Agentic AI Design Training in Kuala Lumpur, Malaysia

This course introduces participants to the design principles and frameworks for building Agentic AI systems—autonomous, reasoning, and tool-using AI agents powered by LLMs. It covers the architectural foundations, workflow design, and practical implementations of agent-based systems across industries. Participants will explore how to design, test, and deploy agentic systems with attention to scalability, safety, and ethics.

Fundamentals of Agentic AI Design

Introduction to Agentic AI

• From generative AI to agentic AI

• Core principles: autonomy, reasoning, planning, feedback loops

• Overview of frameworks: LangChain, LangGraph, AutoGPT, crewAI

Building Blocks of an AI Agent

• Models (LLMs, chat models, embeddings)

• Prompts, tools, and memory

• Architectures: reactive agents vs. deliberative/planning agents

Designing Workflows for Autonomy

• Task decomposition and planning strategies

• Memory design: short-term, long-term, and vector store-backed

Advanced Agent Design & Applications

Multi-Agent Systems

• Collaboration between agents (task delegation, orchestration)

• Communication protocols for agents

Safety, Ethics, and Governance in Agent Design

• Risks of autonomy: hallucination, overreach, compliance issues

• Guardrails, monitoring, and human-in-the-loop design

• Responsible AI principles for agentic systems

Hands-on Exercises

Summary and Conclusion