Article: Evaluating AI Agents in Practice: Benchmarks, Frameworks, and Lessons Learned

This article introduces practical methods for evaluating AI agents operating in real-world environments. It explains how to combine benchmarks, automated evaluation pipelines, and human review to measure reliability, task success, and multi-step agent behavior. The article also discusses the challenges of evaluating systems that plan, use tools, and operate across multiple interaction turns. By Amit Kumar Padhy

• Article: Evaluating AI Agents in Practice: Benchmarks, Frameworks, and Lessons Learned
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