Show HN: A replayable A2A jury for tracing how agents influence decisions
ProtoLink is an experimental tool that creates a 'replayable jury' of AI agents to analyze decision-making processes in complex scenarios, such as autonomous vehicle liability. It provides observable transcripts and data to help researchers understand how agents influence each other.
Why it matters
It provides a framework for auditing AI decision-making, which is critical for safety and accountability in autonomous systems.
Can AI agents talk themselves into a better answer, or a worse one?
This ProtoLink showcase puts autonomous agents inside a fictional liability tribunal and makes their communication observable. The case is memorable, but the case is not the product. The product is the interaction:
The default run is deterministic and offline. It produces JSON results, ProtoLink traces, a public transcript, and standalone interactive HTML reports.
Everything and everyone in this example is fictional. It is a software experiment, not legal analysis, legal advice, or a validated safety assessment.
At 21:47 on a rain-soaked evening, an autonomous Aster Vale robotaxi struck and killed 31-year-old cyclist Lina Ortega inside a temporary crossing. The car began emergency braking only 0.35 seconds before impact. Thirty-six hours earlier it received the Orchid 4.8 software release.
Is Aster Vale Mobility guilty of criminally negligent deployment of an autonomous vehicle system that caused Lina Ortega's death?
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