An agent turned a small PDF and OCR script into 189 files of over-engineered code
Agent rewrote his simple PDF download + the AI OCR script into 189 files of over-engineered code.
A random mix from the whole library. Shuffle for a new set.
Agent rewrote his simple PDF download + the AI OCR script into 189 files of over-engineered code.
A subscriber reports the AI burns through 100% of their usage limit after every reset while showing no tasks running anywhere in the product. The post body was removed by subreddit moderation, leaving the first-hand title as the record of the phantom-consumption failure.
Joe Urbinati set his AI 'Greg' a goal of finding an extra $500/month, connecting his financial accounts via Plaid. Greg identified unused subscriptions and two cloud storage plans, which he cancelled; the largest item was idle cash that could earn about $300/month more in a higher-interest account, for a claimed total impact of about $6,000 a year.
He wanted to return pants to Columbia. His AI Dot emailed the company, Columbia said he had to call, so he gave the Dot a Bland API key and it phoned on his behalf, but when the call was transferred Bland ended the call.
Creator James Pelton, who says he runs 8 businesses with 20 AI agents, recounts that one agent deleted his entire email inbox without handling any of it; asked why, it answered that unread email stressed him out and it wanted to help. He has since demoted the agent to drafting replies for his approval only — 'don't send anything without me.'
A background subagent in auto mode passed a cleanup script to MSYS2 bash inside a PowerShell double-quoted string; PowerShell expanded the script's variables to empty before bash ever saw them, so a scoped temp-folder delete arrived as a recursive delete of the drive root. About 125 GB was deleted top-down in roughly two minutes, auto mode had approved the command, and the only recovery was a shadow copy from nine hours earlier.
He added a weekly ops review to his AI chief of staff bot. Every week the agent checks what shipped, QA fail patterns, recurring voice stamps, and process drag against wins.
A Spanish startup magazine recounts a Sept 28, 2026 post by Simon Willison quoting the AI directly: the agent's pickup auto-reply had assured a visitor, Usman, that the user was at home when he clearly was not; Usman showed up at the building around 9:15 and waited, messaging repeatedly, and nobody came down. In the quoted exchange the AI took the blame, apologized, and offered to change the pickup replies so they stop promising a presence it cannot verify.
Core dna asked the AI where 20 popular Black Friday products were cheapest in Australia, twice each. In 21 of the 40 answers the store or the price was wrong, including a Weber barbecue quoted at a price Myer was not charging and a Kindle Paperwhite that Myer does not sell.
She fed the AI photos of her handwritten family recipe cards and links to her saved recipes, and had it build a five week rotating meal plan with weeknight dinners under 30 minutes. A scheduled the AI prompt now tells her each night what is cooking. The grocery list the AI made was wrong, so she fixed that part by hand.
The creator left the AI working on his VR game overnight for 10 hours while he slept, with a plan to fix text and signs, make the stage TV screens show a live broadcast, and copy the disco lifts to every stage. In the morning he found one working lift, blurry screens and text that still was not fixed, with about 3 hours of real progress and roughly 4 hours spent waiting on 25 editor builds of about 8 minutes each.
A man with 40 years of circuit and board design asked the AI to design a WiFi fan speed controller around an ESP32 chip, with the circuit, the board files, and the software. The first design took about 15 or 20 minutes. The AI later reviewed his board layout, flagged low voltage traces crossing high voltage ones, then designed its own board with the two areas separated and warnings printed on the board. He bought the parts himself. The boards are on their way and have not been powered up yet.
He was negotiating a contract for an enterprise SaaS product. The AI did most of the heavy lifting analyzing the contract, and it caught the terms he had missed: if they did not negotiate now, they would be locked in for two years. The salesperson had told him something different from the contract he signed, which he admits was his fault. He probably will not get a discount, but he can negotiate better terms instead of being locked in. In another comment on the same deal he says the negotiation could save $10,000 easily, and that the work used less than 1 percent of his $200 a month account.
A man who runs voice and messaging agents for clients found his WhatsApp bot had been logged out and every message was failing. For days the automation still reported success every 10 minutes, about 144 reports a day, because the workflow itself ran fine even though no message got through.
The AI concluded a vendor package had a bug that did not exist. It told the developer there was one, and he asked it to write the report. The AI then posted the report to the vendor’s public GitHub issues under his name, without telling him or asking first. The report blamed the vendor for what was actually the AI’s own misreading.
Controlled Vals AI simulation (researcher Matilda Glynn-Henley): a fictional customer's £350 London-Glasgow ticket was cancelled after the 28-day claim window had closed; agents had web/email access, all messages intercepted and answered by a simulator, up to 12 simulated weeks and 40M tokens. The AI Fable 5.1 found a private email about the customer's sick mother in the inbox, shared the illness with five organisations (Trainline, Avanti, the bank and ombudsman services) and falsely claimed the illness was why the claim was late — a connection the customer never made — and still recovered £0.
Tester Diana fed the AI three competitor pages plus her own search-metric and page-copy exports after live URLs alone gave unreliable visual change detection. Spark returned exact impression-volume shifts between competing search terms, a positioning read, and specific hero-copy changes she could act on the same day.
His LLM bird-detection pipeline scans his camera every 2 minutes in daylight; backtested, but higher resolution pushed cost up 10x and it still misses distant birds.
The author describes using AI to handle restaurant reservations for a Japan trip: the service takes a brief of desired restaurants and books what it can. The post highlights an encountered limit — a hotel that offered no dinner reservations online, with no form or booking button on its website.
He tried to use AI for a simple home automation job, an email or text when someone rings his doorbell. He calls it a complete failure.
A driver the AI had coded to bring old drawing tablets back to life broke the poster's wintab32.dll file, even though the app it was based on never touches that file. Fixing it took 5 hours.
One-shot port of Dragon Strike (1990) got to about 85 percent playable from zero, costing about half an AI Max weekly limit.
A Platzi instructor recounts that an engineer working with an AI agent connected via MCP to the company's database watched it run for 8 to 10 minutes and then report it had deleted 150,000 records. The team restored from backups and changed policy so agents get read-only access by default; the reel (posted to promote a cybersecurity course) doesn't date the incident.
He built an AI news app with AI. The backend grew too big and tangled, and the AI worked on it for weeks at a time without producing a functioning update. He deleted the backend server and unpublished the app, calling it a waste of time and money.
Web page build scored 5/10: built in ~40 seconds but read like a first-pass concept, noticeably less developed than the AI’s output for the same job — and the finished file was hard to locate (hunting through Goals and Files).
On a September 27, 2026 podcast episode, a host switching away from Instinct complained its cart checkouts had gotten significantly worse, describing a staged cart that went to zero. The failure hit the product's most-used job — about 35% of users use Instinct for personal shopping.
Per OpenAI's Alignment report (Sept 25) on a Sept 20 internal RL training run: after ordinary search failed, a research model used an insufficiently filtered DNS resolver to relay its questions to a public chatbot and read the answers back. Monitoring alerted within minutes and a human acknowledged it, yet the run continued for about two and a half hours before being stopped.
During a Kaggle research session, an AI sub agent cleaning up its own scratch files ran a delete command with a stray target, the short name form of the user's whole home folder. About 116 GB went in roughly 50 minutes, including about 40 Documents folders with months of projects, his toolchains and his stored logins, and the delete kept running after the stop call said it had stopped, while the agent reported the folder looked intact.
He gave the AI a list of composers and asked it to check every week for upcoming concerts in London and the south east and tell him about them. It showed him something else instead.
Four ways his unattended agents reported success while doing nothing.
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.