Constitutional AI and Rule Overrides

Anthropic's January 22, 2026 Claude Constitution runs 79 pages and is CC0. It moves from rule-based to reason-based alignment and establishes a four-tier priority hierarchy: (1) safety and supporting human oversight, (2) ethics, (3) Anthropic guidelines, (4) helpfulness. Behaviours split into hardcoded prohibitions (bioweapons uplift, CSAM) that operators and users cannot override and soft-coded defaults that operators can adjust within defined bounds. The 2022 original (Bai et al.) trained harmlessness via self-critique and RLAIF against a constitution. The honest caveat: reason-based alignment relies on the model generalising principles to unanticipated situations. Anthropic's own 2023 participatory experiment showed ~50% divergence between public-sourced and corporate principles; the 2026 version did not incorporate those findings.

Learn 1 hr Python (stdlib, four-tier priority resolver)

Prerequisites: Phase 15 · 06 (Automated alignment research), Phase 15 · 10 (Permission modes)

#The Problem

A fielded agent sees inputs that its designers never saw. No rule list is long enough to cover them. No rule list is short enough to apply quickly under compute pressure. The practical question: how do you align an agent to principles that survive both a long tail of cases and fast inference?

Rule-based alignment (RBA): list every disallowed thing. Fast to check, easy to audit, impossible to keep current, often over-refuses on close analogs it didn't anticipate. Reason-based alignment (the 2026 Claude Constitution): encode principles, let the model reason. Scales across unseen cases, harder to audit, failure mode is principle-misapplication rather than miss-the-rule.

The 2026 Constitution takes an explicit middle position. Hardcoded prohibitions — things whose wrongness does not depend on context (bioweapons uplift, CSAM) — are RBA: never, regardless of operator or user instruction. Everything else is reason-based within a four-tier hierarchy: safety and supporting human oversight first; ethics second; Anthropic-declared guidelines third; helpfulness last. Operators can adjust defaults within the soft-coded zone but cannot touch the hardcoded prohibitions.

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The text and code of this lesson are based on AI Engineering from Scratch by Rohit Ghumare, MIT licensed.