In the news
Introducing Align Evals: Streamlining LLM Application Evaluation
LangChain · Published · 3 min read
In 30 seconds
- What happened
- LangChain released Align Evals, a LangSmith feature that calibrates LLM evaluators to match human judgment on application outputs.
- Why it matters
- Teams building LLM applications need this when evaluation scores diverge from human expectations, causing noisy comparisons and wasted debugging effort.
- Watch out
- The feature requires manually grading representative examples upfront to create a baseline, which demands significant human effort before alignment can begin.
Listen to this summary
- llm
- eval
The patterns behind this
- Eval-Driven Development (Agent CI)
- Agent Observability & Tracing
- Reinforcement Learning from AI Feedback
Each one covers how the technique works, when it earns its cost, and where it breaks.
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