I build ML systems that turn traces, evaluations, and tools into clearer next actions.

Anish Shah builds agent systems, evaluation and observability workflows, and technical education at Weights & Biases. His work focuses on what happens after an AI demo: tracing behavior, testing whether an application works, designing tool interfaces people can inspect, and deciding where human review belongs.

His path spans programming education, computer-vision research, analytics, recommendation systems, production ML, customer-facing ML support, and MLOps growth. That range shapes talks that connect system design to the practical decisions teams face when they build and operate AI applications. He uses concrete implementations and public work to explain what worked, what failed, and which conclusions the evidence can actually support.