Claude Code isn’t a chatbot that suggests code. It’s an autonomous agent that inhabits your terminal, reads your entire codebase, runs commands, edits files, commits changes, and iterates until the job is done — all from a single natural language instruction. Table of contents The Fundamental Shift: From Autocomplete to Autonomous Agent To understand what […]
Read More →Anthropic shipped Code Review for Claude Code on March 9, 2026. A team of agents runs a deep review on every pull request. They built it for themselves first, then opened it as a research preview for Team and Enterprise customers. The announcement from Anthropic put it plainly: Code output per Anthropic engineer is up […]
Read More →I’ve spent the last few months living in Claude Code. If you’re wondering if it’s worth the hype, the answer is yes—but probably not for the reasons you think. It isn’t just a better autocomplete. It’s more like a competent pair programmer that actually reads your whole codebase, runs your terminal commands, and never needs […]
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 →If you’ve been anywhere near the AI development world lately, you’ve probably heard about MCP — the Model Context Protocol. And your first reaction was probably: “Isn’t this just… an API?” Fair question. Both let systems talk to each other. Both move data around. But MCP and APIs solve fundamentally different problems, and once you see […]
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