Will Prompt Engineer be the new "sexiest job of the 21st century"?

How AI leaders can prepare their teams for generative AI

Photo by Luis Quintero (Pexels)

In 2012, Thomas H. Davenport and DJ Patil called Data Scientist “the sexiest job of the 21st century” (Havard Business Review). That might have been true at the time. And even today, deep expertise building AI-based systems remains a skill that is in high demand (and in short supply). Since this claim has been made more than 10 years ago, the data science landscape and tools have evolved significantly. Developers with foundational knowledge of data science can create models that are “good enough”. Good enough to start with or to even put into production. While data scientists are still needed for complex AI projects, it makes AI more accessible to a broader group of people. A similar trend could also shape up over the next few years in a different area of the AI space: To instruct generative AI systems to create a desired output — text, image, audio/video, etc. — with minimum effort and high accuracy. This task is called “prompt engineering”.

What is prompt engineering?

Current generative AI systems work by having a user enter a so-called “prompt”. This is a set of commands, written in plain English, that instructs the AI system to generate an output. For example, “Pretend you’re a technical writer. Describe what this code does in English language.” or “Write a blog post about the 3 best cities to host an AI conference in. Keep it under 2000 words. Use a professional tone.” If it’s written in plain English, what’s the craft then?

Using generative AI applications feels a lot like experimenting. It can take a long time until the system generates what you want it to. For example, iterating on a text prompt and making small tweaks before the output matches your intention. The key to getting results quickly is having an understanding of what you want the end result to be and how to articulate that in plain English. The iterations of a prompt might be rather small, for example changing a word, but it will likely change the generated output. You just don’t quite know exactly how before you submit your prompt. But generative AI systems will evolve and will become easier to use.

In a recent interview, Sam Altman (CEO of OpenAI, the company behind of ChatGPT) shared that prompt engineering will no longer be necessary within the next 5 years (YouTube). If that’s the case, how might we use AI?

I currently see three scenarios how using generative AI could evolve:

• Personalization: AI systems will know enough about their users and preferences and will require less context

• Focus: Generative AI will evolve from being the product to being just a product feature and will require less explicit instructions

• User experience: How we interact with it will feel less like coding and, at a minimum, more like using our current UIs

What can AI leaders do now?

A huge part of the renewed interest in AI is its mass appeal and ease of use in addition to its unprecedented capabilities. While some user training and experimentation is needed, users don’t need to become experts in statistics and mathematical optimization first in order to use it. This makes generative AI much more accessible compared to traditional data science where models are built from the ground up. It also creates opportunities for businesses to benefit from AI-driven innovation more quickly and with a much shorter learning curve. AI and technology leaders can further support this and:

1. Encourage their teams to experiment with the available generative AI systems,

2. Educate how they can try it out safely (challenges/ pitfalls, information security),

3. Provide hands-on opportunities (hackathons) and compare notes and outputs,

and embrace this evolution of AI. For the time being, Prompt Engineering might succeed Data Science as the “sexiest” job — of the decade.

How are you honing your “Prompt Engineering” skills?

Watch the replay: » 1,400+ participants have already learned on LinkedIn about the top trends in AI & automation in 2023. «

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What’s next?

The next few weeks will bring a number of exciting live streams and sessions for leading AI projects in business:

• February 09 - Join me on LinkedIn Learning’s “The Future of Tech” live stream on Crafting an AI Strategy for Your Business

Join us for the upcoming episodes of “What’s the BUZZ?”:

• February 16 - Alexander Leonida, Founder SilkFlo will share what to look for in Automation in a Multi-Vendor World

• February 28 - Mary Purk, Managing Director AI & Analytics Center, Wharton School of Business at the University of Pennsylvania, will provide insights into Accelerating Your AI Adoption Across The Business.

• March 14 - Tom H. Davenport, Professor and Author, and I will talk about going all-in on generative AI — and what that entails (event link in next newsletter)

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Together, let’s turn hype into outcome. 👍🏻 
—Andreas

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