Introduction

When working with AI APIs, token usage directly affects cost, speed, and scalability. Many users unknowingly inflate token consumption by asking inefficient or repetitive prompts.

The solution is not to use less AI, but to prompt more intelligently. The following 6 prompt patterns are designed to reduce waste and improve output precision, sometimes cutting token usage significantly depending on the workflow.

1. The Strict Output Format Prompt

Respond only in JSON. No explanations. No extra text.

This removes unnecessary conversational filler and forces structured output.

Best use cases: APIs, data extraction, structured responses

2. The Minimal Expansion Prompt

Explain in 3–5 bullet points only. Each point under 15 words.

This controls verbosity at the source instead of trimming output later.

Best use cases: summaries, documentation, learning content

3. The No Repetition Rule Prompt

Do not repeat ideas. Each sentence must introduce new information.

Prevents AI from rephrasing the same idea multiple times, reducing token waste.

Best use cases: long-form articles, technical explanations

4. The Assume Context Prompt

Assume prior context. Do not re-explain basics.

Removes redundant explanations that AI typically adds for clarity.

Best use cases: multi-step workflows, iterative development, chat systems

5. The Direct Answer Only Prompt

Answer directly. Skip introduction and conclusion.

Eliminates conversational padding and unnecessary closing statements.

Best use cases: Q&A systems, APIs, embedded assistants

6. The Compressed Explanation Mode Prompt

Explain using maximum information density. No filler words.

Forces concise, high-value responses with maximum information per token.

Best use cases: technical explanations, AI summarization, developer tools

Conclusion

Token efficiency is not about limiting AI capability—it is about controlling output structure and verbosity. These six prompt patterns can significantly reduce unnecessary token usage while improving clarity.