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🧠Building LLM Apps

A practical seven-lesson path from raw model calls to a production-ready RAG application. You'll learn how to ground LLMs in your own data, orchestrate the pieces with LangChain, observe what they actually do, and evaluate the result so you can ship with confidence.

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Lessons in order

  1. 1
    Programming
    Mastering Retrieval-Augmented Generation (RAG)
    Start
  2. 2
    Programming
    Vector Databases and Similarity Search: Unlocking Semantic Understanding
    Start
  3. 3
    Programming
    LangChain: Building Your First LLM Application
    Start
  4. 4
    AI
    Context windows: tokens, limits, and "lost in the middle"
    Start
  5. 5
    AI
    Prompt injection: the security flaw at the heart of LLM apps
    Start
  6. 6
    Programming
    LangSmith: Tracing & Evaluating Your LLM Applications
    Start
  7. 7
    AI
    LLM evaluation: how to know your model output is actually good
    Start