AI & Tools desk — breakout report
How to Build a Model Router in the Harness
LangChain's upload has reached 8.6K views — about 3.4× the ≈2.5K this channel typically draws at the same age.
Key facts
- •3.4x LangChain's own 90-day median — this channel normally draws about 2.5K views at the same age.
- •8.6K views so far, published 14 days ago.
- •Category: Science & Technology · Language: en · Quality: HD · Captions: yes
- •"Breakout" is measured against this exact channel's trailing 90-day median at matching video age — not a generic niche average.
Updated 2026-10-06 23:10 UTC
View trajectory
Views this upload has gathered since it published, last measured about 169h in — from our own tracking.
Published Oct 6, 2026 · 14 days ago. How breakouts are measured →
From the creator
Sydney Runkle, product manager for LangChain's open source team, walks through how the team built a model router into Open SWE, LangChain's open source coding agent. She covers the four steps: mapping the task mix from LangSmith traces, picking models along the Pareto frontier, building the router in the harness, and…
Category: Science & Technology · Language: en · Quality: HD · Captions: yes
Topics: Business · Knowledge
Tags: model router, model routing, LLM routing, how to build a model router, agent harness, model routing middleware, LangChain, Open SWE, coding agent, AI agents, LangSmith, LLM cost optimization
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