Rules alone break at the edges, Anthropic argues, so an AI model needs reasons it can apply to situations its authors did not predict. That idea drives the constitution the company has written for Claude, its AI assistant. It is a single document setting out the values the model should follow. Anthropic says the document is written mainly for Claude, to help it handle tradeoffs, situations where good goals collide.
A rule can help, but it can also be gamed, misread or applied too rigidly as the context changes. The company’s answer is a kind of moral education. It tries to put the “why” inside the model, so Claude can work out the right behavior without waiting for a new rule. For a business, the payoff is reliability, because brittle behavior creates rework, escalation and slow decisions.
When values collide, the constitution ranks them. Safety comes first, then ethics, then the company’s own guidelines, then helpfulness. Because tradeoffs come up constantly in real work, an unclear order would be costly.
The document also lets Claude act as a “conscientious objector” and refuse unethical instructions, even when they come from Anthropic itself. That builds a right to disobey the company into the model’s identity. Whether it is a deep act of humility or theatre, the practical result is the same. Obedience is no longer the default measure of success.
Rules come back for the worst cases. The constitution does not pretend values alone can cover every catastrophic risk. It keeps flat bans, which it calls hard constraints, for cases where judgment is not acceptable. Reasoning handles the wide middle, where context matters.
Anthropic also uses the document in training. It helps produce large numbers of practice examples for the model, and helps rank its answers so Claude learns which ones are better. The method follows a line of research called Constitutional AI, which trains a model using a written set of principles.
The reason is cost. Training that relies on people rating answers is expensive, and slow to extend across the awkward situations real use throws up. A written document can be reused across those situations instead of rebuilt case by case. So the principles are meant to cut how much human rating is needed, while keeping the model’s behavior tied to its stated values.
