AI Product Manager experienced in delivering zero-to-one products, combining AI systems knowledge, data analysis, market insights, design thinking, and customer-centric strategies to build innovative products.
Single-turn tests can miss failures that emerge as conversations evolve. Learn how AI agent simulation uses realistic user goals, behaviours, and personas to test multi-turn interactions, uncover hidden failures, and improve agent reliability before deployment.
AI agent testing shouldn't end at deployment. Learn how offline and online evaluation, regression testing, and production monitoring help teams catch failures, measure quality, and continuously improve AI agent reliability.
Learn how AI agent observability helps teams trace LLM calls, tool use, retrievals, latency, token usage, cost, and failures across production agent workflows.
Learn how to manage AI agent prompts with versioning, testing, evaluation, deployment controls, and observability using Netra Prompt Studio.
