How-To Deep
Dives
Step-by-step implementation guides for the operational governance controls that frameworks mandate and tools don't provide. Written for the people who have to actually build them.
How to Build a Pre-Deployment AI Risk Assessment
Most AI incidents are not failures of the model — they are failures of the deployment process. A structured pre-deployment risk assessment is the single highest-leverage governance intervention available to any organisation deploying AI. This guide shows exactly how to do it.
Building a Tested Incident Response Capability for AI Systems
The AI Human Proof standard requires a documented, tested process for detecting, triaging, responding to and learning from AI incidents. Most organisations have the document and have never run the test. This guide sets out what a tested capability contains, using two 2026 incidents where the gap between having a process and having run it is visible in the public record — including a state Attorney General's subpoena that shows exactly what an organisation is asked to produce when an incident becomes compulsory process.
Designing Human-in-the-Loop Systems That Actually Work
Human-in-the-loop (HITL) is cited in almost every AI governance framework as a key mitigation. It is also one of the most poorly implemented governance controls in practice. This guide separates effective HITL design from performative HITL that creates the appearance of oversight without the substance.