diff --git a/reinforcement_learning/clean_pufferl.py b/reinforcement_learning/clean_pufferl.py
index 3ec5e65..909fd17 100644
--- a/reinforcement_learning/clean_pufferl.py
+++ b/reinforcement_learning/clean_pufferl.py
@@ -335,15 +335,12 @@ def evaluate(data):
                 env_ids = [info["env_id"] for info in i["learner"]]
 
                 update = {
-                    "update_type": "on_demand",
-                    "metrics": {
-                        "value": data.prev_value,
-                        "next_value": value,
-                        "rew": r,
-                        "dones": d,
-                        "tasks": tasks,
-                        "env_ids": env_ids
-                    },
+                    "value": data.prev_value,
+                    "next_value": value,
+                    "rew": r,
+                    "dones": d,
+                    "tasks": tasks,
+                    "env_ids": env_ids
                 }
                 data.curriculum.update(update)
             data.prev_value = value
diff --git a/reinforcement_learning/environment.py b/reinforcement_learning/environment.py
index 852fd02..d6450b2 100644
--- a/reinforcement_learning/environment.py
+++ b/reinforcement_learning/environment.py
@@ -4,7 +4,7 @@
 import pufferlib
 import pufferlib.emulation
 from pettingzoo.utils.wrappers.base_parallel import BaseParallelWrapper
-from syllabus.core import PettingZooMultiProcessingSyncWrapper as SyllabusSyncWrapper
+from syllabus.core import PettingZooSyncWrapper as SyllabusSyncWrapper
 
 from syllabus_wrapper import SyllabusSeedWrapper
 
@@ -63,9 +63,8 @@ def env_creator(*args, **kwargs):
         if syllabus is not None:
             env = SyllabusSyncWrapper(
                 env,
-                syllabus.get_components(),
-                update_on_step=syllabus.requires_step_updates,
-                task_space=env.task_space,
+                env.task_space,
+                syllabus.components,
                 batch_size=8,
             )
 
diff --git a/syllabus_wrapper.py b/syllabus_wrapper.py
index fad72eb..435537d 100644
--- a/syllabus_wrapper.py
+++ b/syllabus_wrapper.py
@@ -6,7 +6,7 @@
 import copy
 from collections import defaultdict
 from reinforcement_learning import environment
-from syllabus.task_space import TaskSpace
+from syllabus.task_space import DiscreteTaskSpace
 from syllabus.core.evaluator import CleanRLDiscreteEvaluator, Evaluator
 from syllabus.core.task_interface import PettingZooTaskWrapper
 from syllabus.curricula import SequentialCurriculum, PrioritizedLevelReplay, CentralizedPrioritizedLevelReplay
@@ -191,13 +191,13 @@ class SyllabusSeedWrapper(PettingZooTaskWrapper):
     Wrapper to handle tasks for the Neural MMO environment.
     """
 
-    task_space = TaskSpace(200)
+    task_space = DiscreteTaskSpace(200)
 
     def __init__(self, env: gym.Env):
         super().__init__(env)
         self.env = env
 
-        self.task_space = SyllabusTaskWrapper.task_space
+        self.task_space = SyllabusSeedWrapper.task_space
         self.change_task(self.task_space.sample())
         self._task_index = None
         self.task_fn = None
@@ -227,7 +227,7 @@ class SyllabusTaskWrapper(PettingZooTaskWrapper):
     """
 
     # task_space = TaskSpace((18, 200), [tuple(np.arange(18)), tuple(np.arange(200))])
-    task_space = TaskSpace(200)
+    task_space = DiscreteTaskSpace(200)
 
     # task_space = TaskSpace((2719, 200), [tuple(np.arange(2719)), tuple(np.arange(200))])
 
diff --git a/train_helper.py b/train_helper.py
index e9d44c4..bde697e 100644
--- a/train_helper.py
+++ b/train_helper.py
@@ -78,7 +78,7 @@ def train(args, env_creator, agent_creator, syllabus=None):
         env_outputs = evaluate_agent(args, eval_data, env_outputs, data.wandb, data.global_step)
 
         if syllabus is not None:
-            syllabus.log_metrics(data.wandb, step=data.global_step)
+            syllabus.log_metrics(data.wandb, [], step=data.global_step)
 
         clean_pufferl.train(data)