Last month, our LLM API bills hit $47,000 .

This month: $2,800 .

Same product. Same user experience. Same performance.

94% cost reduction without sacrificing quality.

Here's the architecture that made it possible.

The Wake-Up Call

CFO's message: "Fix this or we shut down the AI features."

We had 90 days.

Most teams would panic and start cutting features. We treated it as an architecture problem, not a budget problem.

The Solution: 3-Layer Caching + Intelligent Routing

Layer 1: Prompt Caching (68% hit rate)

Problem: Every request pays for the same tokens repeatedly.

Standard system prompts, documentation, static context—all charged every time.

Solution: Claude's native prompt caching.

import anthropic

client = anthropic . Anthropic ( api_key = " your-key " )

# Mark cacheable content with cache_control message = client . messages .…