Discover the role of prompt engineer—what it entails and where it’s going—and begin taking steps to become a prompt engineer.
Prompt engineering is the process of optimizing the output of large language models like ChatGPT or Google Gemini by crafting input prompts that help them generate the desired output.
Prompt engineering is all about asking a language model better questions, providing better instructions, and even assigning it a role so that it generates the output you want, such as a list of blog topics, product descriptions, and coding documentation. Good prompts connect what a human wants to create with what a machine can generate.
As a prompt engineer, you’ll need to be able to build concise but effective prompts using different techniques that yield the outputs you need.
Read more: What Is Prompt Engineering? Definition and Examples
Prompt engineering is primarily used with text-to-text models, meaning that text comprises the input (prompt) and output. Other models like text-to-audio and text-to-image allow prompt engineers to input text and have the model produce audio files or images.
Prompt engineers are also referred to as AI (artificial intelligence) prompt engineers or LLM (large language model) prompt engineers. It is a fairly new field that emerged alongside generative AI. They can work in industries as varied as marketing, education, finance, human resources, and health care.
As a prompt engineer, you’ll be responsible for:
Crafting AI prompts to get desired outputs
Testing and analyzing outputs from the AI by experimenting with different prompts
Considering the ethics, cultural sensitivity, fairness, and bias involved with a prompt and the output it enables
Using your human judgment to identify what’s lacking in AI-generated output and then refining prompts to optimize output
Embedding AI prompts into applications and software for use in automating complex or repetitive tasks
Working on cross-functional teams to develop products
Integrating AI chatbots into a team’s workflow
Monitoring AI systems’ performance
This field is still new, so it may be too soon to accurately predict what prompt engineering will look like in the near future and beyond.
On the one hand, quality standards for LLM outputs will become higher, according to Zapier, so prompt engineers will need better skills [1]. On the other hand, an article in the Harvard Business Review suggests that “AI systems will get more intuitive and adept at understanding natural language, reducing the need for meticulously engineered prompts” [2].
Read more: What is Natural Language Processing? Definition and Examples
Prompt engineering can be an exciting career path. You can explore AI language models and technology in general, leverage your existing skills or interest in writing, and help companies achieve their business goals.
To get started in this field, follow these steps:
Before launching your career or switching fields, it’s a good idea to reflect on your career goals, so that you can focus your efforts on the actions that are most likely to lead to success. Here are some examples of goals:
Bring prompt engineering into your current role
Use prompt engineering to help you grow your own business
Get a job as an in-house prompt engineer for an organization
Master prompt engineering skills and help to develop AI language model technology
Monitor how AI technology evolves, along with the job roles that spring out of it. Stay mindful of trends and how companies are using AI to achieve their goals, and adjust your own career goals accordingly.
If your goal is to get a job as a prompt engineer, you may find it helpful in your job search to earn relevant credentials. As with other fields, a prompt engineering credential can show employers you are committed to professionalizing and mastering the latest techniques.
Depending on what different employers require, credentials for a prompt engineering role might include:
A bachelor’s degree in computer science, data science, engineering, or a related field
A certification in prompt engineering, like the one offered by Blockchain Council
In addition to earning credentials, consider taking prompt engineering courses. These can be a great way to learn in-demand skills in a structured format and, in some cases, with the support of the course instructor.
Prompt engineers need diverse abilities to succeed, including creativity, proficiency with technology, and even an understanding of human psychology.
Let’s look at some prompt engineering skills.
Writing skills ensure that you write prompts that are clear to the language model and natural to the user. Practice writing commands or questions using a conversational tone. Refine prompts in a “chat” to teach the AI how to produce a better output. You can change words and sentences around in a follow-up prompt to be more precise. Or you could add specificity to a previous set of instructions, such as asking the language model to elaborate on one example and discard the rest.
For some outputs, you might find it useful to prompt the language model to mimic specific styles. For example, you could ask the LLM to “Generate a sales pitch in the tone and style of XYZ Company’s brand voice.”
