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Home » What you need for prompt engineering
Technology

What you need for prompt engineering

Alausa-Issa Zainab
October 14, 2025
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Prompt engineering is the process of formulating instructions to produce an answer or outputs from a generative artificial intelligence. ‘Prompt’ is a natural language text that directs AI on what to do. It could be a command, query, providing a context or just a statement. 

Contents
  • Skills you need as a prompt engineer
    • 1. Data structures and algorithms 
    • 2. Interpret technical concepts 
    • 3. Large language models
    • 4. Communication skills
    • 5. Programming languages 

The main aim of prompt engineering is to be able to optimise outputs; being precise, ensures that the generated AI output aligns with the goal or desired result. An hallmark of a prompt engineer is to be able to bring the best out of different generative AI models. For instance, Open AI’s GPT-3 and GPT-4 are different from Google Gemini. Hence, they require different styles to get what you want. 

As a prompt engineer, expected to design, test and refine prompt to bring out the best performance from generative AI models, you must be able to understand and familiarise yourself with the capacities and differences of artificial intelligence models including their limitations. 

Skills you need as a prompt engineer

Technological companies hire prompt engineers to improve machine translation and to also introduce content. These are the skills that can help you secure a job:

1. Data structures and algorithms 

You need to have the knowledge of how data structures and algorithms help in optimising prompts including understanding the mechanisms of generative AI systems.

2. Interpret technical concepts 

One of the exceptional qualities you can possess is to be able to interpret technical concepts in a very relative way that even non technical professionals would understand.

3. Large language models

You must understand how Large Language Models (LLM) work in order to create effective prompts and optimised AI outputs. Their capabilities and limitations are also important.

4. Communication skills

Communication skills are very vital. You should be able to communicate in clear and precise language instructions to AI models.

5. Programming languages 

Proficiency in programming languages such as python is key for understanding and designing AI solutions and automating workflows.


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