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.
Holdy logged the AI into his medical provider's portal and had it pull his itemized bills and question every line. It found several cases of double billing, asked for discounts, and has saved him over $4,000 so far.
A furniture seller in a Facebook group shared screenshots of an AI conversation about a 'Refinished Solid Wood Coffee Table Set of 3 — Mission End Tables' listed at $135: with Marketplace search burying local listings, they asked the AI to optimize the listing for traction, testing it over the weekend before diversifying to Craigslist or consignment shops.
A man used AI to plan a weekend trip to Vegas with elderly family, shortlisting dining and events around dietary restrictions. The AI also built a web app dashboard for the trip and handled the payment splitting: he told it what each person spent for the group, it kept running totals split three ways, and when a Venmo email arrived saying someone had sent money, it updated the balance sheet by itself.
The use-cases directory records someone having the AI monitor the Apple Store online and notify when an iPhone became available to pre-order — stock-watch automation for a launch.
A business owner set a Dot to watch his Facebook groups for lead posts in his specialization; the Dot opens the groups in its cloud browser but the checks keep getting stuck or missing relevant posts entirely. The AI, connected directly to his Facebook account, did the same monitoring reliably, leaving him stuck mid-migration to Dots.
Over four weeks of evenings, an AI agent wrote the firmware, the live web chart, the Node-RED automation and the enclosure CAD for his radar stair light, driving a live Fusion 360 session through its scripting API. He reviewed, printed and measured, and the second half of the video lists what the agent got confidently wrong, including a radome gap that landed on exactly a quarter wavelength.
His AI runs four standing jobs: each evening it checks new job posts in his niche and emails him only the ones worth his time; his messy end of day notes come back as tasks with due dates in his to do app; receipts he forwards get logged into a spreadsheet by amount, date and category; and on Sundays it tells him what slipped and what he keeps avoiding.
Runs a personal-assistant session via Signal that tracks tasks and delegates to per-project agent sessions on other machines; it is now his only direct interface.
Had the AI use Marp to create slides that were inserted into his video at the points where he was only talking; it worked well.
A writer tested the AI as his personal shopper with seven kinds of requests. Three worked: it found a Batman omnibus for $74.99 against a $125 list price, the cheapest PS5 DualSense at Walmart for $67.61, and a used PS4 game on eBay for $54.99. Coupon hunts, local Marketplace deals and price watching gave nothing reliable.
He runs Qood News. When the AI 2.5 was retired, moving to the AI 3.1 would have tripled his AI bill, so a decision model called Jev now decides what counts as good news and costs stay about the same. In testing Jev approved 39 of 110 stories while the AI approved 53, mostly dropping filler.
A man connected his local agent to Monarch Money through an open source MCP project, with some AI help on the login. The agent can now pull his transactions and look at spending patterns, and the AI generates a daily report from it.
Agent acted as a dogged advocate in a commercial dispute and won it.
He teaches chemistry and built a website with AI where his students form crews, make an avatar and a spaceship, and travel between planets that stand for class units, entering learning academies to fight boss battles or other crews. He funds it himself, uses AI for some of the interactive lessons and Canva for graphics, and posted asking how to work more efficiently and use fewer tokens.
A man let an agent live on his home network and finally get his hundred or so sensors and smart devices configured and talking to each other. This year he set up garden sensors with its help, tied soil, rain and sunlight readings into automated watering, and had by far the largest hot pepper harvest he has ever had.
Made Astra reverse-engineer Onshape's UI to build a middle-man extension exposing an API that bypasses the official API pricing, now used for AI CAD with AI and the AI.
A home services business was losing leads nobody followed up. The AI scores each new lead A, B or C against the owner's 4 rules, writes a short summary on the contact, and drafts personal WhatsApp follow-ups that a person checks and sends each morning. The poster says it brings in 5 extra contracts a month at about 9,500 euros each.
Using the AI with Blender, he had a Turkish lamp modeled from his description, then brought the model into Clip Studio. The red lamp on the left was finished from instructions he sent remotely while riding an exercise bike.
The AI enabled a camera on a test device and he taught it to reboot into the previous kernel on build failure so it could iterate for days; ended with a usable setup and camera login working.
Marco H asked the AI to audit his 15,000 Instagram followers and identify which ones don't follow him back. The agent worked through the full follower list and returned the non-follow-backs.
He asked the AI to make a technical diagram with gpt-image-1. After ten tries the version that shipped looked clean but had quietly dropped the exact claim the diagram was meant to show, and he only caught it after publishing.
He gave the AI a prompt to search 24 months of his Gmail, 2,812 emails, and list the subscriptions he was still paying for. With his approval it cancelled ClassPass at 9,900 yen a month, a saving of 118,800 yen a year, and a confirmation email arrived to prove the cancellation went through.
The solo maintainer of the karasu modeling language runs dependency updates through an AI skill that investigates each Dependabot PR before anyone merges: release notes, the diff between tags, publisher or ownership changes, install-time scripts, lockfile edges and known advisories, written up as merge, hold or reject recommendations in a design doc. In the week of Oct 10–17 three triage rounds fed 88 merged PRs (16 from Dependabot) and 12 architecture decision records, and the process caught a rebuilt lockfile silently moving a package off the reviewed version.
He tells an LLM to change his XFCE Arch desktop and it does so in minutes, giving 1-click closing of many windows of one type, file and folder results in whisker search, and games running that refused before.
In the same week, Alec Ellin had the AI mine his own Instagram and LinkedIn connections and turn them into a leads list — prospecting built from the network he already had rather than a purchased list.
In shipwithmuse.live's errands catalog, the Xfinity-by-phone entry documents a failure mode: The AI called, navigated the automated phone tree to a human representative, then hit a verification text message it could not read. Its fallback was to patch the user into the live call.
The AI writes daily blog post drafts for his app and checks draft approval status every 2 hours, pinging only when something changes.
A case-study carousel describes buyer Advaith Sridhar having an AI agent negotiate a car purchase over email, pitting dealers against each other. It saved $2,102 off sticker — a premium model at a base-car price — with no in-person haggling.
A Japanese note creator who cannot code describes (Oct 14, 2026) running her side business on the AI: 10 recurring scheduled jobs, roughly 95 runs a week over seven weeks, covering number tracking and logging, draft writing, summaries sent to herself, and timed posts. Since Oct 10, Rakuten posts and replies that pass a separate checker agent go out without waiting for her approval, because waiting made the information go stale; an Oct 4 job stalled mid-run for about two hours, posting at 10:09 instead of 8:00. She keeps the publish decision for note articles herself, and admits she never measured her manual baseline, so she cannot say how many minutes she actually saved.
A maker had the AI redesign his KiCad board, including selecting parts from JLCPCB's catalog and suggesting cheaper equivalent components that cut his bill of materials significantly. When assembly proved too expensive, the AI redrew the schematic around through-hole parts he could source himself.
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.