Guardrails and Constitutional AI in Practice
Explore how to design and implement layered guardrails for Claude deployments using Anthropic's Constitutional AI methodology. Understand the role of guardrails in enforcing customer-specific rules beyond built-in safety, including input screening, output checks, and monitoring. Learn how to tune guardrails to minimize false positives and negatives and ensure a deployment operates securely within defined principles.
Claude arrives at every deployment with safety built in. It declines clearly harmful requests, resists many manipulation attempts, and treats instructions hidden in documents with suspicion. None of that training, however, tells Claude a customer’s refund policy, which data a support agent may reveal, or which questions must go to a specialist.
Guardrails are the controls around the model that keep a deployment within its intended behavior. They cover what reaches Claude, what Claude is told, what leaves Claude, and what Claude is allowed to do. An FDE designs them for every deployment, and interviewers expect a candidate to explain both what Claude handles on its own and what the deployment must add.
What Constitutional AI gives Claude
Constitutional AI is the method Anthropic developed to train Claude against a written set of principles, called a constitution. In the first phase, the model drafts responses, critiques them against the principles, and revises them, and it learns from those revisions. In the second phase, AI feedback based on the same principles, rather than human labels for every example, guides reinforcement learning. The result is a model whose values come from principles that can be read, discussed, and updated. Claude’s constitution, covered earlier in the course, is the current version of those principles.
Anthropic adds Constitutional Classifiers for the highest-risk areas, such as weapons capable of mass harm. These are separate models, trained on examples generated from ...