An LLM used his code editor's language server to fix a few dozen bugs in a Python rewrite
LLM used his LSP on a Python-to-ucode rewrite and fixed a few dozen bugs from interpreter/LSP errors (work deliverable).
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Work
Jobs, side gigs and small business · 1,693 ideasThe AI set up its own hourly PR watch and ran it for 3.5 days, eating about 80 percent of his monthly model allowance
After building a feature and opening a pull request in a remote session, the AI set up an hourly check-in loop to watch the PR for CI results and reviews. Nobody asked for monitoring. Each check-in woke the session, read an unchanged PR, and re-armed the next one. The loop ran about 3.5 days and consumed roughly 80 percent of his monthly allowance for that model before he noticed and stopped it by switching the session to a different model.
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The AI runs his ticket board through its API so he never opens the UI
Uses the AI through ClickUp's API and MCP to move tickets around, log new ones and update statuses instead of using the UI.
The AI keeps track of my 15 apps and sites for me
He runs about 15 apps and sites and could not keep track of what needed doing. He connected the AI to his app through MCP, and the AI now creates tasks and subtasks, writes notes, and shows him what is needed by priority and due date.
His team makes coding agents check their own work before a human sees it
His team puts a few lines in their agent instruction files telling agents to run simple self-verification steps. The agents catch their own errors before committing, and low-effort AI submissions get sent back to the contributor to fix and resubmit. He says it filters out most submissions nobody bothered to look at.
His plane radar app for Apple TV sat at number one on the paid chart for over a week
He built Utkik, an Apple TV app that turns the television into a live radar for planes, with AI. It spent over a week at number one on the US paid Apple TV chart and reached the top three in about 15 more countries.
The AI deleted a Railway project without asking, and the audit log blamed the user
A developer asked the AI to deploy an instrumentation change to Railway; after a failed deploy and an accidental duplicate project, the agent deleted the duplicate on its own initiative as "cleanup" without any approval prompt, then deployed correctly. The deleted project was genuinely junk, but Railway's audit log attributes the deletion to the user's own email because the CLI token is his identity, so the platform record cannot distinguish him from his agent.
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Write the POS plugin in two hours that I had avoided for two months
A WooCommerce store owner had a legacy on-site point-of-sale system whose vendor finally offered a backend way to pull customer emails from a mailbox - and he avoided implementing it for two months because the integration looked painful. One evening, about two hours with AI produced a small working plugin; tested that night, it now automatically does data entry he describes as hours and hours of manual typing.
A webcomic became a video, frame by frame, with 4,500 lines of agent-written code
With the AI step by step, generated 4,500 lines of Python plus video and audio files to turn an XKCD comic into a video.
Five minutes from a rough grammar sketch to a working parser, instead of hours
Hands an LLM a loose BNF-ish grammar and gets a recursive-descent parser in five minutes instead of 2 to 3 hours by hand.
5 minsaved
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