diff --git a/python/packages/core/agent_framework/_types.py b/python/packages/core/agent_framework/_types.py
index 98e0967374..fce99b3488 100644
--- a/python/packages/core/agent_framework/_types.py
+++ b/python/packages/core/agent_framework/_types.py
@@ -2861,14 +2861,13 @@ def __init__(
         self.created_at = created_at
         self.finish_reason = finish_reason
         self.usage_details = usage_details
-        self.value = value
+        self._value: Any | None = value
+        self._response_format: type[BaseModel] | None = response_format
+        self._value_parsed: bool = value is not None
         self.additional_properties = additional_properties or {}
         self.additional_properties.update(kwargs or {})
         self.raw_representation: Any | list[Any] | None = raw_representation
 
-        if response_format:
-            self.try_parse_value(output_format_type=response_format)
-
     @classmethod
     def from_chat_response_updates(
         cls: type[TChatResponse],
@@ -2933,12 +2932,13 @@ async def from_chat_response_generator(
         Keyword Args:
             output_format_type: Optional Pydantic model type to parse the response text into structured data.
         """
-        msg = cls(messages=[])
+        response_format = output_format_type if isinstance(output_format_type, type) else None
+        msg = cls(messages=[], response_format=response_format)
         async for update in updates:
             _process_update(msg, update)
         _finalize_response(msg)
-        if output_format_type and isinstance(output_format_type, type) and issubclass(output_format_type, BaseModel):
-            msg.try_parse_value(output_format_type)
+        if response_format and issubclass(response_format, BaseModel):
+            msg.try_parse_value(response_format)
         return msg
 
     @property
@@ -2946,16 +2946,64 @@ def text(self) -> str:
         """Returns the concatenated text of all messages in the response."""
         return ("\n".join(message.text for message in self.messages if isinstance(message, ChatMessage))).strip()
 
+    @property
+    def value(self) -> Any | None:
+        """Get the parsed structured output value.
+
+        If a response_format was provided and parsing hasn't been attempted yet,
+        this will attempt to parse the text into the specified type.
+
+        Raises:
+            ValidationError: If the response text doesn't match the expected schema.
+        """
+        if self._value_parsed:
+            return self._value
+        if (
+            self._response_format is not None
+            and isinstance(self._response_format, type)
+            and issubclass(self._response_format, BaseModel)
+        ):
+            self._value = self._response_format.model_validate_json(self.text)
+            self._value_parsed = True
+        return self._value
+
     def __str__(self) -> str:
         return self.text
 
-    def try_parse_value(self, output_format_type: type[BaseModel]) -> None:
-        """If there is a value, does nothing, otherwise tries to parse the text into the value."""
-        if self.value is None and isinstance(output_format_type, type) and issubclass(output_format_type, BaseModel):
-            try:
-                self.value = output_format_type.model_validate_json(self.text)  # type: ignore[reportUnknownMemberType]
-            except ValidationError as ex:
-                logger.debug("Failed to parse value from chat response text: %s", ex)
+    def try_parse_value(self, output_format_type: type[_T] | None = None) -> _T | None:
+        """Try to parse the text into a typed value.
+
+        This is the safe alternative to accessing the value property directly.
+        Returns the parsed value on success, or None on failure.
+
+        Args:
+            output_format_type: The Pydantic model type to parse into.
+                               If None, uses the response_format from initialization.
+
+        Returns:
+            The parsed value as the specified type, or None if parsing fails.
+        """
+        format_type = output_format_type or self._response_format
+        if format_type is None or not (isinstance(format_type, type) and issubclass(format_type, BaseModel)):
+            return None
+
+        # Cache the result unless a different schema than the configured response_format is requested.
+        # This prevents calls with a different schema from polluting the cached value.
+        use_cache = (
+            self._response_format is None or output_format_type is None or output_format_type is self._response_format
+        )
+
+        if use_cache and self._value_parsed and self._value is not None:
+            return self._value  # type: ignore[return-value, no-any-return]
+        try:
+            parsed_value = format_type.model_validate_json(self.text)  # type: ignore[reportUnknownMemberType]
+            if use_cache:
+                self._value = parsed_value
+                self._value_parsed = True
+            return parsed_value  # type: ignore[return-value]
+        except ValidationError as ex:
+            logger.warning("Failed to parse value from chat response text: %s", ex)
+            return None
 
