12 November 2026 12:00 - 12:30
Panel | Why do agent systems break in production? The gap between design and reality
As agentic systems become more autonomous, engineering teams must contend with unpredictable behaviour, cascading failures, unreliable tool interactions, changing model performance, and limited visibility into complex decision-making.
In this panel, engineering leaders share the lessons learned from deploying AI agents in real-world environments. Explore the architectural patterns, evaluation strategies, and operational practices that help teams build agentic systems that remain reliable, observable, and resilient long after deployment.
Key takeaways
→ The most common reasons agent systems fail in production and how to design around them.
→ How leading teams evaluate, monitor, and debug increasingly autonomous agents.
→ Architectural patterns that improve reliability, resilience, and observability at scale.
→ Lessons learned from deploying agentic systems in real-world production environments.