Experiments at work

In building AI systems, we often obsess over model capabilities, prompt engineering, and token efficiency. But there's a hidden cost that compounds silently: context pollution. And most AI assistants today don't let you do much about it. The Problem: Everything is Always Loaded Imagine this scenario. You're using Claude Code (or similar assistants) and you want to write a blog post using the write-blog skill. That skill talks to the Blogger API via an MCP (Model Context Protocol). Simple enough. But here's the catch: Claude Code loads every single skill and every single MCP into your context window by default. This means when you're writing a blog, the write-linkedin-post skill is also in context. And it loads the LinkedIn MCP. Along with tools for email, databases, APIs you might never touch. Your context window is now polluted with information irrelevant to your current task. These tools sit there, consuming tokens, complicating the model's decisio...