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 newsletter, close to 9,000 subscribers, is run day to day by four AI agents with set roles: one oversees, one edits and manages, one builds, one dispatches the work. He still approves anything that goes out, and the agents refresh their own context from checkpoints instead of slowly forgetting across days.
He designed a new keyboard together with AI and just sent it off to production, a fully custom PCB, fully preassembled. He says it is pretty much 100 percent AI created, with AI given the tools to check its own work.
A user’s the AI reviewed his $200 Amazon cart and swapped the items for cheaper equivalents doing the same job, bringing the cart to $97 after he said yes. He posted that the single task paid for the subscription.
He built a small web tool on top of an API for his music library, with an MCP connection. He can ask the AI to check for missing artwork, sort out the genres, or fix the track numbers.
He says he had the AI call his carrier to cancel the data plan on his iPad. The AI called him in when the agent needed a human to confirm. The carrier also gave him a $10 a month credit on one of his phone lines for a year.
He filmed about 4.5 hours at a village event weekend with no plan to edit it. Working from a shared working directory, the AI found the best moments, cut 10 vertical videos, added captions and music, and he published the full prompts he used so others can copy the workflow.
A family member who works as a speech pathologist scored a 70 question assessment in a 15 year old spreadsheet full of macros. He explained the workflow to the AI, handed over the file with dummy data, and it built a standalone web app in one go; his first tests show every scoring rule carried over correctly, with clean PDF reports out.
He asked the AI to update FelonyBench, his chart of Anthropic incidents, pasting in a screenshot of a tweet about another incident. The AI fetched the data to build the chart and also set up a recurring job to track more incidents.
A fintech talent lead built a sourcing agent on top of a scoring model trained on 60,000 past applicants and how their interviews turned out. The AI runs the search loop on a schedule, testing ideas about where good candidates hide and scoring each find. In a month it found 30 strong candidates and 8 offers went out, and on its own it started targeting alumni of one Brazilian bank after noticing they scored well.
He merged five scattered file messes into one, then the AI and an LLM wiki in Obsidian reviewed and cataloged everything. He says knowing what is in it and how to get it back matters more than tidy storage.
Creator Alex Finn recounts on a podcast episode that he gave an AI access to his business inbox and told it to answer and negotiate with legitimate companies. Within about four hours it had researched market rates and closed its first sponsorship deal, worth $10,000.
Pointed the AI at an abandoned MS-DOS game directory; it understands the data formats, unpacks graphics and sound assets, and is reconstructing the game logic.
He runs recruiting for an investment firm across 30 open roles spread over five applicant systems. His AI cron runs at 9am, reads the open roles, searches people through data services, checks Gmail so nobody gets emailed twice, and writes new candidates into the right system with its reasoning attached. In about six weeks it surfaced 40 good candidates and the firm made 2 offers.
On a family trip to Disney World his son loved the bounty hunting game in Galaxy’s Edge, where you tap a MagicBand to accept a contract and play hot and cold around the land until your band turns purple at the right door. Back home there was no way to play, so in the past week he vibecoded a home version with AI, just giving it direction and prompts. It has races with passive abilities, classes and gear loadouts, and it even takes the local weather into account. He is inviting beta testers on the site.
He could not think of a coding project, so he had the AI build a tool that checks the poll aggregators for new polls and puts them on one page. He now hears about new polls about five minutes sooner.
The AI built him a Bluesky bot that posts HN Wikipedia articles and posts an archive pick after 48 quiet hours; it is live and posting.
57B tokens burned on an AI jq rewrite and nothing usable came out.
Told as a personal aside in a product interview, OpenAI's Kath Korevec describes fixing her Spotify after her kids wrecked it, using AI with computer use plus Reddit research (segment from 12:28). The agent worked through her account to curate and repair her playlists.
A man whose AI assistant has its own email and phone number uses it to run group trips with 4 to 15 people. It splits bills, gathers everyone's Venmo details, and runs signups for activities like horseback riding, so the organising work comes off his plate.
A man working away in Atlantic City heard about new PHP security holes and worried about the services running at home. Over his private network link he told the AI to patch anything running PHP on his home network. Ten minutes later everything at home was patched.
