Every change breaks something else. We'll tell you why.
Structural diagnostic for apps built with Cursor, Lovable, Bolt.new, Replit, and v0. One score tells you if your codebase is safe to scale — or silently falling apart. Results in 24 hours.
Used to diagnose AI-generated codebases across SaaS, internal tools, and production applications.
Architecture patterns documented in the ASA Standard.
Quick Scan — Structural diagnostic of your repository
Delivered in 24 hours. Fixed price. No commitment required.
AI Chaos — the structural cost of prompt-driven development
AI-generated codebases often function correctly in early stages.
Structural instability emerges later, when prompt-driven changes accumulate faster than architectural boundaries can contain them. Each session optimizes for the immediate task without awareness of the cumulative structural state. The result is predictable: architecture drift, dependency corruption, and regression cascades.
This condition is referred to as AI Chaos. It is not a consequence of using the wrong tool or writing bad prompts. It is a structural consequence of how prompt-driven development works.
“AI magnifies existing strengths and dysfunctions rather than automatically improving delivery outcomes.”— DORA, 2025 (Google Research, 5,000 respondents)
“Low-quality code contains up to 15× more defects than high-quality code.”— Tornhill & Borg, 2022 (39 proprietary codebases)
Your codebase may be structurally unstable if:
If you recognize three or more of these symptoms, the structural cause is likely measurable.
How the diagnostic works
Root cause analysis
Your repository is analyzed against five root cause dimensions: architecture drift, dependency corruption, structural entropy, test infrastructure, and deployment safety (RC01–RC05). Each is identified and scored.
Risk classification
Codebase is classified by the AI Chaos Index (ACI) — a quantitative measure of structural risk from 0 (stable) to 100 (critical).
Diagnostic report delivery
Clear explanation of structural condition, prioritized findings, and recommended next steps. Delivered in 24 hours (Quick Scan) or 2–3 days (Full Audit).
Example diagnostic output
Repository: client-app (Next.js + Supabase)
Generated with: Lovable
Age: 4 months | 38k LOC
Root Cause Analysis
RC01 Architecture Drift 7.2 / 10 HIGH
RC02 Dependency Corruption 5.8 / 10 ELEVATED
RC03 Structural Entropy 4.1 / 10 MODERATE
RC04 Test Infrastructure 8.5 / 10 CRITICAL
RC05 Deployment Safety 6.3 / 10 HIGH
AI Chaos Index: 64.8 / 100 Risk Band: HIGH
Top Findings
[CRITICAL] 14 files exceed 500 LOC (max: 1,847)
[CRITICAL] Test coverage ratio: 3%
[HIGH] 6 circular dependency chains detected
[HIGH] No CI/CD pipeline
[ELEVATED] Business logic in 8 route handlers
Recommendation: Structural stabilization
recommended before adding features.
This is an example output. Your report will reflect the actual structural state of your repository.
24h delivery. File-level findings. Stabilization roadmap.
Behind the Audit
Our structural audits are powered by the ASA Engine — a deterministic boundary enforcement scanner we also provide as a free local CLI tool.
The path to stability
Four phases. Each is a separate engagement. You decide at each step whether to continue.
Diagnose
Architecture Audit
Structural failure patterns identified. AI Chaos Score. Prioritized roadmap.
OPEN — $297Learn more →Stabilize
Cap, Bridge & Grow
Freeze legacy. Fix boundaries. Zero-rewrite architecture migration.
POST-AUDITLearn more →Deploy
Production Launch
Auth, database, payments, domain & SSL. Production-ready in days.
POST-AUDITLearn more →Enforce
Continuous Protection
CI/CD safety pipeline. Boundary linting. Automated guardrails.
POST-AUDITLearn more →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.
Every week without diagnosis is a week where architecture drift, dependency corruption, and regression risk continue to accumulate. The earlier the structural state is measured, the lower the remediation cost.