Iterative Refinement Workflow

The best prompt engineers don't write perfect prompts — they refine outputs through conversation. Learn this systematic approach.

Wrong approach: Accept whatever AI gives you first Right approach: Treat AI output as a starting point to improve

Most people stop too early. The magic happens in refinement.

The Refine-Evaluate-Adjust Cycle

┌─────────────┐
│   Prompt    │
└──────┬──────┘
       ▼
┌─────────────┐
│   Output    │◄──────┐
└──────┬──────┘       │
       ▼              │
┌─────────────┐       │
│  Evaluate   │       │
└──────┬──────┘       │
       ▼              │
┌─────────────┐       │
│   Refine    │───────┘
└─────────────┘

Make It Better:

Goal	Prompt
Shorter	"Make this more concise — aim for half the length"
Longer	"Expand the section on [X] with more detail"
Simpler	"Rewrite this for someone with no technical background"
Professional	"Make the tone more formal and executive-ready"
Engaging	"Make this more compelling — add hooks and stronger verbs"

Fix Specific Issues:

Issue	Prompt
Missing info	"Add [specific topic] to the second paragraph"
Wrong audience	"Rewrite this for [new audience]"
Too generic	"Make this more specific to [industry/context]"
Needs examples	"Add a concrete example for each point"

Get Alternatives:

"Give me 3 alternative versions with different approaches" "Rewrite this with a completely different structure" "What's another way to say this?"

When to Refine vs. Start Over

Refine When	Start Over When
Close but not quite right	Completely off-topic
Needs minor adjustments	Wrong approach entirely
Good structure, weak content	Fundamental misunderstanding
Right direction, wrong details	Multiple major issues

Real Workflow Example

Initial prompt:

"Write a customer apology email for a service outage"

First output: Generic, lacks specifics

Refinement 1:

"Good start. Add that the outage lasted 4 hours and affected billing features specifically."

Second output: Better, but too formal

Refinement 2:

"Soften the tone — make it sound human, not corporate. Add what we're doing to prevent this."

Third output: Perfect for use ✓

Build Your Template Library

When you get a great result, save the winning prompt:

Copy the final prompt that worked
Create a template with placeholders
Add notes on what refinements were needed
Store in your prompt library for reuse

Example template:

Role: Customer support lead
Tone: Professional but warm
Structure: Acknowledge → Explain → Resolve → Prevent
Variables: [issue], [duration], [affected features], [compensation]

Key Takeaway

Don't accept the first output — refine it. Use specific feedback: "make it shorter," "add X," "change the tone to Y." The conversation IS the process. Save winning prompts for future use.

Congratulations! You've completed Module 2. Take the quiz to test your understanding of core prompting techniques. :::

The Refinement Mindset