query classification

**Query Classification** is **the categorization of incoming prompts to guide downstream routing and policy decisions** - It is a core method in modern semiconductor AI serving and inference-optimization workflows. **What Is Query Classification?** - **Definition**: the categorization of incoming prompts to guide downstream routing and policy decisions. - **Core Mechanism**: Classifiers infer intent, risk, and complexity labels that drive model and tool selection. - **Operational Scope**: It is applied in semiconductor manufacturing operations and AI-agent systems to improve autonomous execution reliability, safety, and scalability. - **Failure Modes**: Misclassification can route difficult queries to weak models or bypass safety controls. **Why Query Classification Matters** - **Outcome Quality**: Better methods improve decision reliability, efficiency, and measurable impact. - **Risk Management**: Structured controls reduce instability, bias loops, and hidden failure modes. - **Operational Efficiency**: Well-calibrated methods lower rework and accelerate learning cycles. - **Strategic Alignment**: Clear metrics connect technical actions to business and sustainability goals. - **Scalable Deployment**: Robust approaches transfer effectively across domains and operating conditions. **How It Is Used in Practice** - **Method Selection**: Choose approaches by risk profile, implementation complexity, and measurable impact. - **Calibration**: Validate classifier precision per class and monitor drift with periodic relabeling audits. - **Validation**: Track objective metrics, compliance rates, and operational outcomes through recurring controlled reviews. Query Classification is **a high-impact method for resilient semiconductor operations execution** - It enables intelligent triage before expensive inference steps.