Voices of Search // A Search Engine Optimization (SEO) & Content Marketing Podcast Working w/Embeddings & Building Your Own Code
Nov 17, 2025
Ryland M Bacorn, founder and growth advisor at Boca Day, shares his expertise in leveraging embedding-based SEO tools to enhance content relevance. He reveals that 55% of online content is now AI-generated, reshaping SEO strategies. Ryland discusses how embeddings can optimize content production, clean keyword lists, and improve site search. He highlights practical approaches for non-developers to create embedding tools and shares a compelling case study showing significant gains from embedding-driven content shifts. Visualization techniques for stakeholder buy-in are also covered.
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Embeddings Translate Meaning Into Relevance
- Embeddings are numeric vectors that let machines represent the meaning of words, sentences, and documents.
- This representation enables search engines to return semantically relevant results beyond exact keyword matches.
Embeddings Extend Beyond On-Page SEO
- Embeddings power more than content: they improve site search, product recommendations, and internal linking decisions.
- Cosine similarity filters noisy keyword lists and highlights semantically relevant queries to prioritize.
Prototype With IDEs And Reset Chat Context
- Use modern IDEs like Cursor or Windsurf to prototype embedding tools without deep terminal knowledge.
- Iterate with chat agents, test frequently, and reset context to avoid "context pollution" in chats.