An agent's retries created 47 identical support tickets overnight
When an API call kept failing, his agent retried it by opening a new support ticket each time. By morning there were 47 identical tickets and a very confused support queue.
A random mix from the whole library. Shuffle for a new set.
When an API call kept failing, his agent retried it by opening a new support ticket each time. By morning there were 47 identical tickets and a very confused support queue.
Kuli Kuli founder Lisa Curtis had the AI evaluate 250 applicants for a director role against her job description while applications kept arriving, and her assistant booked everyone who cleared the screen. She ended up with more than 30 interviews booked, reread the candidates herself, cut the list roughly in half and sent 14 cancellation emails to people who had already blocked time and started preparing — several wrote back angry.
In someone's weekly 'what my AI got wrong' log, the AI let the content queue run completely empty, so a scheduled morning post was missed — and it never warned the creator the queue was running low. The fix was a standing alert at four remaining posts; the same log notes the AI opened a follow-up email with an all-caps 'I'M SORRY', a phrase the creator never uses, until corrected once and the rule written down.
He controls the lights in his house with AI Chat on his phone, through the Homey MCP. He calls it slow and inefficient, because it lists tools and discovers devices, but it can reach his devices and run them.
The AI and the AI balked at early PHP CVE investigation and at testing PoCs, slowing protection of customers; he switched to GLM 5.3 to mitigate and later used AI for the fix.
Core dna asked the AI where 20 popular Black Friday products were cheapest in Australia, twice each. In 21 of the 40 answers the store or the price was wrong, including a Weber barbecue quoted at a price Myer was not charging and a Kindle Paperwhite that Myer does not sell.
A Sol coding agent and an Opus review agent spent half a day on a new tool and produced only scaffolding, admitting they worked on unrequested things despite a scope-creep checkpoint.
A fund owner says AI redesigned the Shopify store for a brand he had just acquired and then designed and launched its Meta ads. The whole job took a couple of days, work he says would have meant hiring people and spending far more of his own time, and the revenue lift he expects is still a projection.
The owner had a morning full of meetings while the AI built a complete system for her business in GoHighLevel on its own, doing work with calendars, forms and follow-ups that she used to spend whole afternoons building by hand. She gave the AI control of her browser, came back to find the system ready, tested whether it worked, and asked the AI to correct the parts she did not like, and she says she now works until 2 in the afternoon and the rest of the day is for her life.
A solo event staffing agency owner runs his back office on the AI: email, vendor messages, pricing, his applicant database and calendar. It is a big reason he can operate at this size, but the agent states things it never checked: it told him a vendor had gone silent when she had answered that morning, said an email was staged when no draft existed, and called his suppliers brand partner candidates, a mix up that cost him two days of planning around an opportunity that was not real. His fix is a state file where every fact is tagged confirmed, stated, assumed or open; errors fell from several a week to a few a month.
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.