Practical guide to layering guardrails (accuracy-first then risk-based) and using evals to cut hallucinations and ensure reliability in live agent deployments. Practical guide to layering guardrails (accuracy-first then risk-based) and using evals to cut hallucinations and ensure reliability in live agent deployments. 2026 production momentum shows 57%+ have agents live; addresses common failure modes with pragmatic, measurable controls. Includes controls, pitfalls, and a phased implementation path. Practical guide to layering guardrails (accuracy-first then risk-based) and using evals to cut hallucinations and ensure reliability in live agent deployments. Why this matters Teams are under pressure to deliver AI capability quickly, but speed without control creates operational and governance risk. This guide focuses on practical execution patterns that hold up in production. Prerequisites Clear ownership for delivery and risk decisions. Baseline observability for mod...
Practical AI engineering guidance on agents, MCP, frameworks, security, ethics, and AI in insurance — implementation-first, production-ready.