Practical use of AI/LLM

Context driven AI Agents

Shubhangi Goyal

Shubhangi Goyal

Shubhangi is an award winning data and AI professional worked in Fortune 500 companies to agile start-ups. She has a background in computer science engineering with an MSc in Business Analytics from the University of Bath, UK. She works as a Senior Analyst at a leading FTSE100 company in financial services and insurance in the UK.

Previously, she led multiple projects at ICS AI Ltd, a Microsoft UK inner circle partner, focusing on artificial intelligence and data at the forefront of technology for the public sector in the UK. She has spent nearly a decade in data analytics, data science, data strategy, and AI, leveraging algorithms to extract insights, identify patterns, and understand human language in large datasets.

She leads the London Chapter for Women In Data which is a platform for tech enthusiasts of all backgrounds to connect, grow and learn together. She is a verified expert and mentor at TopMate. She has delivered sessions in over 10 countries. She has also been nominated for several awards including WomenTechNetwork global awards.

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In this session, I will explore how agents are built and use dynamic context to execute complex tasks and deliver real value. This also includes using context engineering to move beyond single prompt based interactions. The key takeaways would be :

  • Context engineering, manage memory tools, and tasks for adaptive behaviour
  • Agent architecture, LLMs and feedback loops
  • Prompt engineering into the larger system
  • Real world use case and common pitfalls when deploying AI agents