diff --git a/docs/source/user_guide/basic_concepts/dataframe_introduction.rst b/docs/source/user_guide/basic_concepts/dataframe_introduction.rst
index a549210b08..51fba9dbba 100644
--- a/docs/source/user_guide/basic_concepts/dataframe_introduction.rst
+++ b/docs/source/user_guide/basic_concepts/dataframe_introduction.rst
@@ -78,7 +78,7 @@ In this case, Daft is just deferring the work required to read the data and sele
 
     When you call methods on a Daft Dataframe, it defers the work by adding to an internal "plan". You can examine the current plan of a DataFrame by calling :meth:`df.explain() <daft.DataFrame.explain>`!
 
-    Passing the ``show_optimized=True`` argument will show you the plan after Daft applies its query optimizations, and passing ``include_physical=True`` will also show you the physical (lower-level) plan.
+    Passing the ``show_all=True`` argument will show you the plan after Daft applies its query optimizations and the physical (lower-level) plan.
 
 We can tell Daft to execute our DataFrame and cache the results using :meth:`df.collect() <daft.DataFrame.collect>`:
 
diff --git a/tutorials/image_querying/top_n_red_color.ipynb b/tutorials/image_querying/top_n_red_color.ipynb
index 940c0ac7ea..2e9b90a1a6 100644
--- a/tutorials/image_querying/top_n_red_color.ipynb
+++ b/tutorials/image_querying/top_n_red_color.ipynb
@@ -218,7 +218,7 @@
    "source": [
     "Doing these two `Filter`s one after another is really inefficient since we have to pass through the data twice!\n",
     "\n",
-    "Don't worry though - Daft's query optimizer will actually optimize this at runtime and merge the two `Filter` operations into one. You can view the optimized plan with `show_optimized=True`:"
+    "Don't worry though - Daft's query optimizer will actually optimize this at runtime and merge the two `Filter` operations into one. You can view the optimized plan with `show_all=True`:"
    ]
   },
   {
@@ -230,7 +230,7 @@
    },
    "outputs": [],
    "source": [
-    "df.explain(show_optimized=True)"
+    "df.explain(show_all=True)"
    ]
   },
   {
@@ -500,7 +500,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.9.18"
   },
   "vscode": {
    "interpreter": {
diff --git a/tutorials/intro.ipynb b/tutorials/intro.ipynb
index 793ecd59e7..7214cb8dd8 100644
--- a/tutorials/intro.ipynb
+++ b/tutorials/intro.ipynb
@@ -198,7 +198,7 @@
    "outputs": [],
    "source": [
     "# df.explain()\n",
-    "# df.explain(show_optimized=True)"
+    "# df.explain(show_all=True)"
    ]
   },
   {
@@ -294,7 +294,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.9.18"
   },
   "orig_nbformat": 4
  },