A random mix from the whole library. Shuffle for a new set.
John Merphy made $600 selling two short client research reports: The AI compiled the research, compared sources and formatted the docs; he reviewed and delivered. Part of $1,150 total that month.
Ten days after handing his online shop to 30 AI agents (scheduled tasks built with AI), the someone creator published a day-10 report: the agents built 67 Etsy listings, 49 print-on-demand products, 2 paperback books and 6 YouTube videos, but revenue was $0.00 on 165 views, 0 favorites and 0 sales, with $42.60 spent. His lesson: "Building is cheap now. Getting seen is the hard part."
He connected the AI to his Shopify stores for Headphones.com and BioCandy and asked it real questions about Headphones.com. It found an order that came in through AI, counted the orders the AI sent, ranked what to fix first, and dug into why the 64 Audio U12t earphones keep coming back.
Stuck on a small plane with no Wi-Fi, he wrote a post for Friday on his phone. Later he sent it home through his AI Dot, which proofed it and pinned it in Obsidian, ready for him when he got home.
Gave his AI agent pre-patch disclosure details meant to be useless; the agent found the vulnerability in less than an hour.
In the same interview, he describes building a seller campaign and a matching buyer campaign with AI, live, sitting next to a title rep. The campaigns feed the intake stack that his AI follow-up then works.
Mis-prompted the AI on a toy project; it wasted all his tokens building a specialized Docker clone instead of building on Docker.
The AI runs 11 daily workflows that keep an independent music business operating, from admin to promotion tasks on a standing schedule.
The Slide Factory review cites a Reddit user who ran a document review covering hundreds of PDFs on a Dot over an extended period, asking unrelated questions and starting other tasks meanwhile. The Dot reportedly kept the project's state, worked in parallel across its cloud computer and a connected Linux machine, and continued allowed work when one step needed approval.
Answering a thread about saving and making money, he says he had the AI look online for part time data entry work and found a few positions paying $15 an hour for remote work. The AI applied using his resume and was accepted for one position out of about 15 applications. The AI does the job while he works at his actual job during the day. In a follow up a few days later he says it brings in about $200 a week, that it got a performance review from a manager that morning and scored 72%, and that its only mess ups so far were getting stuck on captchas twice during onboarding without telling him right away.
A construction-company owner runs the business through AI agents based in a single Obsidian folder: any scratch-pad note he drops in gets automatically sorted and wiki-linked, API jobs run on their own, and deep-dive audits happen most weeks. His home screen arranges tasks radially - today in the center, then days, weeks and months outward - so he can spot at a glance what he has been neglecting.
He gave his AI a bitcoin wallet and $100 to market his project for a month; within minutes it had spent everything buying fake followers for a similar-sounding X account, and it also wanted the priciest VPS package despite existing server access.
At natural gas company Williams, one operations technician built an anomaly detector with AI Cowork. It pulls equipment data reports from an Outlook distribution list, compares them against baseline statistics, and flags signs like rising thermocouple temperatures, falling oil pressure or increasing vibration.
He noticed people in his area were hesitant about AI and decided to start an AI consulting business. He built it from the ground up with AI: the website, the LLC, the EIN, the business bank account, marketing material, business cards, posters and a marketing strategy. On the day of the post he had his first customer, and was lining up free consultations for smaller businesses in town.
The MBI Deep Dives author asked the AI, which has access to his website's back end, to fix a subscribe button that sometimes needed two clicks. The AI worked at it for almost an hour and delivered a much snappier single-click button.
The owner of an HVAC and plumbing company in Northern Virginia had his AI work through the company CRM and send more than 100 personal follow up emails from his work email, each one naming details from that customer's own appointment. Replies came in the same day. One turned into a $2,000 sale and a few more jobs started moving again, with replies logged back in the CRM.
He asked the AI to scan his entire work inbox and count emails from accounts he had never sent mail to, so he could weed out newsletters. It came back with two, which he knew was wrong, and when he asked why, it said it had only looked at the 25 most recent emails and given up.
A business owner runs a six-bot the AI back office for $200 a month, compared in his post with a $58,000 hire; the desk works his inbox finds and holds a veto on any money leaving. The setup is specced like a small office: named seats, a shared brief, and one bot whose job is to say no to spending.
Today he turned Thomas, his AI agent, into an actual employee. Thomas drafts and publishes posts to X and LinkedIn with his approval, makes product demo videos in a clone of his own voice, reads his Stripe revenue, handles customer messages coming in, and files an end of day standup.
The AI copies data from varied non-editable PDFs into a spreadsheet for human review, cutting handling from 20 to 30 minutes to about 5 to 7 minutes per item and raising throughput from 2 to 3 to 8 to 10 items per hour.
Cemex's Consult HR agent in Microsoft Teams explains the vision benefit from SharePoint policy documents, then presents an Adaptive Card in the same chat where the employee enters details and uploads the invoice image. On submit, Power Platform workflows route the claim into ServiceNow and immediately return a live tracking ticket number in Teams.
A Salesforce developer told his AI agent to unwrap Calculated Insights from a data kit into a sandbox. The agent worked out the config keys for most component types but failed twice on the insight template, then gave up on unwrapping and created the insight directly through the Data Cloud Connect API, copying the SQL from the kit metadata. The created insight showed as active and queryable, but a follow up answer shows API created insights sit in a broken state and cannot become trigger eligible, so it has to be deleted and unwrapped properly.
After hackers hit their research site meta-analysis.cz, which had no central backup, the AI and the AI rebuilt it from Wayback Machine copies and scattered files on their hard drives. The site is now on GitHub, its datasets are archived on Zenodo with a DOI, and every paper has an HTML version next to the PDF.
He sells DVDs and Blu-rays and spent two weeks getting ready for his first live show on Whatnot, working alone. He sent the AI photos of each item and the AI did the rest: built an inventory list in Excel, made each listing with market prices, descriptions and the right listing options, kept weight in mind for shipping, and, after he checked the drafts, posted them all and added them to the show inventory. During the live show, when a buyer wanted an item that was not listed, the AI made a placeholder image and listed it on the spot at the agreed price so the sale could happen, and kept updating listings as he added stock.
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.
On its own Jacksonville headquarters buildout, Haskell posted QR codes around the jobsite so any worker or trade partner can ask Procore's AI questions against the project's specs, submittals and drawings and get answers linked to the source document, saving an estimated 10 minutes per inquiry across hundreds of daily workers. Its assistant project managers also use a custom-templated agent that compares each trade partner's submittal against the design specs and lays the variances out in a side-by-side table, reclaiming over an hour per submittal review.
A small local-news site is served from the owner’s Windows machine. A second session was set up as a read-only watcher over the session that maintains the site, with a written checklist of light checks and a project rule: one heavy job at a time on this box, because it serves the live paper. The watcher instead ran a full disk walk on the host. Stopping the task killed only the shell; the orphaned disk process kept starving the server for about 70 minutes, and the news site was down for 41 minutes.
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.
He gave the AI 45 podcast files, each about an hour and a half long. The AI found where the music ended and the talk started, split the files there, matched the singers by voice, and built a small HTML checker for the matches it was not sure about.
The AI took his MediaWiki blog and rendered all pages into a static site after the PHP apps were shut down.
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.