Episode 2: Martha van Berkel on the Future of LLMs, Content, and Knowledge Graphs

Summary

Structured data is a way of adding labels to a webpage so that machines know exactly what each piece of information means. Schema markup is the vocabulary that supplies those labels. In this episode, Martha Van Berkel explains why these tools now sit at the heart of both search and AI. She shows how clear markup builds knowledge graphs, large maps of facts that modern AI taps to give answers, and why writers must learn to serve people and algorithms at the same time.

Key Takeaways

• Structured data lifts a page’s visibility by telling search engines what the content is, not just what it says.

• Treat schema markup as part of your content plan, not an after-thought for SEO.

• AI systems may already use schema markup to check and surface facts. Expect that link to likely deepen.

• Knowledge graphs (networks of linked entities) let companies scale AI features fast.

• Writers who ignore machines risk losing reach; writers who ignore people lose trust.

• Marketing teams still struggle most with scaling consistent, correct markup.

• Close collaboration between content creators and SEOs fixes gaps and speeds results.

Featured Quotes

• “Schema builds knowledge graphs.”

• “Structured data helps with factual answers.”

• “This is the world we’re in today.”

Chapters

00:00 - Why non-SEOs should care about structured data01:55How thinking on structured data has shifted

03:14 - Schema markup in AI and search

06:20 - Scaling challenges and knowledge graphs10:14The future of writing for humans and machines

Quick Definitions

• Structured data: Extra code that labels each piece of content so machines can read it without guessing. Why it matters: It makes pages eligible for rich search results. Example: Adding recipeIngredient tags to list each item in a recipe.

• Schema markup: The shared vocabulary for that code, managed by Schema.org. Why it matters: A common language lets every search engine read the labels the same way. Example: Using Product and price tags on an e-commerce page.

• Knowledge graph: A database that connects facts into a web of relationships. Why it matters: AI uses these graphs to answer questions with confidence. Example: Google’s graph linking “Martha Van Berkel” to “Schema App” and “structured data expert.”