Machine Learning, AI Agents, and Autonomy // MLOps Podcast #283 with Zach Wallace, Staff Software Engineer at Nearpod Inc.// AbstractDemetrios 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.// BioSoftware 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/Merchhttps://shop.mlops.community/// Related Linkshttps://medium.com/renaissance-learning-r-d/data-platform-transform-a-data-monolith-9d5290a552ef --------------- ✌️Connect With Us ✌️ -------------Join our Slack community: https://go.mlops.community/slackFollow us on Twitter: @mlopscommunitySign up for the next meetup: https://go.mlops.community/registerCatch all episodes, blogs, newsletters, and more: https://mlops.community/Connect with Demetrios on LinkedIn: /dpbrinkm/Connect with Zach on LinkedIn: https: /zachary-wallace/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
