Fix false-positive self-referential useCallback in linting

Frontend teams using React hooks increasingly hit noisy lint warnings when rules flag "self-referential" useCallback or useEffect dependencies that are actually harmless, slowing reviews and encouraging unsafe rule disablement. This affects roughly 27 million professional developers working on React at companies from startups to large enterprises, and causes measurable CI churn and developer time loss on otherwise high-quality codebases. You could build a precise linting plugin and service that combines ESLint/TypeScript integration, whole-project alias-aware dataflow, and optional LLM- or graph-based semantic inference to distinguish true dependency-cycle risks from benign self-references; the product would offer editor integration, repo-wide autofix suggestions, and CI-friendly batch analysis. The core would be open source to drive adoption and trust, with a commercial layer (dashboard, enforcement policies, historical analytics) for teams that need governance. The timing is favorable: hooks proliferation and a shift-left push for stricter CI checks make accurate, low-noise rules more valuable, and the total addressable market is roughly $2.7B (27M developers × $100/year), with a Market Score of 92/100 and a Revenue Potential assessed at 78/100. Advances in AI-assisted code understanding make semantic, cross-file reasoning feasible now in ways it wasn’t three years ago. To stand out you must deliver demonstrable precision (aim for well under 1% false-positive rate), sub-second incremental analysis in editors, and explainable diagnostics so teams trust automatic suggestions; the open-source + paid model lowers adoption friction while giving enterprise upsell paths. The principal challenges are engineering complexity, maintaining soundness with evolving React and TypeScript semantics, and competing against established linters, but the combination of higher precision, explainability, and operational integrations can create a defensible niche.