Building LLM apps that actually work starts with better chunking. Ricardo Ferreira breaks down how smart text segmentation helps embeddings return answers that make sense. Learn how to structure content for context, reduce noise, and improve vector search accuracy. Whether you’re creating semantic search, RAG pipelines, or conversational agents, mastering chunking is the key to more reliable results.
9 minutes
Key topics
Why chunking is critical for precise LLM responses
How to balance chunk size for accuracy and context
Fixed-size, content-aware, recursive, and semantic chunking strategies
Practical LangChain examples to test each approach
How to find the optimal chunk size for your use case
