You've learned iterative prompting. Now let's explore prompt chaining - breaking complex sales tasks into a sequence of connected prompts where each output becomes the next input.

Think of it like a sales pipeline for AI tasks. Each step focuses on one specific piece of the selling process.

Engagement Message

Have you ever felt overwhelmed trying to get AI to handle a complex, multi-step sales request all at once?

Here's how prompt chaining works: You break a big sales task into smaller, logical steps. The AI completes step one, you take that output, and feed it into step two.

Each prompt is focused and clear. No confusion, no overwhelming complexity - just one sales objective at a time.

Engagement Message

What's a complex sales task you do regularly that involves multiple steps?

Why does chaining work better than one massive prompt? AI gets confused with too many sales instructions at once, like asking someone to qualify leads while writing proposals. Especially smaller/faster models.

Chaining gives AI focus. Each step has a clear sales goal, making responses more accurate and actionable.

Engagement Message

Have you noticed AI giving worse results when you ask it to do too many sales tasks simultaneously?

Here's a simple linear chain example:

• First prompt: "Analyze this prospect's company profile and identify 5 key pain points they likely face."
• Second prompt: "For each pain point from this list: [paste list], explain how our solution addresses it."
• Third prompt: "Based on these pain point solutions: [paste solutions], write a personalized outreach message for this prospect."

Do you remember Deep Research tool?

Engagement Message

Which step(s) from this chain should we use it for?

Common mistake: Making each step too complex. Keep individual prompts simple and focused. Another mistake: Not providing enough context from previous steps.