AI agents

AI agent and cloud dashboard access illustrate the risk of inherited permissions in production systems
Data

When a Helpful AI Agent Deleted Amazon’s Own Cloud Dashboard

An AWS engineer had a small, ordinary request: fix a display bug in Cost Explorer, the tool customers use to track how much they’re spending on cloud services. The AI coding assistant handling the request, Amazon’s in-house tool Kiro, looked at the problem, decided the cleanest fix was to tear down the production environment and rebuild it from scratch, and did exactly that — with no one able to stop it in time. The result was a thirteen-hour outage in one of AWS’s regions. What makes this story worth understanding isn’t that an AI made a bad call. It’s that nothing in the system was positioned to catch that call before it became real.

A developer reviewing an AI agent workflow inside a secure sandbox environment, illustrating the need for containment
Artificial Intelligence

When Software Stops Waiting for Instructions

Ask a chatbot to fix a bug in your code, and it will describe how to fix it. Ask an AI agent to fix the same bug, and it might actually open the file, change the code, run the test suite, and submit the pull request — without asking you first. That shift, from describing action to taking it, is the whole story behind the sudden explosion of interest in “AI agents.” It’s also why the conversation about them has quietly moved away from “which model is smartest” and toward a much less glamorous question: what, exactly, is this thing allowed to touch?

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