Agentic AI systems are rapidly moving from experimentation to production — but most failures don’t come from the model, they come from the architecture.
In this talk, we’ll explore agentic design patterns that turn large language models into reliable, goal‑driven systems. Starting from single‑agent designs, we’ll progressively evolve toward multi‑agent architectures such as sequential, parallel, coordinator, review‑and‑critique, hierarchical, and swarm patterns.
You’ll learn when to use each pattern, the tradeoffs in latency, cost, and safety, and how to avoid common failure modes like infinite loops, context overload, and runaway autonomy. The session combines architectural diagrams, real examples, and decision frameworks you can immediately apply to your own agentic systems.