Free Lesson

Build Production-Ready Agent Evals

Hosted by Dr Ankur Narang and Kush Khurana

Fri, Aug 14, 2026

3:00 PM UTC (45 minutes)

Virtual (Zoom)

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Build Production AI Agents for 10x-100x ROI
Dr Ankur Narang, Kush Khurana, and Dr Aveek Brahmachari
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What you'll learn

Build a representative golden dataset

Learn to create compact but effective set of normal, difficult, ambiguous and high-risk scenarios for evaluating agents

Separate deterministic checks from LLM evaluation

Understand which tests should be implemented in code and which tests may benefit from an LLM judge.

Measure business correctness, not just text quality

Learn how to evaluate whether an agent’s recommendation improves the business outcome it was designed to influence.

Create production acceptance thresholds

Define measurable release gates for: task-completion rate; policy compliance; decision accuracy; grounded responses;

Why this topic matters

A production AI agent cannot be approved on the strength of one successful demonstration. Agents are probabilistic systems. Their outputs can vary across repeated runs, tool responses, changing context and incomplete data. This session gives participants a practical framework for answering all the evaluation related questions before deploying an agent into a live business process.

You'll learn from

Dr Ankur Narang

Dr. Ankur Narang brings 30+ yrs exp in AI, Tech across MNCs & many verticals

Dr. Ankur Narang is the Founder & CEO of DeepCoreX Labs and brings 30+ years of experience across AI, technology leadership, venture building, enterprise transformation, and applied R&D. He has held senior AI and technology roles across research labs, startups, and large enterprises, and has worked on AI systems, decision science, agentic workflows, and deeptech venture creation.

Kush Khurana

AI & ML leader; Venture Partner, DeepCoreX; Ashoka faculty

Kush Khurana is an AI/ML leader, Venture Partner at DeepCoreX, and Visiting Professor at Ashoka University. He has 12+ years of experience building production AI systems, leading technical teams, and shaping AI-native products. He works with founders and learners to turn frontier AI and deep-tech ideas into practical, scalable systems.

IBM; Apparel Group; Yatra; Oracle; Hike

Apparel Group
Oracle
Meta
Hike
Yatra
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