Prompt Engineering: The Next Job Skill, Not The Next Job

As AI technology improves, the ability to use it will become a critical skill for individuals who want to stay competitive. Prompt engineering, the process of creating, developing, and refining prompts to communicate with AI models, has recently been touted as the next big job in tech. However, prompt engineering is not a full-fledged job role unto itself, but rather a skillset, like “proficient in Excel” or “great communicator”. Instead, it will become part of the core skillsets employers look for in the new information age, the Generative Information Age.

A Skill, Not a Job

Prompt generation will be a single line item in a job description for many, just like capabilities to build solid PowerPoint presentations or navigate project management tools. However, this doesn’t mean it is a skill to be diminished in its necessity or impact. The ability to excel in prompt generation skills will be how we remain relevant in our growing and changing industries.

Embracing Generative AI

Generative AI isn’t a job-stealer, but rather a tool to enable our own capabilities in the jobs we have to become more efficient and impactful. In the same way that we adapted to the shift in computing from house-sized mainframe computing to multiple computing devices on every desk and in every pocket, we will also adapt and embrace generative AI in the new way of doing business. Soon, it will be such a core piece that we may even assume it to be a base skill for entering the job market in tech and other industries.

The Benefits of Building Prompt Engineer Skills

The benefits of acquiring prompt engineer skills are plentiful. From a productivity perspective, effective prompts can dramatically enhance the performance of AI models, leading to more accurate results and improved efficiency. This can revolutionize various sectors, including healthcare, finance, and education. From an employability standpoint, as the demand for prompt engineering skills grow, individuals with these skills will find themselves in high demand in the job market. This translates to attractive salary packages and offers the opportunity to work at the cutting edge of AI innovation. Simply said, these skills will improve your efficiency and thereby your value to any company for which you choose to work.

Acquiring Prompt Engineering Skills

Acquiring skills in prompt engineering involves a journey through several stages. It begins with a solid grounding in AI and machine learning, which can be obtained through numerous online courses like Coursera and edX. Next, a good understanding of Natural Language Processing (NLP) is helpful, as prompts are primarily text-based. Finally, the best way to sharpen your skills is through practice. Much like whiskies tastings to hone your nose and palate, experimenting with different AI models and prompts reveals how slight variations can significantly impact the output. Since AI is a rapidly evolving field, staying up-to-date is essential.

Google Cloud Skills Boost Launches New Learning Path on Generative AI

As it turns out, Google Cloud Skills Boost has launched a new free learning path on Generative AI, so acquiring these skills just became multitudes easier. This learning path is packed with courses that will teach you how to build and implement Generative AI using Google’s tools. The courses are aimed at both beginners and advanced learners, and cover everything from introductory concepts to advanced techniques.

Learning Path Activities

The learning path includes the following activities:

• • Introduction to Generative AI: This course explains what Generative AI is, how it is used, and how it differs from traditional machine learning methods.
  • Introduction to Large Language Models: This course explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance.
  • Introduction to Responsible AI: This course explains what responsible AI is, why it’s important, and how Google implements responsible AI in their products.
  • Introduction to Image Generation: This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space.
  • Encoder-Decoder Architecture: This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering.
  • Attention Mechanism: This course introduces you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence.
  • Transformer Models and BERT Model: This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model.
  • Create Image Captioning Models: This course teaches you how to create an image captioning model by using deep learning.
  • Introduction to Generative AI Studio: This course introduces Generative AI Studio, a product on Vertex AI, that helps you prototype and customize generative AI models so you can use their capabilities in your applications.

All courses are available for free on Google Cloud Skills Boost.

So, while prompt engineering may not become its own new profession, gaining the skill will absolutely offer opportunities for those willing to explore this progressive intersection of AI, linguistics, and creativity. Not only opportunity, however, necessity as this will help you continue to remain relevant in the changing landscape of work as we enter the Generative Information Age.