High Cost Question 195 of 223

How should you structure prompts to maximize prefix caching?

GenAI / LLM · Speak this in 60–90 seconds · Faridabad & Delhi NCR

PICTURE THIS: AN LLM TURN

Text inTokens
TransformerAttention
Text outNext token

Simple meaning

Put the large static system prompt, tool schemas, and stable few-shot block first.

1

WHY — Tokens instead of words?

LLMs use tokens (not full words) because it helps them:

Cost questions separate people

who only read docs from people who shipped.

Keep it short, concrete,

and tied to GenAI / LLM work.

Stable token IDs

Each piece maps to a number the network can learn.

Fits the model

Fixed pieces are what transformers expect as input.

2

STEPS — What happens step by step?

Before you speak the answer, walk the interviewer through these steps:

  1. 1
    Put the large static

    system prompt, tool schemas, and stable few-shot block first.

  2. 2
    Put user-specific and retrieved

    text last so the prefix hash stays stable.

  3. 3
    Reordering a cached prefix

    busts the cache and you pay full price again.

  4. 4
    Give an example

    One tiny concrete case you can say aloud.

  5. 5
    Common mistake

    What juniors usually get wrong.

  6. 6
    Close

    When you pick this over the alternative.

3

EXAMPLE — See it in action

Here's a short line you can speak, broken into clear beats:

Say this line
“Put user-specific and retrieved text last so the prefix hash stays stable.”
Break into beats
Putuserspecificandretrievedtext
Speaking order
2987408337471632900

Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.

Key takeaway

Put the large static system prompt, tool schemas, and stable few-shot block first. Put user-specific and retrieved text last so the prefix hash stays stable.

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