diff --git a/docs/fundamentals/pipelines.md b/docs/fundamentals/pipelines.md
index 1f5c11a1..e74dbf4e 100644
--- a/docs/fundamentals/pipelines.md
+++ b/docs/fundamentals/pipelines.md
@@ -85,10 +85,7 @@ Custom pipelines usually involve cloning template tasks, modifying their paramet
 them to queues (for execution by [agents](../clearml_agent.md)). It's possible to create custom logic that controls inputs 
 (e.g. overriding hyperparameters and artifacts) and acts upon task outputs.
 
-See examples of custom pipelines: 
-   * [Task Piping](../guides/automation/task_piping.md)
-   * [Manual Random Parameter Search](../guides/automation/manual_random_param_search_example.md)
-
+See [Manual Random Parameter Search](../guides/automation/manual_random_param_search_example.md) example of a custom pipeline.
 
 ## Pipeline from Function Decorator
 
diff --git a/docs/fundamentals/task.md b/docs/fundamentals/task.md
index 145e0a9b..1782b732 100644
--- a/docs/fundamentals/task.md
+++ b/docs/fundamentals/task.md
@@ -293,7 +293,7 @@ Task.enqueue(
 )
 ```
 
-See enqueue [example](https://github.com/allegroai/clearml/blob/master/examples/automation/task_piping_example.py).
+See enqueue [example](https://github.com/allegroai/clearml/blob/master/examples/automation/programmatic_orchestration.py).
 
 ### Advanced Remote Execution
 
diff --git a/docs/guides/automation/task_piping.md b/docs/guides/automation/task_piping.md
index 0204397d..78327da4 100644
--- a/docs/guides/automation/task_piping.md
+++ b/docs/guides/automation/task_piping.md
@@ -1,8 +1,8 @@
 ---
-title: Task Piping
+title: Programmatic Orchestration
 ---
 
-The [task_piping_example.py](https://github.com/allegroai/clearml/blob/master/examples/automation/task_piping_example.py) 
+The [programmatic_orchestration.py](https://github.com/allegroai/clearml/blob/master/examples/automation/programmatic_orchestration.py) 
 example demonstrates: 
 1. Creating an instance of a Task from a template Task.
 1. Customizing that instance by changing the value of a parameter
@@ -11,10 +11,10 @@ example demonstrates:
 This example accomplishes a task pipe by doing the following:
 
 1. Creating the template Task which is named `Toy Base Task`. It must be stored in **ClearML Server** before instances of 
-   it can be created. To create it, run another **ClearML** example script, [toy_base_task.py](https://github.com/allegroai/clearml/blob/master/examples/automation/toy_base_task.py).
+   it can be created. To create it, run another ClearML example script, [toy_base_task.py](https://github.com/allegroai/clearml/blob/master/examples/automation/toy_base_task.py).
    The template Task has a parameter dictionary, which is connected to the Task: `{'Example_Param': 1}`. 
-1. Back in `task_piping_example.py`, creating a parameter dictionary, which is connected to the Task by calling [Task.connect](../../references/sdk/task.md#connect) 
-   so that the parameters are logged by **ClearML**. The dictionary contains the name of the parameter from the template 
+1. Back in `programmatic_orchestration.py`, creating a parameter dictionary, which is connected to the Task by calling [Task.connect](../../references/sdk/task.md#connect) 
+   so that the parameters are logged by ClearML. The dictionary contains the name of the parameter from the template 
    Task that is going to be customized (`Example_Param`), as well as its new value.
 1. Creating a Task object referencing the template Task. See [Task.get_task](../../references/sdk/task.md#taskget_task).
 1. Creating an instance of the template Task by cloning it.