In the last couple of years, architecture of AI solutions has matured. As an industry, we have found some design patterns and best practices as we've realized that single-agent designs may struggle with reliability and scale when we move from experimentation to production.

In this talk, we explore how multi-agent architectures address requirements by decomposing AI systems into specialized, coordinated components, with an understanding of the trade-offs.

After this talk, you will have an understanding of the different approaches to multi-agent architectures, why are they needed, and what could happen next in the evolution of agentic development.