diff --git a/examples/hessian.ipynb b/examples/hessian.ipynb
index b3858fc9..4d54791e 100644
--- a/examples/hessian.ipynb
+++ b/examples/hessian.ipynb
@@ -78,9 +78,9 @@
    "id": "a3ec6532-5b0a-4e4c-af33-bef58c0a7319",
    "metadata": {},
    "source": [
-    "Note the use of the `scan_kind` argument to `Tsit5`. By default, Diffrax internally uses constructs that are optimised specifically for first-order reverse mode autodifferentiation. This argument is needed to switch to a different implementation that is compatible with higher-order autodiff. (In this case: for the loop-over-stages in the Runge--Kutta solver.)\n",
+    "Note the use of the `scan_kind` argument to `Tsit5`. By default, Diffrax internally uses constructs that are optimised specifically for first-order reverse-mode autodifferentiation. This argument is needed to switch to a different implementation that is compatible with higher-order autodiff. (In this case: for the loop-over-stages in the Runge--Kutta solver.)\n",
     "\n",
-    "In similar fashion, if using `saveat=SaveAt(steps=True)` then you will need to pass `adjoint=DirectAdjoint()`. (In this case: for the loop-over-saving output.)"
+    "In similar fashion, if using `saveat=SaveAt(ts=...)` (or a handful of other esoteric cases) then you will need to pass `adjoint=DirectAdjoint()`. (In this case: for the loop-over-saving output.)"
    ]
   }
  ],