Artificial intelligence has developed to the extent that it can automate entire workflows, digital and physical. We're already seeing AI agents handle complex tasks - writing code, managing infrastructure, or making operational decisions. 

These systems can operate at scales and speeds impossible for human oversight, unlocking efficiency across every domain that requires judgment, adaptation, and decision-making. But without the infrastructure to verify its reasoning, validate  safety, and detect failures, we remain unable to grant it the autonomy its capabilities demand.

Traditional software is built deterministically. You can audit the logic, trace the execution, predict the outcome. Agentic systems are fundamentally different. They are built on stochastic foundations; probabilistic, emergent, and irreducible to simple rules.

As a result we'll need new infrastructure, one that's intentionally built for this level of machine autonomy. Infrastructure that evaluates autonomous systems continuously, learns, and adapts accordingly.