diff --git a/neps/optimizers/multi_fidelity/mf_bo.py b/neps/optimizers/multi_fidelity/mf_bo.py
index 66f84071..eac578f8 100755
--- a/neps/optimizers/multi_fidelity/mf_bo.py
+++ b/neps/optimizers/multi_fidelity/mf_bo.py
@@ -9,11 +9,9 @@
 from neps.utils.common import instance_from_map
 from neps.optimizers.bayesian_optimization.models import SurrogateModelMapping
 from neps.optimizers.utils import map_real_hyperparameters_from_tabular_ids
-from neps.optimizers.multi_fidelity_prior.utils import (
-    calc_total_resources_spent, normalize_vectorize_config, update_fidelity
-)
+from neps.optimizers.multi_fidelity_prior.utils import calc_total_resources_spent, update_fidelity
 from neps.search_spaces.search_space import SearchSpace
-from neps.optimizers.multi_fidelity.utils import 
+from neps.optimizers.multi_fidelity.utils import normalize_vectorize_config
 
 class MFBOBase:
     """Designed to work with model-based search on SH-based multi-fidelity algorithms.
@@ -213,6 +211,10 @@ def _fantasize_pending(self, train_x, train_y, pending_x):
         )
         pending_condition = self.observed_configs.pending_condition
         if pending_condition.any():
+            raise NotImplementedError(
+                "Fantasization not implemented yet!"
+                "This optimizer cannot be run with multiple workers yet."
+            )
             print(f"\n\nFound pending: {pending_condition.sum()}\n\n")
             pending_configs = self.observed_configs.df.loc[pending_condition]
             self._fit(train_x, train_y, train_lcs)