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*Agents, Causal AI & The Future of DoWhy*

The idea of agentic systems taking over more complex human tasks is compelling.

New "production-grade" frameworks to build agentic systems pop up, suggesting that we're close to achieving full automation of these challenging multi-step tasks.

But is the underlying agentic technology itself ready for production?

And if not, can LLM-based systems help us making better decisions?

Recent new developments in the DoWhy/PyWhy ecosystem might bring some answers.

Will they—combined with new methods for validating causal models now available in DoWhy—impact the way we build and interact with causal models in industry?

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Video version available on Youtube: 

https://youtu.be/8yWKQqNFrmY

Recorded on Mar 12, 2025 in Bengaluru, India.

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*About The Guest*
Amit Sharma is a Principal Researcher at Microsoft Research and one of the original creators of the open-source Python library DoWhy, considered the "scikit-learn of causal inference." He holds a PhD in Computer Science from Cornell University. His research focuses on causality and its intersection with LLM-based and agentic systems. Amit deeply cares about the social impact of machine learning systems and sees causality as one of the main drivers of more useful and robust systems.

Connect with Amit:
- Amit on LinkedIn: https://www.linkedin.com/in/amitshar/
- Amit on BlueSky:
- Amit 's web page: http://amitsharma.in/

*About The Host*

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