Five skills needed to become an AI prompt engineer

Prompt engineering is a fascinating new profession that is expanding alongside the recent spectacular growth of generative AI. Five talents that you must have if you want to work as a prompt engineer professionally are listed below.

1. Recognize AI, ML, and NLP

Developing knowledge of how natural language processing, machine learning, and artificial intelligence truly operate is a crucial place to start. If you’re going to work with large language models, you should be aware of what they are, the many kinds of LLMs available, the kinds of tasks they excel at, and their weaknesses.

This doesn’t necessarily imply that you must develop into a computer scientist capable of designing your own LLM, but it does imply that you must have a thorough understanding of the capabilities and internal workings of the tools you plan to base your profession on. The secret will be to educate oneself using any and all accessible tools, such as conventional courseware, a lot of reading of articles and technical papers, going to conferences, and doing your own experiments.

2. Clarify problem descriptions and provide specific inquiries.

Fundamentally, this aptitude is the capacity for crystal-clear communication. The key to prompt engineering knows how to communicate your needs to the AI. To do that, you must be very clear about what you hope to gain from the conversation.

Here is one instance. Assume you wish to learn more about Salem, the state of Oregon’s capital. On at least two fronts, you must be crystal clear. Whether you want to know about the political system, challenges with municipal administration, traffic, or where the greatest doughnut shop is, you must first describe the types of topics you want to know. Second, you must be able to communicate to the AI that you are referring to Salem, Oregon, and not Salem, Connecticut, Virginia, or Indiana, nor Salem, Massachusetts, where the Salem witch trials took place, nor Winston-Salem, North Carolina, nor any of the Salems in England, Wales, Australia, or Canada.

Developing the ability to articulate how to position the AI to grasp the perspective it must adopt in order to bring value as well as the context and scope of the problem you want it to address in a specific query will also be necessary.

3. Be imaginative and hone your communication abilities.

Instead of being a programming exercise, prompt engineering is much more of a discussion between participants. Although LLMs are undoubtedly not sentient, they frequently interact with one another in a manner like to that of a coworker or subordinate.

You’ll frequently need to think creatively while defining your issue statements and queries. The internal representation of the AI might not match the image in your brain. To get the outcomes you desire, you’ll need to be able to consider a number of conversational stances and gambits.

4. Build your topic expertise while learning about writing and artistic techniques.

In addition to writing responses for you, chatbots frequently do so in the desired manner.

It’s critical for you to acquire (or have access to) the subject expertise in the field for which you are setting up prompts in addition to having a working knowledge of writing and artistic styles. For instance, it’s crucial that you are knowledgeable enough to be able to elicit the replies you want and determine whether they are accurate or inaccurate if you are working on an AI application for vehicle diagnostics.

5. Develop your scripting and coding abilities

Have you ever noticed that anytime someone begins a sentence with the phrase “it goes without saying,” there is always a saying going on? In any event, it should go without saying (but I’ll say it anyway) that having programming abilities would be useful. While some prompt engineering jobs may only include interacting with chatbots, the higher-paying jobs will probably require integrating AI prompts into software and services that subsequently offer distinctive value.

Even while writing the entire application’s code may not be required, you will provide far more value if you can write some code, test your ideas in the context of the apps you’re creating, run debugging code, and participate in the interactive programming process. Instead of needing to implement prompt engineering and test it as a whole distinct activity, it will be far simpler for a team to advance if it happens as a natural part of the process.