Prevent your AI-built app from breaking again.

Continuous architecture enforcement — boundary linter and automated CI/CD guardrails that block unsafe changes before they reach production.

Long-term protection is available after diagnostic confirmation establishes the structural baseline.

Who this is for

You stabilized your AI-generated codebase — or you're about to. Now you need to make sure it stays stable:

  • You've fixed circular dependencies and don't want them to return
  • Your team continues developing with AI tools (Cursor, Lovable, Bolt.new, v0)
  • You need to ensure new prompt-driven changes don't erode the architecture
  • You want automated enforcement — not manual reviews
  • You want to continue development without regression fear

Without continuous enforcement, the same structural violations recur in every subsequent prompt session.

Two layers of continuous enforcement

Layer 1: Architecture Enforcement Tooling

An automated enforcement layer that runs at development time. Powered by the ASA CLI:

  • Boundary linter — validates architectural boundaries on every commit
  • Dependency graph checks — detects circular dependencies before they merge
  • File size monitoring — flags files exceeding structural thresholds
  • Layer violation detection — blocks business logic in wrong layers

Layer 2: CI/CD Safety Pipeline

A four-stage automated pipeline that enforces structural integrity on every deployment:

1. Lint stage — boundary validation, architectural rules
2. Test stage — structural test baseline execution
3. Build stage — compilation and build verification
4. Deploy stage — only reached if all prior stages pass

Coming later: Structural Monitoring

Periodic ACI score tracking, trend detection, and architecture health reports. This layer is planned for a future release and is not part of the current offering.

Why diagnostic first

Long-term protection requires a structural baseline.

The enforcement layer must know what “correct” looks like before it can enforce it. The diagnostic establishes:

  • Current architectural boundaries (what to enforce)
  • Current dependency graph (what to protect)
  • Current test coverage (what to maintain)
  • Current ACI score (baseline for trend tracking)

Without this baseline, enforcement rules are arbitrary. With it, enforcement rules are precise.

The protection model

  DIAGNOSE              STABILIZE              ENFORCE (ongoing)
  ────────              ─────────              ─────────────────
  Establish baseline →  Freeze legacy     →    Boundary linter
  Map boundaries        Map dependencies       CI/CD pipeline
  Measure ACI           Document state         Automated guardrails

Protection is the third phase. It follows diagnosis and stabilization — it does not replace them.

FAQ

Can I set up enforcement without stabilization first?

It depends on the structural state. If the current codebase has significant violations, enforcement would flag everything — making it unusable. The diagnostic determines whether enforcement can be applied directly.

Does this work with AI development tools?

Yes. The enforcement layer works with AI-native IDEs like Windsurf and Claude Code. It prevents AI-generated changes from violating architectural boundaries — regardless of which AI model or tool generates the code.

What happens if I stop using the enforcement tooling?

Your codebase and deployment continue working normally. The enforcement layer is a development-time tool — not a runtime dependency. However, without automated enforcement, structural violations will start accumulating again with every AI-generated change, and you'll need to catch them manually.

Can my team manage this independently?

Yes. The enforcement tooling is designed for self-serve operation after initial setup. The CLI runs locally, the CI/CD pipeline runs in your infrastructure.

The path to stability

Four phases. Each is a separate engagement. You decide at each step whether to continue.

Remediation services are available after diagnostic confirmation. Because structural failures differ significantly between codebases, stabilization is performed only after forensic analysis identifies the root causes.

Structural risks compound over time.

Continuous enforcement costs a fraction of repeated stabilization.