Your AI Saved 10,000 Hours. So What?
AI productivity is becoming easier to demonstrate. Converting that productivity into business value is the harder problem. Imagine presenting an AI initiative to the executive team […]
AI productivity is becoming easier to demonstrate. Converting that productivity into business value is the harder problem. Imagine presenting an AI initiative to the executive team […]
For decades, we have asked people to navigate dashboards to find answers in data. AI is beginning to reverse that relationship. For the past twenty years, […]
AI agents need authoritative business meaning, not merely access to more documents. A practical architecture test for building trustworthy enterprise context.
AI lowers the cost of creating software, but not the cost of owning it. A practical enterprise architecture test for deciding what to buy, configure, compose, or build.
MCP’s stateless core makes agent infrastructure easier to scale, but it moves responsibility for authority, progress, and recovery into the application. Here is the architecture test enterprises should run.
Enterprise AI agents should be evaluated against authoritative business state, not merely their execution traces. A practical architecture test for outcomes, authority and recovery.
The enterprise AI conversation is shifting from model selection to governed execution. Here are the architecture decisions behind identity, MCP, orchestration, semantics and observability.