Building an AI agent is the easy part now. Trusting it with your company’s data, credentials, and credit card? That’s where things get interesting. That’s exactly the problem Google Cloud is tackling this month with Advent of Agents Season 3, a free, 31-day tutorial series running through October 2026. Here’s what it is, why it […]
Read More →Imagine hiring a brilliant assistant, handing them a 200-page manual, and asking a question. They read all 200 pages, answer, and then promptly forget everything. Next question? They read all 200 pages again. And you pay them by the page. That’s roughly how large language models (LLMs) work by default. Prompt caching is the fix. […]
Read More →Docker Sandboxes (sbx) is Docker’s dedicated security tool for running autonomous AI coding agents — Claude Code, Gemini CLI, GitHub Copilot, and others — inside fully isolated MicroVM environments. This post covers the core security architecture, essential CLI commands, and customization options, so you can evaluate whether sbx belongs in your AI-assisted development workflow. Table of Contents […]
Read More →Large Language Models (LLMs) all predict text, but they differ a lot in how they follow instructions, use context, handle tools, and optimize for safety, speed, or cost. If you treat them as interchangeable, you’ll ship brittle prompts. If you treat them as different runtimes with different affordances, you’ll get reliable results. This post explains the major differences across […]
Read More →A practical guide for software engineers navigating the evolving landscape of Large Language Models Introduction: Why This Matters As a developer in 2025, you’re likely interacting with Large Language Models (LLMs) daily—whether through coding assistants, chat interfaces, or integrated APIs. But here’s the thing: not all LLMs are created equal, and the way you communicate with […]
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