Agentic AI Playbook: Complete Guide for Tech Leaders

About this course

This course contains the use of artificial intelligence for generating the slides based content. Are you leading product teams or innovation initiatives and wondering how AI agents like AutoGPT, CrewAI, or LangGraph actually work—and how they apply to your world?

This course offers a practical, non-technical guide designed specifically for product managers, tech leads, and strategy heads who want to turn AI buzzwords into real impact.

Agentic AI is more than just chatbots and copilots. It represents a major shift in how software operates—from reactive prompts to autonomous, goal-seeking agents that can plan, decide, and act across tools and systems.

This course provides a strategic roadmap to help you understand, evaluate, and implement Agentic AI in your products, platforms, and workflows—without needing to write a single line of code.

In this six-week structured guide, you'll gain clarity on:

• What Agentic AI is and how it differs from traditional AI and LLM-based copilots
• Key agent components: tools, memory, goals, reflection
• Design patterns: single-shot, reactive, planning-based, multi-agent systems

The agent ecosystem: LangGraph, BeeAI, CrewAI, AutogenTool execution with plugins, APIs, and MCPsUnderstanding GPT-4o, Claude, and open-source or local LLM options

No-code and low-code platforms for agent building

Internal agents for research, data synthesis, and roadmapping

Customer-facing agents for onboarding, demos, and support

Agents for DevOps, data monitoring, and documentation

Frameworks like the Use Case Canvas to identify agent opportunities

Single vs multi-agent architectures and when to use them

Orchestration models: parallel, sequential, hierarchical

Agent roles: researcher, coder, planner, critic

Integrations with tools like Slack, Notion, CRMs, GitHubPlanning pilot projects with measurable KPIsDefining team roles and readiness

Legal, ethical, and governance frameworks for agentic systems

Scaling your age

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