 
 # region ChatResponseUpdate
@@ -3141,6 +3189,7 @@ def __init__(
         created_at: CreatedAtT | None = None,
         usage_details: UsageDetails | MutableMapping[str, Any] | None = None,
         value: Any | None = None,
+        response_format: type[BaseModel] | None = None,
         raw_representation: Any | None = None,
         additional_properties: dict[str, Any] | None = None,
         **kwargs: Any,
@@ -3153,6 +3202,7 @@ def __init__(
             created_at: A timestamp for the chat response.
             usage_details: The usage details for the chat response.
             value: The structured output of the agent run response, if applicable.
+            response_format: Optional response format for the agent response.
             additional_properties: Any additional properties associated with the chat response.
             raw_representation: The raw representation of the chat response from an underlying implementation.
             **kwargs: Additional properties to set on the response.
@@ -3180,7 +3230,9 @@ def __init__(
         self.response_id = response_id
         self.created_at = created_at
         self.usage_details = usage_details
-        self.value = value
+        self._value: Any | None = value
+        self._response_format: type[BaseModel] | None = response_format
+        self._value_parsed: bool = value is not None
         self.additional_properties = additional_properties or {}
         self.additional_properties.update(kwargs or {})
         self.raw_representation = raw_representation
@@ -3190,6 +3242,27 @@ def text(self) -> str:
         """Get the concatenated text of all messages."""
         return "".join(msg.text for msg in self.messages) if self.messages else ""
 
+    @property
+    def value(self) -> Any | None:
+        """Get the parsed structured output value.
+
+        If a response_format was provided and parsing hasn't been attempted yet,
+        this will attempt to parse the text into the specified type.
+
+        Raises:
+            ValidationError: If the response text doesn't match the expected schema.
+        """
+        if self._value_parsed:
+            return self._value
+        if (
+            self._response_format is not None
+            and isinstance(self._response_format, type)
+            and issubclass(self._response_format, BaseModel)
+        ):
+            self._value = self._response_format.model_validate_json(self.text)
+            self._value_parsed = True
+        return self._value
+
     @property
     def user_input_requests(self) -> list[UserInputRequestContents]:
         """Get all BaseUserInputRequest messages from the response."""
@@ -3215,7 +3288,7 @@ def from_agent_run_response_updates(
         Keyword Args:
             output_format_type: Optional Pydantic model type to parse the response text into structured data.
         """
-        msg = cls(messages=[])
+        msg = cls(messages=[], response_format=output_format_type)
         for update in updates:
             _process_update(msg, update)
         _finalize_response(msg)
@@ -3238,7 +3311,7 @@ async def from_agent_response_generator(
         Keyword Args:
             output_format_type: Optional Pydantic model type to parse the response text into structured data
         """
-        msg = cls(messages=[])
+        msg = cls(messages=[], response_format=output_format_type)
         async for update in updates:
             _process_update(msg, update)
         _finalize_response(msg)
@@ -3249,13 +3322,40 @@ async def from_agent_response_generator(
     def __str__(self) -> str:
         return self.text
 
