prompt-tuninglisted

# Prompt tuning — working with non-deterministic output > Every rule here has a measured cost behind it. The first one alone accounts > for three tuning rounds spent moving a number that had never moved. ## Measure before you change anything **1. Take a noise baseline BEFORE the first edit.** Same prompt, same inputs, at least two runs; record the spread of every metric you care about. A delta smaller than the spread is noise, not the effect of your change. To compare two versions, run each at least three times per input and compare **medians**. Measured: ±20% output length and a jumping paragraph count **with no change to the prompt at all**. Three rounds of tuning were spent chasing that before anyone ran the same prompt twice. **2. Measure conversion factors between representations; never assume them.** One initiative assumed a 1.15× expansion between two languages and measured 1.3–1.4×. The assumption would have invalidated the entire budget built on it. When a factor's spread is wider than your target band, no source-side budget can guarantee the target — catch the tail with a gate **after** the transformation instead of tightening the budget before it. **3. After three failed rewordings of the same defect on the same case, name it a KNOWN LIMITATION** and hand it to a human. A fourth blind iteration is chasing noise with extra steps. ## Writing the prompt **4. Every numeric example becomes a quota; every template phrase becomes a verbatim anchor.** Describe the