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Prompt Engineering & LLM Optimization for Developers · Lesson

Caching & Cost Optimization for LLM Apps

LLM calls are slow and expensive. Learn caching strategies, prompt-token reduction, model routing, and batching to cut cost and latency in production.

Why Optimize Cost?

At scale, LLM API bills grow fast — you pay per input and output token on every call. Smart caching and routing can cut costs by an order of magnitude with no quality loss.

Exact-Match Response Cache

The simplest win: cache the full response keyed by the exact prompt. Identical requests return instantly and free.

const key = hash(model + JSON.stringify(messages));
const hit = cache.get(key);
if (hit) return hit;
const res = await llm(messages);
cache.set(key, res);

All lessons in this course

  1. LLM Operations (LLMops) Principles
  2. Deployment Strategies & Monitoring
  3. Scalable LLM Application Architectures
  4. Caching & Cost Optimization for LLM Apps
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