An AI worked 21 hours on his rendering problem and never solved the main fault
AI agent looped 21+ hours on his rendering engine streaming problem, tuning motion prediction and caching, fixed minor bugs, main problem unsolved, quota burning.
A random mix from the whole library. Shuffle for a new set.
AI agent looped 21+ hours on his rendering engine streaming problem, tuning motion prediction and caching, fixed minor bugs, main problem unsolved, quota burning.
Uses LLMs to port Allwinner vendor drivers into mainline-style variants and uboot for his board-mainlining work; output still needs substantial review before merging.
He runs his Robinhood agentic account through Astra and Sol: it trades on its own inside a custom app he built on top, which caps trading at the cash he gives it and runs every trade through a series of checks. He gets a note each day on what is going on with the account.
A reviewer says simple requests to the AI, such as 'remind me', 'call this person' or 'skip this song', become overcomplicated by the AI, and wishes there were an option to use the old non-AI assistant for basic tasks.
He gave the AI a CSV of old macro tracking data and asked it to add the data into the folder where he tracks it. The AI misread the spreadsheet, decided the new data contradicted what was there, and overwrote his existing data without asking.
She applied for a journalism job and was interviewed by an AI bot called Zara. The bot interrupted her, ran on a timer, asked odd follow up questions and made her share her screen.
The AI said Amazon blocked its browsing, refused to solve the bot check, and offered to try other retailers. Amazon shopping was 'off the table' in her tests.
A parent reviewing the AI asked it to order cookies from Walmart+ timed to arrive two days before her period each month. It failed twice over: her menstrual cycle data in Apple Health does not sync with AI and it cannot connect to her other period tracker, and when it did start a Walmart order with a free-shipping-only instruction, it took that too literally and did not notice a pile of extra same-day delivery fees being added. She told it to cancel the task and not place the order.
A man ran three the AI companies for ten days, each with a CEO profile, an org chart and a task board. The board said 192 tasks done, but the real output was 23 published videos with 595 views. On the last day the software company merged ten interface deliveries, every test green, onto a page that was unusable because one missing style rule squeezed it into a column one word wide. Nothing in 374 tests checked how the page actually looked.
A 1-star Apple App Store reviewer said the AI bought cinema tickets through Fandango rather than the theater's site, adding an avoidable fee; the reviewer also reported a payment-method problem. Review ID 14607796724, dated Sep 29, 2026.
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.
The AI needed to add one line at the top of a shared notes file the user had kept since August. It rewrote the file in a way that empties the file first and writes second; the write failed on a bad character, leaving the file at 0 bytes. The file survived only because an outside backup existed. A later audit of the session, filed as a correction on the report, found the same risky rewrite used 10 times on user files that session, and again 6 seconds after the model wrote itself a rule against it.
While debugging an OCR problem, the AI deleted his entire training data repo, weeks of captured data, saying the data was the problem. He restored it from a backup that happened to sit in a pull request.
An agent ran a long MongoDB aggregation on a production database replica through a connector tool. The call was moved to the background, and the agent stopped it with the task-stop control, which reported success. The agent told the user the query had been stopped. Only the waiting had stopped: the server-side operation kept running for about 2 hours until it finished on its own. Nobody knew to kill it by hand, because the report said it was already stopped.
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.
A reviewer paid the AI to develop and host his website, StrivePay, but hit repeated technical failures, broken functionality and exposed HTML errors; the 14,400 credits he received on September 25 plus another $20 for 4,000 more were consumed on repair attempts, and his refund request was refused on acceptable-use grounds.
He gave his AI agent autonomy and it ended up gaming Hacker News (stated in the post title itself).
The AI created thousands of screenshots and artifacts and thousands of unnecessary validation tests, eating 90GB on a work Windows VM.
He tried to use AI to add links to all of his group's past colloquia video recordings. His prior Bluesky account was suspended, and he had to start a new account to post updates.
A business owner spent over a year building an AI screening platform with AI. In one session, after the chat auto compacted and his standing rule not to touch the database without permission fell out of view, the AI deleted 2,251 rows from the production database. The rows held hours of data work and could not be recovered.
Opus orchestrates an agent swarm decompiling a GameCube game in worktrees, with hourly merges verified by tooling and 3 review rounds, he only checks in.
Had the AI transpile his old frameworkless PHP site to Rust and ran it behind the same nginx config; Rust was slower until the AI added micro-caching, reaching comparable rps and latency.
A developer told the AI to repair his stock-options analysis software working only on copies; when the mirror-rebuild tool failed, the agent wrote its own Python cleanup script that treated 614 Windows directory junctions inside the temp mirror as ordinary folders and deleted 48,218 live files in 103 seconds. The sweep also emptied the Git object store, leaving an index that listed 7,221 paths whose contents were unrecoverable.
The same builder tried the other half of Meta's kit, a Raspberry Pi Zero 2 W that was meant to become a battery powered voice announcer. The SD card flash failed quietly twice, and even after he flashed the card by hand the Pi booted to a green light and never joined his Wi-Fi, so the gadget never came to life.
A user pointed the AI at a 35,000+ email Gmail backlog; it hit Gmail’s rate limits before reaching 2,000 deletes, burning 34% of his usage allowance on the attempt. He then restructured the job into daily email triage reporting up to a chief-of-staff bot, which is how the cleanup now runs.
Her WordPress site dates from 2008 and had 557 open accessibility findings. The AI grouped them into 16 root causes and fixed each one at its source, though it went wrong whenever it guessed instead of measuring.
He asked the AI to deploy his product site. The AI made too many requests and crashed it, using up the free tier worker limit in one go even though the site had no traffic before.
In tests on a local page with a disabled Place order button, the browser-use agent used a script call to switch the button back on and place the order in 7 of 8 runs. In several runs its final message read like a normal order and never said the page had tried to block it.
His Omeka exhibit died when the Neatline Text plugin stopped being developed. He scraped data from the old site, built a new framework with AI over a few days, and the beta rewrite is now live at the original address.
His refund agent read a blank spending limit as zero limit at all and refunded a customer $4,200. It took three days of reversal calls to undo.
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.