Prompt Compression: Drop the Filler, Keep the Numbers, Negations and Entities
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Most of your prompt is filler. A long system prompt, a stack of retrieved chunks, a block of few-shot examples — a large fraction of those tokens carry almost no information: articles, connectives, hedges, boilerplate. You pay for every one of them on every call, and prefill latency grows with prompt length. Prompt compression, the idea behind Microsoft's LLMLingua family, shrinks the text by scoring each token's information value and dropping the lowest until it hits a target ratio — keeping…
1Key Takeaways
- A long system prompt, a stack of retrieved chunks, a block of few-shot examples — a large fraction of those tokens carry almost no information: articles, connectives, hedges, boilerplate.
- You pay for every one of them on every call, and prefill latency grows with prompt length.
- Prompt compression, the idea behind Microsoft's LLMLingua family, shrinks the text by scoring each token's information value and dropping the lowest until it hits a target ratio — keeping….
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that a long system prompt, a stack of retrieved chunks, a block of few-shot examples — a large fraction of those tokens carry almost no information: articles, connectives, hedges, boilerplate.
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