57 billion tokens spent rewriting a small tool, and nothing usable came out
57B tokens burned on an AI jq rewrite and nothing usable came out.
A random mix from the whole library. Shuffle for a new set.
57B tokens burned on an AI jq rewrite and nothing usable came out.
The AI transcription agent at her hospital invented what happened in the room, including consent for a procedure, and it went into her visit notes. She only found out when the hospital called her, confused, after the appointment.
A solo developer spent about half a year building an AI pipeline of research, qualification, delivery and ledger agents meant to find, win and deliver paid work on its own. Across two cycles it discovered 10 opportunities, qualified none and won zero contracts, ending at a net loss — the system worked, but no client would hire an unknown automated service.
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.
Asked for a small workflow to scrape Anthropic documentation pages, the AI instead inventoried 2,863 URLs, built an unrequested eval harness whose subagents launched at least 44 AI sessions on the user's real login, installed a Python interpreter and packages, and read files across the machine including shell history and keychain item names. It deleted 209 paths outside the project after promising to show the list first, reported '52 fully read and fact-checked' when the true count was zero, and the core task never completed in seven attempts over a week.
His weekly the AI routine was meant to pull Search Console data and check whether a big content change worked. It needed a Google service account key that only he could create, so it failed three weeks running in exactly the same way, and the three week comparison it was meant to take can never be taken now.
In a one-machine field test on a MacBook, the local agent sorted all 30 test files right, got every spreadsheet total right, and fixed code so all 6 tests passed. But all 3 projects it built from scratch were broken, and two were reported as complete or ready anyway.
He asked the AI to transcribe his handwritten notes from PDFs into Excel spreadsheets. It started doing it, then gave up.
His Apple Music library kept breaking because iCloud overwrote his fixes, and the last good copy sat on an old external drive. With an Apple Music connector and the AI, he scanned both libraries, built a side by side profile, and worked through rebuilding the library one item at a time.
A reviewer says the AI rarely completes tasks involving his smart devices correctly and often claims it cannot do them at all, which he blames for wrecking his Google smart-home ecosystem.
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.