The Etsy Gifting Assistant: From Prototype to Production | Interrupt 26

Derrick Kondo from Etsy's GenAI Enablement team walks through how Etsy built and shipped a conversational gifting assistant using LangChain, LangGraph, and LangSmith in just six weeks. The agent helps shoppers find the perfect gift through collaborative, iterative recommendations across Etsy's unique, unstructured inventory.

0:00 Introduction
0:38 Inventory search challenges
1:22 Why build an agent for gifting
2:04 Beta release results
2:36 Engineering overview
2:52 Solution architecture with LangChain 
3:27 Agent tools and middleware design
4:37 Engineering challenges and solutions
4:47 Stopping repeated tool calls (spin)
5:48 Fixing listing ID hallucinations
6:36 Memory management and the terminal UI debugger
7:36 Streaming architecture and socket passing
9:21 Evaluation methodology overview
9:46 Pass-K trajectory testing
10:21 LLM judge for outcome evaluation
11:09 Etsy Agents CLI and LangSmith integration
11:32 Batch simulation for dataset generation
12:06 LangSmith deployments for online and offline parity
13:34 Automated judge alignment
13:56 LangSmith for judgment stability
14:08 Deploying to production
14:17 Etsy Agents monorepo and automated CI/CD
14:51 Six weeks from start to beta
15:12 Summary and closing thoughts

Extra resources:
• Everything we shipped at Interrupt: https://www.langchain.com/blog/interrupt-2026-overview
• Meet LangSmith Engine: https://www.langchain.com/blog/introducing-langsmith-engine
• LangSmith Platform: https://www.langchain.com/langsmith-platform
• About LangChain: https://www.langchain.com/