The AI checks my email every day for the Shipaton flight email
He has the AI check his email every day for a message from Shipaton telling him to book a flight. He is still waiting for that email to land.
A random mix from the whole library. Shuffle for a new set.
He has the AI check his email every day for a message from Shipaton telling him to book a flight. He is still waiting for that email to land.
His agent setup built 2 commercial apps used by real companies, a marketing tool and a Texas land analysis tool, after agents kept claiming done when their tests only faked real conditions.
Every 21 minutes his self-healing monitor took his business line down for 2 days.
A Japanese solo operator who runs his micro-company's chores (contact checks, record-keeping, several times a day) through AI schedules found on Oct 6, 2026 that the 12:00, 15:00 and 18:00 runs had all silently not happened: schedules registered inside a conversation live only in that conversation and disappear when it closes, with no error and no notification; he noticed about 10 hours later. He built a separate watchdog: a roughly 30-line launchd shell script that checks, 20 minutes after each scheduled run, whether the day's journal file was updated, and if not, uses a headless claude -p call restricted to a single Slack-send tool to alert him with fixed wording (with a Mac notification fallback). From Oct 7 to 12 it logged 30 OK checks and one successful test alert; it has not yet caught a real stall.
He found a problem on his website with the embedded Cal.com widget he uses for people contacting him. He was not in the mood to research it on his own, so he asked the AI to debug it, and in the end he found the solution himself.
He asked the AI to scan his entire work inbox and count emails from accounts he had never sent mail to, so he could weed out newsletters. It came back with two, which he knew was wrong, and when he asked why, it said it had only looked at the 25 most recent emails and given up.
Last spring he gave an agent an API key with no cap on it. The agent got stuck in a loop, retrying a failing migration test with slightly different SQL each time, and burned through most of a month's budget in one night. Nothing malicious, just a loop with no exit. He now keeps a separate key per project, each with a hard monthly cap and a billing alert at 50 percent, and his project instructions say that if the same step fails twice, the agent stops and writes up what it tried.
Diana gave the AI Fable 5.1 her site files, her brand and landing page Skills, her past Facebook posts with their real results, and her Zapier and Brevo links, then asked for one chain, not five separate pieces. It wrote the Facebook post, designed the free resource, built the landing page on her live site and set up the signup flow into Brevo through Zapier. The page is live. She made one fix to the page layout. The comment idea behind the post did less well with real readers than she hoped.
Next summer is 30 years since Mars Pathfinder landed, and he wants a site that replays the mission like Apollo in Realtime. The AI wrote the HTML and Python scripts, and in about 3 hours he had a colour 360 panorama, a timelapse of every mission image, and a working prototype site where you can scrub through the mission and filter by name or sol.
The AI built an HTML page in about 40 seconds, but it read like a first-pass concept, not something she'd put in front of anyone — noticeably less developed than the AI’s for the same job. Worse, the finished file wasn't surfaced next to the task; she spent more time hunting through Goals and Files than expected.
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.