Agents
Much of the valuable information in agent traces isn’t directly filterable with existing techniques like full text search or metadata filter…
Much of the valuable information in agent traces isn’t directly filterable with existing techniques like full text search or metadata filtering. AI Search in LangSmith closes that gap. You describe wh
Much of the valuable information in agent traces isn’t directly filterable with existing techniques like full text search or metadata filtering. AI Search in LangSmith closes that gap. You describe what you're looking for in plain natural language and can issue queries like "user frustrated" and "pii leaked" on the fly, which was previously impossible to do without defining an online evaluator ahead of time. 🔎 Announced at Interrupt: AI Search in LangSmith You used to need an evaluator or read hours of conversations to find traces that answer questions such as: 💬 Does the user seemed frustrated?" 💬 Where did the agent fail to complete the task? 💬 Where is the user trying to cance…
Related
- How do you support full-text search JSON filtering over agent traces that span up to hundreds of MBs, while keeping a median (P50) latency o…
- Technical blog on how we built SmithDB (our database purpose built for agent traces)
- This looks great - kudos @LangChain team
Source: Harrison Chase (X) | 2026-10-13