3 Patterns for AI Agents That Analyze Stock Charts

<p>In December 2025, something remarkable happened in the fractious world of artificial intelligence. Anthropic, OpenAI, Google, Microsoft, and a constellation of other technology

<p>A few months ago I had a question that didn't let me sleep. When people ask ChatGPT "what's the best tool for X", which brands actually get mentioned? And more importantly:

<h1> Google Remy and Meta Hatch: The Technical Architecture Behind 24/7 Personal AI Agents </h1> <p>Two big AI agent stories broke this week that every developer building on top

<p>Everyone's building agents. Most are building them wrong. Not because they lack skill, but because they lack the right mental models. Before you write a line of code, you need

<p>Most AI agents sound impressive until you ask for something that depends on the present moment:</p> <blockquote> <p>"What's Apple trading at right now?"<br /> "Show me the

<p>If you’ve browsed agent engineering discussions recently, you’ve seen the same hype everywhere: MCP (Model Context Protocol) is the new standard for AI agents. Every new

<h1> Anthropic Managed Agents Architecture: Decoupling Brain from Hands </h1> <p>Anthropic published <a href="https://www.anthropic.com/engineering/managed-agents" rel="noopener

<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