PARCER as an Operational Contract to Reduce Variance, Cost, and Risk in LLM Systems

Researchers propose PARCER, a new framework that acts as an operational contract to address major governance challenges in Large Language Model systems. The framework uses structured YAML configurations to reduce variance, improve cost control, and enhance predictability in LLM operations through seven operational phases and decision hygiene practices.

• →PARCER framework addresses critical LLM governance issues including stochastic variance and context utilization degradation in long inputs.
• →The system transforms unstructured LLM interactions into versioned and executable artifacts using declarative YAML contracts.
• →Framework implements seven operational phases with decision hygiene practices inspired by legal judgments to reduce systemic noise.
• →PARCER introduces adaptive token budgeting and formalized recovery routes to preserve context and control costs.
• →The approach represents an evolution from simple prompt engineering to comprehensive context engineering with governable oversight.