AI Agents – a pragmatic approach

We are in the midst of a fundamental technological shift. While conversational AI like ChatGPT opened the door, the next, more powerful evolution is already here: AI Agents. These are no longer passive chatbots waiting for a prompt; they are autonomous systems integrated into the modern workplace, capable of executing complex tasks and managing entire workflows independently.

The question is no longer if AI Agents will change the business world, but how fast your organization can successfully integrate these new digital employees. This workshop gives you the strategic and practical answer.

Productivity and Impact

Organizations are moving past manual bottlenecks. HR is no longer bogged down by repetitive inquiries, and Finance has moved beyond hours of manual data aggregation. Data professionals are breaking free from the cycle of repetitive SQL queries and manual data cleaning just to keep dashboards alive, while operations and IT teams have automated shipment tracking and employee onboarding. Your workday remains eight hours, but your productivity and impact grow exponentially. They enable you to:

• Work more strategically: Focus on high-value tasks while AI Agents handle routine processes.
• Improve collaboration: Use AI Agents as an interface for quick access to process information or customer data.
• Accelerate innovation: Integrate AI Agents into your business architecture to streamline workflows and unlock new possibilities.

With the right configuration and context, AI Agents deliver not just efficiency, but also a consistent, high-quality contribution to your organization. The rise of advanced language models, such as the technology behind ChatGPT, was just the beginning. AI Agents go further by combining these language models with external data sources, memory functionality, and workflow logic.

Learning Objectives

AI Agents promise a revolution in efficiency, but the step from a promising experiment to a secure, scalable, and fully integrated enterprise solution is a massive challenge. How do you ensure your agents perform reliably with complex business data? How do you guarantee security and governance? And how do you integrate these systems seamlessly with your existing processes and IT infrastructure?

This workshop is designed to bridge that gap. We go beyond theory and give you the hands-on knowledge to tackle these challenges. You will learn, among other things:

• Defining AI Agents: You will learn the core concepts, from autonomous systems that perceive and act to the technology and mechanisms behind the brains of the Agents: the Large Language Models (LLMs).
• Setting Up the Right Architecture: You will learn how to design the technical blueprint of an agent, from a simple Retrieval-Augmented Generation (RAG) pipeline to complex multi-agent systems with memory and planning.
• Choosing the Perfect Model: You will learn to weigh the trade-offs between powerful LLMs for generic tasks and smaller, domain-specific models for specific use cases.
• The Data Foundation for Autonomy: Learn how to transform your existing data into a reliable “source of truth,” ensuring that your integration pipelines and data quality standards are optimized to prevent hallucinations and drive accurate agent performance.
• Bridging Data and Intelligence: How to architect your data streams for AI readiness, moving beyond simple storage to creating structured, high-quality integrations that allow agents to access and reason with your business data effectively.
• Training Agents Effectively: You will learn the process of data preparation and setting up annotation workflows to feed your model with high-quality, relevant business data.
• Integrating Tool Interaction: How to make an agent action-oriented by linking it to external tools and APIs so it can execute tasks within your existing systems.
• Model Maintenance and Management: You will learn how to keep your agent’s performance up to par through re-training with new data and drift detection to prevent quality loss.
• Designing Concrete Business Scenarios: You will learn to translate theory into practice by developing scenarios where agents support processes, prepare decisions, and report automatically.
• Controlling Costs: You will get concrete tools for managing budgets by choosing cost-efficient models, optimizing cloud resources, and applying prompt engineering to minimize token usage.
• Ensuring Human Control: How to implement human-in-the-loop systems for supervision on decisions and setting up feedback loops for continuous improvement.
• Successful Deployment: You will learn the roadmap to technically take an AI agent live, from cloud hosting via various providers to seamless integration into your existing business applications.

Hands-on: During the workshop, you will build various AI Agents in a low-code tool, ranging from a simple Agent to a Multi-Agent Architecture with complex memory and tool usage—and then go home with working prototypes.

Who is it for?

IT & Enterprise Architects, BI and Data-Professionals, Data Architects, Functional & Business Analysts,  Digital Transformation Officers, Change Managers, Innovation Officers.

No technical background or software development skills are required to participate on this course.

Language: this course is delivered in English unless we have an all-Dutch group.