Read more: How To Write ChatGPT Prompts: Your 2024 Guide
Knowing how to use different language models, including ChatGPT-3.5, ChatGPT-4, Google Gemini, and Microsoft Copilot, can benefit you in a prompt engineering role in several ways:
Being able to work around the nuances of each LLM and use their capabilities fully
Knowing which LLM will work best for various projects
Being able to recommend one LLM over another for a particular use case
Alongside writing skills, you’ll also need to know specific prompting techniques. Some examples include:
Zero-shot prompting provides a prompt that is not part of the data you use to train the model but still generates the desired output.
Few-shot prompting guides the model to produce an output based on examples of what you want.
Chain of thought prompting is when you prompt the model through a series of intermediate steps before it arrives at its final answer to a multi-step problem. You can think of this technique as continuing a conversation with an AI model, with each question building on the answer that precedes it.
Knowledge generation prompting is a way of asking the model questions or giving it directions so it can provide you with information on a topic.
Context in prompt engineering refers to the information, background, or situation related to a task you need an LLM to perform. As the prompt engineer, you’ll provide contextual information in the prompt itself so that the LLM can yield the desired result. Contextual information examples include:
Details about your employment history for a cover letter the LLM will write
Asking an LLM to explain photosynthesis but specifying that the output needs to be appropriate for third-graders
Being able to empathize with the user and understand their needs is crucial to crafting effective prompts. For example, if you’re building a chatbot for a company’s customer support portal, knowing users’ purchase behavior, product challenges, and previous interactions with customer support can help you craft better prompts.
Skills or experience in machine learning can benefit your work as a prompt engineer. For example, machine learning can be used to predict user behavior based on how users have interacted with a system in the past. Prompt engineers can then finesse how they prompt an LLM to generate material for user experiences. Additionally, machine learning can help you understand the user's current situation or needs so that you can craft prompts accordingly.
Read more: Machine Learning vs. AI: Differences, Uses, and Benefits
Having technical knowledge of programming languages can allow you to customize your interaction with different LLMs for uses like:
Automating repetitive tasks
Fine-tuning prompts
Implementing security measures
Prompt engineers can use data analysis to improve prompts. One way is to gather and analyze user feedback on outputs in order to evaluate prompt performance. Another way is to use data analysis to identify trending topics or content gaps to generate new content.
Subject matter expertise in prompt engineering means you can serve users within your field of expertise. You can draw upon your expertise to craft effective prompts so that an LLM generates useful outputs. For example, if you have professional experience in horseback riding, your prompts can effectively get an LLM to generate content that horseback riding enthusiasts will want to consume.
Given that this career path is still new, it may be that the easiest way to get experience in prompt engineering prior to employment is to create your own opportunities to hone your skills and apply them to real-world scenarios. Here are some ideas to get you started:
Practice using a variety of AI language models
Design your own projects using prompt engineering, such as creating chatbots or building a health care tool that offers medical advice based on a user’s symptoms.
Work with your current manager or supervisor to come up with applications for prompt engineering in your role
Keep in mind that you may need experience in engineering, developing, and coding to be a strong candidate for a prompt engineering role.
To stay current on trending conversations in this field, follow or subscribe to influencers in emerging technology, such as Bernard Marr, Fei-Fei Li, Andrew Ng (Coursera co-founder), and Ronald van Loon.
Begin prompt engineering job search in an industry you want to be a part of. When you’ve found several job openings that interest you, update your application materials, including:
Resume that reflects your skills, credentials, and experience in prompt engineering
Cover letter template to tailor to each application
Portfolio or website to showcase your prompt engineering work
Update your LinkedIn profile
Read more: Prompt Engineering Jobs: Your 2024 Career Guide
If you’re ready to launch your prompt engineering career, consider one of Coursera’s online courses offered by leading organizations. By registering for Prompt Engineering for ChatGPT from Vanderbilt University, part of the Prompt Engineering Specialization, you can learn important terminology in this field, practice using and building prompt-based applications, and gain job-ready skills.
Zapier. “What Is Prompt Engineering?” https://zapier.com/blog/prompt-engineering/.” Accessed October 24, 2024.
Harvard Business Review. “AI Prompt Engineering Isn’t the Future, https://hbr.org/2023/06/ai-prompt-engineering-isnt-the-future.” Accessed October 24, 2024.
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