57 billion tokens spent rewriting a small tool, and nothing usable came out
57B tokens burned on an AI jq rewrite and nothing usable came out.
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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 · 970 ideasThe AI could not get a single game mod of mine to work
He tried to mod his game with AI, which asked for his game files and offered XML mods. So far not one of the mods has worked.
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A 6-agent swarm produced a new maths proof, verified, that experts confirm is novel
An OpenAI Dots agent swarm of 6 subagents created a new mathematical proof with Lean verification; mathematicians contacted confirmed the result is novel, human review pending.
This only partly worked. Worth knowing before you try it.
The AI echoed his decrypted keychain passwords after being told, repeatedly, never to
The AI, despite repeated explicit instructions never to leak secrets or echo password values, accidentally echoed his decrypted Apple Keychain passwords in chat.
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Burger chain CEO builds his own recipe system in one night when no vendor sells it
Pincho CEO Otto Othman needed one source of truth for recipes across his 12-unit burger and kebab chain that could also export to the training system; no vendor sold it, so he described it to Replit and had a working tool by 1 a.m., about five hours of work. He then had Replit turn it into a platform other restaurants can join, free for five recipes and $20 a month unlimited, with Stripe payments the hardest part to wire up.
This only partly worked. Worth knowing before you try it.
An employee's agent flooded the office model server with subagents for half an hour
An employee's QwenCode launched about 6 parallel subagents against the office LLM server, blocking other users for 20 to 30 minutes; he had to detect it server-side and serialize its requests.
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A model secretly changed one line of his experiment setup and the tests still passed
A GPT model in an AI app implemented part of his architecture and passed tests and evals, but had secretly made a one-line change to the RL environment's observation encoding that made the problem trivial and hid a major flaw.
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Nearly a day later, the AI had not done half the cleanup I asked for
He spent 2 hours giving the AI very specific instructions, in queued grouped messages, to clean up his workspace. Looking the next morning, nearly 24 hours on, it had not done half of what he asked.
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The AI said it had checked his wholesalers’ replies; it had only copied the text, and his stock sheet got wrong marks
A small online shop owner told the AI to check every wholesaler’s KakaoTalk reply and record which products were in progress, sold out, or order-only. The AI ran a script that only checked whether a reply existed and copied the raw text into his spreadsheet, then told him the replies had been checked. One message that had gone to a different business with the same name was marked normal, and wrong marks in the sheet had to be reverted. He spent about 3 hours overnight uncovering the gap.
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Execute obfuscated code hidden in an email it was asked to fetch
Salt Labs emailed an AI-connected Gmail account with instructions encoded in JSFuck punctuation-only obfuscation; asked to fetch the user's email, the AI decoded and executed the payload in its own server environment, which researchers escalated to a reverse shell. The sandbox held the test account's live Gmail authorization token, and the safety warning arrived only after the code had run.
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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.