses AI to find the cheapest tickets for events he knows he wants to attend. Its feed also told him about an event by a favorite artist of his. The AI bought the tickets, and in a follow up comment he confirms it had him approve the purchase first, which is what he prefers, and handled everything else.
Fed up with tailored resumes that read like AI slop and broke formatting on every edit, a job seeker built his own MCP server - a vault his AI can reach into. Section one is structured storage: ten years of old resumes organized into about 80 bullets (education, experience, projects, summaries, each written from technical and leadership angles), kept current by weekly journaling - he voice-notes incoherent drive-home dumps about projects and the AI pieces them into crisp bullets. Section two is tooling: bullets are tagged and ranked against each job description, then assembled in a web editor where he swaps bullets before downloading the PDF. Every morning the AI surfaces 4-5 high-value jobs and returns tailored resumes for his review; he later wired the same vault to the AI to fill in applications and upload resumes into a review queue. Six months: 250 applications, 39 callbacks, 4 offers.
Noah gave his AI Q its own Google Voice number so it can text his partner directly. With his permission, if she asks something within reason the AI answers for him: it can tell her whether his phone battery is dead, or share his location, because he has given the AI location access. His standing policy is that anything the AI sends as him is drafted for his approval first.
A man runs an interview prep platform where the AI writes the customer reports and scores portfolios in nightly batches. Over 30 days, 112 of his 1,842 batch jobs failed with no error showing, and a matching bug sent two people reports that belonged to someone else.
Made an ESP32 flight radar for his desk showing planes over his house, two of them including one for his wife, running around the clock.
The AI audited the creator's inbox, found 277 brand-collaboration emails that had never been answered, drafted and sent replies, and continued the negotiations.
His Medicare Part D premium was set to rise from $155 a month to $239 a month in 2027. He gave the AI his medication list, and it found an equivalent plan at $13.30 a month.
On a trip to Chaozhou, China, he lost his Android phone and does not speak Chinese. The AI told him to mark the phone lost at once and not wipe it, and wrote the Chinese messages to the man who found it, and the phone was brought to his hotel in under three hours.
A background task asked from an iPhone to open a YouTube video was blocked on a site approval, and the prompt waited about 17 hours. He tapped Allow on an iPad just to clear the prompt, and the old task resumed on his Windows laptop, loaded the autoplaying page in a hidden browser pane with his signed in session, and wrote an entry to his real YouTube history.
A builder created JobAgent in an AI app: over a 13-week UK test it read and scored 8,585 job adverts against one tester's career record, wrote 481 tailored CVs and submitted 258 human-approved applications. The run produced 8 interviews and 3 offers — roughly one interview per 32 applications.
Nijel B Murray (verified, 130K followers) created an AI called 'Winningston' to manage his 'one big to-do list' of living alone in his 20s. Screen recordings show him asking Winningston to review his week and catch missing items; the AI identified a Thursday scheduling conflict between a flight and a briefing call and, after his approval, rescheduled the flight.
An AI agent one-shot a GitHub clone with PRs, stacks, actions and git-client compatibility on Cloudflare Workers and R2; still working.
The AI patched fan thresholds and power management on his 2015 MacBook Pro running EndeavourOS, making it fast and usable.
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.