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AWS and LangChain detail AI agent evaluation framework

AWS and LangChain have collaborated on a guide for evaluating AI agents, leveraging LangSmith on AWS. The guide details methods for testing agent behavior, including offline evaluations with pytest and online monitoring for production systems. It incorporates insights from LangChain's experience and Anthropic's approach to agent evaluation, focusing on practical application for improving agent reliability. AI

IMPACT Provides a framework for improving the reliability and performance of AI agents in production environments.

RANK_REASON The cluster describes a practical guide and framework for evaluating AI agents, drawing on learnings from partner companies and detailing specific evaluation patterns and technical implementation.

Read on AWS Machine Learning Blog →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

AWS and LangChain detail AI agent evaluation framework

COVERAGE [2]

  1. AWS Machine Learning Blog TIER_1 English(EN) · Jagdeep Singh Soni ·

    Evaluating Deep Agents using LangSmith on AWS

    This post combines learnings from LangChain’s work on evaluating deep agents and Anthropic’s guide to demystifying evals for AI agents into a practical guide. In this post, you will learn how to: 1) apply five evaluation patterns for deep agents, 2) build offline evaluations usin…

  2. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    🤖 Evaluating Deep Agents using LangSmith on AWS This post combines learnings from LangChain’s work on evaluating deep agents and Anthropic’s guide to demystifyi

    🤖 Evaluating Deep Agents using LangSmith on AWS This post combines learnings from LangChain’s work on evaluating deep agents and Anthropic’s guide to demystifying evals for AI agents into a practical guide. In this post, you will learn how to: 1... 📰 Source: Artificial Intelligen…