What 10 Open Source Repos Reveal About Development Drift in the AI Era

Every major tech company is pushing AI-generated code. Microsoft says 30% (targeting 80%). Google says 30%. Uber reports 65-72%. Amazon mandated 80% AI tool usage. Shopify made AI "mandatory." But Google's own DORA research shows a paradox: AI increases throughput while decreasing delivery stability. Teams ship faster, but the code breaks more often. I wanted to understand why . So I built Evolution Engine , an open source CLI that detects development process drift — when patterns in commit history, CI builds, deployments, and dependency signals shift in ways that often precede production issues. Then I ran it on 10 major open source repos across cloud infrastructure, frontend frameworks, AI tooling, and developer platforms. No AI APIs are called during analysis. All pattern detection is deterministic and statistical. The tool runs entirely locally — your code never leaves your machine. Here's what I found. The scale Across 10 repos, the tool analyzed over 130,000 commits, generating 2