AI Quality Paradox: How Code Complexity Drives Rework in AI-Assisted Development

The AI Quality Paradox: How Code Complexity Drives Rework in AI-Assisted Development Skip to main You are using an outdated browser. Please upgrade your browser to improve your experience. Published March 12, 2026 | Version 1.0 Preprint Open The AI Quality Paradox: How Code Complexity Drives Rework in AI-Assisted Development Authors/Creators Mennillo, Antonio Description Adopting AI coding tools without proportional QA investment does not accelerate delivery — it amplifies technical debt. We model software development as a coupled ODE system where AI-generated code erodes the team's cognitive validation capacity (σ) at rate γ·v/σ, while QA restores it at rate η(1−σ). The resulting saddle-node bifurcation defines a critical QA threshold η_c = 4γv below which no stable equilibrium exists and the system collapses into unrecoverable technical debt. Calibration across 1,594,764 file-touch events from 27 datasets and 7 language ecosystems (Python, JavaScript, Java, Go, C++, Ruby, TypeScript) yields: AI-assisted code erodes validation capacity ~12× faster than human code (γ_AI = 0.028 vs γ_human = 0.002); net velocity drops to 0.85× without QA but rises to 1.32× with a single dedicated tester (ROI: 18:1); the regime classifier sign(β(log_files)) identifies collapse trajectories from git log data alone, with no ODE calibration required. All predictions are falsifiable. All 26 analysis scripts are documented with full source code in the Supplementary Materials. The paper includes an extraction script (extract_all.sh) that reproduces the entire 1.2M-event OSS dataset from public GitHub repositories. Three documents: full paper (38 pp), executive summary (16 pp), supplementary code repository (110 pp). Files ai-quality-paradox-v5.7-EN.pdf Files (1.8 MB) Name Size Download all ai-quality-paradox-executive-summary-v5.7.pdf md5:1258848def53393bbad9b5b015e0cde1 259.7 kB Preview Download ai-quality-paradox-supplementary-v5.7.pdf md5:bec0c82c2b1d6b7d9cd55c818620ff11 1.1 MB Preview Download ai-quality-paradox-v5.7-EN.pdf md5:ff7aaec5625edc04152038f01b1d934c 412.6 kB Preview Download 2K Views 0 Downloads Show more details All versions This version Views Total views 2,296 2,296 Downloads Total downloads 0 0 Data volume Total data volume 0 Bytes 0 Bytes More info on how stats are collected.... Versions External resources Indexed in OpenAIRE Communities Keywords and subjects Keywords AI-assisted software development technical debt dynamical systems saddle-node bifurcation software quality assurance empirical software engineering queuing theory Details DOI DOI Badge DOI 10.5281/zenodo.18971198 Markdown [](https://doi.org/10.5281/zenodo.18971198) reStructuredText .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.18971198.svg :target: https://doi.org/10.5281/zenodo.18971198 HTML Image URL https://zenodo.org/badge/DOI/10.5281/zenodo.18971198.svg Target URL https://doi.org/10.5281/zenodo.18971198 Resource type Preprint Publisher Zenodo Rights License Creative Commons Attribution 4.0 International The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited. Read more Citation Export Technical metadata Created March 12, 2026 Modified March 12, 2026 Jump up This site uses cookies. Find out more on how we use cookies Accept all cookies Accept only essential cookies