Agentic AI Architecture (NL)
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What is Agentic AI Architecture
Agentic AI is rapidly becoming the next step after traditional and generative AI. Instead of single interactions, organizations are moving towards systems of collaborating agents that plan, decide, and act across workflows. This shift introduces new architectural challenges around orchestration, data, governance, and integration with existing IT landscapes.
This training helps you understand how to design these systems in a structured and scalable way. You will learn how to move from isolated AI use cases to end-to-end agent-driven solutions, including how to balance autonomy with control, and innovation with enterprise standards.
Our trainers bring hands-on experience from real client implementations, translating architectural theory into practical patterns, decisions, and proven approaches you can apply directly in your own environment.
Agentic AI Architecture focuses on designing systems where multiple AI agents collaborate to perform tasks autonomously within defined boundaries. Unlike traditional AI or GenAI solutions that respond to prompts, agentic systems can plan actions, interact with tools, orchestrate workflows, and learn from feedback over time.
An Agentic AI architecture typically consists of several layers, including an experience layer, an orchestration layer managing agent workflows, a data and knowledge layer for context and retrieval, and a model and infrastructure layer providing AI capabilities.
Key aspects include defining agent responsibilities, designing orchestration logic, integrating enterprise data and APIs, and implementing governance mechanisms such as guardrails, observability, and compliance. The goal is to create scalable, maintainable systems that can handle complex, end-to-end processes while ensuring reliability, security, and business alignment.
Agentic AI Architecture training focuses on designing scalable multi-agent systems, orchestration layers, and enterprise-ready AI architectures.
Who should attend Agentic AI Architecture
- Solution Architects who need to design scalable AI-driven systems and integrate agent-based capabilities into enterprise architectures
- Enterprise Architects who define reference architectures and governance models for AI adoption
- AI Engineers who build and implement agent-based solutions and orchestration workflows
- Software Engineers who integrate AI agents into applications and services
- Data Engineers who design data pipelines and knowledge layers for agentic systems
Prerequisites
Basic understanding of software architecture, APIs, and cloud platforms is recommended. Familiarity with AI concepts such as machine learning or generative AI is helpful but not required. Experience with software engineering or system design will support deeper understanding.
Objectives
At the end of the training you will be able to:
- Explain the key principles and differences between traditional AI, GenAI, and Agentic AI systems
- Describe the core architectural layers of Agentic AI solutions and their responsibilities
- Design agent-based architectures that combine orchestration, data, and models effectively
- Analyze when and where to apply agentic patterns in enterprise use cases
- Apply architectural patterns for agent orchestration, tool integration, and workflow management
- Evaluate trade-offs between autonomy, control, performance, and cost in agentic systems
- Implement governance, observability, and guardrails for reliable and compliant AI solutions
- Create a high-level architecture for an Agentic AI use case within your organization
e-CF competences with this course
- A.6. Application Design
- B.1. Application Development
- D.10. Information and Knowledge Management
- D.7. Data Science and Analytics
- E.1. Forecast Development
- E.5. Process Improvement
Classroom, online, blended and in-company
At Capgemini Academy you learn in the way that suits you. Do you prefer classroom training, online or a combination of the two (blended)? You can follow most training courses in-company: within your own organization. We use a variety of tools to make learning even more fun and effective. Consider videos, games, quizzes, webinars and case studies, for example. And you can always contact your trainer with any questions.
In-company training courses
With an in-company training you have several advantages:
- You choose the location.
- You train with your colleagues, ensuring it aligns with your practice.
- The trainer tailors explanations, examples and assignments to your organization.
- In consultation, exercises can be adapted to organization-specific questions.
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