Talking to AI is trickier than newbies assume. Writing prompts for complex, multi-step tasks requires good communication skills and a solid understanding of language models. AI relies solely on the input provided. It won’t generate optimal output if you feed it vague, ambiguous directions.

Learn to write clear, precise prompts. Here are eight hard and soft skills that prompt engineers must focus on when upskilling.

1. Critical Thinking

AI systems can quickly analyze input. They only need minutes to spot patterns, themes, and inconsistencies hidden in large volumes of data. Meanwhile, manually sifting through the same figures might take days.

Despite their speed, you shouldn’t wholly rely on AI tools for analyses and evaluations. Their reports are limited to their datasets. AI provides output based on what it has been trained on—it doesn’t analyze and observe problems the way humans do. Laying down raw data might cause errors.

To produce optimal results, feed your tools precise, detailed prompts. Use your critical skills to solve potential roadblocks right from the get-go. Leave no room for error—AI only takes input at face value.

2. Numeracy

Systems using advanced language models were trained on vast datasets, including mathematical formulas. They solve basic to intermediate arithmetic equations within minutes.

This example below shows ChatGPT answering an intermediate-level Algebra question correctly.

While AI tools also solve complex equations, e.g., statistics, calculus, or physics, they’re not always accurate. AI only runs formulas it understands. Errors might arise if the platform uses the wrong equation or misreads numerical patterns.

This example shows ChatGPT incorrectly answering a simple statistics problem. The answer should be 50 percent.

To compensate for AI’s inaccuracies, prompt engineers must have excellent numeracy. Spot mathematical errors yourself. Most AI tools improve their accuracy if you provide them with more context in the prompts. Your instructions should indicate the correct formulas or patterns.

3. Good Communication

Language models use English-based syntax. So whether you’re crafting user-generated input or predetermined instructions, good communication skills will help you convey messages. Simple tasks are easy to execute. You can ask general knowledge questions and one-step commands outright. Just indicate them in your prompt.

On the contrary, complex, multi-step projects require more detailed instructions. You must clearly explain your orders step by step to boost precision and accuracy. Vague prompts confuse AI.

If AI misinterprets you, try changing your word choice and phrasing. Minimize ambiguity by replacing weak verbs, breaking down instructions, predicting patterns, and setting trigger phrases.

Take this prompt as an example. It explicitly outlines orders to ensure that ChatGPT provides the expected output, even if it must bypass restrictions.

4. Attention to Detail

Prompt engineers need a keen eye for detail. Overlooking typos and omissions compromises accuracy, especially when executing multi-step projects. You’ll keep getting subpar outputs until you resolve them.

While meticulousness is an inherent, intangible trait, adults can still develop it. There are several ways to practice soft skills online. For prompt engineering, start by editing brief prompts under 100 words—correct typos, ambiguous terms, and vague phrasing.

Work on longer, more complex prompts as your skills improve. To streamline analyses, turn your revisions and their generated outputs into diagrams. You’ll lose track of combinations otherwise.

Also, note that language models react differently to prompts. If you plan on integrating multiple platforms for one complex task, you might have to rephrase specific instructions. Consider your tools’ datasets, limitations, and capabilities.

5. Versatility

AI has significantly evolved over the past few years. Global tech leaders like Google, Microsoft, and OpenAI have already released their language models, and they’re still working on new language model projects. You can expect more AI tools to hit the market soon.

Although exciting and innovative, some might find the fast-paced evolution of AI overwhelming. Even Elon Musk calls for a pause in AI development. Newly introduced platforms overtake more popular competitors after just weeks of performing well.

For prompt engineers, the best approach is to study multiple platforms. Apart from keeping up with new AI tools, know how to write prompts for their language models. Don’t focus on one platform—any AI product could become obsolete.

6. Teamwork

Apart from honing technical skills, aspiring prompt engineers must also learn to be team players. AI development isn’t a one-person job. Most projects will require you to collaborate with other specialists, like programmers, AI trainers, and UX designers.

Familiarize yourself with the different areas of AI. Knowing your teammates’ tasks and roles lets you provide better support. Help them meet their goals. Create a streamlined system wherein they review your prompts and suggest improvements.

But instead of sending emails back and forth, consider using project management tools. They let you track, assign, and edit prompts in one platform. It’s a more organized approach than forwarding revisions and sending carbon copies to third parties.

7. Coding and Programming

Prompt engineers should at least learn basic coding. Knowing the programming languages that AI developers use will help you write more effective, precise prompts. Ensure your instructions suit each model’s unique capabilities.

Also, use the Open AI Playground to explore the application of programming languages with LLMs. It lets you test different GPT-3 models. You can structure prompts more efficiently if you understand how AI processes inputs.

8. A/B Testing

Several factors affect prompt accuracy. Changing your tone, language, phrasing, and data consistency triggers different outputs. Unfortunately, AI won’t execute your instructed tasks unless you use the correct formulas.

Take this conversation as an example. ChatGPT rejected our simple request because it violated its terms of use.

After altering the prompt, we received our desired response. ChatGPT ignored its restrictions and prioritized our requests—even if doing so violated OpenAI’s policies.

This example shows what minor alterations do to brief prompts. Simple changes can be done quickly. However, if you need to modify complex prompts spanning thousands of words, expect to spend more time on A/B testing. See which variables impact output accuracy the most.

Keep track of all your results. A/B testing takes up much time and resources—avoid repeating comparison tests when possible.

Build the Skill Set of a Professional Prompt Engineer

The above skills will help you craft more detailed, precise instructions for multi-step projects. Anyone can make ChatGPT answer general questions. But conditioning language models to produce specific output and recognize patterns requires precision.

Just note that prompt engineering goes beyond upskilling. Once you have the necessary skills, start looking for job openings, research the appropriate rates, and study industry trends. Make sure you can utilize the latest industry developments.