diff --git a/README.md b/README.md
index 2ef91dc980a13b5c9da75f569219742f199d9223..060d2f0964ec0ab51426d2f0e956c94db067d90a 100644
--- a/README.md
+++ b/README.md
@@ -62,10 +62,11 @@ The following image represent the application workflow. Each step in the flowcha
 #### Create a blank step function
 * Log into the AWS Management Console and navigate to the AWS Step Functions page.
 * Click on Create state machine to start the process of creating your workflow template.
-* Choose **Blank** to create a workflow from scratch. 
+* Choose **Blank** to create a workflow from scratch.
+* Choose a relevant name for your Step function (VERY IMPORTANT: do not forget that you are working on the same AWS Amazon account with the other students)
 Inside the workflow studio, navigate to the left-hand panel and select **Flow** control.
 #### Step 1: Map block
-Choose **Map**, which allows for parallel processing:
+Choose **Map**, which allows for parallel worflow for each item in a dataset (in our case each .tif file is an item):
 * Assign a suitable name 
 * Select the processing mode as 'Distributed,' facilitating the creation of separate child workflows for each image.
 * Choose the item source as 'Amazon S3,' then select 'S3 object list' as the S3 item source. Navigate to the S3 bucket **'satellite-images-ndvi'**, where the NDVI images are stored.