diff --git a/python/samples/03-workflows/human-in-the-loop/guessing_game_with_human_input.py b/python/samples/03-workflows/human-in-the-loop/guessing_game_with_human_input.py
index 06e9a738f5..f764de6cb7 100644
--- a/python/samples/03-workflows/human-in-the-loop/guessing_game_with_human_input.py
+++ b/python/samples/03-workflows/human-in-the-loop/guessing_game_with_human_input.py
@@ -102,12 +102,19 @@ async def on_agent_response(
         """Handle the agent's guess and request human guidance.
 
         Steps:
-        1) Parse the agent's JSON into GuessOutput for robustness.
+        1) Use .value to access the parsed structured output directly.
         2) Request info with a HumanFeedbackRequest as the payload.
         """
-        # Parse structured model output
-        text = result.agent_response.text
-        last_guess = GuessOutput.model_validate_json(text).guess
+        # Access the parsed structured model output via .value.
+        # Since the agent is configured with response_format=GuessOutput,
+        # .value returns the parsed GuessOutput instance directly.
+        agent_value = result.agent_response.value
+        if agent_value is None:
+            raise RuntimeError(
+                "AgentResponse.value is None. Ensure that the agent is invoked with "
+                "options={'response_format': GuessOutput} so structured output is available."
+            )
+        last_guess = agent_value.guess
 
         # Craft a precise human prompt that defines higher and lower relative to the agent's guess.
         prompt = (