What is Prompt Caching?
Prompt Caching
A capability of modern LLM APIs to cache portions of prompts (typically system prompts and few-shot examples), reducing cost and latency on subsequent requests that share the cached prefix.
How Prompt Caching Works
When a request shares a prefix with a recent cached request, the LLM provider serves the cached intermediate results rather than recomputing them. Anthropic's prompt caching reduces input token costs by up to 90% on cached portions. OpenAI's caching is automatic for prompts over 1024 tokens with prefixes that match recent requests. Cache TTL varies by provider (typically 5 minutes to 1 hour). Engineers structure prompts to maximize cache hits: stable instructions and examples first, variable user input last.
Why Prompt Caching Matters
For applications with long system prompts or many examples (most production LLM apps), prompt caching produces 50-90% cost reductions on input tokens. The savings compound across millions of requests. Engineers building cost-sensitive AI products should treat prompt caching as a baseline optimization, not an advanced technique.
Practical Example
A SaaS company's AI customer support tool sends a 4,000-token system prompt with every request. After enabling Anthropic prompt caching, their input token costs dropped 80%. The total monthly LLM bill dropped from $48,000 to $11,000 with no change in quality.
Use Cases
- Production cost reduction
- High-volume applications
- RAG with stable retrievers
- Customer-facing AI
Salary Impact
Cost optimization expertise is valued in senior AI engineering and infrastructure roles.
Where this skill pays off
This skill shows up most in software engineering roles. See live data on the AI premium, the tools, and what hiring managers screen for.
AI for Software Engineering → · Skills page · Salary breakdown
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Frequently Asked Questions
What does Prompt Caching stand for?
Prompt Caching stands for Prompt Caching. A capability of modern LLM APIs to cache portions of prompts (typically system prompts and few-shot examples), reducing cost and latency on subsequent requests that share the cached prefix.
What skills do I need to work with Prompt Caching?
Key skills for Prompt Caching include: LLM APIs, Anthropic SDK, OpenAI SDK, Prompt Engineering. Most roles also expect Python proficiency and experience with production systems.
How does Prompt Caching affect salary?
Cost optimization expertise is valued in senior AI engineering and infrastructure roles.
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