diff --git a/src/lerobot/annotations/steerable_pipeline/executor.py b/src/lerobot/annotations/steerable_pipeline/executor.py
index b910b9e19..903fa0831 100644
--- a/src/lerobot/annotations/steerable_pipeline/executor.py
+++ b/src/lerobot/annotations/steerable_pipeline/executor.py
@@ -186,7 +186,7 @@ class Executor:
         staging_dir: Path,
         module: Any,
     ) -> PhaseResult:
-        if not module.enabled:
+        if module is None or not module.enabled:
             print(f"[annotate] phase={name} skipped (module disabled)", flush=True)
             return PhaseResult(name=name, episodes_processed=0, episodes_skipped=len(records))
         n = len(records)
@@ -238,7 +238,7 @@ class Executor:
         ``plan`` module with the interjection timestamps so its existing
         prompt path is reused.
         """
-        if not self.plan.enabled or not self.interjections.enabled:
+        if not self.plan or not self.plan.enabled or not self.interjections or not self.interjections.enabled:
             return PhaseResult(name="plan_update", episodes_processed=0, episodes_skipped=len(records))
         processed = 0
         for record in records:
diff --git a/src/lerobot/scripts/lerobot_annotate.py b/src/lerobot/scripts/lerobot_annotate.py
index 7444daaa1..6bda51978 100644
--- a/src/lerobot/scripts/lerobot_annotate.py
+++ b/src/lerobot/scripts/lerobot_annotate.py
@@ -64,17 +64,23 @@ def annotate(cfg: AnnotationPipelineConfig) -> None:
     root = _resolve_root(cfg)
     logger.info("annotate: root=%s", root)
 
-    vlm = make_vlm_client(cfg.vlm)
-    frame_provider = make_frame_provider(root, camera_key=cfg.vlm.camera_key, video_backend=cfg.video_backend)
+    needs_vlm = cfg.plan.enabled or cfg.interjections.enabled or cfg.vqa.enabled
+    vlm = make_vlm_client(cfg.vlm) if needs_vlm else None
+    frame_provider = (
+        make_frame_provider(root, camera_key=cfg.vlm.camera_key, video_backend=cfg.video_backend)
+        if needs_vlm
+        else None
+    )
     # Surface the resolved cameras up front so a silent vqa-module no-op
     # is obvious in job output rather than discovered post-hoc by counting
     # parquet rows.
-    cam_keys = list(getattr(frame_provider, "camera_keys", []) or [])
-    logger.info(
-        "annotate: frame_provider default camera=%r, all cameras=%s",
-        getattr(frame_provider, "camera_key", None),
-        cam_keys,
-    )
+    cam_keys = list(getattr(frame_provider, "camera_keys", []) or []) if frame_provider else []
+    if frame_provider:
+        logger.info(
+            "annotate: frame_provider default camera=%r, all cameras=%s",
+            getattr(frame_provider, "camera_key", None),
+            cam_keys,
+        )
     if cfg.vqa.enabled and not cam_keys:
         logger.warning(
             "annotate: the vqa module is enabled but no cameras were "
@@ -82,15 +88,27 @@ def annotate(cfg: AnnotationPipelineConfig) -> None:
             "meta/info.json for observation.images.* features, or pass "
             "--vlm.camera_key=<key> to seed the cameras list."
         )
-    plan = PlanSubtasksMemoryModule(vlm=vlm, config=cfg.plan, frame_provider=frame_provider)
-    interjections = InterjectionsAndSpeechModule(
-        vlm=vlm, config=cfg.interjections, seed=cfg.seed, frame_provider=frame_provider
+    plan = (
+        PlanSubtasksMemoryModule(vlm=vlm, config=cfg.plan, frame_provider=frame_provider)
+        if needs_vlm
+        else None
+    )
+    interjections = (
+        InterjectionsAndSpeechModule(
+            vlm=vlm, config=cfg.interjections, seed=cfg.seed, frame_provider=frame_provider
+        )
+        if needs_vlm
+        else None
+    )
+    vqa = (
+        GeneralVqaModule(vlm=vlm, config=cfg.vqa, seed=cfg.seed, frame_provider=frame_provider)
+        if needs_vlm
+        else None
     )
-    vqa = GeneralVqaModule(vlm=vlm, config=cfg.vqa, seed=cfg.seed, frame_provider=frame_provider)
     advantage = AdvantageModule(config=cfg.advantage)
     writer = LanguageColumnsWriter()
     validator = StagingValidator(
-        dataset_camera_keys=tuple(getattr(frame_provider, "camera_keys", []) or []) or None,
+        dataset_camera_keys=tuple(cam_keys) or None,
     )
 
     executor = Executor(