Craft Better Prompts: Sharpening Your Intuitions

Key Points:

1. Prompt engineering is a specialized field within AI development, focused on designing queries that improve AI interactions, notably with tools like ChatGPT or Bard.
2. While the technical aspects of prompt engineering might be complex, users can adopt its strategies to craft better queries for more effective AI communication.
3. Often, effective prompting mirrors human interaction, asking how one might approach a task and breaking it down into comprehensible parts for the AI.
4. By guiding the AI through a step-by-step analysis of a problem, users can mimic human cognitive processes to arrive at more comprehensive conclusions.
5. Techniques that encourage self-reflection involve the AI evaluating its responses and refining them, similar to how humans improve through self-reflection.
6. Encouraging the AI to adopt various personas enhances its response quality, offering insights from multiple viewpoints.
7. Meta-Prompting for complex tasks is a method which decomposes tasks into subtasks handled by specialized prompts within the AI, then integrates these for a holistic solution, akin to a team-based problem-solving approach. Users can mimic this approach with crafted prompts that leverage meta-prompting concepts.

Prompt engineering is a niche within AI development that's complex and technical, often beyond the direct use of most people. It involves specialized skills in programming and working with AI's underlying mechanisms, which means the advancements in this area aren't immediately accessible to everyone.

However, everyday users can still adopt the essence of these advanced strategies to improve how we interact with AI tools like ChatGPT or Bard. By understanding the principles behind the evolving field of prompt engineering, we can craft better queries and engage more effectively with AI. They're insights we can all use to sharpen our own interactions with AI, even if we're not writing the code ourselves. It's about taking those high-level concepts developed by experts and applying them to our everyday digital conversations.

There's plenty we can do to enhance our AI interactions by developing better intuitions for the way a large language model responds to different kinds of prompt styles.

Here’s how we think about adapting prompt engineering research to every day prompt crafting:

1. Intuition: How would you ask a human? What’s the core intuition around the task that informs your strategy?
2. Mental Model: What is your mental model for how to complete this task? Who, what, when, and how? What is the causal modal and how do the various parts fit together?
3. Prompt Structure: What levers can you adopt from the prompt design and apply strategically?

Here’s how we apply this with some important prompt engineering techniques: chain-of-thought reasoning, iterative self-feedback, role-playing, and meta-prompting.