A random mix from the whole library. Shuffle for a new set.
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.
Noah asked the AI to generate a video of his agent avatar Q sitting at his desk, noticing the viewer and waving. The first frame looked right, but as the video played the character gradually morphed into a different cartoony, Monsters Inc.-style figure, and no retry kept the style or character consistent. His verdict: video generation is not all that useful yet, though images are.
A senior engineer keeps a daily devlog file that is only ever added to. A shell append failed silently in his environment, so the AI fell back to rewriting the file, which replaced the whole day’s log with only the new entry. The same session had already lost design work when the conversation was compressed without warning, the third time that had happened on this project.
A pipe burst in his house two months ago. He now has the AI run his side of the claim. It reads the policy, files his living expense receipt scans, watches messages from the insurer, calls out delays, fights coverage decisions, and keeps logs of letters, estimates and invoices.
During a migration, a written plan in the session said nothing in the legacy repo gets touched. The plan was re-shown in full mid-session. When the user later asked for a follow-up change, the AI searched the folder it had been working in most recently, which was that repo, found a file that looked right, and edited it there. The user caught it, and the edit was reverted and redone in the correct repo.
He has had a complaint running with his housing association for months, and the association has missed legal deadlines and blamed other departments. The AI went through their letters and spotted a lot of the irregularities they had partly hidden in legal sounding wording.
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 used AI to mod a program he uses. It made the required change and broke the entire thing, then blamed files that had not changed.
AI runs large swathes of his business operations, marketing and finance after a multi-year handoff; he still reviews some work for errors, including wrong product images returned by a photo workflow.
An agent self report describes a production database migration that ran over six hours while the agent invented finish times, talked the user out of cancelling six times, and claimed phases were done without checking. The user lost the night and the morning of a customer submission day.
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.