Orchestrating Multiple AI Models in Sync
Design patterns for building complex systems that utilize different models for specialized tasks.
The "one model to rule them all" approach is becoming obsolete. The future of AI systems lies in orchestration—using specialized, smaller models for high-frequency tasks and orchestrating them to feed into larger, more capable models for complex reasoning.
Model Routing Patterns
Implement a "Router" pattern in your architecture. When a request comes in, a fast, cheap router model (like a distilled Llama) analyzes the intent and determines which model should handle the payload. A simple coding task gets routed to a specialized coding model, while a complex analytical request is routed to a high-reasoning model (like Claude or GPT).
Shared Memory State
When orchestrating models, you need a shared "blackboard" or persistent state where models can post findings and read context from each other. This enables complex, multi-model collaboration where one model can "pass the baton" to another, keeping the flow of reasoning consistent.