The Doug Macy

Tired of getting generic responses from your AI collaborator? Want to transform your interactions with Large Language Models (LLMs) and get results that feel more human? That’s where conversational scaffolding comes in.

As an experienced educator, I understand the importance of structured guidance for maximizing learning potential. The same principle applies to our AI tools! Instead of overwhelming LLMs with complex requests, a step-by-step approach will significantly boost their performance.

I have developed a technique I call ‘Conversational Scaffolding’?

It’s about breaking down complex tasks into a series of smaller, related prompts. This focused approach primes the LLM for your goal, helps it build context, and aligns it with your specific needs.  Think of it like building a multi-course meal – by prepping ingredients, following recipes for each dish, and then assembling a final presentation, you get a better result than asking for a finished meal with a single instruction.

Example: Writing a Persuasive Email

Wrong approach: “Write a persuasive email to get senior executives to sign up for a software demo.”

My approach: “What are common pain points of senior IT executives?” (let it answer)
“How might busy executives respond to different email tones?” (let it answer)
“Now craft a persuasive email addressing those pain points with an appropriate tone [include insights from previous answers].”

Power-Up Tip: Get the LLM involved in building its own scaffolding!

Try this phrase after stating your goal: “List the 3 most important questions to ask and answer to reach my goal.” This customization maximizes the AI’s focus on your unique needs.

Why This Works

Priming and Focus: You guide the LLM’s “thinking” towards your specific vocabulary and task.
Complexity Management: Smaller prompts are easier for LLMs to process, leading to better output.
Rich Context: Each answer builds upon the last, providing valuable context for the final goal.
Iterative Improvement: You can refine and adjust your prompts based on the LLM’s responses.

With conversational scaffolding, I’ve seen massive improvements in the quality and relevance of LLM output. Ready to transform your AI interactions? Let’s dive into how this technique can supercharge your projects!