He resells Amazon liquidation pallets on Facebook Marketplace. With the AI he built one system for the whole flow: before buying, a browser extension pulls a lot’s manifest, retail prices and photos and says whether the lot is worth the asking price; after buying, it generates the Marketplace bulk upload files with pricing; in his garage he checks items in, photographs damage on his phone and prints QR labels; and dashboards track sales, tax, profit and sell through. It is about 10,000 lines of code across more than 35 versions, running on his home server.
Tom Mulholland, 66, owner of Mulholland Grocery (Malvern, IA; team of ten; US Chamber 2026 top-100 small business), had the AI produce social ads: he sent pictures of warehouse-catalog items and got ads in ~15 minutes vs hours of typing.
He gave an AI one job: earn a first real payment from an open source bounty. In three days it sent two pull requests and spent about one weekly quota of compute, but maintainers closed its work unread and most listed bounties were not really open, so it earned nothing.
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WisePPC has AI agents fix its Amazon listings. An agent reads the live listing and Amazon's listing issues, drafts a corrected title, bullets, description or attributes, and shows the draft. Nothing is submitted until a person says go. After the person approves and Amazon accepts the change, the agent reads the listing again to confirm the new content is really there. Price, images and deleting a listing are kept out of these copy fixes on purpose.
He runs a small home service business. On site his crew capture photos and notes into a CRM; the AI reads the CRM over a connector, studies the photos and writes the full client report he used to write himself. When the report is done he tells the AI to send the invoice, and it builds the Stripe invoice from the project notes and sends it to the customer.
A solo litigator had about 15,000 pages of discovery to dig through for a summary judgment motion. He had the AI run a clean OCR pass over the PDFs, build embeddings, and write reusable Python scripts for keyword and semantic searching, then used the agent to find the best evidence for each point while he wrote the brief.
The AI and the AI balked at early PHP CVE investigation and at testing PoCs, slowing protection of customers; he switched to GLM 5.3 to mitigate and later used AI for the fix.
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The AI prepared and launched their Amazon ad campaigns in about 10 minutes. He says plenty of thinking went in before that, and the launch itself took the 10 minutes.
Constraints: zero ad budget, no existing audience, ~4 hrs/week of human time; assets: a subdomain, Cloudflare access, DodoPayments. Ruled out: custom AI songs, mixing/mastering services, automated day trading, 'information arbitrage'.
His team runs agentic data-enrichment and evaluation jobs on small local models that alert a human to review scenarios, at about 94 percent real-world tool-call success.
He had an email with stage times and used AI to tidy it into a Stage, Day, Time, Artist list. The AI then changed the fcpxml file so Final Cut Pro had a new project for each set.
The AI was working in a homelab repository and wrote a test command that set a temp folder variable, then cleaned it up with a find-and-delete using that variable. An earlier step in the chain failed, so the variable was never set. Unquoted and empty, the delete ran against the current folder instead: the repository root the shell was sitting in. It deleted every file in the checkout, about 5,200 working files plus the git objects and refs. Only files the sandbox mounted read-only survived.
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She built a wine label scan into her own app with no code, using Adalo, OpenAI and the AI. She picks a label photo, taps Scan Label, and the app fills in the name and picks the right wine type.
A community college counselor of 16 years turned her idea for paid degree planning into a working side business: The AI helped with the business plan, built and edited her website, including a later round where Work mode edited the live Squarespace site directly, found leads and shaped her replies to potential clients. She has her first client and a lot of leads.
The AI goes through his sent emails to learn which sorts he typically responds to, pings him when it thinks he left something unanswered he'd want to answer, and repeats the exercise monthly to stay current.
Ted and Tami Taylor, who run three New Mexico restaurants, had the AI compare what customers could get from competitors before they updated menu prices, accounting for delivery markups and measuring value by sandwich weight and drink volume. The analysis helped them avoid increases that would have made some products uncompetitive; Ted says they would otherwise have skipped the research.
The same business owner runs AI on a weekly cycle for search traffic. It scans competitor sites for the keywords he tracks, compares his own pages against them, suggests changes, and finds and puts in internal linking fixes itself.