Skip to content

Details

About the Event

​Most discussions around AI agents stop at theory or simple demos. But building useful AI systems requires understanding how to translate a business problem into an agent that can reason, retrieve information, and execute tasks effectively.

AI Builders Weekend is Masters' Union's hands-on workshop series for aspiring AI engineers, developers, and builders looking to move beyond theory and learn by building real AI applications. As part of the next edition, we are hosting From Idea to AI Agent – Live Building Workshop.

Register on LUMA: Click Here

​This hands-on session will explore how modern AI agents are built to solve real-world business problems, with participants building an AI agent designed for an e-commerce use case tackling challenges such as inventory management, SKU planning, and intelligent product discovery.

​Led by Divij Bajaj, Data & Applied Scientist II at Microsoft, this session will showcase how AI agents can be designed to solve domain-specific problems by combining reasoning, retrieval, and structured workflows.

In this workshop we’ll cover:

  • ​How to translate a business problem into an AI agent workflow
  • ​Building an AI agent for an e-commerce use case, focused on inventory management, SKU planning, and product discovery
  • ​How AI agents can automate and enhance decision-making across e-commerce operations
  • ​What separates prototype AI demos from production-grade AI systems

Who is this workshop for?

​This session is designed for software engineers, developers, students, and aspiring AI professionals who want to gain hands-on experience building real AI applications and strengthen their portfolio with practical proof of work.

About the Speaker
​Divij Bajaj is a Data & Applied Scientist II at Microsoft, where he works on building Generative AI solutions for real-world applications. With prior experience at VMware and nearly seven years of experience across machine learning and production AI systems, he has worked extensively on building, scaling, and deploying AI solutions that solve business problems at scale.

Related topics

AI and Society
Data Engineering
Data Science
AI Ethics

You may also like