diff --git a/src/primaite/agents/agent.py b/src/primaite/agents/agent.py
index 685fe776..37735812 100644
--- a/src/primaite/agents/agent.py
+++ b/src/primaite/agents/agent.py
@@ -257,10 +257,17 @@ class AgentSessionABC(ABC):
             raise FileNotFoundError(msg)
         pass
 
-    @abstractmethod
-    def save(self):
+    def save(self, path_str: str | Path):
         """Save the agent."""
-        self._agent.save(self.session_path)
+        if path_str:
+            self._agent.save(path_str)
+            return
+
+        # if no path, save to root but with a random UUID
+        self._agent.save(
+            self.session_path
+            / f"{self._training_config.agent_framework}_{self._training_config.agent_identifier}_{uuid4()}"
+        )
 
     @abstractmethod
     def export(self):
diff --git a/src/primaite/agents/rllib.py b/src/primaite/agents/rllib.py
index d851ba9c..b058ffc7 100644
--- a/src/primaite/agents/rllib.py
+++ b/src/primaite/agents/rllib.py
@@ -142,6 +142,7 @@ class RLlibAgent(AgentSessionABC):
             self._save_checkpoint()
         self._agent.stop()
         super().learn()
+        self.save(self.learning_path / f"rllib_{self._training_config.agent_identifier}_{self.timestamp_str}.zip")
 
     def evaluate(
         self,
@@ -162,10 +163,6 @@ class RLlibAgent(AgentSessionABC):
         """Load an agent from file."""
         raise NotImplementedError
 
-    def save(self):
-        """Save the agent."""
-        raise NotImplementedError
-
     def export(self):
         """Export the agent to transportable file format."""
         raise NotImplementedError
diff --git a/src/primaite/agents/sb3.py b/src/primaite/agents/sb3.py
index f5ac44cb..e0c1ee79 100644
--- a/src/primaite/agents/sb3.py
+++ b/src/primaite/agents/sb3.py
@@ -89,6 +89,7 @@ class SB3Agent(AgentSessionABC):
         for i in range(episodes):
             self._agent.learn(total_timesteps=time_steps)
             self._save_checkpoint()
+        self.save(self.learning_path / f"sb3_{self._training_config.agent_identifier}_{self.timestamp_str}.zip")
         self._env.reset()
         self._env.close()
         super().learn()
@@ -123,6 +124,7 @@ class SB3Agent(AgentSessionABC):
                 if isinstance(action, np.ndarray):
                     action = np.int64(action)
                 obs, rewards, done, info = self._env.step(action)
+        self.save(self.evaluation_path / f"sb3_{self._training_config.agent_identifier}_{self.timestamp_str}.zip")
         self._env.reset()
         self._env.close()
         super().evaluate()
@@ -132,10 +134,6 @@ class SB3Agent(AgentSessionABC):
         """Load an agent from file."""
         raise NotImplementedError
 
-    def save(self):
-        """Save the agent."""
-        raise NotImplementedError
-
     def export(self):
         """Export the agent to transportable file format."""
         raise NotImplementedError