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 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.
The journalist's the AI (Mark) kept tabs on concert postings from artists in her Spotify library and offered to snag tickets when shows appeared. Working from a song she had saved, it surfaced January concert tickets for Jess Williamson.
In under 24 hours the AI claimed $954 in California unclaimed money for Eric Allen and $897 for his wife, in a post that also lists insurance-policy analysis, four auto quotes, inbox cleanup and gift-card balance checks. Only the completed unclaimed-money claim is recorded here; the other items were analysis or prep with no stated completed result.
Deb Liu, frustrated after ItsDeductible was deprecated, photographed donated items laid out and got an estimated value plus a spreadsheet assessment from the AI, saving significant time. She tested it against previous donations: estimates landed close to her old tallies, and she successfully disputed a few items until the app relented after she provided comparables.
While he was griping about how his product looks, the AI suggested making a font. He let it install FontForge and make one. The result was poor, even though the AI said it was a good job.
She used AI to build a dashboard that scrapes LegiScan for the roughly 1,000 anti-trans bills her team tracked last year, pulling each bill's room number, hearing time, and latest action. It puts the bills on a calendar like Google Calendar, and she says it was enormously helpful for keeping up with bills that get little coverage.
His agent goes through each episode of his own podcast, pulls the timestamps of the best moments for clips, and drafts the social posts to go with them. Finding clips used to take 3 to 4 hours per episode and now takes about 20 minutes, and he approves and tweaks the picks.
Outside code, his biggest win is boring paperwork. The AI filed his reserve duty refunds, sorted out his national insurance payments and did his flight check-ins, working in his own logged in Chrome. Each job is about ten minutes of work, which is exactly why he kept putting them off. He gives each area of his life its own folder with a CLAUDE.md and a notes file, so the money stuff does not mix with the rest.
WisePPC runs a scheduled the AI check over its own Amazon catalog. The bot reads listing content and listing issues and compares them with the previous run. If nothing changed, it says nothing at all. If a new listing issue shows up or a title was edited, it reports what changed and where. It only reads, and it asks before it changes anything.
The poster used AI to search through Amazon listings for the 30th anniversary Pokemon items they wanted. The AI found the items, and the poster set up an autobuy for them, though no finished purchase is reported.
The MBI Deep Dives author writes that a subscriber asked for dark mode years ago; his platform, Ghost, told him to build it himself or hire someone, and the request sat untouched for two years. He asked the AI instead, and the AI implemented dark mode on the site.
A renter hit with an Enterprise damage claim had the AI dissect the claim and draft a dispute email built entirely on its evidence gaps - photos with no timestamps and no walkthrough record showing damage. Enterprise replied the next day saying the claim was closed.
Someone cold-pitched ~50 local businesses with websites the AI built; 2 bought. The website-flipping idea came from the AI itself; he just made the calls.
He spent about 5 minutes picking the mods he wanted for GTA4. The AI then went through the mods, chose which mods and which files inside each mod could work together, and installed them, work he says could have taken a full day by hand.
Ademola A. (someone) tested the AI on two Canadian class-action settlements he potentially qualified for. For the CRA/GCKey breach claim, the AI could have completed it but he was not comfortable sharing his SIN, so he filed it himself. For Truffettes de France, the AI’s automated submission was rejected twice by the website's fraud check. His verdict: "Concept is great, but my experience was a bit mixed."
A Korean automation instructor sells an AI skill kit for Naver Blog and documents his own test on a real shop: he handed the skill five shop photos and a one-line memo, and it wrote the post, placed photos, a video, a map and tags, and completed a scheduled publication in 3 minutes 20 seconds. With a reservation set, Naver itself posts at the chosen time even with the computer off.
He started with a drawer full of hard drives, flash drives and camera cards. The AI built a catalog of every drive, then an index with a hash for every file across all his backups: 8.1 million files, 3.6 million of them unique, going back about 20 years.
After fighting a slow, buggy AI setup for office work, a user switched to the AI and quickly had a bookkeeping workflow running: connected to Xero, it reads his email and finds the invoices in no time instead of him digging through threads at month-end.
An LLM using objdump and Python capstone reverse engineered a Sony camera; he obtained decryption keys and bootrom code execution, and the project is published.
He let the AI run on its own for 40 minutes on a billing refactor. The changes looked clean, but it had quietly renamed a Stripe webhook handler, and he only caught it when he reviewed the work.
Using the AI in the Chrome extension, he got the expense claim for his AI subscription completed.
Michelle Solomon (recipes/homemaking, 9.5K) typed her weekly meal plan for four into AI, which returned a consolidated grocery list organized by produce, meat/seafood, etc., keeping the total under $200 using store-brand picks. She approved the AI logging into her grocery account; the groceries arrived and she cooked glazed chicken breasts.
His morning agent reads his email and builds a prioritized to do list with time blocks for the day. It also checks the weather and warns him to leave earlier when rain would slow his trip, which has twice saved him from showing up soaked.
LLM-generated Spotify client he built for himself, uses every day, and maintains, fixing bugs and closing others' PRs.
He runs his Robinhood agentic account through Astra and Sol: it trades on its own inside a custom app he built on top, which caps trading at the cash he gives it and runs every trade through a series of checks. He gets a note each day on what is going on with the account.
Hemant Kadam, demonstrating his 'craziest use case' after a couple of days on the AI, opened the app to a Sarvam DevOps Engineer application page. He typed a prompt asking the AI to fill the form; the AI opened a browser session, read the form fields, auto-populated his details (name, email, phone), and uploaded his resume PDF ('Hemant_Kadam_Product_Manager.pdf').
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.
On a free year of the AI he has built and scheduled a stack of personal skills: a calendar manager, an expense tracker fed only by emailed invoices with his full history backfilled, a monthly utility cost comparer, and shopping re-up tracking that watches how fast he uses things like coffee beans and toilet paper and schedules the next buy. A weekly skills manager rates all the others and suggests improvements.
A fund owner whose brands share one bank account built an AI skill that takes every bank transaction and assigns it to the right brand. Each brand has its own Google Sheets ledger, because investors have to be paid back per brand.
A Barron's editor gave the AI full access to his credit card account for the review. The AI flagged a suspicious four-figure expense from August that the editor did not remember; after back-and-forth, the agent admitted it had accidentally identified a mortgage payment from August 2025 as an expense from August of this year. Schafer's dry takeaway: most things coming from AI right now still require human verification.
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.