Building Alyx: How Arize AI Dogfooded Its Way to an Agentic Future - podcast episode cover

Building Alyx: How Arize AI Dogfooded Its Way to an Agentic Future

Oct 09, 202549 minEp. 5
--:--
--:--
Download Metacast podcast app
Listen to this episode in Metacast mobile app
Don't just listen to podcasts. Learn from them with transcripts, summaries, and chapters for every episode. Skim, search, and bookmark insights. Learn more

Episode description

Guests:

  • SallyAnn DeLucia, Director of Product, Arize
  • Jack Zhou, Staff Engineer, Arize

In this episode, we cover:

  • What tracing, observability, and evals really mean in GenAI applications
  • How Arize used its own platform to build Alyx, its AI agent
  • The role of customer success engineers in surfacing repeatable workflows
  • Why early prototyping looked like messy notebooks and hacked-together local apps
  • How dogfooding shaped Alyx’s evolution and built confidence for launch
  • Why evals start messy, and how Arize layered evals across tool calls, sessions, and system-level decisions
  • The importance of cross-functional, boundary-spanning teams in building AI products
  • What’s next for Alyx: moving from “on rails” workflows to more autonomous, agentic planning loops

Resources & Links

  • Arize AI — Sign up for a free account and try Alex
  • Arize Blog — Lessons learned from building AI products
  • Maven AI Evals Course — The course Teresa took to learn about evals (Get 35% off with Teresa’s affiliate link)
  • Cursor — The AI-powered code editor used by the Arize engineering team
  • DataDog — For understanding application traces
  • OpenAI GPT Models — GPT-3.5, GPT-4, and newer models used in early and current versions of Alex
  • Jupyter Notebooks — A tool for combining code, data, and notes, used in Arise’s prototyping
  • Axial Coding Method by Hamel Husain — A framework for analyzing data and designing evals

Chapters: 00:00 Introduction to Sally Ann and Jack 01:08 Overview of Arize.ai and Its Core Components 01:44 Deep Dive into Tracing, Observability, and Evals 03:56 Introduction to Alyx: Arize's AI Agent 04:15 The Genesis and Evolution of Alyx 08:51 Challenges and Solutions in Building Alyx 24:33 Prototyping and Early Development of Alyx 26:22 Exploring the Power of Coding Notebooks 26:51 Early Experiments with Alyx 27:59 Challenges with Real Data 29:20 Internal Testing and Dogfooding 31:55 The Importance of Evals 35:16 Developing Custom Evals 43:09 Future Plans for Alyx 47:59 How to Get Started with Alyx

For the best experience, listen in Metacast app for iOS or Android