Cut your AI cost IN HALF (EASY)

The video introduces the concept of model routing as a method to reduce AI costs by intelligently selecting the appropriate model for a given task. It highlights that AI models have different costs associated with their token usage and complexity, with some models being much cheaper but less capable than others. The speaker explains that instead of using the most powerful model for every task, model routing allows for the selection of the best-fit model, thus saving significant costs. An example is provided where building a feature spec is done with a cheaper model ('Fable') while writing the code uses a more expensive but capable model ('Codex'). The speaker demonstrates the cost difference using hypothetical pricing, showing substantial savings by utilizing cheaper models for simpler tasks and more capable ones for complex tasks. The video concludes by emphasizing the importance of optimizing model selection for cost-efficiency and efficiency.