Evaluating AI Agents — Trajectory Testing, Tool Use Accuracy, and Task Completion
Master agent evaluation: trajectory analysis, tool accuracy, task completion rates, efficiency scoring, and LLM-as-judge evaluation frameworks.
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6 articles
Master agent evaluation: trajectory analysis, tool accuracy, task completion rates, efficiency scoring, and LLM-as-judge evaluation frameworks.
Guide to building domain-specific LLM benchmarks, task-based evaluation, adversarial testing, and detecting benchmark contamination for production use cases.
Build automated evaluation pipelines with LLM-as-judge, DeepEval metrics, and RAGAS to catch quality regressions before users see them.
Comprehensive guide to evaluating LLM performance in production using offline metrics, online evaluation, human sampling, pairwise comparisons, and continuous monitoring pipelines.
Build feedback loops: log retrieval signals, identify failures, A/B test changes, and automatically improve your RAG pipeline from production data.
Master the RAGAS framework and build evaluation pipelines that measure faithfulness, context relevance, and answer quality without expensive human annotation.