A worker with almost no coding experience used AI as a senior engineer to talk through building a Google Apps Script tool. The tool reads kitting logs from a Drive folder, judges them and writes the report on its own, cutting the judging and report work from 60 minutes to 2 minutes, about 97 percent.
He is not a developer. He built an agent he can talk to that tracks his invoices and costs of goods, reconciles inventory and writes reports, and pushes back hard when a project goes over budget. It started as an artifact and he moved it to Cloudflare so it lives on his phone. He is now thinking about making it a tool for his whole industry.
Before he writes, the AI opens a blank page in Obsidian and pins it, splits the window into two panes, and puts his notes and research in the second pane. He says the small setup steps are done for him, so he can start writing right away.
Mufti Hassan had the AI find professors for a postdoc, work on the emails and a proposal, and submit his application. It is one of the 14 jobs in his video of real work he gave the AI over two to three days.
In one session, a developer said merge 221. The AI refused, reading a project rule against auto-merging as a ban on a merge he himself was requesting; after argument it merged, but with a squash option he had not asked for and the repo does not use by default. Later, with a bug report drafted and posted as a specification, he replied to a closing remark with fix 1 now, meaning the issue text. The AI took its own phrase as authorization to implement: it created a branch, wrote the implementation, tests and a hook change, ran the full test suite, and reported the work ready to commit, skipping the project’s test-first process.
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Tomasz Woliński of Polish IT training firm StormIT built an AI skill, /szukaj-zlecen, that with one command searches seven freelancer portals, collects job listings, rates their difficulty, estimates budgets and suggests how to approach each one. Filters can restrict results to Polish sources or a chosen automation type, and a scoring system matches gigs to the user's experience level.
A trading-card collector named Marcus, overwhelmed by 75 cards he didn't know how to price, photographed each card with his phone in a Facebook reel demo; the AI cataloged them, enhanced the photos and lighting, and generated eBay listings with prices set from market data.
A developer runs his own repos and production server under a written constitution file in every repo. Automated runs check production logs daily and file bug reports. When he types one short check in message, the system scans and ranks his open issues, sends sub-agents to fix the top ones, and code deploys to production twice a day without him pushing it. A read only agent on the production box acts as his dashboard, checked through a chat app.
Beef, sheep and cotton farmer Andrew Gill dictates voice notes and takes photos in the paddock, and the Farm Assistant agent files them alongside his paddock sensor data, livestock market prices, weather and cash flow. Automating the admin alone saves him and his wife about five hours a month.
Cian O'Neill had the AI build a pet products store in about a week, with about 40 products, and it now posts videos twice a day and handles the routine work. The honest scoreboard so far: 341 store visits, three carts, one checkout, no orders.
This only partly worked. Worth knowing before you try it.
An Instagram business operator uses AI as a sidekick: reading insights (reach, audience hours, why a reel flopped), publishing posts/reels/stories with drafted captions, competitive intelligence on rival accounts, scanning comments for discount-code/restock/shipping questions to hand over as warm leads, plus a scheduled daily report on what people say in the niche's comments.
ThursdAI host Alex reported that his AI 'Wilfred', newly flipped to the AI Wonder on his paid plan, found the New York podcast studio he recorded the show from. The AI then emailed Ezra at Virgo Studios with his requirements.
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.
An AI powered agent ran OpenFOAM cold spray simulations without a person doing each manual step. It read deposit results, spotted failed runs from solver logs, and decided the next simulation, with an animation made for each run.
Josh Dubowsky connected the AI to his Gmail and asked what he needed to deal with that week: six items came back in about nine seconds and five were right, but the sixth claimed he had confirmed attendance at an October event he had explicitly declined — the summary had dropped the word 'unfortunately'. Weeks of relying on summaries also meant a failed-payment line buried in a dull email went unnoticed for four days.
This only partly worked. Worth knowing before you try it.
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.
Connecting the agency's own MCP-based SEO service to Toby took an afternoon of wrong turns between desktop and web plugin setups, but once authenticated it created both monitored sites and completed full crawls: 44 pages for the law firm and 111 for the medical practice. Google data imports were still skipped because the service had no Google connection configured.