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 'A Month with AI', the MBI Deep Dives author writes that the AI filled out forms with five auto insurance carriers from his details and showed him quotes; switching at the same coverage saved $1,530 per year. He then set the AI to repeat the shop every five months, ahead of each six-month renewal, indefinitely.
Grupo Marista uses AI Enterprise agents to analyze hospital claims. Analysis that took 72 hours now takes 4 hours.
A couple filed their own taxes - his simple, hers split between employment and freelancing. The AI made sense of the Excel spreadsheet their accountant sent and translated it into exactly what the tax portal expected, beating the tax advisor they hired two years earlier, who had made a significant mistake.
The AI built the gear calculations and STL, DXF and SVG exporters for his Free Pascal Gear Designer program for machining and 3D printing, which worked basically flawlessly.
Alongside a media tracker site he built for himself, he has it check in daily: local news alerts, and deal scans on the products he buys regularly, using price ranges he gave it, with a buy now alert when a price drops into range.
During a Moneywise hands-on test, the AI went beyond the three assigned money tasks and unprompted created a personalized feed surfacing deals and news related to the journalist's past questions, plus a goal-tracking list and ideas for new tasks she could delegate.
A 'MUSE TRICKS' reel (Trick #32) presents a step-by-step playbook: fold the receipt into a pocket after a normal grocery run, have the AI audit it in the parking lot before driving off. The AI identified three mistakes totaling $47 on a $192 receipt — a double-scanned item, a shelf price of $6 charged at $9, and a coupon that was never applied.
He runs the AI on his PC with ha-mcp on the same machine, so the AI can reach into Home Assistant and make the changes he asks for. He keeps it on his own PC only, and says a new dashboard is done as soon as he describes it.
He was quoted $10,000 for a newsletter automation. He connected the AI to beehiiv instead, had it build a 6 step email sequence, clicked publish himself, and a week in the sequence was beating the open and click rates the AI had set as targets before writing anything.
His role was cut on Tuesday morning, 22 September. That evening he asked the AI for something fun, gave it one standing instruction to go forward and only pause when his input was needed, and by 6:37 the next morning a three stage beat em up about the job hunt was live on the internet, with his real CV linked from the end card.
Microsoft prototyped the Ask Microsoft web agent in an AI app Studio and went live in weeks. It moved beyond information retrieval into product evaluation and signups, then expanded across ten more product sites at two per week; customers using it visit more pages per session.
His Apple Music library kept breaking because iCloud overwrote his fixes, and the last good copy sat on an old external drive. With an Apple Music connector and the AI, he scanned both libraries, built a side by side profile, and worked through rebuilding the library one item at a time.
He has been building a fantasy sports app with AI since June. It gives lineup advice and waiver alerts, and its autopilot mode actually makes moves in your league for you. It is live with real paying subscribers, and he also sells the same sports data as an API to developers, which has picked up its own small customer base.
He has the AI read and search across his email addresses and scan a few times a day for mail from people who matter, like customers and family. He has basically stopped checking email forty times a day. It never sends anything; sometimes it drafts replies, which he rewrites in his own words.
The AI wrote Zig tools in real use, including a wasm utility integrated into a site and reverse engineering a USB wire protocol for an industrial camera driver.
Mufti Hassan had the AI clean up his full Gmail inbox. The chapter title gives the size of the job: 12,000 emails.
A user asked for a single audit of one Excel deliverable. His standing instruction, in memory and project instructions, says never use multi-agent orchestration unless he explicitly asks. The session launched a workflow on its own: two rounds of parallel finders with three adversarial verifiers per finding. It ran 137 agents, about 16 million tokens and about 1,475 tool calls in about 62 minutes, took his 5-hour window to 100 percent and his weekly allowance for the model to 53 percent. There was no estimate, cap, or confirmation. He stopped it manually.
She told the AI Astra to build a GTA 6 style trailer. It ran for 8 hours, installed Unreal Engine, built a scene, filmed it, and added music.
An AI finance desk handled a business’s finance admin around an $87,055 receipts figure, run with read-only account access plus a dedicated receipts@ inbox so the week never has to be rebuilt from browser tabs. The desk’s design keeps money movement out of the bot’s hands.
Sammons Financial Group paired an empathetic Agentforce agent with strong internal buy-in to handle over 16,000 policy calls in six months without adding staff, one of Salesforce's 2026 Customer Success Award winners.
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.