Policy-as-Code for AI Agent Workflows
CTOs and platform engineers evaluating policy-as-code approaches to govern AI agent actions in enterprise workflows.
El problema
Policy-as-code for AI agents means expressing business rules, compliance constraints, and escalation thresholds as version-controlled, machine-executable code — and evaluating every AI-proposed action against that code at runtime, before execution. The key properties that make this work: (1) determinism — the same input and policy version always produce the same output; (2) compile-time validation — policy expressions are validated when they are authored, not when they evaluate a real decision; (3) parameter separation — policy logic and tenant-specific values are stored separately, so changing a discount cap does not require a code change; (4) version control — every published policy set is versioned, and historical decisions remain linked to the version that governed them. Corules uses CEL (Common Expression Language) — an open-source Google standard — as the policy expression language, providing all four properties.
Cómo lo resuelve Corules
Corules's policy runtime evaluates structured context against compiled CEL expressions — returning ALLOW, BLOCK, or ESCALATE with a reason and audit ID.
Ejemplo de política
// Policy-as-code: version-controlled, compile-time validated, parameterized
// Logic stays constant; parameters change when business rules change
// Gate 1: what may the AI propose? (evaluated before AI reasoning)
POST /v1/constraints
→ { max_discount: 0.25, required_fields: ["customer_id", "deal_value"] }
// Gate 2: is this specific proposal valid? (evaluated before execution)
POST /v1/validate
Body: { discount_pct: 0.20, customer_tier: "premium" }
→ { outcome: "ALLOW", audit_id: "aud_01J..." }Frequently Asked Questions
What is the difference between policy-as-code and prompt-based enforcement?
Prompt-based enforcement instructs an LLM to follow rules in natural language — output is probabilistic and subject to prompt injection. Policy-as-code compiles rules into deterministic expressions that evaluate to the same result every time — independent of the AI model, user inputs, and context variations.
How do non-engineers author policies?
CEL expressions are structured and readable. Corules provides a policy authoring interface where business users define rules in a guided format. The platform compiles and validates expressions before publishing — catching errors before they reach production decisions.
What does policy versioning mean in practice?
Each time you publish a policy change, a new version is created. Existing decisions reference the version that was active when they were evaluated. The new version activates atomically — in-flight decisions complete against the previous version. You can compare outcome distributions across versions before and after a change.