diff --git a/tests/agent_test.py b/tests/agent_test.py
index 4aacac17f..87c32b5e8 100644
--- a/tests/agent_test.py
+++ b/tests/agent_test.py
@@ -1675,25 +1675,25 @@ def test_agent_uses_task_knowledge():
             mock_knowledge = MockKnowledge.return_value
             mock_knowledge.query.return_value = [{"content": content}]
             
-            # Create an agent with a simple mocked LLM
-            with patch("crewai.llm.LLM", autospec=True) as MockLLM:
-                mock_llm = MockLLM.return_value
-                mock_llm.call.return_value = "The capital of France is Paris, where the Eiffel Tower is located."
-                
-                agent = Agent(
-                    role="Geography Teacher",
-                    goal="Provide accurate geographic information",
-                    backstory="You are a geography expert who teaches students about world capitals.",
-                    llm=mock_llm,
-                )
-                
-                # Create a task with knowledge
-                task = Task(
-                    description="What is the capital of France?",
-                    expected_output="The capital of France.",
-                    agent=agent,
-                    knowledge=mock_knowledge,
-                )
+            # Create a real LLM but patch its call method
+            agent = Agent(
+                role="Geography Teacher",
+                goal="Provide accurate geographic information",
+                backstory="You are a geography expert who teaches students about world capitals.",
+                llm=LLM(model="gpt-4o-mini"),
+            )
+            
+            # Create a task with knowledge
+            task = Task(
+                description="What is the capital of France?",
+                expected_output="The capital of France.",
+                agent=agent,
+                knowledge=mock_knowledge,
+            )
+            
+            # Mock the agent's execute_task method to avoid actual LLM calls
+            with patch.object(agent.llm, "call") as mock_llm_call:
+                mock_llm_call.return_value = "The capital of France is Paris, where the Eiffel Tower is located."
                 
                 # Execute the task
                 result = agent.execute_task(task)
@@ -1723,25 +1723,25 @@ def test_agent_with_empty_task_knowledge():
             mock_knowledge = MockKnowledge.return_value
             mock_knowledge.query.return_value = []
             
-            # Create an agent with a simple mocked LLM
-            with patch("crewai.llm.LLM", autospec=True) as MockLLM:
-                mock_llm = MockLLM.return_value
-                mock_llm.call.return_value = "The capital of France is Paris."
-                
-                agent = Agent(
-                    role="Geography Teacher",
-                    goal="Provide accurate geographic information",
-                    backstory="You are a geography expert who teaches students about world capitals.",
-                    llm=mock_llm,
-                )
-                
-                # Create a task with empty knowledge
-                task = Task(
-                    description="What is the capital of France?",
-                    expected_output="The capital of France.",
-                    agent=agent,
-                    knowledge=mock_knowledge,
-                )
+            # Create a real LLM but patch its call method
+            agent = Agent(
+                role="Geography Teacher",
+                goal="Provide accurate geographic information",
+                backstory="You are a geography expert who teaches students about world capitals.",
+                llm=LLM(model="gpt-4o-mini"),
+            )
+            
+            # Create a task with empty knowledge
+            task = Task(
+                description="What is the capital of France?",
+                expected_output="The capital of France.",
+                agent=agent,
+                knowledge=mock_knowledge,
+            )
+            
+            # Mock the agent's execute_task method to avoid actual LLM calls
+            with patch.object(agent.llm, "call") as mock_llm_call:
+                mock_llm_call.return_value = "The capital of France is Paris."
                 
                 # Execute the task
                 result = agent.execute_task(task)