Controlling AI Models from the Inside
<p>As generative AI moves into production, traditional guardrails and input/output filters can prove too slow, too expensive, and/or too limited. In this episode, Alizishaan Khatri of Wrynx joins Daniel and Chris to explore a fundamentally different approach to AI safety and interpretability. They unpack the limits of today’s black-box defenses, the role of interpretability, and how model-native, runtime signals can enable safer AI systems. </p><p>Featuring:</p><ul><li>Alizishaan Khatri – <a href="https://www.linkedin.com/in/alizishaan-khatri-32a20637/">LinkedIn</a></li><li>Chris Benson – <a href="https://chrisbenson.com/">Website</a>, <a href="https://www.linkedin.com/in/chrisbenson">LinkedIn</a>, <a href="https://bsky.app/profile/chrisbenson.bsky.social">Bluesky</a>, <a href="https://github.com/chrisbenson">GitHub</a>, <a …
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