Governance, Safety & Risk Management

Keeping systems safe and compliant: layered guardrails, prompt-injection defence, failing closed, human-in-the-loop placement, GDPR, HIPAA and FedRAMP obligations, and fairness and transparency.

1. 5.1Risks, Limitations and Failure ModesKnow what model training covers and what the architect owns, recognize the recurring risk classes of LLM systems, and assess a proposed design for them before it ships.
2. 5.2Guardrails and Safety ControlsPlace guardrails at the three control points (input, output and action authorization), choose model-based or deterministic checks for each, chain them, and decide what each does when it fails.
3. 5.3Human-in-the-Loop ValidationRoute decisions to people by stakes rather than by volume, place the review where it protects against the real harm, and design the reviewer's job so oversight stays meaningful instead of becoming a rubber stamp.
4. 5.4Regulatory ComplianceTurn regulatory obligations such as HIPAA, GDPR, data residency and FedRAMP into a control register where every obligation has a technical control, an accountable owner and evidence that it works.
5. 5.5Fairness, Bias and TransparencyFind the points where an AI system can treat people unequally, measure outcomes by group where lawful, and log decisions so each one can be explained to the person affected, an auditor and an engineer.