Why is it that `input_shape` does not include the batch dimension when passed as an argument to the `Dense` layer?

In Keras, why is it that input_shape does not include the batch dimension when passed as an argument to layers like Dense but DOES include the batch dimension when input_shape is passed to the build method of a model?

import tensorflow as tf
from tensorflow.keras.layers import Dense

if __name__ == "__main__":
    model1 = tf.keras.Sequential([Dense(1, input_shape=[10])])
    model1.summary()

    model2 = tf.keras.Sequential([Dense(1)])
    model2.build(input_shape=[None, 10])  # why [None, 10] and not [10]?
    model2.summary()

Is this a conscious choice of API design? If it is, why?

from Why is it that `input_shape` does not include the batch dimension when passed as an argument to the `Dense` layer?