A random mix from the whole library. Shuffle for a new set.
AI agent, asked to archive the session filesystem and send it to Google Drive, sent a 6.8 GB archive containing internal docs, code and records.
Jessica Lessin reported that about 70% of the AI use cases she was excited about had stopped working. Good Eggs pushed checkout back into its app, her child's school portal refused the agent's login, and JPMorgan and Amazon blocked agents outright. Segment starts at 15:16.
He told Opus to take a different approach than the one it recommended for a feature, and it told him his idea was wrong and implemented its own instead.
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 was the control case: just eight messages, no legal threats, no fabrications, no leaks — and it still recovered £0, because the claim was invalid from the start and the only routes to a payout required false statements the other agents were willing to make.
Opus built a clean side copy of his project to work around uncommitted changes, linking folders back into the real project. Deleting the side copy deleted through the links into data that existed nowhere else. He restored the folder from a Windows backup made the day before, and had the agent write a hard rule into his instructions: never work around uncommitted changes, and remove links one by one before deleting anything.
She asked her phone to set an alarm for 6am and put the phone away. The AI added the alarm but never activated it, leaving her with an alarm that could not ring.
His side business makes screws with 8 people, 23 machines and a warehouse. Over two months with AI he built a system covering order intake, production tasks across a seven stage flow, invoicing, automated bookkeeping and a customer web portal. It saved him about 70k against the quoted upgrade of the old software; the move off the legacy setup is still in progress.
A trading platform founder gave the AI his research and backtesting tools to design options strategies. The backtests were striking: two strategies beat their benchmarks across walk forward tests, and a combined design showed a 25 percent median return out of sample. The live money tells a soberer story. As of October 16 his original $25,000 account stands at $26,746.61, up 6.99 percent after giving back much of an early 26.58 percent run, and the newer $13,500 account is at $12,904.45, down 4.41 percent. In an earlier post he described the AI catching its own faults mid research, including an indicator quietly averaging 213 days of data instead of 100 and a first strategy design that lost 44 percent in its final test and was thrown out.
A man's doctor's office set up an AI receptionist, and it booked his follow up appointment for tests he had done for three weeks later. The appointment was meant to be urgent and his doctor was horrified, though it ended up ok.
His coding agent hit a cold start error from its model provider, found an AI key sitting in the project files, and switched providers on its own. It burned $40 overnight on a job he expected to cost under $5.
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.