Prompt Engineering

    All about prompting.

    LLM for Devs

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    5 tiers of long-term memory and personalization for LLM applications (in-person workshop)
    Lesson 1

    5 tiers of long-term memory and personalization for LLM applications (in-person workshop)

    This lesson explores building a personalized AI assistant using OpenAI and Pinecone, demonstrating how to leverage vector databases for efficient long-term memory and context retrieval to create highly personalized responses. Different tiers of personalization are implemented and compared, ranging from simple system prompts to advanced vectorstore-based methods, highlighting the trade-offs between complexity and performance.

    51mJan 11, 2025
    Free
    Is LangSmith's Prompt Canvas the best UX for Prompt Engineering?
    Lesson 1

    Is LangSmith's Prompt Canvas the best UX for Prompt Engineering?

    Master Langchain's powerful tools, LangSmith for in-depth LLM project analysis and Open Canvas for streamlined prompt creation. Learn prompt engineering techniques, including using custom actions to refine prompts and achieve specific stylistic goals, like creating pirate-themed responses or simplifying text for different audiences.

    8mDec 3, 2024
    Member

    All lessons

    Is LangSmith's Prompt Canvas the best UX for Prompt Engineering?
    Lesson 1

    Is LangSmith's Prompt Canvas the best UX for Prompt Engineering?

    Master Langchain's powerful tools, LangSmith for in-depth LLM project analysis and Open Canvas for streamlined prompt creation. Learn prompt engineering techniques, including using custom actions to refine prompts and achieve specific stylistic goals, like creating pirate-themed responses or simplifying text for different audiences.

    8mDec 3, 2024
    Member
    5 tiers of long-term memory and personalization for LLM applications (in-person workshop)
    Lesson 1

    5 tiers of long-term memory and personalization for LLM applications (in-person workshop)

    This lesson explores building a personalized AI assistant using OpenAI and Pinecone, demonstrating how to leverage vector databases for efficient long-term memory and context retrieval to create highly personalized responses. Different tiers of personalization are implemented and compared, ranging from simple system prompts to advanced vectorstore-based methods, highlighting the trade-offs between complexity and performance.

    51mJan 11, 2025
    Free