Tech Term Decoded: Prompt Engineering

Definition

Prompt engineering is a technique that involves writing effective instructions for a model, enabling it to consistently generate content that satisfies your need. This is achieved by thoughtfully crafting prompts that guides the model with context, instructions, and examples that assist it to understand your intent and respond in a meaningful way. It is just like providing a roadmap for the AI, steering it towards the specific output that you desire [1].

For example, lets take a look at a food delivery app that needs SMS alerts for customers during fuel scarcity that affects delivery time.

A basic prompt for this scenario may go like this:

"Tell customers about delivery delays."

But with an Engineered Prompt:

"Write a 100-word SMS for ChopChop customers in Abuja experiencing 45-minute delivery delays due to fuel scarcity. Apologize sincerely, offer ₦200 discount on next order, mention our delivery partners are trying their best. Use respectful English. Reference current fuel queue situation everyone understands."

This well engineered prompt will transform a generic delay message into an empathetic, culturally aware communication that acknowledges shared experiences (fuel scarcity) while providing concrete compensation and maintaining customer relationships.

Illustration of prompt engineering [2].

Origin

The origin of Prompt engineering can be traced back to the early days of the development and evolution of natural language processing (NLP) and artificial intelligence (AI) systems. During this time period, researchers primarily focused on rule-based systems that relied on predefined grammatical rules and dictionaries to process and generate text. Prompting, as we know it today, was not a significant concept in these systems.

But the release of GPT-3 by OpenAI in 2020 ushered in a new era in the journey of prompt engineering. Its 175 billion parameters demonstrated the capability of large-scale pretrained models. Researchers and developers began to explore the art of crafting effective prompts to control and guide the model's behavior [3].

Context and Usage

Prompt Engineering saves time, boosts creativity and increases your productivity. Learning it doesn’t take time even as someone without a tech background. It has so many applications that span across various fields and industries such as the following;

Analysts automate reports with it
It helps Students summarize research
Designers use it to generate concepts
Marketers use it for drafting campaigns
It helps teachers create lesson plans
Freelancers use it to write proposals

Why it Matters

Since the launch of generative AI, Prompt engineering jobs have experienced massive growth. Prompt engineers create synergy between end users and the large language model. They identify scripts and templates that your users can customize and complete to get the best result from the language models. These engineers test run different kinds of inputs to build a prompt library that application developers can reuse in different scenarios. Prompt engineering makes AI applications more efficient and effective. Application developers typically encapsulate open-ended user input inside a prompt before passing it to the AI model [4].

In Practice

A3logics, a leading prompt engineering company, is a good example of a real-life case study of prompt engineering in practice. Their prompt engineering experts specialize in providing custom prompt engineering solutions to help their customers unlock the true potential of LLM’S like chatgpt, claude or google gemini [5].

Tech Term Decoded: Prompt Engineering

Post a Comment

Contact Form