AI governance isn't abstract—it's decisions under constraints. Foundations covers what matters: tech concepts vital to governance (yes, we geek out here), how obligations work in practice, what privacy means for product design, and why frameworks taking shape now determine what you can build next.
The architectural shift to persistent, structured memory is happening now. Teams building these systems need to classify the memory types their agents require and define the associated governance policies upfront.
The NIST AI RMF shifts AI risk management from abstract principles to a structured, operational process...When AI is ubiquitous, trust matters. The RMF provides a tool for building that trust through continuous improvement.
The shift to widespread AI requires a shift in approach: from reactive problem-solving to intentional design... The organizations that get ahead of this will be the ones that can prove their AI systems work as intended—and can be trusted accordingly.