How to evolve your observability practices to keep pace with AI  

Artificial intelligence is changing the way modern systems are built—and how teams are expected to debug and operate them. But as AI-driven complexity grows, so too does the need for deep, reliable, and fast visibility into what's really happening inside our software. In this timely and thought-provoking session, Christine Yen, CEO and Co-founder of Honeycomb, explores how observability practices must evolve to keep pace with AI.

Drawing from hard-won lessons across production environments, Christine will challenge the myth that more automation means less need for human insight. Instead, she argues, observability that maps to what matters in software becomes even more critical when AI is in the mix—helping teams move from reactive firefighting to proactive engineering with precision and confidence.

Key learning points: 

• Why conventional monitoring breaks down in AI-augmented systems
• The difference between telemetry noise and high-signal observability
• How modern teams are using observability to understand LLM-driven workflows, hallucinations, and emergent behaviors
• What it takes to build AI-ready software with real-world reliability

Who should attend: 
Whether you're experimenting with AI features or already shipping them in production, this session will equip you with a clearer mental model—and practical guidance—for navigating the intersection of AI and modern software operations.