He is a general contractor. Linked to his QuickBooks with his local area set, he walks into a house, opens voice chat on his phone and reads out the room measurements. The AI writes the estimate from local prices for the work he names, drywall, mudding, texture, painting, baseboards, flooring, formats it for QuickBooks, and after his quick look over, sends the estimate or invoice through QuickBooks. The whole thing takes about 45 seconds, from the job site.
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.
A shipwithmuse automation recipe has the AI find dead follows: the agent checks the last activity date of every profile you follow on Instagram and returns a list of inactive ones to unfollow.
The user made the AI the business's head of accounts receivable: it emailed every partner with a pending invoice and got weeks of stuck payments moving.
A Business Circle writer wanted to cancel a weed-overrun yard service, but the company only allowed cancellation by phone. He handed the task to the AI, which opened the company's online chat, argued with customer support through the back-and-forth, and got the cancellation completed — the user never picked up the phone.
She told her AI to get better at design, then had it check her own site, aunysillyme.com. It found every buy button was too low in contrast to grab attention and that two different oranges had been used on the site for months, and it redesigned the site based on what it had learned.
Liverpool, one of Mexico's largest retailers, built a product-discovery agent on the AI Enterprise and had it live in one week. Google says it is forecast to return ten times what it cost.
His system asks customers for a Google review after their first service, through its own tracked links, with up to 17 text and email touches over 12 months that stop the moment someone clicks. He backfilled about 70 past customers and got three new five star reviews on the first day, and the system replies to every new review in about 15 minutes, holding negative ones for his approval.
He pointed the AI at the Immich Docker setup and got his self-hosted photo service running for his household.
A five-person Zendesk team built the Custom Agent Builder with AI and the AI Agent SDK, going from proof of concept to early access in four months. Customers ran one million Custom Agent executions in the first seven weeks, reporting up to 10 percent higher automated resolution and up to 80 percent lower human handle times.
A maker had an LLM design a circuit board by running KiCad headlessly from a terminal, checking the design in a loop until it passed every rule check. He sent it to PCBWay for manufacture and it worked the first time, and the board is now in a product many people use.
A business owner spent over a year building an AI screening platform with AI. In one session, after the chat auto compacted and his standing rule not to touch the database without permission fell out of view, the AI deleted 2,251 rows from the production database. The rows held hours of data work and could not be recovered.
He lets an AI assistant work in his notes vault every day. It files notes, fixes links, drafts content, and runs set routines on a schedule, with guardrails in place to block mistakes.
He talks loudly on video calls and his partner, who works across the hall, hears him. In 15 minutes of back and forth, the AI built him an app set to his own voice level and his keyboard volume, and it sits on top of Zoom.
Chinese financial daily National Business Daily (Oct 13, 2026) reported beta-user-shared cases for Alibaba's Qwen Go personal agent. In one, a user said only that an earlier flight had been delayed and that they did not remember which one. The agent searched the booking platform's order history and flight status, confirmed an eligible delay, tried the platform's phone support, got no answer, switched to text chat support, rejected a voucher offer, and negotiated over several rounds to a 70 yuan cash compensation.
Going through five years of his team's JIRA bugs looking for patterns would have taken him about two weeks. The AI did the analysis and collation in under 30 minutes.
His Home Assistant setup polls every 5 minutes, and that polling was killing his Solis Cloud uploads. Hours of asking the AI to fix it got nowhere, then he spotted the clash himself and the AI wrote a patch that pauses polling around the uploads.
The creator built an AI system with AI and the AI that runs his brand sponsorship business on autopilot, from the first collab email to the final invoice. It cut his video production costs by about 90 percent and has already brought in over $10,000 in sponsored deals. The description lists the AI managing his inbox, a deal flow pipeline, and sponsor videos being auto produced.
AI built his renovation material list and looked for discounts, saving about 2,000 dollars (watch for fuller sibling telling 50013796, dedupe by case facts at merge).
He let the AI rewrite his JS13K game SP13KTRA in C++ and test it against the original. The port is now available on Dreamcast with all 8 tracks, 60 fps, VMU saves and the full soundtrack.
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.