AI & ML

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The “Data Center Rebellion” Is Here

This post first appeared on Ben Lorica’s Gradient FlowSubstack newsletter and is being republished here with the author’s permission. Even the most ardent cheerleaders for artificial intelligence now quietly concede we are navigating a massive AI bubble. The numbers are stark: Hyperscalers are deploying roughly $400 billion annually into data centers and specialized chips while

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Fast Paths and Slow Paths

Autonomous AI systems force architects into an uncomfortable question that cannot be avoided much longer: Does every decision need to be governed synchronously to be safe? At first glance, the answer appears obvious. If AI systems reason, retrieve information, and act autonomously, then surely every step should pass through a control plane to ensure correctness,

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Soft Forks: How Agent Skills Create Specialized AI Without Training

Our previous article framed the Model Context Protocol (MCP) as the toolbox that provides AI agents tools and Agent Skills as materials that teach AI agents how to complete tasks. This is different from pre- or posttraining, which determine a model’s general behavior and expertise. Agent Skills do not “train” agents. They soft-fork agent behavior

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Soft Forks: How Agent Skills Create Specialized AI Without Training

Our previous article framed the Model Context Protocol (MCP) as the toolbox that provides AI agents tools and Agent Skills as materials that teach AI agents how to complete tasks. This is different from pre- or posttraining, which determine a model’s general behavior and expertise. Agent Skills do not “train” agents. They soft-fork agent behavior

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