Definition
Prompt Optimization is the iterative process of refining input templates, instruction hierarchies, and retrieved context structures to maximize an LLM's performance, reliability, and cost-efficiency. It requires balancing context window density (token cost) against model reasoning accuracy to achieve deterministic outcomes in agentic workflows.
Moves beyond manual 'trial-and-error' phrasing toward programmatic, data-driven instruction engineering.
"An audio engineer adjusting a mixing board to isolate a clear signal while minimizing background noise and distortion."
- Prompt Engineering(Foundational Prerequisite)
- Few-Shot Prompting(Optimization Component)
- DSPy(Algorithmic Framework)
- LLM Evaluation (Eval)(Performance Metric)
Conceptual Overview
Prompt Optimization is the iterative process of refining input templates, instruction hierarchies, and retrieved context structures to maximize an LLM's performance, reliability, and cost-efficiency. It requires balancing context window density (token cost) against model reasoning accuracy to achieve deterministic outcomes in agentic workflows.
Disambiguation
Moves beyond manual 'trial-and-error' phrasing toward programmatic, data-driven instruction engineering.
Visual Analog
An audio engineer adjusting a mixing board to isolate a clear signal while minimizing background noise and distortion.