diff --git a/README.md b/README.md
index e2e5d8d..a729eb7 100644
--- a/README.md
+++ b/README.md
@@ -16,12 +16,13 @@ This repo is the red circle in the diagram. It will be running on Code Ocean and
 ## Key elements
 - [Task schema](https://github.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/blob/main/code/aind_auto_train/schema/task.py) defines schema for training parameters
 - [Curriculum schema](https://github.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/blob/main/code/aind_auto_train/schema/curriculum.py) defines schema for the curriculum, especially the `evaluate_transitions` method
-- [Curriculum manager](https://github.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/blob/main/code/aind_auto_train/automation.py)  (WIP) fetches data from `df_behavior` and updates `df_manager`.
+- [Auto train manager](https://github.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/blob/main/code/aind_auto_train/auto_train_manager.py) fetches data from `df_behavior` and updates `df_manager` (or "tables" on any other database)
+- [Curriculum manager](https://github.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/blob/main/code/aind_auto_train/curriculum_manager.py) manages all available pre-generated curriculums (on any S3 bucket).
 
 ## Usage
 1. Design the curriculum, i.e., all [training stages](https://github.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/blob/main/code/aind_auto_train/curriculums/coupled_baiting.py#L199-L204) and [transition rules](https://github.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/blob/main/code/aind_auto_train/curriculums/coupled_baiting.py#L223-L247).
    - Here is an [example curriculum](https://github.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/blob/main/code/aind_auto_train/curriculums/coupled_baiting.py) for the dynamic foraging task.
-   - Here is automatically generated [json file](https://github.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/blob/main/code/aind_auto_train/curriculums/curriculum_Coupled%20Baiting_0.1_1.0.json) 
+   - Here is automatically generated [json file](https://github.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/blob/main/code/aind_auto_train/curriculums/Coupled%20Baiting_v1.0_curriculum_v0.1_schema_v0.1.json) 
    - Here are automatically rendered diagrams for stage transitions rules and parameters (click the images to try the hover feature :blush:)
 
 | rules | parameters |
@@ -29,7 +30,7 @@ This repo is the red circle in the diagram. It will be running on Code Ocean and
 |<img width="700" src="https://raw.githubusercontent.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/main/code/aind_auto_train/curriculums/Coupled%20Baiting_v1.0_curriculum_v0.1_schema_v0.1_rules.svg">|<img width="500" src="https://raw.githubusercontent.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/main/code/aind_auto_train/curriculums/Coupled%20Baiting_v1.0_curriculum_v0.1_schema_v0.1_paras.svg">|
 
 2. Create `AutoTrainManager` and connect it to the behavior database `df_behavior`.
-3. Feed all necessary metrics to `Curriculum manager` and let it run.
+3. Feed all necessary metrics to `Auto train manager` and let it run.
    - Here is an open-loop simulation with our old mice<br>
      <img width="500" src="https://github.com/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/assets/24734299/885ce4eb-33e9-471b-94e3-bb4fec4d24a8">
 
@@ -41,4 +42,5 @@ This repo is the red circle in the diagram. It will be running on Code Ocean and
 - Demo notebook for the [curriculum manager](https://nbviewer.org/github/AllenNeuralDynamics/aind-foraging-behavior-bonsai-automatic-training/blob/main/code/aind_auto_train/demo_curriculum_manager.ipynb)
 
 ## Compared with SLIMS/mTrack
+<!-- markdown-link-check-disable-next-line -->
 See [this thread](https://github.com/AllenNeuralDynamics/aind-behavior-blog/discussions/124)