Explore a comprehensive video tutorial on simplifying the development of AI agents. Learn about a successful methodology for creating versatile agents like Jar3d, capable of orchestrating smaller tool-using agents to achieve goals. Discover how to leverage LangSmith for improved observability and debugging, implement structured outputs for enhanced system integrity, and utilize meta prompting for flexible, autonomous agent collaboration. Gain insights into the powerful combination of AI Agents, LangGraph, LangSmith, and structured outputs as the foundation for efficient AI system development. The tutorial covers key topics including meta prompting, adding new agents, structured outputs, setup processes, demonstrating observability with LangSmith, and additional considerations for AI agent development.
Building AI Agents - Simplifying Development with Meta Prompting and LangSmith
Data Centric via YouTube
Overview
Syllabus
Building AI Agents is Hard:
Meta Prompting:
Adding new Agents:
Structured Outputs:
Setup:
Demonstrating Observability LangSmith:
Additional Considerations:
Taught by
Data Centric
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