Input validation, output guardrails, the 5-layer defense stack, and monitoring patterns for AI systems in production.
Defense layer one: validating inputs before they reach the model, engineering prompts for robustness, and why you cannot sanitize your way out of injection.
Defense layer two: catching dangerous outputs before they reach users or downstream systems. Content classifiers, output schemas, and the tradeoff between safety and utility.
A complete defensive architecture for production AI systems. Each layer, what it catches, and how layers work together to stop what individual controls miss.
You cannot defend what you cannot see. Logging AI interactions, detecting attacks in production, alerting on agent behavior anomalies, and incident response.