Real World AI Agent Stories // Zach Wallace // #283

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Jan 15, 2025

Zach Wallace, a Staff Software Engineer at Nearpod Inc., shares his expertise in AI integration within e-commerce and edtech. He discusses how AI agents enhance personalized user targeting and streamline data with tools like Redshift and DBT. The conversation delves into the challenges of maintaining AI systems, ensuring data quality, and the balance between specialization and cost in agent performance. Zach emphasizes the transformative potential of LLMs in education and the importance of educator involvement for effective AI tool development.

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ANECDOTE

AI Agents for Education

Zach Wallace's team built AI agents for question generation to help teachers reduce workload.
Initial agents were like "three-year consultants," requiring refinement with subject matter experts.

INSIGHT

Agents vs. LLMs

Agents excel in domain-specific tasks, like validating input for sensitive topics or generating questions.
LLMs without data lack quality and reliability, making data platforms essential.

ANECDOTE

E-commerce Use Case

In e-commerce, agents can personalize product recommendations by analyzing user interests and business needs.
Data platforms enable feedback loops to improve agent performance and identify areas for autonomous learning.

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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