Transform a messy long prompt into a compact context pack that improves inference.
Same budget question, same model. What changed between the messy prompt and the useful answer? Before: everything pasted at once After: curated context pack The latest constraint moved from buried history into the current context, so the model could attend to it during generation. Stale drafts were removed, reducing the chance that next-token prediction imitates outdated assumptions. The task and output format were stated explicitly, turning inference from open-ended completion into a bounded workplace answer. Retrieved excerpts were included directly, because embedding search only helps after the right passages enter the prompt. Context quality is a control surface. Context pack…
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