-    def try_parse_value(self, output_format_type: type[BaseModel]) -> None:
-        """If there is a value, does nothing, otherwise tries to parse the text into the value."""
-        if self.value is None:
-            try:
-                self.value = output_format_type.model_validate_json(self.text)  # type: ignore[reportUnknownMemberType]
-            except ValidationError as ex:
-                logger.debug("Failed to parse value from agent run response text: %s", ex)
+    def try_parse_value(self, output_format_type: type[_T] | None = None) -> _T | None:
+        """Try to parse the text into a typed value.
+
+        This is the safe alternative when you need to parse the response text into a typed value.
+        Returns the parsed value on success, or None on failure.
+
+        Args:
+            output_format_type: The Pydantic model type to parse into.
+                               If None, uses the response_format from initialization.
+
+        Returns:
+            The parsed value as the specified type, or None if parsing fails.
+        """
+        format_type = output_format_type or self._response_format
+        if format_type is None or not (isinstance(format_type, type) and issubclass(format_type, BaseModel)):
+            return None
+
+        # Cache the result unless a different schema than the configured response_format is requested.
+        # This prevents calls with a different schema from polluting the cached value.
+        use_cache = (
+            self._response_format is None or output_format_type is None or output_format_type is self._response_format
+        )
+
+        if use_cache and self._value_parsed and self._value is not None:
+            return self._value  # type: ignore[return-value, no-any-return]
+        try:
+            parsed_value = format_type.model_validate_json(self.text)  # type: ignore[reportUnknownMemberType]
+            if use_cache:
+                self._value = parsed_value
+                self._value_parsed = True
+            return parsed_value  # type: ignore[return-value]
+        except ValidationError as ex:
+            logger.warning("Failed to parse value from agent run response text: %s", ex)
+            return None
 
 
 # region AgentResponseUpdate
diff --git a/python/packages/core/tests/core/test_types.py b/python/packages/core/tests/core/test_types.py
index c5187fd960..fe719967db 100644
--- a/python/packages/core/tests/core/test_types.py
+++ b/python/packages/core/tests/core/test_types.py
@@ -705,6 +705,124 @@ def test_chat_response_with_format_init():
     assert response.value.response == "Hello"
 
