TensorFlow's automatic differentiation simplifies gradient computation through tf.GradientTape, enabling efficient reverse-mode differentiation. This powerful feature supports nested gradients, higher-order derivatives, and complex models like multi-layer perceptrons. With eager execution and tf.function, TensorFlow balances usability and performance, streamlining machine learning workflows.