5 Non-Tech Prompt Engineering Skills (that you probably already have)

The day-to-day activities of a prompt engineer should be of interest to anyone who interacts with generative AI for two very good reasons: (1) It illuminates the tech’s capabilities and limitations. (2) It gives people a good understanding of how they can use skills they already possess to have better conversations with AI. Here’s a look at five non-tech skills contributing to the development of AI technology via the multidisciplinary field of prompt engineering.


Like project managers, teachers, or anybody who regularly briefs other people on how to successfully complete a task, prompt engineers need to be good at giving instructions. Most people need a lot of examples to fully understand instructions, and the same is true for AI.

Edward Tian, who built GPTZero, an AI detection tool that helps uncover whether a high school essay was written by AI, shows examples to large language models, so it can write using different voices. Of course, Tian is a machine learning engineer with deep technical skills, but this approach can be used by anyone who’s developing a prompt and wants a chatbot to write in a particular way, whether it’s as a seasoned professional or an elementary school student.

Subject matter expertise

Many prompt engineers are responsible for tuning a chatbot for a specific use case, such as healthcare research. This is why prompt engineering job postings are cropping up requesting industry-specific expertise. For example, Mishcon de Reya LLP, a British Law Firm, had a job opening for a GPT Legal Prompt Engineer. They were seeking candidates who have “a deep understanding of legal practice.” Subject matter expertise, whether it’s in healthcare, law, marketing, or carpentry, is useful for crafting powerful prompts. The devil’s in the details, and real-world experience counts for a lot when talking with AI.


To get the AI to succeed, it needs to be fed with intent. That’s why people who are adept at using verbs, vocabulary, and tenses to express an overarching goal have the wherewithal to improve AI performance. When Anna Bernstein started her job at Copy.ai, she found it useful to see her prompts as a kind of magical spell: one wrong word produces a very different outcome than intended.

“As a poet, the role […] feeds into my obsessive nature with approaching language. It’s a really strange intersection of my literary background and analytical thinking,” she said in this Business Insider interview. Instead of using programming languages, AI prompting uses prose, which means that people should unleash their inner linguistics enthusiast when developing prompts.

Critical thinking

Generative AI is great at synthesizing vast amounts of information, but it can hallucinate (that’s a real technical term). AI hallucinations occur when a chatbot was trained or designed with poor quality or insufficient data. When a chatbot hallucinates, it simply spews out false information (in a rather authoritative, convincing way).

Prompt engineers poke at this weakness and then train the bot to become better. For example, Riley Goodside, a prompt engineer at the AI startup Scale AI, got the wrong answer when he asked a chatbot the following question: “What NFL team won the Super Bowl in the year Justin Bieber was born?” He then asked the chatbot to list a chain of step-by-step logical deductions for producing the answer.

Eventually, it corrected its own error. This underscores that having the right level of familiarity with the subject matter is key: it’s probably not a good idea for someone to have a chatbot produce something they can’t reliably fact-check.


Trying new things is the very definition of creativity, and it’s also the essence of good prompt engineering. Anthropic’s job posting states that the company is looking for a prompt engineer who has “a creative hacker spirit,” among other qualifications. Yes, being precise with language is important, but a little experimentation also needs to be thrown in.

The larger the model, the greater the complexity, and in turn, the higher the potential for unexpected, but potentially amazing, results. By trying out a variety of prompts and then refining those instructions based on the results, generative AI users can increase the probability of coming up with something truly unique.

How to Make Money with Prompt Engineering?

As AI continues to permeate every facet of our lives, the role of prompt engineering has become more important and lucrative. But how does one go about making money in this emerging field? Here are some potential avenues for monetizing your prompt engineering skills.

1. Full-time employment: As AI language models become integral to more businesses and services, many companies are hiring full-time prompt engineers to help refine their AI interactions. These roles can be found in a wide array of industries, from tech firms and AI startups to larger corporations that are integrating AI into their services. Keep an eye on job listings (prompt engineering jobs) in AI, machine learning, and data science sectors to find these opportunities.

2. Freelancing: If you prefer a more flexible work arrangement, freelancing as a prompt engineer could be an excellent option. Many businesses require AI optimization but don’t have the need or resources for a full-time employee. You can offer your services on freelance platforms like Upwork or PromptBase, or create your own website to attract clients.

3. Consulting: If you’ve built a strong reputation and have extensive experience in prompt engineering, you could consider offering consulting services. Many organizations are just beginning to explore AI applications and would value expert guidance on how to effectively interact with AI models.

4. Training and education: As an emerging field, there’s a growing demand for education in prompt engineering. You could create an online course, offer personalized training sessions, or even write a book on the subject.

5. AI content creation: Prompt engineers can also make money by using their skills to generate AI-created content. This might involve writing AI-generated articles, books, or other forms of content that can be sold or used for marketing.

6. Building and selling AI tools: If you have the technical skills and are experienced with programming languages, you can build AI tools that leverage effective prompt engineering. These tools could then be sold to businesses or individuals.

As with any field, your ability to make money as a prompt engineer will depend on several factors, including your level of expertise, your reputation, and the market demand for your services. It’s also a rapidly evolving field, so staying up-to-date with the latest developments in AI and machine learning will be essential for success. With the right skills and a proactive approach, there’s no limit to the opportunities in the exciting world of prompt engineering!

How Can You Learn Prompt Engineering?

There are many resources available online that can help you master this skill. You can start by reading some guides and tutorials on prompt engineering for ChatGPT or taking some courses and certifications on this topic. You can also learn by trying out different prompts on ChatGPT playgrounds or APIs, comparing the outputs, and tweaking the parameters until you get what you want.

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