diff --git a/generator/ctrl/training_utils/training.py b/generator/ctrl/training_utils/training.py
index e439fdd..4b9c787 100644
--- a/generator/ctrl/training_utils/training.py
+++ b/generator/ctrl/training_utils/training.py
@@ -142,7 +142,7 @@ def loss(labels, logits):
 # the optimizer is not used since this code only supports inference
 # however, to compile the model, we still define it
 optimizer = tf.contrib.estimator.clip_gradients_by_norm(
-    tf.train.AdagradOptimizer(learning_rate=3e-3), 0.25)
+    tf.train.AdagradOptimizer(learning_rate=1e-2), 0.25)
 
 # compile the model with the optimizer and loss
 model.compile(optimizer=optimizer, loss=loss)
diff --git a/story/story_manager.py b/story/story_manager.py
index c1bec84..c2ee15d 100644
--- a/story/story_manager.py
+++ b/story/story_manager.py
@@ -41,9 +41,7 @@ class Story():
         self.results.append(story_block)
 
     def latest_result(self):
-        if len(self.results) >= 2:
-            return self.context + self.results[-2] + self.actions[-1] + self.results[-1]
-        elif len(self.results) >= 1:
+        if len(self.results) >= 1:
             return self.context + self.actions[-1] + self.results[-1]
         else:
             return self.context + self.story_start