4 posts on platform & architecture.
Mandiant M-Trends 2026 measured median attack handoff at 22 seconds. At that tempo, log-and-alert fails as a control. Inline enforcement at the AI request boundary makes the policy decision before the request reaches the model. Under 50 ms enforcement overhead is invisible against 500 ms to 5 second model inference.
Model guardrails are trained behaviors inside the inference process. They degrade under fine-tuning, adversarial prompting, and role-play framing. External enforcement at the AI request boundary produces deterministic controls and identity-bound audit records that guardrails alone cannot.
Zero trust applied to AI means evaluating every model request against verified identity, current policy, and prompt-level classification. The architectural pattern is an enforcement proxy at the HTTP AI request boundary. The post-authentication gap is the most common failure mode in current deployments.
NIST Pillar 1 names verified agent identity as the foundation of the AI agent identity and authorization framework. Per-agent identifiers, delegated authority from the authorizing user, and structured propagation to the model API call are the production requirements. Static service credentials fail the test.