Machine Learning, AI Agents, and Autonomy // MLOps Podcast #283 with Zach Wallace, Staff Software Engineer at Nearpod Inc.

// Abstract

Demetrios chats with Zach Wallace, engineering manager at Nearpod, about integrating AI agents in e-commerce and edtech. They discuss using agents for personalized user targeting, adapting AI models with real-time data, and ensuring efficiency through clear task definitions. Zach shares how Nearpod streamlined data integration with tools like Redshift and DBT, enabling real-time updates. The conversation covers challenges like maintaining AI in production, handling high-quality data, and meeting regulatory standards. Zach also highlights the cost-efficiency framework for deploying and decommissioning agents and the transformative potential of LLMs in education.

// Bio

Software Engineer with 10 years of experience. Started my career as an Application Engineer, but I have transformed into a Platform Engineer. As a Platform Engineer, I have handled the problems described below: - Localization across 6-7 different languages - Building a custom local environment tool for our engineers - Building a Data Platform - Building standards and interfaces for Agentic AI within ed-tech.

// MLOps Swag/Merch

https://shop.mlops.community/

// Related Links

https://medium.com/renaissance-learning-r-d/data-platform-transform-a-data-monolith-9d5290a552ef

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Timestamps:

[00:00] Zach's preferred coffee

[00:24] Takeaways

[01:25] Data platform pivot

[04:06] Data integration with DBT

[06:50] Data mesh partial adoption

[08:55] Data product

[10:11] Agent Architectures and Deployment

[15:35] Agent vs LLM

[20:28] AI Agent Analytics

[22:18] Agent Design and Scope

[26:52] DAG Agent Workflow Design

[30:25] Cost Considerations in AI

[35:00] Agent Deployment and Costing

[42:25] AI Evaluation Use Cases

[45:25] Agent vs ML for Contracts

[46:55] Wrap up