Mute Logic Lab studies how AI systems change behavior after safety layers, fine-tuning, and governance controls are applied.
Most AI work focuses on how to build systems. We focus on what systems become.
Deployed AI systems operate in a permanent post-intervention state.
After controls are introduced, behavior fragments, relocates, camouflages, and drifts over time.
These post-intervention states are not side effects. They are the dominant operating condition of deployed systems.
Mute Logic Lab treats post-intervention behavior as a first-class engineering object.
We conduct field studies on open-source systems and with selected organizations.
Outputs are used to make post-deployment risk legible—not to promise elimination, but to enable informed navigation.
Controlled prompt probing and behavioral classification across model versions and configurations.
Temporal drift analysis and comparison of documentation and localization against observed behavior.
Operating on open-source systems and with organizational partners.