Add ClearML Agent flow clarification (#490)

docs/clearml_agent.md

@@ -27,11 +27,18 @@ The diagram above demonstrates a typical flow where an agent executes a task:
 
 While the agent is running, it continuously reports system metrics to the ClearML Server (These can be monitored in the **Workers and Queues** page).  
 
-Continue using **ClearML Agent** once it is running on a target machine. Reproduce experiments and execute 
+Continue using ClearML Agent once it is running on a target machine. Reproduce experiments and execute 
 automated workflows in one (or both) of the following ways: 
-* Programmatically
-* By using the **ClearML Web UI** (without directly working with code), by enqueuing experiments 
-to the queue that a **ClearML Agent** is listening to.
+* Programmatically (using [`Task.enqueue`](references/sdk/task.md#taskenqueue) or [`Task.execute_remotely`](references/sdk/task.md#execute_remotely))
+* Through the ClearML Web UI (without working directly with code), by cloning experiments and enqueuing them to the 
+  queue that a ClearML Agent is servicing.
+
+  The agent facilitates [overriding task execution detail](webapp/webapp_exp_tuning.md) values through the UI without 
+  code modification. Modifying a task clone’s configuration will have the ClearML agent executing it override the 
+  original values:
+  * Modified package requirements will have the experiment script run with updated packages
+  * Modified recorded command line arguments will have the ClearML agent inject the new values in their stead
+  * Code-level configuration instrumented with [`Task.connect`](references/sdk/task.md#connect) will be overridden by modified hyperparameters
 
 For more information, see [ClearML Agent Reference](clearml_agent/clearml_agent_ref.md), 
 and [configuration options](configs/clearml_conf.md#agent-section).

docs/fundamentals/task.md

@@ -17,13 +17,27 @@ model checkpoints, artifacts, and charts to cloud storage (see [Storage](../inte
 you can work with tasks in Offline Mode, in which all information is saved in a local folder (see 
 [Storing Task Data Offline](../guides/set_offline.md)).
 
-In the UI and code, tasks are grouped into [projects](projects.md), which are logical entities similar to folders. Users can decide
+Tasks are grouped into a [project](projects.md) hierarchical structure, similar to file folders. Users can decide
 how to group tasks, though different models or objectives are usually grouped into different projects.
 
-Tasks that are in the system can be accessed and utilized with code. To [access a task](../clearml_sdk/task_sdk.md#accessing-tasks), it can be identified either by a 
-project name & task name combination or by a unique ID. 
+Tasks can be accessed and utilized with code. [Access a task](../clearml_sdk/task_sdk.md#accessing-tasks) by 
+specifying project name & task name combination or by a unique ID. 
+
+It's possible to create copies of a task ([clone](../webapp/webapp_exp_reproducing.md)) then execute them with 
+[ClearML Agent](../clearml_agent.md). When an agent executes a task, it uses the specified configuration to:
+
+* Install required Python packages
+* Apply code patches
+* Set hyperparameter and run-time configuration values
+
+Modifying a task clone's configuration will have the executing ClearML agent override the original values:
+* Modified package requirements will have the experiment script run with updated packages.
+* Modified recorded command line arguments will have the ClearML agent inject the new values in their stead
+* Code-level configuration instrumented with [`Task.connect`](../references/sdk/task.md#connect) will be overridden by 
+modified hyperparameters.
+ 
+
 
-It's possible to copy ([clone](../webapp/webapp_exp_reproducing.md)) a task multiple times and to modify it for re-execution.  
 
 ![Task](../img/fundamentals_task.png)