A Case for Agentic Governance and Policy Management
Why are we still coding security policy in Rego, YAML, or JavaScript when developers are using AI to write application code?
Security posture management is stuck in the past. Traditional policy-as-code is too slow, too rigid, and creates silos of expertise that can’t keep up with modern cloud environments.
Developers Have AI Co-pilots, Why Don’t Security Teams?
AI-powered coding assistants have transformed developer productivity. Security teams, on the other hand, are still writing policies as code. Why not empower security teams to define policy as intent and let AI-native agents handle enforcement, validation, and adoption—across infrastructure, applications, and environments?
This post makes the case for a new model: Agentic Governance and Policy Management (AGPM) — a paradigm where policy is no longer static code but dynamic, intent-driven, and AI-native. In AGPM, CISOs and security teams express high-level security goals in natural language, and AI agents handle implementation, validation, and enforcement.
What is Agentic Governance and Policy Management (AGPM)?
Agentic Governance and Policy Management (AGPM) reimagines policy management where security policy is defined by human intent, not complex code.
Instead of writing scripts in Rego, YAML, or DSLs, you state your goal in a natural language prompt. An intelligent agent then translates that intent into enforceable rules and applies them across your entire stack.
Tools like Open Policy Agent (OPA), Kyverno, and HashiCorp Sentinel are powerful, but they rely on “policy-as-code,” which requires security engineers to learn and maintain complex, domain-specific languages - Too Much Code, Not Enough Agility — This slows down the entire security lifecycle and making policy changes a tedious, error-prone process.
From Policy as Code → Policy as Prompt™
In AGPM, policy is expressed in natural language. This makes intent the new source of truth, allowing security leaders to define goals directly without translating them into code. It’s a shift from Policy as Code → Policy as Prompt™. For example:
“Ensure all AWS cloud storage buckets are private and encrypted.”
“Enable CIS benchmarks for Kubernetes Deployments.”
“Update existing rule for EFS to enforce encryption at rest.”
“Validate EC2 instances have autoscaling enabled.”
No Rego. No YAML. Just intent.
Unified Policy Across the Stack
AGPMs are designed to interface across the entire software and infrastructure lifecycle—from Terraform and Kubernetes to application dependencies and API schemas. This provides a single, prompt-driven interface to manage and enforce policy across the stack.
Enforce in Minutes, Not Weeks
By moving from manual policy authoring to AI-assisted enforcement, AGPM drastically reduces the time it takes to implement new security controls. Teams can define an intent, let the agent translate, enforce, monitor, and iterate on the results in near real-time.
Agentic Governance and Policy Management isn’t an incremental improvement or a layered enhancement to traditional tools like OPA, Kyverno, or Sentinel. It is a fundamental shift from coding brittle rules to orchestrating intelligent agents that understand our goals -> A New Foundation for Security
Just as AI code assistants revolutionized software development, AGPM will revolutionize how we secure that software—collaboratively, continuously, and intelligently.
Building the Future at Pegasys.ai, we are turning this vision into reality. We’re building Aegis, an AI-native engine that allows you to manage policy with prompts, not code.