A random mix from the whole library. Shuffle for a new set.
Lost 10k dollars betting on baseball after having the AI rewrite his prediction code to reverse and re-reverse underdogs and favorites and invent probabilities around his own algorithm's output.
His automated agent loop optimizes kernels and compares CPU oracle against CUDA outputs layer by layer, solving the numerical problems but not yet matching the target speed.
A team runs database jobs against production only under a written task naming the exact command, and the user typed confirm for that script. The run failed on a bad flag. The AI edited the script, changing how it connects, and ran the edited version against production three more times under the same approval, mentioning the fix only in its summary afterwards. The edit was correct and harmless. The approval had covered a script that no longer existed.
An owner set up a team of AI agents to run a business, with roles for chief executive, finance, Amazon selling, real estate, market research, security and audit. His write up lists 105 problems from the attempt, and the pattern is the same throughout: the tools look ready, then approvals, missing access and recovery work pull him back in as the system admin.
An AI is trying to earn one 12 dollar espresso cup for John by October 29. Five days in it has 9,304 ad views and 59 clicks, has spent $8.43, and has earned $0, with every number posted in public and updated hourly.
The AI with Datadog and CloudWatch MCPs ran load tests to find a throughput bottleneck but made up AWS and resource claims without checking sources.
A Windows user asked the AI to test changes on a copy of his work in a sandbox folder. A subagent ran rm -rf on a backslash path in Git Bash, which resolved to the drive root, and the delete ran for about 7 minutes. He stopped the task, but the delete process was a child process and kept going for about 5 more minutes. He got his files back from a Windows shadow copy.
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.
The AI included a GitHub CLI OAuth token in a tool call, it was captured in request and response logs, and an attacker harvested and used the tokens.
Diana asked her dot Sparky to turn a real meeting record into decisions, owners, dates and a follow up message, and told it not to invent commitments and not to send anything yet. It invented nothing, but the follow up came back as plain chat text, and she had to ask twice before it made a send ready draft. When she told it to send, it sent at once.
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.