 
+def test_chat_response_value_raises_on_invalid_schema():
+    """Test that value property raises ValidationError with field constraint details."""
+    from typing import Literal
+
+    from pydantic import Field, ValidationError
+
+    class StrictSchema(BaseModel):
+        id: Literal[5]
+        name: str = Field(min_length=10)
+        score: int = Field(gt=0, le=100)
+
+    message = ChatMessage(role="assistant", text='{"id": 1, "name": "test", "score": -5}')
+    response = ChatResponse(messages=message, response_format=StrictSchema)
+
+    with raises(ValidationError) as exc_info:
+        _ = response.value
+
+    errors = exc_info.value.errors()
+    error_fields = {e["loc"][0] for e in errors}
+    assert "id" in error_fields, "Expected 'id' Literal constraint error"
+    assert "name" in error_fields, "Expected 'name' min_length constraint error"
+    assert "score" in error_fields, "Expected 'score' gt constraint error"
+
+
+def test_chat_response_try_parse_value_returns_none_on_invalid():
+    """Test that try_parse_value returns None on validation failure with Field constraints."""
+    from typing import Literal
+
+    from pydantic import Field
+
+    class StrictSchema(BaseModel):
+        id: Literal[5]
+        name: str = Field(min_length=10)
+        score: int = Field(gt=0, le=100)
+
+    message = ChatMessage(role="assistant", text='{"id": 1, "name": "test", "score": -5}')
+    response = ChatResponse(messages=message)
+
+    result = response.try_parse_value(StrictSchema)
+    assert result is None
+
+
+def test_chat_response_try_parse_value_returns_value_on_success():
+    """Test that try_parse_value returns parsed value when all constraints pass."""
+    from pydantic import Field
+
+    class MySchema(BaseModel):
+        name: str = Field(min_length=3)
+        score: int = Field(ge=0, le=100)
+
+    message = ChatMessage(role="assistant", text='{"name": "test", "score": 85}')
+    response = ChatResponse(messages=message)
+
+    result = response.try_parse_value(MySchema)
+    assert result is not None
+    assert result.name == "test"
+    assert result.score == 85
+
+
+def test_agent_response_value_raises_on_invalid_schema():
+    """Test that AgentResponse.value property raises ValidationError with field constraint details."""
+    from typing import Literal
+
+    from pydantic import Field, ValidationError
+
+    class StrictSchema(BaseModel):
+        id: Literal[5]
+        name: str = Field(min_length=10)
+        score: int = Field(gt=0, le=100)
+
+    message = ChatMessage(role="assistant", text='{"id": 1, "name": "test", "score": -5}')
+    response = AgentResponse(messages=message, response_format=StrictSchema)
+
+    with raises(ValidationError) as exc_info:
+        _ = response.value
+
+    errors = exc_info.value.errors()
+    error_fields = {e["loc"][0] for e in errors}
+    assert "id" in error_fields, "Expected 'id' Literal constraint error"
+    assert "name" in error_fields, "Expected 'name' min_length constraint error"
+    assert "score" in error_fields, "Expected 'score' gt constraint error"
+
+
+def test_agent_response_try_parse_value_returns_none_on_invalid():
+    """Test that AgentResponse.try_parse_value returns None on Field constraint failure."""
+    from typing import Literal
+
+    from pydantic import Field
+
+    class StrictSchema(BaseModel):
+        id: Literal[5]
+        name: str = Field(min_length=10)
+        score: int = Field(gt=0, le=100)
+
+    message = ChatMessage(role="assistant", text='{"id": 1, "name": "test", "score": -5}')
+    response = AgentResponse(messages=message)
+
+    result = response.try_parse_value(StrictSchema)
+    assert result is None
+
+
+def test_agent_response_try_parse_value_returns_value_on_success():
+    """Test that AgentResponse.try_parse_value returns parsed value when all constraints pass."""
+    from pydantic import Field
+
+    class MySchema(BaseModel):
+        name: str = Field(min_length=3)
+        score: int = Field(ge=0, le=100)
+
+    message = ChatMessage(role="assistant", text='{"name": "test", "score": 85}')
+    response = AgentResponse(messages=message)
+
+    result = response.try_parse_value(MySchema)
+    assert result is not None
+    assert result.name == "test"
+    assert result.score == 85
+
+
 # region ChatResponseUpdate
 
 
diff --git a/python/samples/getting_started/agents/azure_ai/azure_ai_with_response_format.py b/python/samples/getting_started/agents/azure_ai/azure_ai_with_response_format.py
index f446b02c67..a0af51da6a 100644
--- a/python/samples/getting_started/agents/azure_ai/azure_ai_with_response_format.py
+++ b/python/samples/getting_started/agents/azure_ai/azure_ai_with_response_format.py
@@ -41,12 +41,13 @@ async def main() -> None:
         print(f"User: {query}")
         result = await agent.run(query)
 
-        if isinstance(result.value, ReleaseBrief):
-            release_brief = result.value
+        if release_brief := result.try_parse_value(ReleaseBrief):
             print("Agent:")
             print(f"Feature: {release_brief.feature}")
             print(f"Benefit: {release_brief.benefit}")
             print(f"Launch date: {release_brief.launch_date}")
+        else:
+            print(f"Failed to parse response: {result.text}")
 
 
 if __name__ == "__main__":
diff --git a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_response_format.py b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_response_format.py
index 639ce6ac82..1a55724c60 100644
--- a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_response_format.py
+++ b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_response_format.py
@@ -56,13 +56,14 @@ async def main() -> None:
 
         result1 = await agent.run(query1)
 
-        if isinstance(result1.value, WeatherInfo):
-            weather = result1.value
+        if weather := result1.try_parse_value(WeatherInfo):
             print("Agent:")
             print(f"  Location: {weather.location}")
             print(f"  Temperature: {weather.temperature}")
             print(f"  Conditions: {weather.conditions}")
             print(f"  Recommendation: {weather.recommendation}")
+        else:
+            print(f"Failed to parse response: {result1.text}")
 
