In the news
How Similarweb Evaluates Agent Reports with LangSmith
LangChain · Published · 3 min read
In 30 seconds
- What happened
- Similarweb uses LangSmith to evaluate long-form agent research reports with rubrics, faithfulness checks, and baseline comparisons instead of golden answers.
- Why it matters
- Engineers building agents or RAG systems with open-ended outputs need evaluation workflows that connect scores to reasoning and traces before shipping changes.
- Watch out
- Miscalibrated rubrics can hide real improvements or create false regressions. Conflicting criteria and misaligned incentives in scoring anchors require careful calibration before trusting results.
Listen to this summary
- agent
- eval
The patterns behind this
- Deep Research Agent
- Eval-Driven Development (Agent CI)
- Agentic Context Engineering (Evolving Playbook)
Each one covers how the technique works, when it earns its cost, and where it breaks.
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