AI Code Policy for Engineering Teams

Most engineering teams shipping AI-generated code have neither a technical gate nor a human process for it. The technical gate is the deterministic scanner that runs on every commit. The human process is the policy that covers who approves AI-generated PRs, what the escalation path looks like, how the evidence record satisfies compliance requirements, and how new developers inherit the baseline.

BrassCoders covers the technical gate. This page is the canonical reference for the human side.

The Policy Template

BrassCoders produced an AI code review policy template that covers both halves: the technical gate section (which scanner, which stage, which severity threshold triggers a block) and the human review section (who approves, what counts as review, how to handle contested findings). It is a starting point, not a compliance-approved document — every team adapts it to their context.

The policy template post includes the template text teams can use directly. The existing AI team code review policy post covers the strategic reasoning behind each policy decision.

Compliance: What NIST, CISA, and GDPR Require

BrassCoders does not interpret regulations. What it produces is the evidence record: a timestamped YAML findings file for every scan, covering the structural patterns that NIST AI RMF GOVERN 1.7 (documentation of AI system capabilities and limitations) and CISA's Secure AI guidelines describe as part of responsible AI deployment.

Three frameworks are most relevant for teams in regulated industries:

• NIST AI Risk Management Framework 1.0 — The GOVERN function requires documenting AI system capabilities and failure modes. The MAP function requires identifying risks. BrassCoders's findings categories are the technical risk map for AI-generated code; the findings file is the documentation artifact.
• CISA Guidelines for Secure AI System Development — Published with NCSC and Five Eyes partners (November 2023), the Develop phase requirements explicitly call for static analysis in the build pipeline. BrassCoders's CI integration is the implementation.
• GDPR Article 25 (Data Protection by Design) — Applies when AI-generated code processes EU personal data. BrassCoders's --offline flag produces zero outbound data. The findings file is the privacy-by-design documentation artifact.

The regulated industries post documents the specific NIST, CISA, and GDPR obligations and how BrassCoders's evidence record addresses them. The regulated industries research category indexes the primary source documents.

SOC2 Audit Trail for AI-Assisted Development

BrassCoders produces a consistent, timestamped YAML findings file for every scan. Under SOC2 CC7.1 (System Monitoring), auditors want evidence that code was reviewed before deployment. The .brass/ai_instructions.yaml file is that evidence record — timestamped, reproducible, and generated by the same ruleset on every scan.

The AI-specific addition: the audit trail now needs to demonstrate that AI-generated code was scanned, not just human-written code. The SOC2 audit trail for AI development post covers what changes about the evidence package when AI writes the code. The existing SOC2 post covers the baseline BrassCoders + SOC2 integration.

GDPR and AI-Generated Code Data Handling

BrassCoders's --offline flag makes it the GDPR-compatible default: zero bytes leave the machine for the OSS scan, so no data processor relationship is established. The BrassCoders Paid plan sends scanner findings (already redacted at source) and a short project signature to the hosted gateway — never raw source code.

GDPR Article 25 applies when the AI-generated code itself processes EU personal data. The GDPR data handling post covers the Article 25 framing and the practical checklist for European teams.

HIPAA and Audit-Ready Scanning

BrassCoders's immutable scan record satisfies the audit-trail requirement for development teams building software that touches protected health information. The HIPAA and SOC2 scanning post and the audit-ready scan post cover the regulated-environment workflow in detail.

Onboarding Developers to AI-Assisted Workflows

BrassCoders's onboarding path is three steps: install the CLI, add the pre-commit hook, add the CI gate. New developers inherit the security baseline on day one — the same findings format, the same severity thresholds, the same scanner ruleset as the developers who built the codebase. The onboarding playbook post walks through each step with the exact commands.

Agentic Code: The Policy Extension for Autonomous AI

Autonomous AI coding agents — SWE-agent, OpenHands, CI-triggered runners — commit code without a human in the inner loop. The policy extension for agentic code is the same as for human-prompted AI code, plus one addition: the gate must catch what the agent's test suite misses, because there is no human review step between generation and commit.

