diff --git a/doc/release/upcoming_changes/20924.compatibility.rst b/doc/release/upcoming_changes/20924.compatibility.rst
index 68b7e48927b4..0446b714fe94 100644
--- a/doc/release/upcoming_changes/20924.compatibility.rst
+++ b/doc/release/upcoming_changes/20924.compatibility.rst
@@ -8,16 +8,4 @@ now due to the fact that the logic is aligned with item assignment::
     # is now identical to:
     arr[0] = scalar
 
-When previously, effectively ``arr.fill(np.asarray(scalar))`` was used
-in many cases.
-The typical possible change is that errors will be given for example for
-``np.array([0]).fill(1e300)`` or ``np.array([0]).fill(np.nan)``.
-Previously, ``arr.fill()`` would unpack 0-D object arrays if the input
-array was also of object dtype, the 0-D array will now be stored as is::
-
-    >>> arr = np.array([0], dtype=object)
-    >>> arr.fill(np.array(None, dtype=object))
-    >>> arr
-    array([array(None, dtype=object)], dtype=object)
-
-Rather than ``array([None], dtype=object)``.
+Previously casting may have produced slightly different answers when using values that could not be represented in the target `dtype` or when using `object`s.