prompt chaining

**Prompt Chaining** is **a workflow pattern that links multiple prompts sequentially so each step feeds the next stage** - It is a core method in modern LLM workflow execution. **What Is Prompt Chaining?** - **Definition**: a workflow pattern that links multiple prompts sequentially so each step feeds the next stage. - **Core Mechanism**: Pipeline stages perform decomposition, transformation, validation, and synthesis with explicit intermediate states. - **Operational Scope**: It is applied in LLM application engineering and production orchestration workflows to improve reliability, controllability, and measurable output quality. - **Failure Modes**: Weak handoff contracts between stages can propagate errors and amplify drift across the chain. **Why Prompt Chaining 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**: Define typed intermediate outputs and insert validation checkpoints between chain steps. - **Validation**: Track objective metrics, compliance rates, and operational outcomes through recurring controlled reviews. Prompt Chaining is **a high-impact method for resilient LLM execution** - It enables complex multi-step task automation using manageable prompt modules.