Why AI Agents Aren’t Enough for Real-World Applications

Lightning Lessons

Practical skills & tools to accelerate your career

Why AI Agents Aren’t Enough for Real-World Applications

Hosted by Kiriti Badam and Aishwarya Reganti

920 students

What you'll learn

What Are AI Agents Anyway?

Learn our categorization of agents into 4 levels of complexity and how they evolve

Key Building Blocks of Real-World Agentic Systems.

Learn key blocks like business logic integration, robust evaluation mechanisms, compliance, data requirements and more!

Real-World Use-Case Design

A framework for designing agentic systems with business constraints, demonstrated through a real-world use case

Why this topic matters

We're right in the midst of the agentic AI era, where agents are being explored for automation and augmentation. While super promising, many misconceptions still persist. This session takes you from what AI agents are to what they can do, along with a structured framework and checklist to guide effective design and implementation.

You'll learn from

Kiriti Badam

Founding Engineer @ Kumo.ai | Ex-Google

With over a decade of experience designing high-impact and transformative enterprise AI systems, Kiriti Badam is a seasoned expert in AI-centric infrastructure, specializing in large-scale compute, data engineering, and storage systems. At Kumo.ai, a Forbes AI 50 startup, he leads the development of infrastructure capable of training hundreds of models daily, driving significant ARR growth for enterprises.

Kiriti brings a unique blend of startup agility and large-scale enterprise expertise, having worked across companies of varying sizes, including Kumo.ai, Google, Samsung, and Databricks. At Google Ads, he developed globally distributed key-value stores that powered advertising systems generating XX billion dollars in annual revenue.

Kiriti holds a Master’s degree from Carnegie Mellon University and a Bachelor’s degree from IIT Madras, where his research focused on cutting-edge storage systems and distributed databases for AI workloads. A trusted advisor and mentor, he guides startups and organizations in building impactful AI infrastructure, achieving product-market fit, and crafting robust product development strategies.

Aishwarya Reganti

Aishwarya Naresh Reganti is an Applied Science Tech Lead at the AWS Generative AI Innovation Center (GenAIIC), where she leads initiatives to develop and deploy production-ready generative AI solutions for AWS clients. With over 9 years of experience in machine learning, she has published more than 35 research papers at top-tier AI conferences, including NeurIPS, AAAI, and CVPR.

Aishwarya has taught professional courses on generative AI at renowned institutions like MIT and Oxford. She has also designed free courses that have reached over 8,000 students globally and have formed the foundation for several academic programs and industry training curricula.

Recognized as one of the most prominent voices in enterprise AI, with over 80,000 professionals following her on LinkedIn, she is a sought-after thought leader frequently invited to speak at leading conferences and events, including TEDx, MLOps World, and ReWork.

Aishwarya actively collaborates with leading research professors and provides strategic advisory to organizations, enabling them to harness AI effectively to address complex business challenges.

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