diff --git a/docs/examples/tutorials/more-components.md b/docs/examples/tutorials/more-components.md
index 17d378ba..729f9648 100644
--- a/docs/examples/tutorials/more-components.md
+++ b/docs/examples/tutorials/more-components.md
@@ -45,6 +45,7 @@ We're going to use the [`LLMChat`][plugboard.library.LLMChat] to access OpenAI:
 
 1. `LLMChat` can use [structured output](https://docs.llamaindex.ai/en/stable/understanding/extraction/structured_llms/) to process the LLM response into a known format. Here we define a Pydantic model that specifies everything we're expecting back.
 2. Setting `expand_response = True` will unpack `location`, `latitude` and `longitude` into separate outputs on the component.
+3. The LLM model is passed explicitly: LlamaIndex's default (`gpt-3.5-turbo`) has been [deprecated by OpenAI](https://platform.openai.com/docs/deprecations), so always specify a current model.
 
 !!! info
     To run this tutorial you'll need an API key for [OpenAI](https://platform.openai.com/docs/quickstart). Set the `OPENAI_API_KEY` environment variable to provide it to the model.
diff --git a/examples/tutorials/003_more_components/hello_llm.py b/examples/tutorials/003_more_components/hello_llm.py
index d2305c97..8c015a4c 100644
--- a/examples/tutorials/003_more_components/hello_llm.py
+++ b/examples/tutorials/003_more_components/hello_llm.py
@@ -72,6 +72,7 @@ async def main() -> None:
         system_prompt="Identify a geographical location from the input and provide its latitude and longitude",
         response_model=Location,
         expand_response=True,  # (2)!
+        llm_kwargs={"model": "gpt-4o-mini"},  # (3)!
     )
     # --8<-- [end:llm]
     # --8<-- [start:weather]