What's the right way to deploy AI-written code to production?

One pipeline, identical gates

The single biggest deployment mistake AI-heavy teams make is building a parallel pipeline for agent-authored code. That shortcut always ends badly — agents push faster than humans, so the "agent pipeline" tends to get built with fewer checks, and production regressions follow. The right approach is a single pipeline that both humans and agents flow through, with identical gates. bRRAIn's Code Sandbox enforces this — every inbound patch, regardless of author, runs the same CVE scan, coverage check, pattern audit, and dependency review before it can advance.

Add an explicit policy gate

On top of the standard CI gates, add an explicit policy gate. This is where the Security Policy Engine evaluates the patch against organizational rules: which actions require human approval, which namespaces are off-limits, which dependencies are banned, which rate limits apply. The gate runs identically for human and agent authors, but it rejects a higher proportion of agent patches because agents operate at higher volume and sometimes lower taste. That rejection is a feature, not a bug. A patch that fails policy fails because it would have caused harm if deployed — no matter who wrote it.

Require an ADR for nontrivial deploys

Require an Architecture Decision Record for every nontrivial change, stored in the bRRAIn Vault. The ADR documents intent: what problem, which options, which choice, which trade-offs. A human reviewer signs off on the ADR before the patch proceeds to production. The reviewer is not reading every line of the diff — they are reading the intent and checking that it matches their mental model of the system. This upstream check scales with agent volume in a way diff-level review never did, and it becomes a durable institutional record of why the system looks the way it does.

Audit every deploy end to end

Every deploy, human or agent, should be attributable through the Control Plane and recorded in the audit trail. When something breaks in production at 2 a.m., the on-call engineer needs to see exactly which agent ran under which policy at which timestamp, with which ADR in hand. That traceability is non-negotiable in regulated industries, and it is simply good practice everywhere else. bRRAIn's Deploy Checklist in the certification curriculum codifies the full sequence — pipeline, policy gate, ADR review, audit logging — as a repeatable standard across human and AI contributors.

Relevant bRRAIn products and services

• Code Sandbox — the shared pipeline that enforces identical gates on human and agent patches alike.
• Security Policy Engine — the explicit policy gate that blocks harmful changes regardless of author.
• bRRAIn Vault — the ADR store that anchors intent review upstream of code review.
• Control Plane / audit trail — the attribution and traceability layer every deploy flows through.
• Certification program — the Deploy Checklist curriculum that codifies the full deploy sequence as team standard.