diff --git a/examples/two_llms_talking.py b/examples/two_llms_talking.py
new file mode 100644
index 0000000..4971867
--- /dev/null
+++ b/examples/two_llms_talking.py
@@ -0,0 +1,58 @@
+import simplemind as sm
+import time
+
+
+class ConversationPlugin(sm.BasePlugin):
+    def post_send_hook(self, conversation, response):
+        # Print the LLM model and the response text.
+        print(f"{conversation.llm_model}:\n{response.text.strip()}\n\n------------\n")
+
+
+def have_conversation(rounds=3):
+    # Create two conversations - one for each AI
+    with (
+        sm.create_conversation(
+            llm_model="claude-3-5-sonnet-20241022", llm_provider="anthropic"
+        ) as claude_conv,
+        sm.create_conversation(
+            llm_model="llama3.2", llm_provider="ollama"
+        ) as llama_conv,
+    ):
+
+        # Add our plugin to both
+        plugin = ConversationPlugin()
+        claude_conv.add_plugin(plugin)
+        llama_conv.add_plugin(plugin)
+
+        # Start the conversation
+        prompt = "What do you think about the future of artificial intelligence? Please keep your response brief."
+        claude_conv.add_message("user", prompt, meta={})
+        claude_response = claude_conv.send()
+
+        # Have them discuss back and forth
+        for _ in range(rounds):
+            # Llama responds to Claude
+            llama_conv.add_message(
+                "user",
+                f"Respond to this statement from another AI: {claude_response.text}",
+                meta={},
+            )
+            llama_response = llama_conv.send()
+
+            time.sleep(1)  # Add a small delay between responses
+
+            # Claude responds to Llama
+            claude_conv.add_message(
+                "user",
+                f"Respond to this statement from another AI: {llama_response.text}",
+                meta={},
+            )
+            claude_response = claude_conv.send()
+
+            time.sleep(1)
+
+
+if __name__ == "__main__":
+    print("Starting AI conversation...\n")
+    have_conversation()
+    print("\nConversation ended.")