diff --git a/libs/langchain/langchain/chains/openai_functions/base.py b/libs/langchain/langchain/chains/openai_functions/base.py
index 0d7e7cf189c..1a4c269d60a 100644
--- a/libs/langchain/langchain/chains/openai_functions/base.py
+++ b/libs/langchain/langchain/chains/openai_functions/base.py
@@ -34,7 +34,7 @@ from langchain.chains.structured_output.base import (
 __all__ = [
     "get_openai_output_parser",
     "create_openai_fn_runnable",
-    "create_structured_output_runnable",
+    "create_structured_output_runnable",  # deprecated
     "create_openai_fn_chain",  # deprecated
     "create_structured_output_chain",  # deprecated
     "PYTHON_TO_JSON_TYPES",  # backwards compatibility
@@ -144,7 +144,7 @@ def create_openai_fn_chain(
 
 
 @deprecated(
-    since="0.1.1", removal="0.2.0", alternative="create_structured_output_runnable"
+    since="0.1.1", removal="0.2.0", alternative="ChatOpenAI.with_structured_output"
 )
 def create_structured_output_chain(
     output_schema: Union[Dict[str, Any], Type[BaseModel]],
diff --git a/libs/langchain/langchain/chains/structured_output/base.py b/libs/langchain/langchain/chains/structured_output/base.py
index f26902ddf38..524dd2d228d 100644
--- a/libs/langchain/langchain/chains/structured_output/base.py
+++ b/libs/langchain/langchain/chains/structured_output/base.py
@@ -30,15 +30,15 @@ from langchain.output_parsers import (
 @deprecated(
     since="0.1.14",
     message=(
-        "LangChain has introduced a method called `with_structured_output` that"
-        "is available on ChatModels capable of tool calling."
+        "LangChain has introduced a method called `with_structured_output` that "
+        "is available on ChatModels capable of tool calling. "
         "You can read more about the method here: "
-        "https://python.langchain.com/docs/modules/model_io/chat/structured_output/"
-        "Please follow our extraction use case documentation for more guidelines"
-        "on how to do information extraction with LLMs."
-        "https://python.langchain.com/docs/use_cases/extraction/."
+        "https://python.langchain.com/docs/modules/model_io/chat/structured_output/ "
+        "Please follow our extraction use case documentation for more guidelines "
+        "on how to do information extraction with LLMs. "
+        "https://python.langchain.com/docs/use_cases/extraction/. "
         "If you notice other issues, please provide "
-        "feedback here:"
+        "feedback here: "
         "https://github.com/langchain-ai/langchain/discussions/18154"
     ),
     removal="0.3.0",
@@ -146,6 +146,42 @@ def create_openai_fn_runnable(
         return llm.bind(**llm_kwargs_) | output_parser
 
 
+@deprecated(
+    since="0.1.17",
+    message=(
+        "LangChain has introduced a method called `with_structured_output` that "
+        "is available on ChatModels capable of tool calling. "
+        "You can read more about the method here: "
+        "https://python.langchain.com/docs/modules/model_io/chat/structured_output/ "
+        "Please follow our extraction use case documentation for more guidelines "
+        "on how to do information extraction with LLMs. "
+        "https://python.langchain.com/docs/use_cases/extraction/. "
+        "If you notice other issues, please provide "
+        "feedback here: "
+        "https://github.com/langchain-ai/langchain/discussions/18154"
+    ),
+    removal="0.3.0",
+    pending=True,
+    alternative=(
+        """
+            from langchain_core.pydantic_v1 import BaseModel, Field
+            from langchain_anthropic import ChatAnthropic
+
+            class Joke(BaseModel):
+                setup: str = Field(description="The setup of the joke")
+                punchline: str = Field(description="The punchline to the joke") 
+
+            # Or any other chat model that supports tools.
+            # Please reference to to the documentation of structured_output
+            # to see an up to date list of which models support 
+            # with_structured_output.
+            model = ChatAnthropic(model="claude-3-opus-20240229", temperature=0)
+            structured_llm = model.with_structured_output(Joke)
+            structured_llm.invoke("Tell me a joke about cats. 
+                Make sure to call the Joke function.")
+            """
+    ),
+)
 def create_structured_output_runnable(
     output_schema: Union[Dict[str, Any], Type[BaseModel]],
     llm: Runnable,