Maxime Rivest

This talk introduces DSPy, a framework that separates the definition of an AI task from its implementation. By declaring a task's inputs and outputs first, developers can later experiment with different models, settings, and execution strategies without altering the core task definition. This approach aims to make AI engineering more flexible and robust, especially in a rapidly evolving landscape of models and tools.