Designing Real-World Multi-Agent AI Systems

I delivered a talk to the Berlin AI Builders community on what an AI agent is and how multiple agents come together to form a complete system.

The session started with the fundamentals, clarifying how agents differ from LLMs and how agentic systems evolve from single-tool assistants to orchestrated, multi-agent architectures. I then walked through why orchestration matters, common coordination patterns, and what changes when multiple specialized agents share a workflow.

Highlights included:

• Agentic system levels from basic LLM use to multi-agent orchestration
• Architecture building blocks like tools, memory, context, and the orchestration layer
• Coordination patterns (sequential, parallel, and handoff)
• Safety and reliability with guardrails and evaluator agents
• A brief case study on a finance assistant to show real-world interactions

The slides are designed with both horizontal and vertical navigation.