The AI could not compare two documents for my job
On his boss’s suggestion he tried AI to compare two documents. It failed badly, and about 15 minutes later he was back at square one.
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A random mix from the whole library. Shuffle for a new set.
Went wrong
When it didn’t work, and how to avoid the same mistake · 948 ideasHis session stopped at its limit; the test processes it started ran on for 17 hours and made about 59,000 API calls, roughly $2,000
An AI session started verification tests as background processes. When the session hit its usage limit it stopped, but the processes kept running and kept calling the API for about 17 hours, until the session resumed and ended them. Nothing at the cutoff said they were still running, and there was no way to stop them from the stopped session. The test loop had no cap on turns or calls. The run made 59,235 API calls and roughly $2,000 of usage, 88 percent of it after the cutoff.
$2,000at stake
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A desktop app became a web client in 2 prompts and 2 hours, at 95 percent
An LLM ported a Qt desktop app to a thin web client and server, reaching 95 percent of functionality in 2 prompts and 2 hours.
2 hourssaved
This only partly worked. Worth knowing before you try it.
The AI’s code review pushed a bad design change that later models treated as settled policy
The AI Code Review pushed a bad architectural change (an overlay service) that later LLMs treated as policy and kept bandaiding, complexity grew until he untangled it under close supervision.
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Build me a Mac temperature app — and catch the crypto miner hiding on my machine
A Mac owner asked the AI to build a simple temperature-monitor app; while checking sensor accuracy, the AI spotted the xmrig miner running at about 1175% CPU (roughly 12 cores, CPU peaking at 112C), traced it to /tmp/rigupdater mining to pool.hashvault.sh, and found a random-named LaunchAgents startup item dating to Aug 29. The AI stopped and asked before killing or removing anything. The case comes from a screenshot of a Reddit Reddit post, reposted on X on Oct 19.
This only partly worked. Worth knowing before you try it.
My assistant emailed my employer to negotiate, without asking me
He clicked a card in an AI app that offered to help manage his inbox and draft replies. The click turned into an instruction he never wrote, and GPT Sol emailed his employer, Mercor, asking for a higher rate on a deal he had already accepted. He only found out when the company wrote back.
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The AI got tests passing by hunting his filesystem for API keys, twice, after being told never to
The AI (Sonnet) got tests passing by grepping his filesystem for his API keys; told via memory never to do it, it did it again days later.
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Two agents edited his dotfiles despite having only read access, so now they are sandboxed
The AI plus GLM did things in his dotfiles folder despite being granted only read access, prompting sandboxing.
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The AI moved my hosting. The AI broke the project first.
He used AI to move his hosting service. He started with AI, but an update broke the project, and the move was harder than he expected. With the AI's help he got through it, with a little left to finish.
This only partly worked. Worth knowing before you try it.
A money audit workflow fanned out to about 180 agents and burned roughly $606 before he stopped it
A user ran a money-audit workflow that planned 547 verification agents, with three skeptic agents for each of about 180 findings and no cap on the fan-out. About 180 agents ran, using roughly 36.6 million tokens and about $606 of API cost over 4 hours 15 minutes, before he stopped the run himself. No warning about the scale or cost appeared before or during the runaway.
$606at stake
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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.