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VibeDebt — Automated Tech Debt Scoring & Remediation for AI-Generated Codebases

The vibe coding wave of 2025-2026 created millions of functional apps. Now comes the hangover. Founders who built MVPs in a weekend with Cursor, Bolt, or Lovable are discovering they can't maintain what they built. Reddit r/vibecoding is filled with posts like "My codebase is unmaintainable after 3

Score83/100
Mar 26, 2026
TAM
€12.3B — Global code quality & security tooling market (2026, includes SAST, DAST, code review)
SAM
€1.8B — Non-enterprise developers using AI coding tools needing code quality analysis (est. 15% of TAM)
SOM
€1.8M — 1,200 paying customers at avg $125/mo in year 1-2
AINext.jsSaaSAPIHealth

VibeDebt — Automated Tech Debt Scoring & Remediation for AI-Generated Codebases

The Problem

The vibe coding wave of 2025-2026 created millions of functional apps. Now comes the hangover. Founders who built MVPs in a weekend with Cursor, Bolt, or Lovable are discovering they can't maintain what they built. Reddit r/vibecoding is filled with posts like "My codebase is unmaintainable after 3 months" and "Breaking existing features when adding new ones."

The core issue: AI-generated code produces "instant legacy." It works on day one but lacks the architecture, test coverage, and separation of concerns needed for long-term evolution. Studies show AI-generated code has 1.7x more issues per pull request than human-written code, doubles code churn rates, and frequently includes copy-paste patterns that create hidden coupling.

Currently, the only solutions are expensive human services: Redwerk, ISHIR, SoftTeco, and similar agencies charge $5K-$50K for "vibe code cleanup" engagements. There is no self-service SaaS that lets a non-technical founder understand their codebase's health and get actionable remediation steps.

The traditional code quality tools (SonarQube, CodeClimate) analyze code against standard patterns. But vibe-coded apps have DIFFERENT failure modes: oversized God components, tangled state management, missing error boundaries, hardcoded values, no test coverage, and — critically — AI-generated code that confidently explains itself incorrectly when you ask it to fix things.

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