#3 Single vs. Multi-Agent AI Systems

Hosted by Aishwarya Naresh Reganti and Kiriti Badam

Mon, Jul 14, 2025

4:00 PM UTC (45 minutes)

Virtual (Zoom)

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195 students

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Building Agentic AI Applications with a Problem-First Approach
Aishwarya Naresh Reganti and Kiriti Badam
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What you'll learn

What Multi-Agent Systems Are (And Aren’t)

We’ll break down what qualifies as multi-agent, common misconceptions, and the core coordination patterns they use.

When to Use One Agent vs Many

Understand when multi-agent systems are helpful and when they can lead to unnecessary debugging overhead

Hidden Complexities in Multi-Agent Setups

We’ll cover the real-world challenges: context sharing, memory, handoffs, failure handling etc.

Why this topic matters

There’s been a big push toward multi-agent systems, with some even comparing them to microservices. But is more always better? In this session, we’ll break down what multi-agent systems actually are, how they differ from single-agent setups, and where each makes sense.

You'll learn from

Aishwarya Naresh Reganti

AI Tech Lead | Advisor

Aishwarya Naresh Reganti is an Applied Science Tech Lead and leads initiatives to develop and deploy production-ready generative AI solutions enterprise 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 95,000 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.

Kiriti Badam

Member of Technical Staff @ OpenAI | AI Advisor

Kiriti Badam is a member of the technical staff at OpenAI, with over a decade of experience designing high-impact enterprise AI systems. He specializes in AI-centric infrastructure, with deep expertise in large-scale compute, data engineering, and storage systems.

Prior to OpenAI, Kiriti was a founding engineer at Kumo.ai, a Forbes AI 50 startup, where he led the development of infrastructure that enabled training hundreds of models daily—driving significant ARR growth for enterprise clients.

Kiriti brings a rare blend of startup agility and enterprise-scale depth, having worked at companies like Google, Samsung, Databricks, and Kumo.ai. At Google Ads, he built globally distributed key-value stores that powered ad systems generating tens of billions in annual revenue.

He holds a Master’s degree from Carnegie Mellon University and a Bachelor’s from IIT Madras, where his research focused on advanced storage systems and distributed databases for AI workloads. A sought-after mentor and advisor, Kiriti helps startups and organizations design scalable AI infrastructure, reach product-market fit, and build long-term product strategy.

Worked/Taught at

OpenAI
Google
Amazon Web Services
University of Oxford
MIT research group

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