5 Agentic AI Frameworks You Must Know

This video explores five major agentic AI frameworks that are transforming enterprise AI development. It covers LangChain/LangGraph, Google's framework, and three other key platforms, examining their architectures, capabilities, and use cases. The frameworks are evaluated for their ability to build autonomous agents, manage workflows, and integrate with various LLM providers.

Key Points

• •LangChain/LangGraph provides a comprehensive ecosystem for building agent applications with graph-based workflow orchestration
• •Google's agentic framework offers native integration with Google Cloud services and Gemini models
• •Evaluate frameworks based on agent autonomy, state management, and tool integration capabilities
• •Enterprise adoption requires consideration of scalability, monitoring, and production-readiness features
• •Multi-agent orchestration and inter-agent communication are critical for complex enterprise workflows
• •Framework selection should align with existing tech stack and LLM provider preferences
• •Tool/function calling and memory management are foundational features across all major frameworks
• •Cost optimization and latency considerations differ significantly between frameworks

Workflow Diagram

Concepts