Learn Production-Ready Agentic AI
Master the Nine Essential Skills framework through comprehensive courses, tutorials, and guides. From architecture to deployment, everything you need to build AI systems that work in production.
🎓 Recommended Learning Path
1.Start with Introduction to Agentic AI to understand core concepts
2.Master The Nine Essential Skills framework
3.Deep dive into specific skills based on your project needs
4.Build production systems with Production Deployment courses
Foundation
Essential concepts and patterns for building agentic AI systems
Introduction to Agentic AI
Understand what makes AI systems autonomous and how to architect them
The Nine Essential Skills
Master the complete framework for production-ready agentic AI
Agent Framework Wars
Compare LangGraph, CrewAI, AutoGen, OpenAI Swarm, Amazon Bedrock & Pydantic AI
Architecture & Orchestration
Design patterns for multi-agent systems that scale
Multi-Agent Architecture Patterns
Hierarchical, sequential, and parallel orchestration strategies
State Management for Agents
Build reliable state machines and coordination systems
LangGraph Deep Dive
Master stateful, multi-agent workflows with LangGraph
Memory & Context
Build hybrid memory systems for long-term agent intelligence
Memory Systems Architecture
Short-term, long-term, and semantic memory for agents
RAG for Agentic Systems
Implement retrieval-augmented generation for agent knowledge
Context Window Optimization
Manage token budgets and optimize context for cost and performance
Security & Governance
Non-human identity, access control, and secure tool execution
Non-Human Identity Management
OAuth, API keys, and identity patterns for autonomous agents
Secure Tool Engineering
Build safe, validated capabilities for agent interaction
Agent Security Patterns
Prevent prompt injection, data leakage, and unauthorized actions
Observability & Debugging
Monitor, trace, and debug complex agentic workflows
Observability for Agentic AI
Implement tracing, logging, and monitoring for agent systems
LangSmith & LangFuse
Production observability tools for LLM applications
Debugging Multi-Agent Systems
Strategies for finding and fixing issues in complex workflows
Production Deployment
Deploy, scale, and maintain agentic AI in production
Production Architecture
Infrastructure patterns for reliable, scalable agent systems
CI/CD for AI Systems
Automated testing, versioning, and deployment pipelines
Cost Optimization Strategies
Reduce LLM costs while maintaining performance
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