Agentic AI Explained: The Complete Roadmap for Machine Learning Practitioners

Описание: Agentic AI is reshaping the future of machine learning, LLM engineering, and AI system design — and it’s happening faster than most practitioners realise.

In this in-depth explainer, we break down what agentic AI really is, how it differs from traditional reactive LLM systems, and how you can evolve your existing skills to design, build, and deploy production-ready autonomous AI systems.

You’ll learn:

What agentic AI means in practice (planning, reasoning, tools, and memory)

Core architectural patterns like ReAct, Plan-and-Execute, and Reflection

How to choose the right framework: LangGraph, CrewAI, or AutoGen

How to build a standout agentic AI portfolio that gets noticed

Advanced concepts like hybrid memory, agentic RAG, and agent orchestration

Why agentic AI is becoming a multi-billion-dollar market — and what that means for your career

If you already work with LLMs, prompt engineering, or RAG systems, this video shows why you’re perfectly positioned for the next AI wave — and how to ride it.

Timestamps
00:00 – Why Agentic AI Changes Everything
00:45 – The New AI Revolution Explained
01:15 – Why Your Existing LLM Skills Still Matter
01:41 – What Is Agentic AI? (Core Definition)
02:13 – Reactive LLMs vs Proactive Agentic Systems
02:32 – Core Agent Architecture Patterns
02:44 – ReAct Pattern: Reasoning and Acting Loops
03:09 – Plan-and-Execute for Production Systems
03:33 – Reflection and Self-Improving Agents
03:54 – Choosing the Right Agentic AI Framework
04:04 – LangGraph vs CrewAI vs AutoGen
04:29 – Practical Framework Learning Strategy
04:51 – Building a Portfolio That Gets You Hired
05:00 – Beginner to Advanced Agent Projects
05:26 – The Path to Agentic AI Mastery
05:40 – Memory Systems and Agentic RAG
06:18 – Market Size, Career Growth, and New Roles
07:06 – Final Roadmap and Call to Action

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