AI Coding Agent Governance Policy: A Template

Coding agents are in most engineering organizations already, and the policy governing them usually is not. The gap is costly: code goes to providers under unknown terms, agents run in environments that can reach production, review is whatever each team decided, and after an incident nobody can say what was generated. This template closes the gap with a policy that can be adopted in a week and refined quarterly. It implements the governance section of the agentic SDLC whitepaper and pairs with the AI-generated code security checklist. It is general guidance, not legal advice; data and IP terms should be reviewed by counsel.

What does the policy cover?

Section	Question it answers	Owner
Scope and definitions	Which tools count as coding agents; which teams and repositories are covered	Engineering leadership
Permitted tools and models	What may be used; how to request additions	Platform team
Data handling	What code and data may be sent to which providers, under what terms	Security + legal
Access boundaries	What agents may reach: repositories, environments, secrets, systems	Security
Specifications	What a change must be specified with before an agent implements it	Engineering leadership
Verification gates	What every change must pass; the rule on gate edits	Platform team
Review policy	Requirements by risk class	Engineering leadership
Audit	What is recorded for every generated change	Platform team
Incidents	Handling for defects and security events traced to generated code	Security + engineering
Exceptions	How exceptions are requested, approved, and expired	Policy owner
Review cadence	When the policy is revisited	Policy owner

Section templates

Permitted tools and models

"The following tools and model versions are approved for use on covered repositories: [list]. Additions require a request to the platform team including the provider's data-handling terms, security assessment, and intended use. Tools not on the list may not be connected to covered repositories or environments."

Data handling

"Code and data may be sent to approved providers only under terms that exclude training on our content and define retention and residency. The following categories may never be sent: [secrets, customer data, regulated data, specific repositories]. Redaction and local-only modes are required where indicated." Align with AI data privacy compliance.

Access boundaries

"Agents operate under scoped identities with write access limited to designated repositories and branches. Agents have no access to production credentials, secrets, or customer data. Agent environments are isolated with controlled egress. Security-critical paths listed in [appendix] require human authorship or pairing." The identity model is in the agent identity and access control whitepaper.

Specifications and gates

"Agent-implemented changes are specified using the standard template with a risk class. Every change must pass: [gate list]. Changes to tests, CI configuration, analysis rules, or security policies require a separate human-reviewed change. Agents may not approve or merge their own changes."

Review policy

Risk class	Definition	Requirement
Low	Docs, tests for existing behavior, isolated refactors	Gates; sampled review
Medium	Feature code behind flags, internal APIs	Intent and architecture review
High	Auth, payments, migrations, public APIs, infrastructure	Line-level review by named owners; two approvals
Critical	Security controls, cryptography, compliance logic	Human-written or paired

Audit

"For every generated change we record: the tool and model version, the specification, gate results and waivers, reviewers and approvals by class. Records are retained for [period] and linked from incidents."

Incidents

"Defects or security events traced to generated code follow the standard incident process with an additional analysis of the specification, gates, and review that allowed the change, feeding updates to this policy, the gate configuration, and the specification template." A postmortem structure is in AI incident postmortem template.

Exceptions and cadence

"Exceptions are requested through [process], approved by [role], time-limited, and logged. The policy is reviewed quarterly and on any significant tool or model change."

How should the policy be rolled out?

1. Publish a first version within a week; perfect is the enemy of adopted.
2. Enforce access boundaries mechanically before anything else.
3. Configure gates on the pilot codebase; expand with adoption per how to adopt AI coding agents safely.
4. Train reviewers on the risk classes.
5. Collect exceptions for a quarter; they reveal where the policy is wrong.

What are the common mistakes?

1. Bans without alternatives.
2. Policy without enforcement of access and data rules.
3. Uniform review that ignores risk class.
4. No audit, so incidents cannot be traced.
5. Written once, while tools change monthly.

How does FISTA Solutions help?

FISTA Solutions helps engineering and security leaders adopt and enforce this policy as part of its AI enablement practice, with forward deployed engineers configuring access boundaries, gates, and audit inside your pipelines and teams. FISTA has delivered 150+ projects for 50+ companies across 12+ countries.

To adopt the policy with enforcement, message FISTA on WhatsApp, or read the AI acceptable use policy for the organization-wide counterpart.