Prevent your AI-built app from breaking again.
Continuous architecture enforcement — boundary linter, automated CI/CD guardrails, and structural monitoring that blocks 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.
Three layers of continuous enforcement
Layer 1: Architecture Enforcement Tooling
An automated enforcement layer that runs at development time:
- 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:
Layer 3: Structural Monitoring
Ongoing visibility into the structural state of the codebase:
- ACI score tracking — AI Chaos Index measured periodically
- Trend detection — early warning if structural entropy increases
- Architecture health reports — periodic summary of structural state
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 → Fix violations → Boundary linter
Map boundaries Resolve cycles CI/CD pipeline
Measure ACI Build test base ACI monitoring
Trend detectionProtection 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 is designed for teams using Cursor, Lovable, Bolt.new, and similar tools. It prevents AI-generated changes from violating architectural boundaries.
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.
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.
Structural stabilization services are available after diagnostic confirmation. Because structural failures differ significantly between codebases, remediation is performed only after forensic analysis identifies the root causes.
Structural risks compound over time.
Continuous enforcement costs a fraction of repeated stabilization.