diff --git a/swarms/agents/workers/worker.py b/swarms/agents/workers/worker.py
index ca612f0f..5c7a376d 100644
--- a/swarms/agents/workers/worker.py
+++ b/swarms/agents/workers/worker.py
@@ -35,6 +35,10 @@ class WorkerNode:
         )
         self.agent.chain.verbose = True
 
+    def add_tool(self, tool: Tool):
+        """adds a new tool to the agents toolset"""
+        self.tools.append(tool)
+
     def run(self, tool_input: Dict[str, Any]) -> str:
         """Use the tool."""
         prompt = tool_input['prompt']
diff --git a/swarms/swarms.py b/swarms/swarms.py
index 174f8a80..4e1a860a 100644
--- a/swarms/swarms.py
+++ b/swarms/swarms.py
@@ -15,7 +15,7 @@ class Swarms:
         # Initialize language model
         return llm_class(openai_api_key=self.openai_api_key, temperature=temperature)
 
-    def initialize_tools(self, llm_class):
+    def initialize_tools(self, llm_class, worker_node):
         llm = self.initialize_llm(llm_class)
         # Initialize tools
         web_search = DuckDuckGoSearchRun()
@@ -29,6 +29,7 @@ class Swarms:
 
             # RequestsGet()
             Tool(name="RequestsGet", func=RequestsGet.get, description="A portal to the internet, Use this when you need to get specific content from a website. Input should be a  url (i.e. https://www.google.com). The output will be the text response of the GET request."),
+            Tool(name="WorkerNode AI Agent", func=worker_node.run, description="Input: an objective with a todo list for that objective. Output: your task completed: Please be very clear what the objective and task instructions are. The Swarm worker agent is Useful for when you need to spawn an autonomous agent instance as a worker to accomplish any complex tasks, it can search the internet or write code or spawn child multi-modality models to process and generate images and text or audio and so on")
 
             
             # CodeEditor,
@@ -37,6 +38,7 @@ class Swarms:
             # ExitConversation
 
             #code editor + terminal editor + visual agent
+            # Give the worker node itself as a tool
 
         ]
         assert tools is not None, "tools is not initialized"
@@ -76,19 +78,37 @@ class Swarms:
         return BossNode(llm, vectorstore, agent_executor, max_iterations=5)
 
 
-    def run_swarms(self, objective):
-        try:
-            # Run the swarm with the given objective
-            worker_tools = self.initialize_tools(OpenAI)
-            assert worker_tools is not None, "worker_tools is not initialized"
+    def run_swarms(self, objective, run_as="boss"):
+        # try:
+        #     # Run the swarm with the given objective
+        #     worker_tools = self.initialize_tools(OpenAI)
+        #     assert worker_tools is not None, "worker_tools is not initialized"
 
-            vectorstore = self.initialize_vectorstore()
-            worker_node = self.initialize_worker_node(worker_tools, vectorstore)
+        #     vectorstore = self.initialize_vectorstore()
+        #     worker_node = self.initialize_worker_node(worker_tools, vectorstore)
 
-            boss_node = self.initialize_boss_node(vectorstore, worker_node)
+        #     boss_node = self.initialize_boss_node(vectorstore, worker_node)
 
-            task = boss_node.create_task(objective)
-            return boss_node.execute_task(task)
+        #     task = boss_node.create_task(objective)
+        #     return boss_node.execute_task(task)
+        # except Exception as e:
+        #     logging.error(f"An error occurred in run_swarms: {e}")
+        #     raise
+        #===============> optional approach
+        try:
+            # Run the swarm with the given objective
+            vectorstore = self.initialize_vectorstore()
+            worker_node = self.initialize_worker_node([], vectorstore)  # Initialize with an empty tool list
+            worker_tools = self.initialize_tools(OpenAI, worker_node)  # Now the worker_node instance exists and can be passed to initialize_tools
+            worker_node.add_tool(worker_tools[-1])  # Add the self-reference tool to the actual worker_node
+
+            if run_as.lower() == 'worker':
+                tool_input = {'prompt': objective}
+                return worker_node.run(tool_input)
+            else:
+                boss_node = self.initialize_boss_node(vectorstore, worker_node)
+                task = boss_node.create_task(objective)
+                return boss_node.execute_task(task)
         except Exception as e:
             logging.error(f"An error occurred in run_swarms: {e}")
             raise
@@ -98,6 +118,17 @@ class Swarms:
 
 
 
+# usage
+def swarm(api_key, objective):
+    swarms = Swarms(api_key)
+    return swarms.run_swarms(objective)
+
+# # Use the function
+# api_key = "APIKEY"
+# objective = "What is the capital of the UK?"
+# result = swarm(api_key, objective)
+# print(result)  # Prints: "The capital of the UK is London."
+
 
 
 
@@ -214,20 +245,6 @@ class Swarms:
 
 
 
-# usage
-def swarm(api_key, objective):
-    swarms = Swarms(api_key)
-    return swarms.run_swarms(objective)
-
-# # Use the function
-# api_key = "APIKEY"
-# objective = "What is the capital of the UK?"
-# result = swarm(api_key, objective)
-# print(result)  # Prints: "The capital of the UK is London."
-
-
-
-