WhatA tool that measures and reports on the actual quality of AI-generated code in production codebases, flagging when AI output is degrading system reliability or introducing hidden technical debt.
SignalEngineering leaders at companies adopting AI coding tools have no visibility into whether AI-generated code is actually working well or silently creating systemic problems — they are flying blind on quality metrics specific to AI output.
Why NowAI coding tools have hit mainstream enterprise adoption in 2025-2026, but quality measurement infrastructure hasn't kept pace, creating a dangerous gap as companies scale AI code generation.
MarketEngineering VPs and CTOs at mid-to-large companies using AI coding tools; $5B+ DevTools TAM; competitors like SonarQube don't differentiate AI-generated vs human code.
MoatProprietary dataset of AI code failure patterns built from analyzing thousands of production codebases, creating an ever-improving detection model.
I believe there are entire companies right now under AI psychosisView discussion ↗ · Article ↗ · 1,535 pts · May 15, 2026
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