Compound AI Systems: Why Your Best Architecture Uses Three Models, Not One
· 10 min read
The instinct is always to reach for the biggest model. GPT-4o, Claude Opus, Gemini Ultra — pick the frontier model, point it at the problem, and hope that raw capability compensates for architectural laziness. It works in demos. It fails in production.
The teams shipping the most reliable AI systems in 2025 and 2026 aren't using one model. They're composing three, four, sometimes five specialized models into pipelines where each component does exactly one thing well. A classifier routes. A generator produces. A verifier checks. The result is a system that outperforms any single model while costing a fraction of what a frontier-model-for-everything approach would.
