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Have you ever used Generative AI and felt like you didn’t get the results you were looking for? Just like search engines, Generative AI relies heavily on the prompts you submit.

Prompt engineering is quickly becoming an essential aspect of Intelligent Automation development resulting in increased accuracy, time-savings, improved efficiency, scalability, reduction in errors, ease of use, and more.

In the Pathfinder Community Team, we’re constantly exchanging tips and tricks to get the best result possible. Based on our experience, we’ve learned a few things about creating effective prompts:

  • Be clear - use simple language and avoid ambiguous terms
  • Provide examples - use specific examples that are similar to the desired output
  • Use structured data - use tables, lists, and other structured formats to provide input

Our collaboration has inspired this next monthly badge challenge. Let’s gather together as a community and build a repository of intelligent automation-related prompts!

 

 

Contribute & earn your badge in one easy step - reply & share:

What is the most effective prompt you have leveraged to date in your automation development?
 

 

 

Here are a few ideas to help inspire you - 

 

Writing regular expressions

Prompt: write a regular expression to extract the first letter from the first word and last two letters from second word in the example John Smith. Expected output: Jth

Response: 

^(\w{1})\w*\s+\w*(\w{2})\b

 

Reading specific text from unstructured data and responding in structured JSON format

Prompt: Get me the key values from this text in json format. Please find attached invoice number INV-2022-007 for the social media marketing services we provided in July. The subtotal for all line items is $9,000, and an early payment discount of 2% has been applied, for a total of $8,820 along with and sales tax of 8.25%.

Response: 

{
"invoice_number": "INV-2022-007",
"service": "social media marketing",
"month": "July",
"subtotal": "$9,000",
"discount": "2%",
"discount_amount": "$180",
"tax": "8.25%",
"total": "$9,959.50"
}

 

Text Generation: Generate Email responses for Customer Support

Prompt: Generate an email in less than 100 words to respond to an unhappy customer Allen to inform him that the issue with his smartphone will be rectified in 96 hours.

Response: 

Dear Allen,
Thank you for bringing the issue with your smartphone to our attention. We apologize for any inconvenience caused. Our team is currently working on resolving the issue and we assure you that it will be rectified within the next 96 hours. We appreciate your patience and understanding in this matter. Please feel free to contact us if you have any further concerns or questions.
Best regards,
>Your Name]

 

Bonus: Share a tip we are missing from our list of learnings.

By participating in this challenge, you have the opportunity to share your expertise, learn from your peers, and be an active influence in this exciting time for the automation industry.

Don’t miss out on all the recent AI buzz at Automation Anywhere -

 

 

Prompt: Write a macro that dynamically works to delete the blank rows presented over the Actual Data in a specific excel.

Response: 

Sub DeleteRowsMacro(Filepath As String, EndIndex As Integer)
'
' DeleteRowsMacro Macro
'
    Dim sht As Worksheet
    Dim wb As Workbook
    Application.DisplayAlerts = False
    Set wb = Workbooks.Open(Filepath)
    
    Rows("1:" & EndIndex).Select
    Selection.Delete Shift:=xlUp
    Range("A1").Select
    wb.Save
    wb.Close
End Sub
 


Hey ,

This is based on IT support, 

What I tried is reading the email coming end-users and sending the Body to ChatGPT and my specific prompts were extract : Sender’s email ID, Issue description, Issue Category.

For example let the Input email Be : 

 

Hi IT Support,

I am having trouble logging in to my company email account. Every time I try to log in, I receive an error message saying that my username and password are incorrect. Can you please assist me in resolving this issue?  

Thanks,

/John Doe]

 

Prompt would be : Extract support ticket details from above text in format : Brief description of the issue: Issue category: Name of Requestor:

Output :

Brief description of the issue: Error message saying that username and password are incorrect 
Issue category: Login issue 
Name of Requestor: RYour Name]


Reviewing resumes is a time consuming process - because everyone’s resume is formatted uniquely, and sometimes people may be a great candidate, but just horrible at writing resumes (or vice versa!). In the process of figuring out how to best review resumes in bulk using automation, I started exploring how Generative AI could help with the process. My process, and how my prompts changed:

  1. I’d written an automation that would download all the resumes as PDF’s into a folder.
  2. Because they were all text based PDF’s, I wanted to lift the text off of each page for each resume

     

  3. The code that it returned was OK, but it wasn’t accounting for resumes that had multiple pages...so Pro Tip#1: Be VERY SPECIFIC - its only going to give you what you ask for, in this case, I had to ask for an updated version that gets the page count first, then loops through everything.

     

  4. Once I had that code came Pro Tip #2: Review the Output. I had to test the code that was generated because
    1. I had to make sure it actually worked
    2. It was using a dependent library that I didn’t already have installed - which had an impact for me, and for my bot runner.
  5. Once I had the text, I wanted Generative AI to do some things for me as a part of my automation. I wanted to extract the basic information for each applicant so I could easily/quickly identify the best fits worth a closer look.
    1. I wanted to get their basic data - name, location, and 3 most recent employers
    2. I also wanted to get 3-4 bullet points on why they ARE and ARE NOT a great candidate for this role, as well as a general summary on how well they match up against the job description.

       

  6. This worked well as far as the data was concerned, but it wasn’t something that my automation could easily understand and use for creating a spreadsheet of ALL applicants, so Pro Tip #3: Specify the Output Format
    1. Since I needed an automation to be able to make use of this data, I had to specify that I wanted the output in a JSON format.
    2. And back to tip #1 about being specific - I had to give an example of how I wanted the attributes of the JSON to be named - because I noticed that 9/10 times it would return naming as I expected, but EVERY once in awhile, it would return some random JSON attributes which would throw off my automation.

Here is another prompt that can be used to log support tickets (Scenario - Understanding the intent to identify the next steps)


Prompt: I have purchased 32 inch TV and it was working great for a few weeks, however, it started flickering for the last few days and I am not happy with the purchase and would like to request for a replacement. Identify if this text contains a complaint.

Response: Yes, this text contains a complaint.


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