Why human insight is a strategic advantage for building better agents

As agents take on longer, more complex tasks, evaluating their performance means looking beyond the final AI-generated answer. Human review plays an important role in agent development: it helps teams define what good looks like, evaluate performance in context, and turn expert judgment into data that drives improvement. In this blog, we explore three principles for effective human-in-the-loop workflows: defining quality through expert judgment, evaluating agents in context, and turning human feedback into reusable evaluation data that drives continuous improvement. What is an agent trace? An agent trace is a record of everything an agent did in a single attempt: user messages, model responses, tool calls, and intermediate steps. Teams use traces to debug behavior, score quality, and decide what to fix. Often an engineer or an online evaluator flags a trace when something looks off. The flag is a signal, not an explanation. It usually is not…