What is a Prompt Engineer?

Prompt engineering involves the process of refining the text prompt submitted by a user to generative AI models in order to achieve specific tasks.

It enables marketers to effectively utilise generative AI to enhance marketing campaigns and create engaging content. And prompt engineers are integral to this. 

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But what is a prompt engineer? Other than what it says on the tin, of course. Yes, they engineer prompts. But it's so much more than that. 

Prompt engineers are one of the new roles which will spring out of the AI revolution, becoming as important to marketing and AI marketing as copywriters or graphic designers. 

But let's start with the basics:

What is a Prompt?

A "prompt" refers to an input message or signal that is transmitted to an AI system. It is typically displayed on a UI screen or through other means to signify that the system is prepared to receive input or acknowledge a command.

If you have ever opened a Terminal window on your operating system, you have likely encountered prompts.

In the console, the prompt serves as both a notification that the system is awaiting input and a guiding element that assists you in entering commands.

But without prompt writers and engineers, a prompt doesn't even exist. So it's more important to ask:

What is a Prompt Engineer?

A prompt engineer is an individual who inputs a series of elements, including words, phrases, and flags, to achieve a desired outcome.

These skilled operators can assemble diverse components, evaluate outputs, and fine-tune inputs to accomplish specific goals.

While programming knowledge is not mandatory for prompt engineers, some experience in the field is beneficial. They prioritize achieving results over focusing on the underlying code and leverage their input and creative skills to gain insights into various systems' inner workings.

An illustration of how prompt engineers contribute to delivering diverse marketing outputs is Midjourney, an artificial intelligence visual generator.

Utilising neural networks, artificial intelligence, and natural language generation, this tool generates images based on user preferences. Given that the order of inputs influences the output, a robust syntax is crucial to achieve the desired effect.

Prompt engineers collaborate with art directors and designers to generate a multitude of creative ideas for clients, providing a wide range of options that enhance customer choice and satisfaction.

Offering such increased options can help businesses elevate customer satisfaction. When a company seeks to introduce a new product or service but lacks ideas, it can leverage the tool through its agency or in-house team to evaluate the results.

Prompt engineering has simplified the process for creative teams to accumulate a vast collection of high-quality media for their campaigns. The tool can also generate hyper-realistic artworks in various styles based on user preferences.

Prompt engineers can also work alongside content and copywriting teams to develop and refine messaging, ensuring alignment with the overall content and brand messaging.

Proficiency in linguistics, grammar, and writing proves valuable when working on writing prompts, and prompt engineers need to possess strong writing and vocabulary skills.

By providing prompts or suggestions, prompt engineers assist copywriters in generating new and creative ideas for their writing.

For instance, a prompt engineer could create a list of questions or prompts related to a specific topic or theme, serving as inspiration for novel copywriting ideas.

Key skills necessary for prompt engineers include:

  • Natural language understanding: The ability to analyze and interpret natural language inputs from users, extracting relevant information and intents.
  • Prompt design: The capability to craft prompts that are clear, concise, informative, conversational, and elicit desired user responses.
  • Prompt evaluation: The skill to test and measure prompt effectiveness using various metrics, including user satisfaction, task completion, error rate, and conversational quality.
  • Prompt optimisation: The practice of improving and refining prompts based on feedback, data analysis, and best practices.

How Does Prompt Engineering Work?

A prompt refers to the text entered by a user into a text box on a generative AI website or application.

It serves the purpose of guiding the large language model to generate a response based on the provided prompt.

Since generative AI models construct responses based on the most probable way a sentence is completed, prompts can be as simple as "The ocean is." Such a prompt would yield a response that completes the sentence.

Prompt engineering encompasses various types, including Chain of Thought (CoT), zero-shot, one-shot, and few-shot prompting.

  • Zero-shot: A zero-shot prompt is a query for a machine learning model in zero-shot learning. It entails the model generating responses without relying on task-specific examples, solely utilizing its prior knowledge and understanding.
  • One-shot: A one-shot prompt is a query for a machine learning model in one-shot learning. The model learns tasks based on a single example provided. The prompt guides the model to generate appropriate responses by leveraging its understanding of the given example.
  • Few-shot: Few-shot learning involves training a machine learning model to perform well on new tasks using only a small number of examples or training data. In this context, a few-shot prompt refers to a question or input provided to the model, helping it comprehend the task and generate suitable responses based on the limited examples available.
  • Chain of Thought (CoT): CoT revolves around providing a few-shot learning model with exemplars that explicitly illustrate the reasoning process, showcasing specific examples of concepts, behaviours, or principles. This approach enables the model to reveal its reasoning when responding to prompts, often resulting in more accurate outcomes.

The Future of Prompt Engineering

The future of marketing analytics will witness the dominance of AI-powered tools that prompt engineers will utilize to support their teams in comprehending data by automating various tasks, including:

  • Data cleaning: Prompt engineers will employ these AI-powered tools to perform data cleaning, eliminating unnecessary or inaccurate entries from databases. This process ensures the creation of reliable reports and dashboards.
  • Data analysis: With the aid of AI tools, prompt engineers can analyze user data, identifying patterns and trends in user behaviour. These insights can be leveraged to optimize prompt systems and enhance the user experience.
  • Data integration: AI-powered tools facilitate the seamless integration of data from diverse sources into a centralized repository. This empowers all team members to access relevant information instantly.
  • Data visualisation: AI tools enable prompt engineers to transform numerical data into easily understandable visual representations. By utilizing graphical interfaces like Tableau or Power BI, they can present data to audiences unfamiliar with spreadsheet programs like Excel.

Prompt engineers are poised to evolve and adapt to new challenges and opportunities in the future.

As prompts become more intricate and varied, prompt engineers, often referred to as "ChatGPT whisperers," will need to acquire new skills and knowledge to meet evolving demands.

Collaboration with professionals from different domains, such as content writers, data analysts, and user experience designers, will be crucial.

This collaboration ensures the creation of prompts that effectively cater to the needs and expectations of diverse audiences and contexts.