Vanishing Gradients Episode 50: A Field Guide to Rapidly Improving AI Products -- With Hamel Husain
10 snips
Jun 17, 2025 Hamel Husain, an AI specialist with experience at Airbnb, GitHub, and DataRobot, discusses improving AI products through effective evaluation. He highlights the importance of error analysis and systematic iteration in development. The conversation reveals common pitfalls in debugging AI systems, stressing the collaboration between engineers and domain experts to drive progress. Hamel also emphasizes that evaluation should be a comprehensive process, balancing immediate fixes with strategic assessment. This dialogue is a must-hear for anyone grappling with AI system enhancements.
AI Snips
Chapters
Transcript
Episode notes
Defining 'Better' Is Key
- Articulating what 'better' means in AI systems is central and challenging.
- It involves externalizing user needs through interaction with AI outputs and evaluation.
Let Error Analysis Guide You
- Use error analysis to prioritize what part of your AI system to fix first.
- Focus on upstream problems before investing resources in detailed evaluations.
Airbnb Lesson With Spreadsheets
- Hamel's experience at Airbnb showed that even big tech can have gaps like non-versioned spreadsheets for models.
- This insight shaped his understanding of the importance of clear problem definitions.