What is your approach to prototyping AI solutions during the design phase?

My approach to prototyping AI solutions involves several key steps. First, I define clear objectives and requirements for the prototype, focusing on the core functionality needed to validate the idea. Next, I select appropriate tools and frameworks that allow rapid development, such as Jupyter Notebooks for exploratory analysis or pre-built models for quick experimentation. I then create a minimal viable prototype (MVP) that emphasizes critical features and eliminates unnecessary complexity. Finally, I gather feedback from stakeholders through demonstrations and iterate based on their input, ensuring alignment with user needs and refining the solution before full-scale development.