WhatA CI/CD tool that automatically routes AI-generated code through adversarial review — one LLM writes code, a different LLM writes tests, a third audits both — enforcing clean-room separation between generation and verification.
SignalMultiple developers independently discovered that using different LLMs to check each other's work produces dramatically better results than self-review, but setting up these adversarial pipelines is entirely manual and fragile today.
Why NowThe simultaneous availability of multiple competitive coding LLMs (Claude, Codex, Gemini) at API-accessible price points makes cross-model adversarial workflows feasible for the first time — six months ago there wasn't enough model diversity.
MarketEngineering teams using AI code generation (growing rapidly); $20-100/developer/month pricing; no incumbent owns this space — CI/CD tools like GitHub Actions don't have native multi-LLM orchestration.
MoatThe orchestration layer accumulates data on which model combinations and adversarial prompting strategies catch the most bugs per codebase type, creating proprietary effectiveness benchmarks that are expensive to replicate.
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