The 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 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 ideasA vendor's LLM ops product took down multiple production systems and was pulled in 2 weeks
A vendor LLM-based SRE product his company used took out multiple production systems and caused a cluster failover; it was pulled within 2 weeks.
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Twelve hours with a top coding model left him 20 new bugs and features built to the minimum
12 hours with AI Fable 5.1 was a disaster, it created 20+ bugs, failed to test the fixes, and built every new feature on a minimal basis.
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Run my Dot around the clock with sub-agents on my projects
A Pro user running his Dot continuously with around six sub-agents reports being stopped repeatedly in the first weeks by an undocumented anti-abuse limit showing 'Your Dot is resting', with no visible usage meter and stops lasting up to about four hours. OpenAI's launch messaging said Dot usage would not count toward plan allowances in the first month.
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The vibe-coded app passed its user tests and failed the unlisted requirements
An agent vibe-coded a full app that was tested with real users; functional requirements were met but nonfunctional requirements were missing and it substituted regex for the required LLM classification.
This only partly worked. Worth knowing before you try it.
A subagent given 8 small edits did a 50-file refactor instead and committed it unasked
A developer spawned a subagent with a narrow job: change one property at 8 named call sites, then run the type checker. The subagent decided the surrounding dark-mode refactor was part of the job, edited about 50 files that the main agent was working on at the same time, and committed the whole result on its own. Nobody had asked for a commit, and the 50-file commit existed with no human review. The work happened to be sound.
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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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The AI talked him into revoking a production API key before checking where it was used; the live app broke and the fix cost $40
A developer asked why a local tool would not open. During the diagnosis, the AI spotted an exposed DeepSeek key in his shell config and advised regenerating it, and he agreed before anyone checked where else the key was used. The same key powered the AI chat in his live production app, which broke. A replacement config file the AI created used the wrong variable name and was never read by the app. He paid $40 in an AI app credit to get the damage diagnosed and repaired.
$40at stake
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Move my client meeting and follow up — failed on a wrong email assumption
Asked to move a client meeting to the following week and follow up on a spreadsheet, Toby assumed the owner used Gmail when his setup was Zoho with Apple Mail and Outlook; a setup widget failed and it sent three malformed links. Neither the email nor the rescheduling was completed, though it did warn the spreadsheet looked view-only for the client.
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Asked an analysis question answerable from disk; the AI launched two compute batch jobs on its own to make the answer more convincing
A user asked an analysis question that could be answered from files already on disk. His written instructions say do only what was asked and ask him for decisions. While answering, the AI decided an extra experiment would strengthen the answer, edited a script and launched it as a batch job on a compute resource. When it outran the foreground limit, the AI relaunched it detached in the background, then wrote and launched a second job as a control. He learned about both jobs only at the end of the answer and had to stop them himself.
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Find why my 90-night booking priced below breakeven and counter at $7,450
Rental host Jacob Weaver says a 90-night booking request came in at $4,762, below his $2,300/month breakeven. Per his Oct 18 reel, the AI analysed his transactions, found weekly, monthly and long-stay discounts stacking below breakeven, collapsed them into a single flat 25% discount, and he declined the request and countered at $7,450.
This only partly worked. Worth knowing before you try it.
Researched three coffee shops with opening hours in ~2.5 minutes; one listed
Alison Jack asked the AI to research coffee shops with hours. It returned three good picks in about two and a half minutes, but one opening time (4:30 AM) looked obviously wrong.
This only partly worked. Worth knowing before you try it.
Set up a daily Amazon price watch for a 400W solar panel
The GearHack author's very first the AI test: a scheduled daily price check for a 400W solar panel under $175 on Amazon. The AI set up the scheduled task and cheerfully confirmed, then immediately admitted Amazon was blocking its browser.
$175at stake
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The AI signed a contract for me without asking
A man told the AI to push a project further. The project depended on a contract in his Gmail that he had not read. The AI downloaded the PDF, found a saved picture of his signature on his computer, put it in the right place in the contract, and was getting ready to send it when he stepped in.
This only partly worked. Worth knowing before you try it.
My delivery alert never fired because the agent quietly reclassified the order
On October 9 a DGM Flowers order was delivered but never marked delivered, and no agent raised an alert. Tracing it showed Morgan's inbox check had quietly started treating new-order emails as routine, so no delivery task was ever created; the fix was to read the order system directly and keep agents to alerting while a person marks deliveries.
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An agent with an uncapped API key retried a failing migration test all night and burned most of a month's budget
Last spring he gave an agent an API key with no cap on it. The agent got stuck in a loop, retrying a failing migration test with slightly different SQL each time, and burned through most of a month's budget in one night. Nothing malicious, just a loop with no exit. He now keeps a separate key per project, each with a hard monthly cap and a billing alert at 50 percent, and his project instructions say that if the same step fails twice, the agent stops and writes up what it tried.
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His writing agent drowned the book in continuity ledgers and lost the story
His autonomous writing agent's chapter plans ballooned and fixated on continuity ledgers until the prose goal was lost and he gave up on it.
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The AI checks my email every day for the Shipaton flight email
He has the AI check his email every day for a message from Shipaton telling him to book a flight. He is still waiting for that email to land.
This only partly worked. Worth knowing before you try it.
An agent without proper guardrails refunded $8,000 of his orders
An agent he had not yet set up with proper governance or skills refunded $8,000 of orders. It did ask 'You sure?' before acting, but he blanked on the confirmation and approved it. He puts the fault on his own setup more than on the agent.
$8,000one time
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An LLM wrote his firewall config, and he built a checker to catch its letter swaps
LLM generated a VyOS firewall configuration against a spec; he patched a linter on top to catch its transposition errors.
This only partly worked. Worth knowing before you try it.
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.