The two scariest parts of autonomous agents — runaway loops and exposed APIs

<p>Four agents entered an infinite loop in November 2025. They ran for 11 days. The bill was $47,000. Nobody noticed until it was over.</p> <p>The team was running a market

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<p>Your AI system isn't going to crash. It's going to drift.</p> <p>A recommendation engine making 1.4 model calls instead of 1. A retrieval pipeline fetching 5 chunks instead of

<p><em>The AWS Reliability Files, Part 1</em></p> <p>I told an AI a true fact about AWS. Then I had a second AI confidently insist it was wrong. Within one exchange, the first

<p>Your agent passed all the tests. It's been running in production for three weeks. And it has been quietly wrong the entire time.</p> <p>This is not a hypothetical. Galileo's

<ul> <li>GitHub repository: <a href="https://github.com/gezilinll/agent-grove" rel="noopener noreferrer">https://github.com/gezilinll/agent-grove</a> </li> <li>Online

<p>You've heard of DevOps. You've heard of AIOps. You've probably heard of MLOps.</p> <p>But there's a category that doesn't exist yet — and it's the one the AI industry needs

<h1> Production Was Down… But Everything Looked Normal 🤯 </h1> <blockquote> <p>A real debugging story about silent failures and why thinking matters more than tools.</p>