How I cut my AI agent costs 95% without sacrificing quality

Six weeks ago I was spending $340/month on AI API calls for a system running 4 agents 24/7. Today that same system costs $18/month. Same agents. Same quality. Same uptime. Here's exactly how I did it — not theory, actual production code. The problem with "just use the best model" When you start building AI agents, you default to the best model available. Makes sense. You want it to work. But here's what that looks like at scale: Agent checks email every 10 minutes: 720 runs/day Agent writes daily briefing: 1 run/day Agent handles support questions: ~50 runs/day Agent posts social content: ~10 runs/day If every single call uses Claude Opus or GPT-4, you're running a Porsche engine to check if the mail arrived. The fix: a 3-tier model stack After running this in production for 6 weeks, here's the routing I landed on: Tier 1 — FAST + CHEAP ($0.0001/1K tokens) → Routine checks, classification, simple yes/no → Model: Claude Haiku / GPT-4o-mini / Gemini Flash Tier 2 — BALANCED ($0.002/1K tok