Gagan's response effectively outlines the architecture of an AI-based image recognition system using Python. He covers essential aspects such as defining project requirements, selecting appropriate machine learning frameworks like TensorFlow or PyTorch, and designing system architecture involving data collection, preprocessing, model training, and deployment. He also mentions using CNNs for model training and applying MVC and Repository design patterns for modularity and maintainability. Additionally, Gagan discusses deploying the model on cloud platforms and implementing CI/CD pipelines. His response demonstrates a good understanding of the topic, aligning well with the benchmark response.