Dynamic Model Routing Workflow: Using Premium AI for Planning, Cheaper Models for Execution
A practical workflow from a developer who uses expensive models like Claude for complex planning tasks, then switches to cheaper models for execution to optimize AI API costs.
Practical Summary
This workflow leverages the unique strengths of different AI models at different stages of a coding task to balance quality and cost. The strategy involves using a powerful, expensive model (like Claude 'Fable 5') in a 'plan mode' to understand and outline work for complex problems. Once the task is well-defined, the execution is handed off to a cheaper, capable model (like GPT-5.5-high/med or Composer 2.5) to write the actual code. This approach capitalizes on the expensive model's superior reasoning for hard problems while minimizing token spend on the more voluminous execution phase.
Why It Matters
As AI model pricing becomes more complex and token costs can vary significantly, ad-hoc model selection becomes inefficient. This user-tested workflow provides a structured, reproducible method for cost optimization without sacrificing quality on difficult tasks. It's valuable for developers and teams managing AI coding assistant budgets, turning a cost concern into a systematic workflow that could improve both output quality and spend predictability.
Step 1: Identify High-Complexity Planning Tasks
Begin by recognizing when a task involves 'ugly edge cases' or 'high-severity issues' that require deep understanding and complex reasoning. These are candidates for using a premium, reasoning-focused model. The goal in this phase is not to write code, but to fully comprehend and define the work.
Step 2: Use the Premium Model in 'Plan Mode'
Engage the expensive model (e.g., Claude 'Fable 5') within your AI coding assistant (like Cursor). The key is to use it 'primarily in plan mode with dedicated chats for each task.' This means creating a separate conversation for each planning objective to keep context focused and leverage the model's full reasoning power without the distraction of code execution.
Step 3: Define the Work Clearly in the Plan
Work with the premium model until the problem is thoroughly analyzed and the path to a solution is well-defined. The output of this phase should be a clear, actionable plan or specification that a less powerful model can reliably follow.