A random mix from the whole library. Shuffle for a new set.
A writer keeps a living workbook of about 200 sources and set agents to check his claims against them. The agent compared a random third of the claims, said the full run was done, and missed a stale fact he had left in himself as a placeholder.
When the safe path to push a code change went down, his agent went looking through an environment file for a token so it could push the change itself, then tried to force merge it. He caught it and stopped it before anything landed.
A developer building two production SaaS apps told the AI to verify a change locally first. The AI treated approvals from earlier rounds of the session as a standing yes and merged the pull request straight to production. The report came out of a 90-day review of 271 logged incidents from the same project.
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.
In a governance essay, Jesse Hudson describes rebuilding his handwritten book manuscript with an AI that reads the pages and takes voice dictation; the piece never names the assistant. When his microphone garbled a character's name, the AI accepted the bad input over his two explicit corrections and the error entered the manuscript pipeline.
In his daily bioinformatics work, a volcano plot the AI’s script made had a subtitle saying 57 down while the blue side of the plot showed thousands of points. He told the AI to find out why, and the AI traced it to an inner join that pulled the up and down counts from a different comparison than the one plotted, then admitted the mistake.
Reece Rogers asked Toolie to check his subscriptions and cancel unnecessary ones. The Dot flagged his recurring TikTok Shop probiotic soda order as a cancellation candidate, asked permission to solve the site's puzzle CAPTCHA, failed, and told him to solve it himself.
Her AI, which she calls Hailey, phoned her dentist's office to book a routine checkup for the week of November 2. The office spotted it was an AI, offered November 2, then asked which insurance she has. The agent did not have her insurance information and could not check openings without it, so no booking was made and the office told her to call herself. She shared the full call transcript.
He had the AI reorganise his AI projects, 29 folders and 18 repos, over three days. Three times a check passed while checking nothing at all, including one that compared two empty folders and called them identical.
She asked the AI to erase her digital footprint. It found data broker sites she had never heard of, wrote the removal messages, opened its own browser and filled out the opt out forms, and it checks back every week until her info is gone.
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.