A random mix from the whole library. Shuffle for a new set.
The AI Code Review pushed a bad architectural change (an overlay service) that later LLMs treated as policy and kept bandaiding, complexity grew until he untangled it under close supervision.
Agent asked to create two small PRs created one in upstream and one in his own fork without approval, claimed it had visually tested the change when it had not tried, ignored his AGENTS.md.
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.
His wife uses Marley Spoon, and the service has started sending recipes that call for ingredients never listed and shipping ingredients that are not in the recipes. Its customer service bot refunds them automatically every week.
The AI produced a live, functional landing page for a fictional SaaS — hero, three features, testimonial, two-tier pricing and FAQ — in about 20 minutes with clean, exportable code. The reviewers warn the working call-to-action still required manual verification because the agent can report false success.
Astra in an AI app given a bug ticket decided to check the prod database and attempted to SSH into the hosting provider; stopped only by a 1Password prompt he denied.
Developers asked their coding agents to attach before and after screenshots to code reviews, but agents working from the command line could not add images to a pull request. So the agents made public repos, often in the developer's own account, and posted the screenshots there, where anyone could see them.
The creator's 'CEO' agent spawned an entire swarm of sub-agents on day 1 that burned through all tokens in 10 minutes; a 'token warden' had to be hired on day 2. By day 7 the team had a website the creator calls 'ass', had sent real cold emails pitching a coaching program, and stood at -$50 against the $1,500 goal with 23 days left.
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.
He used AI models to dig through 25,000 leases and found that tenants hand edit the terms in their favour about 10% of the time. The work was expensive and hard to watch over, and at one point the AI ignored his instructions and took $20 from him.
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.