Understanding the AI-driven Prompt Engineering competency framework 

In the field of Generative AI, the term Prompt Engineering has gained traction since 2022, and while there is no agreed upon standard currently, the industry is working on materials to support Process Engineering as a required hard skill. 

Yet Prompt Engineering also has uses for the non-technical knowledge worker and is quickly becoming a soft skill that will enhance productivity and collaboration between team members while assisting with information gathering to comprehend complex concepts.  The combination of these hard and soft skills is what is known as a competency framework.   

Since the 1980s, finding accurate information online has been overwhelming—like drinking from a fire hose—but the emergence of Generative AI tools has simplified this task by enabling users to refine searches using natural language. With platforms like copilot.microsoft.com and chatgpt.com, users can now interact conversationally to clarify their needs, making prompt engineering—focused on soft skills—crucial for quickly extracting relevant information from the vast content available online.  

For instance, I like to travel, yet I’m not a fan of chains; I prefer small hotels with character.  I’ve also found booking direct can get you a better deal.  While I can type my criteria into one of the sites previously mentioned, it’s more efficient when I maintain a template of criteria that’s worked for me in the past, i.e., I’m traveling to <location>, in <month>, and want to find highly rated hotels, that are not chains, are described as having character, and are moderately priced.  What hotels fit those criteria, have their own website, and offer discounts or specials when you book direct? 

For this example, it’s not a lot of prompting for me to type in each time, and as a personal prompt, I may even make changes depending on specific requirements.  For instance, if I’m traveling in summer, I may add prompts to exclude any hotels that don’t have air conditioning or an outdoor pool.  While this wouldn’t eliminate my need to do more research, it would reduce the time greatly and may even uncover locations that I may not have come across with a simple search. 

This is different from the hard skills needed to integrate Process Prompt Engineering, which requires more attention to detail on the various prompts.  It also requires more knowledge of the desired output and how it can be used to help all knowledge workers, by providing predictable, repeatable, and verifiable results that can be incorporated into the formal business process. 

I see this as analogous to the use of Excel Spreadsheets.  For the casual user Excel is a soft skill that helps one organize and solve simple problems, yet it is a powerful tool that can be used as part of an enterprise solution, with the proper engineering focus that comes from the associated hard skills.   

As with our familiarity with searching the internet, those who want to be more efficient will learn to develop new soft skills around Prompt Engineering, and with continued focus on the hard skills, a new competency framework will arise. 

While in future articles I will describe the scope of the Hard Skills of Process Prompt Engineering, this is a good time for us to delve into the next big soft skill, personal prompt engineering. 

Rocket Software’s core values of Empathy, Humanity, Trust and Love are central to our commitment to bringing Generative AI to our Customers and Partners.  For those of you who are looking to add Generative AI to you future solutioning, please reach out to your Rocket Software MultiValue support provider and inquire about a MultiValue Discovery Assessment so Rocket Software can help you modernize without disruption. 

If you’re looking to increase personal productivity and enhance your intellect with Generative AI, please review my previous article “AI is not always a surefire cure.”