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Prompt Engineering

In the field of Prompt Engineering, there may be several job titles that are related to this emerging role.

AI/ML Engineer

AI or Machine Learning Engineers often work on creating and optimizing natural language processing (NLP) models, including prompt engineering.

NLP Engineer

Natural Language Processing Engineers focus on developing algorithms and models to understand and generate human language, which is crucial for prompt engineering.

Data Scientist

Data Scientists with NLP expertise may be involved in crafting prompts for AI systems and analyzing their performance.

Conversational AI Engineer

Professionals in this role specialize in building chatbots and virtual assistants, which involves prompt design and optimization.

Language Model Specialist

Some companies might have specialists dedicated to fine-tuning and customizing language models, including prompt engineering.

AI Product Manager

Product managers working on AI products may collaborate with engineers and data scientists to define prompts and user interactions.

Machine Learning Researcher

Researchers in this field often contribute to the development of novel techniques for prompt engineering and NLP.

AI Content Strategist

Content strategists may focus on crafting effective prompts and user interactions to ensure a seamless user experience.

AI Ethicist

Professionals in this role may be responsible for ensuring that prompt engineering adheres to ethical guidelines and avoids biases.

AI Quality Assurance Engineer

QA engineers specializing in AI may test and optimize prompts to enhance the overall performance of AI systems.

Prompt Engineering as Consultant, Advisor, or Coach

The jobs listed above are very technical. Yet there is a need for business-oriented prompt engineering specialists. In the field of prompt creating and the strategic usage of prompts, The job titles below emphasize the role as a consultant, advisor, or coach.

Prompt Consultant

A professional who offers guidance and expertise in creating prompts for various purposes, such as content marketing or brainstorming.

Prompt Strategist

A role focused on developing strategic approaches to prompts, tailored to specific business or communication goals.

Prompt Copywriter

A creative writer who crafts compelling prompts for social media, advertisements, or other marketing materials.


Elevator Talk I of Prompt Consultant

I specialize in helping businesses and individuals find the right words to captivate, engage, and inspire action.

As a Prompt Consultant, I work closely with you to craft prompts that resonate with your audience and drive results.

Whether it's boosting your brand, improving communication, or sparking creativity, I'm here to transform your ideas into compelling messages.

Let's chat about how I can elevate your prompt game and unlock your full potential."



Elevator Talk II of Prompt Consultant

AI am a Prompt Consultant with a passion for optimizing human-AI interactions.

My expertise lies in fine-tuning prompts to get the most out of AI systems like ChatGPT.

I help you unlock the full potential of this new AI large-language-model technology, whether it's for enhancing productivity, problem-solving, or content creation.

I work closely with clients to craft prompts that yield accurate, insightful, and valuable responses. Together, we can explore the intricacies of prompt engineering, tailoring your inputs (your valuable data) to achieve the specific outcomes you desire.

Whether you're the owner of a small business looking to improve customer interactions or an individual and professional seeking more effective communication with AI, I guide people through an assessment process using an AI Capabilities Scorecoard.

In short, I help people harness the power of AI to create value.


prompt tips

Assign an advantageous role. "You are a skilled and creative script-writer." Give the role key qualities. Highlight how good the AI is at the given task.

Describe the task and start with a verb, such as "Generate a (the goal of the task). Be descriptive and precise.

Describe the technique. Tell the model to think in a step-by-step way. Or, better yet, give the AI step-by-step instructions or a step-by-step process on how to perform the task. This is chain-of-thought prompting.

Use the technique emotional stimuli which means adding short phrases that are stimuli. The example is "this is important to my career" and "I appreciate you helping me as this is vital to my business" and in general hype up the importance of the AI's job. This encourages the model to be more thorough.

Describe the context. Describe the company or the purpose of the prompt and the general situation of why the prompt is being used. Describe the type of customers or the values of the company. Describe the importance of the task to the success of the business.

Give examples of how the AI should respond, such as tone. Use 3 to 5 examples; the more the better but you are being charged by the token. Provide examples to the LLM that are input-output examples. This will increase the accuracy. This is a kind of substitute for fine-tuning. This is called few-shot prompting.

Give notes describing last chance instructions. Provide format instructions. Mention things that the AI should do.

It can help to do markdown formatting allowing the AI to understand the structure of the prompt.


Ideas from the article "Prompting Fundamentals and How to Apply them Effectively"

This article (written by Eugene Yan) emphasizes several key concepts for effective prompt engineering:

1. Understanding Prompts as Conditioning: Recognize that prompts guide the language model's output by conditioning it with specific instructions or context. This approach helps steer the model's responses in desired directions.

2. Assigning Roles and Responsibilities: By designating a specific role to the model (e.g., "You are a preschool teacher"), you can influence the tone, style, and depth of its responses, leading to more contextually appropriate outputs.

3. Utilizing Structured Input and Output: Providing input in a structured format (such as XML or JSON) and requesting output in a specific structure can enhance the model's understanding and facilitate easier parsing of its responses.

4. Implementing n-Shot Prompting: Including multiple examples within the prompt (n-shot prompting) can improve the model's performance by demonstrating the desired task and output, thereby guiding its responses more effectively.

5. Prefilling Responses: Starting the model's response with predefined text can ensure consistency and control over the output, especially when specific formatting or content is required.

These strategies collectively enhance the effectiveness of prompt engineering, leading to more accurate and contextually relevant outputs from language models.