AI Agentic Systems

Artificial intelligence is no longer just a tool you prompt and wait for an answer. A new generation of AI is emerging, one that plans, decides, acts, and adapts. Autonomous AI agents are systems capable of executing complex, multi-step tasks across digital environments, coordinating between tools, data sources, and workflows without requiring constant human instruction. This is not a future development. It is happening now, and the professionals who understand how to design and manage these systems are already operating at a level that is simply out of reach for everyone else. The shift is fundamental. Where previous AI tools responded to individual inputs, autonomous agents pursue goals. They break down complex objectives into sequences of actions, interact with external systems and data sources in real time, and coordinate workflows across entire digital environments.

The implications for how organisations operate, how products are built, and how creative and analytical work gets done are profound and immediate. Yet most professionals engaging with AI agents are doing so without a structured approach. They are building experimental prototypes that work unpredictably, fail silently, or cannot be trusted at scale. The problem is not the technology. The problem is the absence of the frameworks required to design agents that are reliable, controllable, and genuinely useful in professional contexts. Without those frameworks, autonomous AI remains a demonstration of what is possible rather than a system you can deploy with confidence.

Designing effective AI agents requires a new kind of fluency. You need to understand how autonomous systems plan and reason, how to structure goals and constraints so agents behave as intended, how to integrate multiple tools and data sources without creating fragile dependencies, and how to build oversight mechanisms that keep complex AI workflows under human control. These are not technical skills reserved for engineers. They are strategic and design competencies that any serious professional working with AI needs to develop.

This masterclass gives you exactly that. From the foundational principles of autonomous AI system design to advanced frameworks for building, managing, and scaling AI agents in real professional environments, you will develop the knowledge and methodology to move beyond experimentation and into systems that perform. The AI Agentic Systems Masterclass is designed for product managers and technology strategists, AI engineers and software developers, business analysts and operations managers, digital transformation leads and innovation consultants, startup founders and technical co-founders, data scientists and machine learning practitioners, IT directors and enterprise architects, marketing technologists and automation specialists, and any professional who works with or alongside AI systems and wants to move from surface-level tool usage to designing and managing autonomous AI workflows that perform reliably at scale.

What Will I Learn?

• Week 1 Introduction to Agentic AI
Understanding the evolution from AI tools to autonomous agents.


• Week 2 Agent Architectures
Planning, reasoning and decision-making frameworks.


• Week 3 Tool Integration
Connecting agents with tools, APIs and data sources.


• Week 4 Multi-Agent Systems
Designing collaborative agent ecosystems.


• Week 5 Workflow Automation
Building agent-driven workflows and task orchestration.


• Week 6 Reliability and Safety
Evaluating risks, control and governance.


• Week 7 Project Development
Designing and building your agentic system.


• Week 8 Final Presentation
Demonstration and expert feedback.

Your Final Project

Participants design and prototype an AI Agent Workflow System:

• An autonomous AI agent capable of performing structured tasks
• Integration with tools, APIs or external data
• Documentation of the agent architecture and workflow
• A presentation demonstrating the system in action

Eligibility

• Age: Participants must be 18+


• Language: Participants must be fluent in English. The language eligibility will be assessed during the interview which will be conducted in English.


• Track Record: Participants must have experience in relevant creative fields including filmmaking, audiovisual, production, digital, and performance (or equivalent) credits.

FAQ

Do I need programming experience?
Basic technical familiarity is helpful, but the course focuses on conceptual frameworks and practical
experimentation.

Which AI technologies will be explored?
Agent frameworks, LLM integrations and workflow orchestration tools.

How much time per week?
Approximately 4–6 hours per week including sessions and project work.

Is this suitable for companies?
Yes. Designed for professionals, innovation teams and organizations exploring AI agents.