Perspectives on governance, architecture, and building AI that works in production.
As AI systems move from experiments to production, organizations are discovering that governance isn't a constraint—it's a requirement for sustainable deployment.
How separating governance, systems, and execution layers creates AI architectures that scale without losing control.
The gap between a working prototype and a production system is wider than most teams expect. Here's what it takes to cross it.
AI agents are powerful when they have freedom to act. They're trustworthy when that freedom has clear limits.
Compliance teams need to understand what AI systems did and why. Here's how to design auditability from the start.
The build-vs-buy decision for AI is more nuanced than for traditional software. A framework for making the right choice.