AP018: Context Engineering for LLMs and Agentic AI
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AP018: Context Engineering for LLMs and Agentic AI
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About this listen
Your Hosts: Fred and Melody
This podcast provides a comprehensive overview of context engineering for large language models (LLMs) and AI agents.
It explains that this field involves dynamically providing LLMs with all necessary information, including user input, retrieved knowledge, developer instructions, and access to tools, to ensure successful task completion.
It differentiates context engineering from prompt engineering, positioning the latter as a subset of the broader discipline.
Key principles discussed include incorporating relevant information, equipping models with tools, dynamic context assembly, and proper formatting, all aimed at setting the LLM up for success. The text also covers memory management strategies, reasoning and acting paradigms like ReAct, and the utility of function calling for structured tool use.
This podcast is based on this technical article.
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