An Introduction to Prompting • Chapter 4
Mastering Complex Conversations
Complex thinking demands clear dialogue. By breaking down intricate challenges and guiding AI through deeper reasoning, you can turn overwhelming problems into structured, solvable steps. Big challenges don’t need simpler answers—they need better questions and instructions. Master this, and you’ll unlock AI’s true power: transforming complexity into clarity.
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Part 1
Clarifying Intent.
Imagine telling a friend about a problem—but without making it clear what you actually want from them. Do you need advice? An opinion? A solution? Or do you just want them to listen? If you don’t set expectations, their response may be well-meaning but completely off the mark.
AI works the same way. Without clear intent, its response can be accurate but irrelevant—technically correct, yet missing what you actually need.
Intent classification is the process of defining the core purpose of your prompt. Are you asking AI to summarise, analyse, generate ideas, or solve a problem? Understanding intent isn’t just about getting better AI responses—it’s about sharpening your own clarity and focus.
Why Intent Matters
Every complex query has a purpose. If the intent isn’t clear, AI’s response might be accurate but ineffective—technically correct, yet missing what you actually need. By defining intent upfront, you transform AI from a general responder into a focused problem-solver.
💡 Consider this:
Information-Seeking Intent: “What is the history of renewable energy in urban design?”
Analytical Intent: “Compare the advantages and disadvantages of renewable energy in urban areas.”
Creative Intent: “Write a short story about a city powered entirely by renewable energy.”
Each prompt is about the same topic, but with a different purpose. When intent is explicit, AI adapts—delivering insights, analysis, or creativity as needed.
How to Classify Intent
1. Define the Purpose
Before prompting, ask yourself: What do I need AI to do?
Is it summarising, analysing, generating ideas, or completing a task? A clear purpose leads to a more precise response.
2. Use Intent-Specific Keywords
Choose words that signal the type of response you expect.
For information-seeking, try “explain”, “summarise” or “define”.
For analytical, try “analyse”, “compare” or “evaluate”.
For creative/generative, try “Imagine”, “create” or “draft”.
Clarifying intent isn’t just about getting better answers—it’s about asking better questions. When your intent is clear, AI doesn’t just respond—it delivers exactly what you need.
Part 2
Summarising for Context
Imagine brainstorming with a colleague for hours. Ideas are flowing, but as the conversation stretches on, things start to feel scattered. What if, at key moments, they paused to recap everything important? Suddenly, you’re grounded again—clear on where you’ve been and where you’re headed.
Summarisation does the same for AI. It helps capture and preserve context, ensuring that insights don’t get lost—especially in long conversations. But summarisation isn’t just about condensing information; it’s about holding onto what matters so you can build on it effectively.
Why Summarisation Matters in AI Conversations
AI operates within a context window—a limit on how much information it can recall at once. In lengthy interactions, earlier parts of the dialogue may fall out of that window, meaning AI can no longer reference them. Summarisation bridges this gap, keeping conversations cohesive and forward-moving.
Let’s say you’re using AI to brainstorm a business idea:
➊ At first, you explore potential industries.
➋ Later, you define your target audience and product features.
➌ Toward the end, you discuss marketing strategies.
Without a summary, AI may lose sight of those early insights. But by prompting it to recap the conversation at certain points, you retain focus and momentum—ensuring your session remains productive.
Using Summarisation to Maintain and Transfer Context
1. Keeping the Conversation Grounded
In long sessions, summarisation serves as a checkpoint. It reinforces key insights, helping AI “remember” what’s important as the discussion evolves.
Example Prompt:
“We’ve discussed several eco-friendly product ideas, including reusable packaging and solar-powered gadgets. Summarise what we’ve covered so far, focusing on the top three most promising ideas.”
✅ How It Helps:
This anchors the conversation, keeping both you and AI aligned on key priorities.
2. Preparing for New Sessions
Want to pick up where you left off in a future session? Summarisation helps carry over context, saving time and ensuring continuity.
Example Prompt:
“Summarise our discussion so far, including the business ideas we’ve explored, the target audience we’ve identified, and the challenges we noted. Format it so I can share it in a new session.”
✅ How It Helps:
This creates a snapshot of your previous conversation, so you can seamlessly resume your work with AI.
3. Collating Insights for Review
Instead of scrolling back through an entire chat, you can ask AI to summarise the key takeaways—giving you a clear, structured reference.
Example Prompt:
“Summarise the key takeaways from our conversation about launching a subscription box service, including product ideas, pricing strategies, and marketing approaches.”
✅ How It Helps:
The summary distils the most relevant insights, allowing you to focus on action rather than information retrieval.
Summarisation: The Key to Clarity
Summarisation isn’t about cutting corners—it’s about creating clarity. Whether refining ideas mid-conversation or carrying context into a new session, it ensures that what matters most stays at the forefront.
It’s the bridge between where you’ve been and where you’re going.
Part 3
Thinking in Steps
Imagine asking someone a complex question and expecting an instant, perfect answer. Chances are, their response would be hurried and superficial—missing depth, nuance, or important details.
AI works the same way. It doesn’t “think” in a human sense, but the way you frame your queries affects the quality of its responses. If you rush it with overloaded prompts, you’ll get shallow, scattered answers. But when you guide AI through a structured process, you unlock deeper, more refined results.
What Does It Mean to Give the AI Time to Think?
In practice, “giving the AI time to think” means structuring prompts in a way that encourages it to tackle problems step by step. Instead of expecting one big answer to a broad question, break it down—allowing the AI to refine its output at each stage.
Example: Overloaded vs. Thoughtful Prompting
❎ Overloaded Prompt:
“Write a business plan for a sustainable coffee shop, including market research, financial projections, and marketing strategies.”
✅ Thoughtful, Step-by-Step Prompting:
Step 1: “What factors should be considered when opening a sustainable coffee shop?”
Step 2: “Based on these factors, what are some key market trends we should explore?”
Step 3: “Using this information, draft an outline for a business plan.”
💡 Why it works
By breaking the task into stages, you allow AI to generate more focused and meaningful responses at each step.
How it Works
✅ Encourages Depth & Focus
Breaking down a request reduces superficial, generic answers. Each step builds on the last, leading to a richer final result.
✅ Improves Coherence
Guiding AI through a process ensures it maintains context, making responses logically consistent and aligned with your goals.
✅ Supports Iteration
This method lets you refine and adjust as you go—improving the final output without relying on AI to get it perfect in one shot.
The Power of Step-by-Step Thinking
It’s natural to want quick answers, but depth requires patience. By guiding AI through stages, you strike the right balance between speed and quality—ensuring responses are not just fast, but thoughtful and actionable.
This approach is especially valuable when you’re not entirely sure what you’re looking for. Asking AI to create a detailed business plan or solve a complex problem can be overwhelming—both for you and the AI. But when you start with exploratory steps—like defining what makes a strong business plan or listing key elements—you gain clarity as you go.
Step-by-step prompting turns AI from a passive responder into an active problem-solving tool—helping you surface key concepts, uncover blind spots, and refine your thinking.
It’s not just about getting better AI responses. It’s about thinking better yourself.
Reflection
The best answers come from better questions.
Clarity isn’t just about getting the perfect response; it’s about refining your questions, step by step, until the answer reveals itself. AI, like any tool, responds to the structure and intent you give it. The more thoughtful and deliberate your approach, the more powerful the outcome.
This isn’t just an AI principle—it’s a way of thinking.
Breakthroughs don’t happen in a single leap. Whether you’re solving problems, building ideas, or navigating the unknown, the key is to simplify the complex, focus on what matters, and move with purpose.