         # Request 2: Override response_format at runtime with CityInfo
         print("\n--- Request 2: Runtime override with CityInfo ---")
@@ -71,12 +72,13 @@ async def main() -> None:
 
         result2 = await agent.run(query2, options={"response_format": CityInfo})
 
-        if isinstance(result2.value, CityInfo):
-            city = result2.value
+        if city := result2.try_parse_value(CityInfo):
             print("Agent:")
             print(f"  City: {city.city_name}")
             print(f"  Population: {city.population}")
             print(f"  Country: {city.country}")
+        else:
+            print(f"Failed to parse response: {result2.text}")
 
 
 if __name__ == "__main__":
diff --git a/python/samples/getting_started/agents/openai/openai_assistants_with_response_format.py b/python/samples/getting_started/agents/openai/openai_assistants_with_response_format.py
index 796bdd803c..e48338b558 100644
--- a/python/samples/getting_started/agents/openai/openai_assistants_with_response_format.py
+++ b/python/samples/getting_started/agents/openai/openai_assistants_with_response_format.py
@@ -59,13 +59,14 @@ async def main() -> None:
 
             result1 = await agent.run(query1)
 
-            if isinstance(result1.value, WeatherInfo):
-                weather = result1.value
+            if weather := result1.try_parse_value(WeatherInfo):
                 print("Agent:")
                 print(f"  Location: {weather.location}")
                 print(f"  Temperature: {weather.temperature}")
                 print(f"  Conditions: {weather.conditions}")
                 print(f"  Recommendation: {weather.recommendation}")
+            else:
+                print(f"Failed to parse response: {result1.text}")
 
             # Request 2: Override response_format at runtime with CityInfo
             print("\n--- Request 2: Runtime override with CityInfo ---")
@@ -74,12 +75,13 @@ async def main() -> None:
 
             result2 = await agent.run(query2, options={"response_format": CityInfo})
 
-            if isinstance(result2.value, CityInfo):
-                city = result2.value
+            if city := result2.try_parse_value(CityInfo):
                 print("Agent:")
                 print(f"  City: {city.city_name}")
                 print(f"  Population: {city.population}")
                 print(f"  Country: {city.country}")
+            else:
+                print(f"Failed to parse response: {result2.text}")
         finally:
             await client.beta.assistants.delete(agent.id)
 
diff --git a/python/samples/getting_started/agents/openai/openai_responses_client_with_structured_output.py b/python/samples/getting_started/agents/openai/openai_responses_client_with_structured_output.py
index c87283947b..c33951d5d3 100644
--- a/python/samples/getting_started/agents/openai/openai_responses_client_with_structured_output.py
+++ b/python/samples/getting_started/agents/openai/openai_responses_client_with_structured_output.py
@@ -37,14 +37,13 @@ async def non_streaming_example() -> None:
     # Get structured response from the agent using response_format parameter
     result = await agent.run(query, options={"response_format": OutputStruct})
 
-    # Access the structured output directly from the response value
-    if result.value:
-        structured_data: OutputStruct = result.value  # type: ignore
-        print("Structured Output Agent (from result.value):")
+    # Access the structured output using try_parse_value for safe parsing
+    if structured_data := result.try_parse_value(OutputStruct):
+        print("Structured Output Agent (from result.try_parse_value):")
         print(f"City: {structured_data.city}")
         print(f"Description: {structured_data.description}")
     else:
-        print("Error: No structured data found in result.value")
+        print(f"Failed to parse response: {result.text}")
 
 
 async def streaming_example() -> None:
@@ -67,14 +66,13 @@ async def streaming_example() -> None:
         output_format_type=OutputStruct,
     )
 
