Checkout the roadmap: https://www.krishnaik.in/ai-roadmaps
Agentic AI involves creating autonomous systems that use Large Language Models (LLMs) to plan, reason, and act to achieve goals, rather than just generating content. To learn this, focus on mastering frameworks like LangGraph, CrewAI, and AutoGen to build multi-agent workflows, and focus on agentic RAG for data access. Key skills include planning, tool usage, and human-in-the-loop interaction. 
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visit : https://krishnaik.in/liveclasses

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A structured 7-step learning roadmap for building production-ready agentic AI applications. The steps cover: (1) LLM fundamentals and ReAct patterns, (2) core components including memory systems and context engineering, (3) orchestration with LangGraph and multi-agent architectures, (4) RAG and retrieval techniques including vectorless RAG, (5) design patterns like router and reflection agents, (6) safety, guardrails, and evaluation, and (7) production deployment using MCP protocol, cloud platforms, and observability. The roadmap is designed to remain relevant as new tools and patterns emerge by providing a stable framework to slot in new developments.

Learn Agentic AI in 2026 With These 7 Steps