Agentic Evaluations
Designing a trust building service for evaluation of AI Agents before deployment
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problem
An Agentic Workflow is a coordinated system in which multiple AI agents plan, act, and adapt together using tools, data, and feedback to achieve a shared goal. To confidently deploy such workflows to production, they must be evaluated for consistent performance across a wide range of scenarios. Risks must be identified, gaps addressed, and trust established. Today, users can create Agentic Workflows and AI Agents in AI Agent Studio, but validation is limited to manual testing of one scenario at a time within the studio. This approach is slow, inefficient, and insufficient for building confidence in real-world performance, making it difficult for teams to move workflows into production.
solution
Agentic Evaluation addresses this challenge by enabling automated, large-scale evaluation of Agentic Workflows across multiple scenarios using structured datasets. Instead of validating whether a workflow succeeds once or twice, Agentic Evaluation tests performance across diverse conditions, ensuring consistency, reliability, and robustness at scale. Through automated evaluations, admin teams gain clear insights into workflow behavior, identify areas for improvement, and significantly accelerate production readiness. This shifts testing from being manual and limited to automated, scalable, and dependable. Agentic Evaluation empowers users to validate Agentic Workflows and AI Agents through structured evaluations that measure quality, reliability, and deployment readiness, enabling faster and more confident adoption of agentic AI in production environments.
My Role as Director - AI Design Team
Defined the product strategy and vision for Agentic Evaluation in close partnership with Product and Engineering, aligning on customer trust, scalability, and production readiness as core success metrics.
Set and championed the Design North Star, leading a multidisciplinary design team to translate complex agentic systems into a coherent, scalable evaluation experience. Established review rituals and a cross-functional collaboration model that enabled rapid iteration and high design quality.
Drove customer-centered validation by partnering with Research and GTM teams to incorporate real client feedback into the design roadmap, ensuring the solution addressed enterprise adoption barriers and accelerated time to production.
Pioneered novel workflow and evaluation patterns, resulting in patentable innovations that strengthen the company’s IP portfolio and long-term differentiation in agentic AI systems.
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