Glossary › Trajectory
Trajectory
The full sequence of an agent's reasoning, tool calls, tool results, and intermediate outputs across a run. Agent evaluation grades the trajectory (did it call the right tools, in a sensible order, without looping) and not only the final answer.
Where Trajectory shows up
All matching postsAgent Evals: Trajectories, Tool Calls, and Regression Suites
An agent produces a trajectory, not an answer, and grading only the final answer misses looping, wrong tools, and failure to recover. Build a task suite from real failures, grade tool-call correctness programmatically, validate an LLM judge, and wire it all into CI as a regression gate.
Agent Evals and AI Security
How do you know an agent works, and how do you keep it from being turned against you? Trajectory grading, task suites built from failures, validated judges, CI regression gates, and the containment architecture for prompt injection: least privilege, approval gates, sandboxes, and a red-team practice you run yourself.
Evaluating AI Agents: Final Answer vs Trajectory vs Per-Turn
Grading an agent on its final answer misses the failures that matter: wrong tools, loops, and failure to recover. Here are the three layers of agent evaluation, what each catches, working code for mechanical trajectory checks, and how to turn the whole thing into a CI gate.