Detecting AI instability in high-stakes agentic deployments

We find the conditions that break AI character before deployment does.

Persona instability Social vulnerability Character alignment Agentic deployment

Our worldview

AI adoption is rapidly transitioning models from conversational partners into autonomous decision-makers embedded in high-stakes systems.

However, frontier models lack stable behavioral characters, routinely abandoning safety commitments and factual truth under social, authority, and narrative pressure.

B-Side Labs builds a science of AI character under pressure by designing discriminative evaluations, real-time drift detection, and interventions to ensure model character remains stable before agentic systems are deployed at scale.

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We care about AI going well and producing experiments researchers can cite and general audiences can point to and say: now I understand why this matters. If that sounds like your kind of lab, send us a message.