Overview
This one-day Agentic AI Foundations course guides you through building autonomous, goal-driven AI agents using AWS technologies.
What will you get out of this course:
- Understand how Agentic AI differs from traditional conversational systems
- Explore tools such as Amazon Q, Kiro, and Amazon Bedrock Agents/AgentCore
- Learn design patterns, architectural strategies, and observability practices for agent systems
By the end of the course, you will be able to:
- Distinguish between workflow, autonomous, and hybrid agents
- Select suitable AWS services for agent development
- Develop basic implementation patterns and interoperability strategies
- Explain how to monitor, optimize, and scale agentic systems
Why Choose KORNERSTONE
- Accredited, practitioner-led, expert certificate trainers to provide high quality training
- Official training material included
- Practical, scenario-based learning – focus on application, not just theory
- Excellent Passing Rate
Skills Covered
In this course, you will learn to:
- Summarize the evolution of Agentic AI and define what makes something “agentic”
- Identify core components of agentic systems
- Distinguish between workflow, autonomous, and hybrid agents
- Compare AWS service options for Agentic AI
- Describe capabilities and use cases of Amazon Q Developer, Amazon Q Business, and Kiro
- Explain Amazon Bedrock AgentCore and Amazon Bedrock Agents fundamentals
- Identify basic implementation patterns for Agentic AI
- Describe observability and interoperability patterns for production agentic AI systems
Prerequisites
We recommend that attendees of this course have:
- Generative AI Essentials or equivalent work experience
- Basic AWS knowledge and software development experience
Target Audience
This course is intended for:
- Software developers new to Agentic AI seeking foundational knowledge
- Technical professionals exploring AI capabilities and interested in core components and applications of agentic AI
- Development teams evaluating Agentic AI solutions and needing to differentiate between agent types
- AWS Users expanding into Agentic AI, including current users of Amazon Q Developer, Amazon Q Business, and Amazon Bedrock Agents
Course Curriculum
Module 1: From LLMs to Agents
- Understanding Large Language Models (LLMs)
- Innovations powering agents
- Evolution timeline from LLMs to Agents
Module 2: Exploring Agentic AI
- Understanding Agentic AI
- Types of AI agents
- Agentic AI applications
Module 3: Understanding Agentic AI Workflow
- Workflow patterns
- Amazon Bedrock flows overview
Module 4: Introducing Autonomous Agents
- How Autonomous Agents work
- ReAct
- ReWoo
- Multi-agent collaboration
- AWS Agentic AI solutions
Module 5: Amazon Q and Agentic Development Tools
- Amazon Q Developer
- Amazon Q Business
- Amazon Q in AWS Services
- Kiro: AI-powered IDE with spec-driven development
Module 6: Agentic AI with Amazon Bedrock
- Amazon Bedrock Agents
- Amazon Bedrock AgentCore
- Hands-on lab: Explore Amazon Bedrock Agents integrated with Amazon Bedrock Knowledge Bases and Amazon Bedrock Guardrails
Module 7: Building DIY Solutions
- DIY solutions
- Observability and Monitoring
- Agent Interoperability
Module 8: Course Wrap-up
- Next steps and additional resources
- Course summary
Dates & Locations
October 7, 2026
October 23, 2026
November 18, 2026
December 9, 2026

Exam & Certification
There is no exam directly associated with this course. However, AWS offers an extensive portfolio of industry-recognized certifications that can help you stand out as a tech professional and beyond. Achieving AWS credentials is one of the most effective ways to validate your skills and accelerate your career.
With our expert-led training, you’ll be prepared to:
- Master in-demand capabilities across Cloud, Data & AI, and Cybersecurity — areas driving global digital transformation.
- Prove your expertise with a globally respected credential recognized by employers worldwide.
- Advance your career by enhancing your credibility, increasing your earning potential, and opening doors to new opportunities.
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