Memory for Agents: Personalization Beyond the Context Window

Part of Global AI Builder Series: by The Gen Academy

Hosted by Aishwarya Srinivasan & Arvind Narayan and Rudraj Mehta

Fri, Aug 28, 2026

4:00 PM UTC (1 hour)

Virtual (Zoom)

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Building a career in AI as a non-coder
Aishwarya Srinivasan
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What you'll learn

Decide what agents should remember

Learn what to store, update, retrieve, and forget in long-lived agent systems.

Build personalization users trust

Connect memory retrieval to useful, inspectable, and correctable experiences.

Reduce stale or risky context

Avoid privacy, trust, and reliability failures caused by poor memory design.

Why this topic matters

Long-lived agents need continuity, but poor memory creates stale context, privacy risk, and user mistrust. Builders need patterns for what to remember, how to retrieve it, and when to forget so agents become more useful over time without becoming unpredictable or intrusive.

You'll learn from

Aishwarya Srinivasan & Arvind Narayan

AI Engineers | Building & Teaching @ The Gen Academy

Aishwarya Srinivasan is the co-founder of The Gen Academy and one of the world's most recognized AI educators, with a community of over 1.2 million AI professionals across social platforms. Previously, she led AI Developer Relations at Fireworks AI and spent over a decade building AI products and ecosystems at Google, Microsoft, and IBM. She holds a Master's in Data Science from Columbia University. Known for breaking down complex AI concepts with clarity and honesty, Aishwarya teaches builders how to move beyond demos and develop production-ready AI systems that solve real business problems.


Arvind Narayanamurthy is the Co-founder of The Gen Academy, Previously AI Solutions Architect at Ema, and Founder of Eikos Health. He has built and deployed enterprise AI systems across Microsoft, IBM, Adobe, and high-growth startups, leading initiatives that translated machine learning into measurable business impact. Arvind holds a Master's degree from Carnegie Mellon University. His teaching focuses on first-principles thinking, practical engineering, and helping builders design, evaluate, and deploy reliable AI systems for production.

Rudraj Mehta

Product @ Mem0

Rudraj Mehta works on product at Mem0, the memory layer for AI agents. He focuses on memory infrastructure, retrieval, and context portability for agentic applications, helping builders think clearly about what agents should keep and recall.

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