-    # Access the structured output directly from the response value
-    if result.value:
-        structured_data: OutputStruct = result.value  # type: ignore
+    # Access the structured output using try_parse_value for safe parsing
+    if structured_data := result.try_parse_value(OutputStruct):
         print("Structured Output (from streaming with AgentResponse.from_agent_response_generator):")
         print(f"City: {structured_data.city}")
         print(f"Description: {structured_data.description}")
     else:
-        print("Error: No structured data found in result.value")
+        print(f"Failed to parse response: {result.text}")
 
 
 async def main() -> None:
diff --git a/python/samples/getting_started/azure_functions/06_multi_agent_orchestration_conditionals/function_app.py b/python/samples/getting_started/azure_functions/06_multi_agent_orchestration_conditionals/function_app.py
index 71332ffcb3..2779c5ee65 100644
--- a/python/samples/getting_started/azure_functions/06_multi_agent_orchestration_conditionals/function_app.py
+++ b/python/samples/getting_started/azure_functions/06_multi_agent_orchestration_conditionals/function_app.py
@@ -12,7 +12,7 @@
 import json
 import logging
 from collections.abc import Mapping
-from typing import Any, cast
+from typing import Any
 
 import azure.functions as func
 from agent_framework.azure import AgentFunctionApp, AzureOpenAIChatClient
@@ -102,7 +102,9 @@ def spam_detection_orchestration(context: DurableOrchestrationContext):
         options={"response_format": SpamDetectionResult},
     )
 
-    spam_result = cast(SpamDetectionResult, spam_result_raw.value)
+    spam_result = spam_result_raw.try_parse_value(SpamDetectionResult)
+    if spam_result is None:
+        raise ValueError("Failed to parse spam detection result")
 
     if spam_result.is_spam:
         result = yield context.call_activity("handle_spam_email", spam_result.reason)
@@ -123,7 +125,9 @@ def spam_detection_orchestration(context: DurableOrchestrationContext):
         options={"response_format": EmailResponse},
     )
 
-    email_result = cast(EmailResponse, email_result_raw.value)
+    email_result = email_result_raw.try_parse_value(EmailResponse)
+    if email_result is None:
+        raise ValueError("Failed to parse email response")
 
     result = yield context.call_activity("send_email", email_result.response)
     return result
diff --git a/python/samples/getting_started/azure_functions/07_single_agent_orchestration_hitl/function_app.py b/python/samples/getting_started/azure_functions/07_single_agent_orchestration_hitl/function_app.py
index 6786e56137..b9665e3d15 100644
--- a/python/samples/getting_started/azure_functions/07_single_agent_orchestration_hitl/function_app.py
+++ b/python/samples/getting_started/azure_functions/07_single_agent_orchestration_hitl/function_app.py
@@ -101,10 +101,10 @@ def content_generation_hitl_orchestration(context: DurableOrchestrationContext):
         options={"response_format": GeneratedContent},
     )
 
-    content = initial_raw.value
+    content = initial_raw.try_parse_value(GeneratedContent)
     logger.info("Type of content after extraction: %s", type(content))
 
-    if content is None or not isinstance(content, GeneratedContent):
+    if content is None:
         raise ValueError("Agent returned no content after extraction.")
 
     attempt = 0
@@ -146,11 +146,9 @@ def content_generation_hitl_orchestration(context: DurableOrchestrationContext):
                 options={"response_format": GeneratedContent},
             )
 
