Fireside Chat with Chris Taylor, VP & Fellow at Google
Christopher Taylor discusses enterprise adoption of AI, the importance of context and data infrastructure, and how graph-based approaches and agent workloads change the engineering tradeoffs.
Christopher Taylor
VP and Engineering Fellow · Google
10Sep
11:15 PM UTC · 45 min
What you’ll explore
1
Assess enterprise adoption
Consider what changes when AI becomes part of routine organizational work.
2
Look beyond the model
Examine context, data, tools, memory and evaluation as system components.
3
Evaluate agent value
Distinguish useful capabilities from unnecessary coordination complexity.
About this session
Christopher Taylor discusses enterprise adoption of AI, the importance of context and data infrastructure, and how graph-based approaches and agent workloads change the engineering tradeoffs.
Guest speaker
Christopher Taylor
VP and Engineering Fellow · Google
Christopher's Google career spans databases, distributed systems and major infrastructure shifts, including long-running technical leadership across database engineering.
Hosted by Aishwarya Srinivasan and Arvind Narayanamurthy.
Aishwarya Srinivasan
AI Advisor / AI Educator
Aishwarya Srinivasan is the Co-Founder of The Gen Academy and a Developer Relations Lead at Nebius. Her experience spans Fireworks AI, Microsoft for Startups, Google Cloud and IBM, where she worked with developers and businesses on practical AI and machine-learning solutions. She holds a postgraduate degree in Data Science from Columbia University and teaches AI engineering, applied machine learning, generative AI and LLMOps.
Founder @ The Gen Academy | AI Solutions Architect | Ex - Adobe, Microsoft, IBM
Arvind brings a cross-company perspective on AI at scale, built across Microsoft, IBM, and Adobe, where he led data science teams and developed production-grade machine-learning solutions. He has built and deployed enterprise AI systems and focuses on translating AI concepts into practical, production-ready solutions. He holds a Master's from Carnegie Mellon University.
