Why Prompt Engineering Isn't Going Anywhere

There’s been a lot of talk about the role of prompts in artificial intelligence (AI). Some people believe prompt engineering is temporary because AI models have yet to be sufficiently developed. However, I believe that prompt engineering is here to stay.

TL;DR:

Prompts explicitly define context, so without a prompt, AI output is bound by its ability to “sense” implicit context.
As humans, we believe we have control, and prompt engineering will be one of the last things we continue to control in a world of artificial intelligence.
Prompt engineering allows an easier way to iterate than fine-tuning or training, and it’s non-destructive, so you can better rely on past prompts performing how you would expect.

Prompts Explicitly Define Context

In a world of artificial intelligence, prompts play an important role in defining the context for a particular output. Without a prompt, an output is bound by its ability to “sense” implicit context. This can be quite limiting. Prompts provide a way to explicitly define the context for an output. And right now, prompts are the only context considered by the most popular models, like GPT-3.

Prompts provide that clarity by defining the parameters within which the model must operate. Prompts are the interface between humans and language models. They provide a way for us to give machines the information they need to perform a task while constraining the possible outcomes. This makes prompts essential for ensuring that an AI system behaves as expected.

For example, let’s say you are asking a question. The answer may not be sufficient after your first ask if you don’t provide context. Prompt engineering allows you to get more specific with your question. Without the context of the prompt, a sufficiently advanced AI may return too much, or too little. Or it might use probability to respond to the most likely context, but that loses utility for advanced users that want deeper knowledge.

Imagine you ask your assistant to book a flight for you. Without any prompts, the assistant might assume you want to fly today and book a flight that leaves immediately. However, if you include the prompt “I need a flight next week,” the assistant will book a flight that leaves next week instead. And in this case, incorrect context from the lack of prompting can turn into a costly mistake.

Prompts help ensure that an AI model’s output is what we expect it to be. They provide a level of control that would otherwise be lacking in a world where machines are making more and more decisions for us.

Humans Crave Control

Even as AI models become more advanced, there will always be a need for prompts in some situations. Why? Because prompts offer explicit control over an AI model’s output, humans will continue to crave control. In a future dominated by artificial intelligence, prompt engineering will be one of the last things we continue to control. This is one of the main reasons why prompt engineering is here to stay.

As much as we’d like to believe that we can create autonomous systems, the reality is that humans still crave control. Prompts allow us to exert some degree of control over how an AI system behaves while allowing it some autonomy.

We like to believe that we’re in control. It’s a core part of our identity as human beings. And when it comes to the technology we use, we want to be able to control it. That’s why prompt engineering will be one of the last things we continue to control in a world of artificial intelligence.

As AI models become more advanced, they will increasingly be able to do things without our prompting. But there will always be areas where humans want or need to retain control. For example, let’s say you’re using a language model to generate product descriptions for an e-commerce site. You don’t want the model spitting out overly generalized content when your brand was built for a specific target audience. So you use prompts to constrain the output and ensure that what it produces accurately reflects the brand.

In these cases, prompts allow us to take back control and tell the AI what we want it to do. So while AI models may theoretically surpass our ability to provide them with useful prompts, there will always be situations where humans crave – and need –control.

Prompt Engineering is Easier to Iterate

Prompt engineering is an easier way to iterate compared to fine-tuning or training. You’re constantly changing your models and making small tweaks when you’re fine-tuning. This can be time-consuming and difficult to keep track of. With prompt engineering, you can rely on past prompts that have performed well and iterate from there.

What’s more, prompt engineering is non-destructive. So if you make a change that doesn’t work out, you can easily go back and try something else without starting from scratch.

In the end, prompt engineering allows for faster iteration and better results. And that’s another reason why it’s here to stay.

Some Prompt Types May Lose Value

Some prompt types may eventually lose value and become obsolete. For example, k-shot prompts containing a fixed number of examples may become less valuable as zero-shot prompts become better understood and AI models become better trained.

So the types of prompts used may change as models become more sophisticated.

The Future Of Prompt Engineering

As we continue to develop artificial intelligence, it’s important to consider the role that prompt engineering will play in our future.

So what does the future hold for prompt engineering? I believe it will play an important role in AI development as we strive to create more autonomous systems. Prompt engineering is a crucial tool that allows us to control the behavior of AI models, and it’s something that we will continue to rely on as AI evolves. In the future, prompt engineering may become even more important as we strive to create smarter and more efficient AI systems.

As AI models become more advanced, the need for prompts may lessen for the average user while their value increases for advanced users.