Staging environment

Architect the Enterprise Context Layer for AI Agents

Hosted by Priyanka Vergadia and Austin Kronz

463 students

In this video

What you'll learn

Define what 'context' means for AI agents

Understand the concept of enterprise context and why it's the missing layer between your data and your AI agents.

Spot the walls that stall enterprise AI deployments

Recognize the three common failure points enterprises hit when scaling AI agents into production.

Sketch the architecture of a context platform

Learn how context compounds over time and see the core components an enterprise context layer needs.

Why this topic matters

Companies are shipping AI agents that don't know anything about how the business actually runs, so the agents guess. This session covers what context means for AI, the three walls that show up once you try to scale agents past a demo, and how to build a context layer so agents work off real business knowledge instead of making things up.

You'll learn from

Priyanka Vergadia

Top 0.1% AI & Cloud Leader | Visual Storyteller | TED Speaker

I've spent 15 years at the frontier of AI and Cloud leading product launches at Google and Microsoft that shaped how companies build with technology.

At Google, I led Developer Advocacy for North America and launched Gemini Code Assist alongside the CEO at Google Cloud Next. At Microsoft, I advise C-suite executives on AI transformation across GitHub Copilot and Azure. I've build a FDE and outcomes based customer facing engineering team from scratch.

I'm a TED speaker, Wharton faculty, and author of 2 bestselling books on Cloud and Generative AI.

But what sets me apart is storytelling. I built one of tech's most recognized visual education brands turning complex AI and Cloud concepts into content that has reached millions.

I teach what I live every day at the world's most innovative companies.

Austin Kronz

Field CDAO @Atlan

Austin is the Field Chief Data and AI Officer at Atlan, working with CIOs, CDAOs, Chief AI Officers, and AI architects at Fortune 500 enterprises on the context layer their AI agents need to work in production. A former Gartner Research Director covering analytics and data science, he now sits between forward-deployed engineering and GTM leadership in the room when the architecture gets drawn, across enough of those rooms to see which patterns repeat. He treats the role as open research his own framing is "expanding my personal context window." He hosts WTF is the Context Layer?Atlan's live series for AI and data leaders: one unresolved question per episode. He started his early career as a practitioner building revenue-cycle and analytics software in the healthcare industry.

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