diff --git a/.jules/bolt.md b/.jules/bolt.md
index f1a8c146..63d801d9 100644
--- a/.jules/bolt.md
+++ b/.jules/bolt.md
@@ -77,3 +77,6 @@ Optimized metric route processing to O(N) by creating a mapping of routes direct
 ## 2024-07-13 - [Optimize Export Dictionary FK lookups]
 **Learning:** Found O(N * C * E) performance bottleneck in ERD export dictionaries due to repeated array searching with `edges.some()` inside a nested loop over nodes and columns.
 **Action:** Replace repeated linear array scans for edges by precomputing O(1) Set lookups of foreign key column handles per node before looping.
+## 2023-10-27 - [Dictionary Lookup over sum() in DBML Import]
+**Learning:** In the backend `dbml_import.py` logic, utilizing `sum(1 for c in columns if c["relation_oid"] == oid) + 1` inside an iteration loops dynamically allocated lists causing a heavy O(N^2) overhead, especially noticeable with wide tables or lots of fields. Also, always add a descriptive comment as Bolt.
+**Action:** Always prefer initializing a dictionary prior to the loop and use `O(1)` dict lookups like `pos = col_count_by_oid.get(oid, 0) + 1` to process sequences where frequency tracking is required within loops.
diff --git a/backend/app/spec/dbml_import.py b/backend/app/spec/dbml_import.py
index b93454a9..a37a60d2 100644
--- a/backend/app/spec/dbml_import.py
+++ b/backend/app/spec/dbml_import.py
@@ -135,6 +135,7 @@ def parse_dbml(text: str) -> dict[str, Any]:
     current: tuple[str, str] | None = None
     in_ignored_block = 0
     in_indexes = False
+    col_count_by_oid: dict[int, int] = {}
 
     for raw_line in text.splitlines():
         # ReDoS guard: no legitimate DBML line approaches this length; capping
@@ -207,11 +208,17 @@ def parse_dbml(text: str) -> dict[str, Any]:
         settings = (cm.group("settings") or "").lower()
         oid = oid_by_table[current]
         is_pk = bool(re.search(r"\bpk\b|primary\s+key", settings))
+
+        # ⚡ Bolt: Performance Optimization
+        # Use an O(1) dictionary counter instead of an O(N^2) sum(...) loop
+        # to calculate column positions efficiently for large DBML files.
+        pos = col_count_by_oid.get(oid, 0) + 1
+        col_count_by_oid[oid] = pos
         columns.append(
             {
                 "relation_oid": oid,
                 "column_name": col_name,
-                "column_position": sum(1 for c in columns if c["relation_oid"] == oid) + 1,
+                "column_position": pos,
                 "data_type": cm.group("type"),
                 "is_not_null": is_pk or "not null" in settings,
                 "has_default": "default:" in settings,