Latest

TL;DR AI agents represent a fundamental shift from traditional LLM applications, requiring specialized evaluation frameworks that go beyond single-turn metrics. Effective agent evaluation combines system efficiency metrics (token usage, completion time, tool calls) with agent quality metrics (task success, trajectory analysis, tool correctness) across both session and node

TL;DR AI agent evaluation has become a production requirement in 2026 as organizations deploy increasingly autonomous agents. This guide examines five platforms for evaluating AI agents: Maxim AI leads the pack with its end-to-end approach combining simulation, experimentation, and observability specifically built for multi-agent systems. LangSmith

As organizations deploy AI agents and LLM-powered applications into production, the need for evaluation frameworks that hold up under load has become critical. Without proper evaluation tools, teams struggle to measure quality improvements, catch regressions before they ship, and maintain reliable performance at scale. The right evaluation platform enables