-            rewritten_value = rewritten_raw.value
-            if rewritten_value is None or not isinstance(rewritten_value, GeneratedContent):
+            content = rewritten_raw.try_parse_value(GeneratedContent)
+            if content is None:
                 raise ValueError("Agent returned no content after rewrite.")
-
-            content = rewritten_value
         else:
             context.set_custom_status(
                 f"Human approval timed out after {payload.approval_timeout_hours} hour(s). Treating as rejection."
diff --git a/python/samples/getting_started/chat_client/azure_responses_client.py b/python/samples/getting_started/chat_client/azure_responses_client.py
index ec15ee7723..756b295d7e 100644
--- a/python/samples/getting_started/chat_client/azure_responses_client.py
+++ b/python/samples/getting_started/chat_client/azure_responses_client.py
@@ -44,11 +44,16 @@ async def main() -> None:
             client.get_streaming_response(message, tools=get_weather, options={"response_format": OutputStruct}),
             output_format_type=OutputStruct,
         )
-        print(f"Assistant: {response.value}")
-
+        if result := response.try_parse_value(OutputStruct):
+            print(f"Assistant: {result}")
+        else:
+            print(f"Assistant: {response.text}")
     else:
         response = await client.get_response(message, tools=get_weather, options={"response_format": OutputStruct})
-        print(f"Assistant: {response.value}")
+        if result := response.try_parse_value(OutputStruct):
+            print(f"Assistant: {result}")
+        else:
+            print(f"Assistant: {response.text}")
 
 
 if __name__ == "__main__":
diff --git a/python/samples/getting_started/context_providers/simple_context_provider.py b/python/samples/getting_started/context_providers/simple_context_provider.py
index f69d5b96c6..e85de6aced 100644
--- a/python/samples/getting_started/context_providers/simple_context_provider.py
+++ b/python/samples/getting_started/context_providers/simple_context_provider.py
@@ -52,11 +52,11 @@ async def invoked(
                 )
 
                 # Update user info with extracted data
-                if result.value and isinstance(result.value, UserInfo):
-                    if self.user_info.name is None and result.value.name:
-                        self.user_info.name = result.value.name
-                    if self.user_info.age is None and result.value.age:
-                        self.user_info.age = result.value.age
+                if extracted := result.try_parse_value(UserInfo):
+                    if self.user_info.name is None and extracted.name:
+                        self.user_info.name = extracted.name
+                    if self.user_info.age is None and extracted.age:
+                        self.user_info.age = extracted.age
 
             except Exception:
                 pass  # Failed to extract, continue without updating
diff --git a/python/samples/getting_started/declarative/azure_openai_responses_agent.py b/python/samples/getting_started/declarative/azure_openai_responses_agent.py
index 37c9d00455..1dbcc6adea 100644
--- a/python/samples/getting_started/declarative/azure_openai_responses_agent.py
+++ b/python/samples/getting_started/declarative/azure_openai_responses_agent.py
@@ -20,7 +20,11 @@ async def main():
     agent = AgentFactory(client_kwargs={"credential": AzureCliCredential()}).create_agent_from_yaml(yaml_str)
     # use the agent
     response = await agent.run("Why is the sky blue, answer in Dutch?")
-    print("Agent response:", response.value.model_dump_json(indent=2))
+    # Use try_parse_value() for safe parsing - returns None if no response_format or parsing fails
+    if parsed := response.try_parse_value():
+        print("Agent response:", parsed.model_dump_json(indent=2))
+    else:
+        print("Agent response:", response.text)
 
 
 if __name__ == "__main__":
diff --git a/python/samples/getting_started/declarative/openai_responses_agent.py b/python/samples/getting_started/declarative/openai_responses_agent.py
index ee3b48787e..ed2cc89d08 100644
--- a/python/samples/getting_started/declarative/openai_responses_agent.py
+++ b/python/samples/getting_started/declarative/openai_responses_agent.py
@@ -19,7 +19,11 @@ async def main():
     agent = AgentFactory().create_agent_from_yaml(yaml_str)
     # use the agent
     response = await agent.run("Why is the sky blue, answer in Dutch?")
-    print("Agent response:", response.value)
+    # Use try_parse_value() for safe parsing - returns None if no response_format or parsing fails
+    if parsed := response.try_parse_value():
+        print("Agent response:", parsed)
+    else:
+        print("Agent response:", response.text)
 
 
 if __name__ == "__main__":