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AI Speeds Up Coding but Slows QA, Raising Technical Debt Costs for Software Teams

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Faros AI's Q3 2026 report, covering 22,000 developers, finds that AI-assisted teams deploy more often but face larger pull requests, more unreviewed merges, and a 300% rise in time spent in QA. Monthly incidents have risen 125%, suggesting the cost of AI-accelerated development has shifted downstream to verification and release. GitClear's analysis of 623 million code changes from 2023 to 2026 reports rising duplicated code, more error-hiding patterns, and a 70% decline in refactoring as AI-assisted commits grew. The article argues that teams adopted AI tools faster than the supporting practices needed for quality, such as shared agent instructions, fast tests, and CI checks for common AI mistakes. The author notes that Faros and GitClear are industry studies rather than peer-reviewed research, though DORA findings point in the same direction.

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