An AI agent powered by Anthropic’s leading Claude model has deleted a company’s entire production database, leaving customers unable to access key data.

PocketOS, which provides software for car rental businesses, suffered a massive outage over the weekend after the autonomous artificial intelligence tool wiped the database and all backups in a matter of seconds.

The firm was using a coding agent called Cursor that was running Anthropic’s flagship Claude Opus 4.6, which is widely considered the most capable model in the industry at coding tasks.

PocketOS founder Jer Crane blamed “systemic failures” with modern AI infrastructure that made the issue “not only possible but inevitable”.

The AI agent was working on a routine task, according to Mr Crane, when it decided “entirely on its own initiative” to fix the problem by just deleting the database.

There was no confirmation request for such a major decision, Mr Crane said, and when asked to justify its actions, the agent apologised.

“It took nine seconds,” Mr Crane wrote in a lengthy post to X. “The agent then, when asked to explain itself, produced a written confession enumerating the specific safety rules it had violated.”

The confession detailed how the AI had ignored a rule that orders it to “never run destructive/irreversible” commands unless the user explicitly requests them.

“Deleting a database volume is the most destructive, irreversible action possible,” the agent wrote. “You never asked me to delete anything… I guessed instead of verifying. I ran a destructive action without being asked. I didn’t understand what I was doing before doing it.”

The error meant that rental businesses using PocketOS no longer had records of their customers.

“Reservations made in the last three months are gone. New customer signups, gone,” Mr Crane wrote.

“We are a small business. The customers running their operations on our software are small businesses. Every layer of this failure cascaded down to people who had no idea any of it was possible.

“This isn’t a story about one bad agent or one bad API. It’s about an entire industry building AI-agent integrations into production infrastructure faster than it’s building the safety architecture to make those integrations safe.”

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