Accuracy scores and leaderboard metrics look impressive—but production-grade AI requires evals that reflect real-world performance, reliability, and user happiness. Traditional benchmarks rarely help you understand how your LLM will perform when embedded in complex workflows or agentic systems. How can you realistically and adequately measure reasoning quality, agent consistency, MCP integration, and user-focused outcomes? In this practical, example-driven talk, we'll go beyond standard benchmarks and dive ...