Cloud AI made a bet that data would flow to the model. In military operating environments that bet fails, for two distinct reasons. This post explains why, and closes a three-part series on the design principle that runs through every layer of defence AI.
The problem in defence software delivery was never really about distance. It was always about how much of the real problem survives the journey from operator to engineer. LLMs change what fidelity is achievable when physical proximity is not possible.
Defence software delivery consistently fails because of the structural distance between the engineer who builds and the operator who uses. The case for forward deployment, why it works, and why the commercial model is the hardest barrier to fix.