diff --git a/GramAddict/core/perception/action_memory.py b/GramAddict/core/perception/action_memory.py
index ee36e27..a3fa1ed 100644
--- a/GramAddict/core/perception/action_memory.py
+++ b/GramAddict/core/perception/action_memory.py
@@ -71,7 +71,10 @@ class ActionMemory:
             self._last_click_context = None
             return
 
-        logger.info(f"✅ [ActionMemory] Confirming success for '{ctx['intent']}'. Boosting confidence.")
+        logger.info(
+            f"✅ [ActionMemory] Confirming success for '{ctx['intent']}'. Boosting confidence.",
+            extra={"color": "\x1b[32m"}
+        )
 
         # Store or boost in Qdrant
         try:
@@ -95,7 +98,10 @@ class ActionMemory:
         if intent and ctx["intent"] != intent:
             return
 
-        logger.warning(f"❌ [ActionMemory] Click failed for '{ctx['intent']}'. Applying penalty.")
+        logger.warning(
+            f"❌ [ActionMemory] Click failed for '{ctx['intent']}'. Applying penalty.",
+            extra={"color": "\x1b[31m"}
+        )
 
         try:
             self.ui_memory.decay_confidence(ctx["intent"], ctx["xml_context"])
diff --git a/GramAddict/core/qdrant_memory.py b/GramAddict/core/qdrant_memory.py
index aff3a14..a0a7a9d 100644
--- a/GramAddict/core/qdrant_memory.py
+++ b/GramAddict/core/qdrant_memory.py
@@ -429,8 +429,9 @@ class UIMemoryDB(QdrantBase):
             if exact_points:
                 eval_result = _evaluate_payload(exact_points[0].payload, score=1.0, point_id=point_id)
                 if eval_result:
-                    logger.debug(
-                        f"Resolved intent '{intent}' from Qdrant Memory via EXACT ID MATCH! (Confidence: {eval_result['effective_confidence']:.2f})"
+                    logger.info(
+                        f"🧠 [Memory] Applying learned pattern for '{intent}' (EXACT MATCH, Confidence: {eval_result['effective_confidence']:.2f})",
+                        extra={"color": "\x1b[36m"}  # Cyan color
                     )
                     return eval_result["solution"]
                 # If exact match failed evaluation (e.g. decayed), we shouldn't fall back to vector search because it's the exact intent!
@@ -459,8 +460,9 @@ class UIMemoryDB(QdrantBase):
             if results and results[0].score >= similarity_threshold:
                 eval_result = _evaluate_payload(results[0].payload, score=results[0].score, point_id=results[0].id)
                 if eval_result:
-                    logger.debug(
-                        f"Resolved intent '{intent}' from Qdrant Memory via vector search! (Score: {results[0].score:.3f}, Confidence: {eval_result['effective_confidence']:.2f})"
+                    logger.info(
+                        f"🧠 [Memory] Applying learned pattern for '{intent}' (VECTOR MATCH, Score: {results[0].score:.3f}, Confidence: {eval_result['effective_confidence']:.2f})",
+                        extra={"color": "\x1b[36m"}  # Cyan color
                     )
                     return eval_result["solution"]
                 return None
@@ -511,7 +513,10 @@ class UIMemoryDB(QdrantBase):
                 ],
                 wait=True,
             )
-            logger.info(f"Learned pattern for '{intent}' and saved to Qdrant Memory (ID: {point_id[:8]}...).")
+            logger.info(
+                f"📥 [Memory] Learned new pattern for '{intent}' and saved to Qdrant (ID: {point_id[:8]}...)",
+                extra={"color": "\x1b[35m"}  # Magenta color
+            )
         except Exception as e:
             logger.debug(f"Qdrant storage error: {e}")
 
@@ -573,7 +578,12 @@ class UIMemoryDB(QdrantBase):
                 payload={"confidence": new_confidence},
                 points=[point_id],
             )
-            logger.debug(f"Confidence for '{intent}' adjusted to {new_confidence:.2f} (delta: {delta:+.2f}).")
+            color = "\x1b[32m" if delta > 0 else "\x1b[31m"  # Green for positive, Red for negative
+            symbol = "📈 [Memory] Positive Reinforcement:" if delta > 0 else "📉 [Memory] Negative Reinforcement:"
+            logger.info(
+                f"{symbol} Confidence for '{intent}' adjusted to {new_confidence:.2f} (delta: {delta:+.2f})",
+                extra={"color": color}
+            )
         except Exception as e:
             logger.debug(f"Confidence adjustment error: {e}")