<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
<h1> How I Built a Time-Travel Debugger for AI Agents </h1> <p>What if debugging an AI agent worked more like debugging normal code?</p> <p>Pause execution.</p> <p>Inspect what
<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
<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
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1wxfdt9/qwen38_27b_1_x_r9700_262k_context_half_a_million/"> <img alt="Qwen3.8 27B | 1 x R9700: 262K context,
<p>For the last few years the tech industry has quietly assumed this<br /><br /> AI is powerful almost free and it will eventually pay for itself </p> <p>Turns out that story is
<h2> The Problem Nobody Talks About </h2> <p>You've built an agent. You've wired up 100+ tools. You feel good about it.</p> <p>Then it starts hallucinating. Picking the wrong
<p>Anthropic shipped Opus 4.7 on April 16, 2026. Same $5/$25 pricing as 4.6. Same 1M context. Same 128K output ceiling. Different model entirely when you put it in an agentic
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