Beyond Simple Agents: Building with LangChain Deep Agents

Part of Global AI Builder Series: by The Gen Academy

Hosted by Aishwarya Srinivasan & Arvind Narayan and Jess Weng

Mon, Aug 31, 2026

5:30 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

Understand the Deep Agent Architecture

Learn what makes a Deep Agent different and how the agent harness enables complex, long-running workflows.

Manage Context for Long-Running Agents

Use memory, skills, summarization, and context offloading to keep agents effective across extended tasks.

Build Agents That Delegate Work

Learn how Deep Agents use subagents and delegation to break complex problems into manageable tasks.

Why this topic matters

Most agents today work well on short, simple tasks but struggle when work becomes longer and more complex. Deep Agents introduce the building blocks needed to go further: planning, memory, context management, delegation, and execution. These patterns help developers build agents that can handle real-world workflows more reliably.

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.

Jess Weng

Education Engineer @ LangChain

Jess Weng is an Education Engineer at LangChain, where she helps developers learn and build with the latest tools and patterns in agentic AI. She creates practical educational content around LangChain’s ecosystem, including Deep Agents, making advanced agent concepts easier to understand and apply.

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