Guests:

• Thom van der Doef, Principal Product Designer at eSpark


• Mary [last name], Director of Learning Design & Product Manager at eSpark


• Ray Lyons, VP of Product & Engineering at eSpark

Topics covered:

• The origin story of Teacher Assistant: connecting administrator mandates with teacher needs


• Why the team abandoned a chatbot interface in favor of a more structured workflow


• How retrieval augmented generation (RAG) and embeddings shaped the product architecture


• Lessons learned from debugging semantic search vs. keyword search


• Building evals with rubrics, Braintrust, and a human-in-the-loop approach


• What’s next for Teacher Assistant: more contextual recommendations using student data

Links & References:

• eSpark Learning


• Braintrust – evals and observability for LLM applications


• AI Evals Course by Hamel Husain and Shreya Shanker (Get 35% off with my affiliate link)

Chapters:
02:05 Overview of Epar's Adaptive Learning Program
07:19 Challenges and Insights from COVID-19
17:06 Developing the Teacher Assistant Feature
24:55 User Experience and Interface Evolution
34:29 Chat GPT-5's New Features
35:16 Balancing Engagement and Efficiency
35:40 Seasonal Business and Real Traffic
36:29 Technical Decisions and RAG Implementation
38:28 Challenges with Embeddings and Metadata
41:24 Improving Recommendations and Data Enrichment
55:18 Evaluating the Teaching Assistant
01:05:51 Future Plans and User Feedback
01:07:57 Conclusion and Final Thoughts