diff --git a/python/test/test_array_multiplication.py b/python/test/test_array_multiplication.py
index 4698a573c..3ef3c02c3 100644
--- a/python/test/test_array_multiplication.py
+++ b/python/test/test_array_multiplication.py
@@ -4,6 +4,18 @@ import kp
 
 def test_array_multiplication():
 
+    # 1. Create Kompute Manager (selects device 0 by default)
+    mgr = kp.Manager()
+
+    # 2. Create Kompute Tensors to hold data
+    tensor_in_a = kp.Tensor([2, 2, 2])
+    tensor_in_b = kp.Tensor([1, 2, 3])
+    tensor_out = kp.Tensor([0, 0, 0])
+
+    # 3. Initialise the Kompute Tensors in the GPU
+    mgr.eval_tensor_create_def([tensor_in_a, tensor_in_b, tensor_out])
+
+    # 4. Define the multiplication shader code to run on the GPU
     @ps.python2shader
     def compute_shader_multiply(index=("input", "GlobalInvocationId", ps.ivec3),
                                 data1=("buffer", 0, ps.Array(ps.f32)),
@@ -12,14 +24,12 @@ def test_array_multiplication():
         i = index.x
         data3[i] = data1[i] * data2[i]
 
-    tensor_in_a = kp.Tensor([2, 2, 2])
-    tensor_in_b = kp.Tensor([1, 2, 3])
-    tensor_out = kp.Tensor([0, 0, 0])
+    # 5. Run shader code against our previously defined tensors
+    mgr.eval_algo_data_def(
+      [tensor_in_a, tensor_in_b, tensor_out],
+      compute_shader_multiply.to_spirv())
 
-    mgr = kp.Manager()
-
-    mgr.eval_tensor_create_def([tensor_in_a, tensor_in_b, tensor_out])
-    mgr.eval_algo_data_def([tensor_in_a, tensor_in_b, tensor_out], compute_shader_multiply.to_spirv())
+    # 6. Sync tensor data from GPU back to local
     mgr.eval_tensor_sync_local_def([tensor_out])
 
     assert tensor_out.data() == [2.0, 4.0, 6.0]