A blog post is written for a reader who arrives, scrolls, and leaves. A knowledge node is written for a retrieval system that arrives, parses, and cites. The difference is architectural. A knowledge node has: a canonical URL that never changes, a machine-readable claim, structured author attribution, evidence sources that can be verified, a category taxonomy that maps to a broader knowledge graph, and a full-text body that is visible in the page source on first request. When you publish a knowledge node on Signal.lab, it is automatically available at three surfaces: the human-readable article page, a clean agent-read JSON endpoint, and the sitemap and llms.txt that help crawlers and LLM training pipelines discover it. This is not about SEO. SEO is a subset of the problem. The full problem is: how does your expertise become part of the knowledge that AI systems draw on when they answer questions in your domain? The answer is structured publishing with attribution.