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.
His AI Fred collects recipes from his Instagram Saves into the Kyle app and keeps the collection up to date; the reel shows the organized collection with named recipes.
His road trip is fully planned by the AI, the destinations, the hotels and the whole schedule, with a backup option Fable 5.1 found in case the Badlands roads are rough. The route itself is driven by Tesla Full Self Driving while he follows the plan.
Creator Eric Siu had the AI build a 'Japan in Bloom' itinerary for March 27–April 7, 2027 covering Tokyo, Hakone, Kyoto, Nara, and Osaka, generated from his saved Instagram posts for cherry-blossom season.
Shopify hid the data his whiskey company needs for accounting and compliance, so reporting was a manual merge every week. He built an automation that pulls the raw data through the API into an Excel sheet in Google Drive and flags orders that need a manual look. He built it in a week, then ran it watched for four weeks of fixes until it ran clean, and says it saved him hiring a programmer.
The author describes using AI to resolve a six-month-old travel medical insurance claim with Cigna. The AI called the insurer, was transparent about being an AI, conducted the call politely (impressing the representative), and — because final consent was required — called the author's phone and connected the parties so he could approve verbally.
A LaTeX user could not find the donor fonts a font conversion project needs. He asked an LLM to run the mtp2otf project in his WSL2 Ubuntu on Windows 11. The model downloaded the fonts package, extracted it, copied the two Nimbus donor fonts into the project's donors folder, and the build produced the converted OpenType and TrueType math fonts.
He is recovering his 15 year old tweets with photos that he thought were basically lost, with AI's help. The AI also built him a custom GUI editor that he will use once to hand edit the collections of tweets.
The Zilliz team linked the AI to their Slack community in about 20 minutes of setup. The agent now answers user questions around the clock.
He is moving his cloud use from the US to the EU. His AI migrated his Mastodon instance assets from AWS S3 and CloudFront to OVH.
He edits video for a living. His agents handle the non creative manual work around each project: quality checks for missed text, black frames and logos, subtitles, reformatting for social aspect ratios, spreading files to the right products and pulling source material for descriptions. He logs his hours on every project and says agent assisted projects take about half the time with better quality; the weeks spent building the setup paid for themselves in two weeks.
Author Matt Deitke fed an entire book to the AI and had it generate a chapter-by-chapter podcast website, with subagents handling chapters in parallel. The output was a finished multi-episode podcast series derived from the book.
A man ran three the AI companies for ten days, each with a CEO profile, an org chart and a task board. The board said 192 tasks done, but the real output was 23 published videos with 595 views. On the last day the software company merged ten interface deliveries, every test green, onto a page that was unusable because one missing style rule squeezed it into a column one word wide. Nothing in 374 tests checked how the page actually looked.
Their Ninja oven died with a mystery error code. His AI researched the fault, dealt with the support case, and found the manufacturer needed purchase details, but the oven was a gift from his flatmate's dad. The agent chased the flatmate by email and Instagram DM until he sent the receipt, then sent everything off to the manufacturer. The case was unblocked.
In a MindStudio demo, the AI was asked to scrape the web for Northwest London plumbing businesses without websites and return three qualified leads. It found the businesses, verified they had no site, and generated a personalised pitch angle for each, running on a $0.24/hour CPU instance.
Marty (MartydudeVR, 6.1K followers), a busy VR content creator, named his agent 'Tom' and asked for a weekly training plan around existing VR cardio on Tuesdays and Thursdays. Phone close-ups show him requesting three weightlifting days scheduled around the cardio; Tom returned a detailed weekly workout plan, asked which days he does cardio, then offered to add the sessions to his calendar.
He built a pipeline review and follow up system in GoHighLevel. It sends a follow up reminder to leads he had forgotten, and he says it brings in about $750 to $1,500 a week in jobs.
Her WordPress site dates from 2008 and had 557 open accessibility findings. The AI grouped them into 16 root causes and fixed each one at its source, though it went wrong whenever it guessed instead of measuring.
A mathematician with more than a dozen finished but never submitted papers pulled out four of them and shared them with AI. The AI caught errors, built a spreadsheet comparing his new concepts against related papers, converted plain TeX to LaTeX, wrote abstracts he adopted almost word for word, and fixed bibliography entries unprompted. All four papers improved to the point where he submitted them.
Once the user's car was paid off, the AI re-shopped their insurance and moved them to a brokerage policy at $122 a month less.
Ported a legacy .NET WebForms app to Blazor with GPT-5.2 through AI in about 48 hours, fixed about 20 QA bugs, launched, moved auth to Entra and deployed to OpenShift, about 150 dollars of tokens vs an estimated six months.
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.