Prompt Engineering

Accelerating Solutions and Efficiency


Prompt Engineering refers to an area of Artificial Intelligence (AI) for ensuring quality and purpose of AI Models. Prompt Engineers are typically Quality Assurance skilled content writers with deep domain knowledge who are able to generate the right prompts to use as input to any Natural Language Processing (NLP) / multimodal text to image/video AI Models such as ChatGPT, Dall-e2, GPT-4,, PaLM, Bard, Midjourney, and Chatbots. Frameworks include LangChain and Eval. Prompt generation approaches include Zero Shot, One Shot and Few Shot prompts (aka Chain of Thought Prompting – CoT) on one hand and Self consistency, Active Prompt, Generated Knowledge Prompting, Directional Stimulus Prompting, ReAct, Multimodal CoT, Graph Prompting and Prompt Injection on the other. Use cases span testing AI Models for topic/Q&A coverage, bias, hallucination, misinformation, answer conflicts, logical reasoning, ability to handle context and security. Coverage strategies include using tools like Answer the Public to generate real prompts.

The Anatomy

The anatomy of an engineered prompt includes basic elements and specifiers.
					Basic Elements: <INITIATION> <VERBS> <DATA INPUT> 

Prompt Engineer Skills

Prompt Engineers design and craft prompts that provide the model the necessary information and context to understand the task at hand. This ranges from providing resources on a specific topic and using specific language to guiding the model’s output to using constraints to shape the outcome.
Prompt Engineering services model ranges from time and material prompt engineers as well as fixed price or sprint milestone outcome based prompt engineering projects.
  • Advisory: Strategy, Tooling, Architecture, Project Plan. Typically 2-4 weeks
  • Delivery: Prompt design, Prompts pipeline, QA
  • Support and Maintenance: Prompts pipeline, QA
Formulate the initial prompt
Carefully frame the question or instruction to make it as clear and specific as possible
Experiment and iterate
Test different prompt variations, phrasings, or context to find the most effective input for generating the desired output.
Incorporate constraints and hints
Use specific keywords, context, or instructions to guide the AI model in generating more accurate or relevant responses.
Leveraging the AI model's capabilities
Understanding the model’s strengths and limitations, and adjusting prompts accordingly to make the best use of the AI’s abilities.
Frameworks, Tools and Technology