🅰️ℹ️ 1️⃣0️⃣1️⃣ The Keys to Prompt Optimization
~ This is a part of our AI 101 series ~ Author of this issue: Isabel González Editor: Ksenia Se
This article breaks prompt optimization down into four core strategies—expansion, decomposition, disambiguation, and abstraction—showing how each can improve the clarity, context, and effectiveness of LLM queries. It covers internal and external expansion, sequential and parallel decomposition, ambiguity resolution, and broader query reframing, while also looking at how these techniques can be combined and automated with tools like DSPy, GEPA, and MIPROv2.
For your convenience, we consolidate our AI explainers, practical guides, and deep dives in one place to help engineers, builders, and curious readers understand the fast-moving AI landscape. Read the complete article for free here: LLM Prompt Optimization Techniques: The Four Pillars
