diff --git a/docs/source/notebooks/AdvancedGuide.ipynb b/docs/source/notebooks/AdvancedGuide.ipynb
index 4c9ba9e..7948b69 100644
--- a/docs/source/notebooks/AdvancedGuide.ipynb
+++ b/docs/source/notebooks/AdvancedGuide.ipynb
@@ -606,6 +606,43 @@
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Param shape with `None`\n",
+    "\n",
+    "Sometimes we know that a Param ought to have a particular number of dimensions, but we don't know ahead of time what size they will be. For example a Param may represent a 2D image, but of any size. We can enforce this by setting the Param shape to `(None, None)`. Now when we set a value for this param, it will need to conform to that expectation. A scalar value will raise an error, and a 3D value will be assumed to be batched. Here is a basic example:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "p = ck.Param(\"image\", shape=(None, None))\n",
+    "print(\"Not very interesting, just returns exactly what we set: \", p.shape)\n",
+    "try:\n",
+    "    p.value = 5\n",
+    "except Exception as e:\n",
+    "    print(\"Got an error: \", e)\n",
+    "\n",
+    "p.value = np.ones((10, 15))\n",
+    "print(\"Now p shape reflects the value that was set: \", p.shape)\n",
+    "\n",
+    "p.value = np.ones((5, 20, 25))\n",
+    "print(\"Now p shape reflects the appropriate 2 dimensions:\", p.shape)\n",
+    "print(\"And the extra dimension is assumed to be a batch dimension: \", p.batch_shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note that the `None` must be in a tuple for it to work this way. So `param.shape = None` means no defined shape, it will just take the shape of `param.value.shape`; a 1D vector of unspecified length must be written as `param.shape = (None,)`. You may also mix and match, so `param.shape = (None, 2)` would be an unspecified number of size `2` vectors, for example."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/src/caskade/param.py b/src/caskade/param.py
index 2e3d997..7fe79a4 100644
--- a/src/caskade/param.py
+++ b/src/caskade/param.py
@@ -12,15 +12,22 @@
 
 
 def valid_shape(batch_shape, shape, value_shape):
-    if shape is None:  # no shape to compare
+    # No shape to compare
+    if shape is None:
         return True
+
+    # Determine what to compare
     if batch_shape is None:
-        if value_shape == shape:  # shapes match
-            return True
-        if value_shape[len(value_shape) - len(shape) :] == shape:  # endswith
-            return True
+        value_shape = value_shape[len(value_shape) - len(shape) :]
+    else:
+        shape = batch_shape + shape
+
+    # Definitely dont match, wrong lengths
+    if len(value_shape) != len(shape):
         return False
-    return value_shape == (batch_shape + shape)
+
+    # Check for match or None
+    return all(s is None or v == s for v, s in zip(value_shape, shape))
 
 
 NULL = object()
@@ -265,13 +272,20 @@ def to_pointer(self, value, link=()):
         self.node_type = "pointer"
 
     @property
-    def shape(self) -> Optional[tuple[int, ...]]:
-        if self._shape is not None:
-            return self._shape
+    def shape(self) -> tuple[int, ...]:
         value = self.value
-        if value is not None:
-            return tuple(value.shape)
-        return ()
+        # 1. Handle cases where no shape template is defined
+        if self._shape is None:
+            return tuple(value.shape) if value is not None else ()
+
+        # 2. If value is missing, return the template as-is
+        if value is None:
+            return self._shape
+
+        # 3. Fill wildcards (None) in _shape using the trailing dimensions of value
+        # Negative indexing handles the alignment automatically
+        n = len(self._shape)
+        return tuple(v if s is None else s for s, v in zip(self._shape, value.shape[-n:]))
 
     @shape.setter
     def shape(self, shape: Optional[Iterable]):
@@ -286,7 +300,9 @@ def shape(self, shape: Optional[Iterable]):
         try:
             shape = tuple(shape)
         except TypeError:
-            raise ParamConfigurationError(f"Param shape must be iterable of ints ({self.name})")
+            raise ParamConfigurationError(
+                f"Param shape must be iterable of ints/None, not: {type(shape)}. ({self.name})"
+            )
         if value is None or valid_shape(self._batch_shape, shape, tuple(value.shape)):
             self._shape = shape
             return
diff --git a/tests/test_param.py b/tests/test_param.py
index 354edf8..0adbb5b 100644
--- a/tests/test_param.py
+++ b/tests/test_param.py
@@ -7,9 +7,7 @@
     ActiveStateError,
     ParamConfigurationError,
     ParamTypeError,
-    GraphError,
     InvalidValueWarning,
-    LinkToAttributeError,
     ActiveContext,
     backend,
 )
@@ -62,6 +60,35 @@ def test_param_creation(many_param, capsys):
     assert captured.out == ""
 
 
+def test_none_shape_param(capsys):
+    p = Param("p", np.ones((3, 4, 5)), shape=(None, 5))
+    assert p.shape == (4, 5)
+    assert p.batch_shape == (3,)
+    p.value = np.ones((2, 3, 5))
+    assert p.shape == (3, 5)
+    assert p.batch_shape == (2,)
+
+    p.value = None
+
+    assert p.shape == (None, 5)
+
+    with pytest.raises(ParamConfigurationError):
+        p.value = np.ones(5)
+    with pytest.raises(ParamConfigurationError):
+        p.value = np.ones((2, 2))
+
+    p.value = np.ones((4, 5))
+
+    with pytest.raises(ValueError):
+        p.shape = (4, 2)
+    with pytest.raises(ValueError):
+        p.shape = (3, 4, 5)
+
+    # Ensure no spurious output
+    captured = capsys.readouterr()
+    assert captured.out == ""
+
+
 @pytest.mark.parametrize("value", [None, 1, [1, 2]])
 @pytest.mark.parametrize("dynamic", [True, False])
 def test_active_state(value, dynamic):