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 . create ( model = " claude-sonnet-4-20250514 " , max_tokens = 1024 , system = [ { " type " : " text " , " text " : " You are a helpful AI assistant for our healthcare platform...…