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Research Direction

Simulation as a Dataset Engine

Generating high-fidelity traces for agent evaluation.

Type
Research Direction
Status
Published
Published
March 15, 2026
Systems
boundary
Evaluation is the bottleneck of AI safety. We cannot wait for agents to fail in production to learn how to secure them. ### Synthetic Traces Boundary generates synthetic traces by running agents against a set of scenario specifications. These scenarios include edge cases like network timeouts, conflicting instructions, and adversarial tool outputs. ### The Replay Factor Every trace generated is replayable. This allows us to re-run the same scenario with a modified governance policy to see if the vulnerability is closed. We believe this 'simulation-first' approach is the only way to build truly robust systems for real-world operational settings.

Citation Artifact

DBRL-RESEARCH-SIMULATION-AS-DATASET-ENGINE-2026