BrassCoders scans whatever lands in the repository — it doesn't know or care whether a human or an agent produced the file. The agentic code security post covers the specific risks autonomous agents introduce and how BrassCoders fits into the agentic stack.

All AI Code Policy Posts

• The AI Code Review Policy Template — working template for technical gate + human review sections
• AI Code Review Policy for Copilot Teams — policy reasoning and team-level decisions
• AI Code Policy in Regulated Industries — NIST, CISA, GDPR obligations mapped to BrassCoders
• Building a SOC2 Audit Trail for AI-Assisted Development — CC7.1 evidence for AI-generated code
• GDPR and AI-Generated Code: What Data Leaves the Machine? — Article 25 framing; offline vs. Paid plan
• Onboarding Developers to AI-Assisted Workflows — three-step baseline; pre-commit; CI
• Agentic Code Security — policy for autonomous coding agents; SWE-bench; OWASP agentic AI
• HIPAA and SOC2 Code Scanning — regulated industry workflow
• What Your Auditor Wants From Your AI Codebase — audit-ready scan workflow

Frequently Asked Questions

Does my team need an AI code review policy?

Yes, if AI-generated code reaches production. An AI code review policy covers two things a team typically lacks: a technical gate (which deterministic scanner runs, at which stage, on what severity threshold) and a human process (who approves AI-generated PRs, what the escalation path is when a finding is disputed). BrassCoders handles the technical gate; the policy defines the human side.

What is the minimum viable AI code review policy?

Three elements: a technical gate (BrassCoders scan in CI, exit-1 on CRITICAL findings), a secrets check (findings file reviewed before merge), and a human approval requirement (at least one reviewer who didn't generate the code). The AI code review policy template post at coppersun.dev/blog/ai-code-review-policy-template/ provides a starting point teams can adapt.

What SOC2 criteria does BrassCoders help satisfy?

SOC2 CC7.1 (System Monitoring) requires evidence that code was reviewed before deployment. BrassCoders produces a timestamped YAML findings file for every scan — the artifact a compliance team presents to show that code review happened. The AI-specific addition: the audit trail must now demonstrate that AI-generated code was scanned, not just human-written code.

What do NIST and CISA require for AI-generated code?

The NIST AI Risk Management Framework's GOVERN function requires documentation of AI system capabilities, limitations, and failure modes. CISA's Guidelines for Secure AI System Development (published with NCSC and Five Eyes partners) explicitly reference static analysis in the Develop phase requirements. Neither framework prescribes BrassCoders specifically; both describe the documentation and analysis obligations that BrassCoders's scan and findings file satisfy.

Does GDPR apply to AI-generated code?

GDPR Article 25 (Data Protection by Design) applies when AI-generated code processes EU personal data. The obligation is to build data protection measures from the start. BrassCoders's --offline flag produces zero outbound data — no data processor relationship is established for the scan itself. The BrassCoders Paid plan sends findings (already redacted at source) and a project signature, not raw source code.

How do I onboard developers to an AI-assisted workflow with security built in?

Three steps: install BrassCoders (pip install brasscoders), add the pre-commit hook (scans automatically on each commit), add the CI gate (scans on every PR before merge). New developers inherit the security baseline automatically — they don't need to know which scanners to run or which rules apply. The onboarding post at coppersun.dev/blog/onboarding-ai-assisted-developers/ walks through each step.

Should we run BrassCoders on code written by autonomous AI agents?

Yes. BrassCoders scans the file on disk regardless of whether a human, a prompted AI assistant, or an autonomous agent produced it. Agentic code carries the same vulnerability patterns as human-prompted AI code; the difference is the review loop is shorter or absent. Running BrassCoders on agent-committed code is the gate that catches what the agent's test suite doesn't.