diff --git a/docs/source-pytorch/common/evaluation_intermediate.rst b/docs/source-pytorch/common/evaluation_intermediate.rst
index b780650cfe..35ae7ad3ba 100644
--- a/docs/source-pytorch/common/evaluation_intermediate.rst
+++ b/docs/source-pytorch/common/evaluation_intermediate.rst
@@ -41,10 +41,10 @@ To run the test set after training completes, use this method.
     # run full training
     trainer.fit(model)
 
-    # (1) load the best checkpoint automatically (lightning tracks this for you)
+    # (1) load the best checkpoint automatically (lightning tracks this for you during .fit())
     trainer.test(ckpt_path="best")
 
-    # (2) load the last available checkpoint
+    # (2) load the last available checkpoint (only works if `ModelCheckpoint(save_last=True)`)
     trainer.test(ckpt_path="last")
 
     # (3) test using a specific checkpoint
diff --git a/src/lightning/pytorch/trainer/connectors/checkpoint_connector.py b/src/lightning/pytorch/trainer/connectors/checkpoint_connector.py
index a2f983d6f9..6ee7c3be4e 100644
--- a/src/lightning/pytorch/trainer/connectors/checkpoint_connector.py
+++ b/src/lightning/pytorch/trainer/connectors/checkpoint_connector.py
@@ -185,7 +185,7 @@ class _CheckpointConnector:
                 # not an error so it can be set and forget before the first `fit` run
                 rank_zero_warn(
                     f'.{fn}(ckpt_path="last") is set, but there is no last checkpoint available.'
-                    " No checkpoint will be loaded."
+                    " No checkpoint will be loaded. HINT: Set `ModelCheckpoint(..., save_last=True)`."
                 )
                 return None
             ckpt_path = max(candidates_ts, key=candidates_ts.get)  # type: ignore[arg-type]