Lab 1 Beginner Core Skill

Question → Instruction

Transform unclear questions into precise instructions that get reliable, useful results from AI systems.

~30 min Duration
3 Exercises Convert prompts
No prerequisites Start here
Begin Learning Back to Practice Studio
The Core Shift
Question

"What are some good marketing strategies?"

Instruction

"List 5 B2B marketing strategies for SaaS startups. Include: name, one-sentence explanation, estimated cost."

Same intent, dramatically different output

What You'll Learn

1

Recognize the difference between questions and instructions

2

Identify what makes a prompt vague vs. precise

3

Apply the G.O.C. framework for converting questions to directives

4

Practice with real examples and self-assess your improvements

The Core Concept

Questions Invite Rambling. Instructions Get Results.

Most people approach AI by asking questions: "What is...?", "Can you...?", "How do I...?" This feels natural - it's how we talk to experts and search engines. But questions invite open-ended, often unfocused responses.

Instructions are different. They tell the AI exactly what to produce, in what format, with what constraints. Instead of hoping the AI guesses what you want, you specify it directly.

The shift from question to instruction is the first mental model change in prompt engineering. It transforms you from a passive requester into an active director of AI output.

Question
"What are some good marketing strategies?"
⚠Vague scope, no format specified, invites rambling
vs
Instruction
"List 5 B2B marketing strategies for SaaS companies with less than $1M ARR. For each, include: the strategy name, one sentence explaining it, and estimated cost to implement."
✓Clear goal, specific format, defined constraints
Key Insight: The same intent, dramatically different outputs. Instructions are specific about format, scope, and constraints.
Your Toolkit

The G.O.C. Framework

Every question can become a precise instruction using three simple steps.

G

Identify the Goal

What do you actually want? Not "learn about X" but "produce Y"

O

Specify the Output

What form should the answer take? List, paragraph, table, code?

C

Add Constraints

Length, audience, tone, scope, format requirements

Remember
Goal → Output → Constraints

G.O.C. - The three ingredients of every effective instruction.

Practice Exercise

Your Turn: Convert These Questions

Each scenario presents a vague question. Your task: transform it into a precise instruction using the G.O.C. framework.

Marketing Scenario 1 of 3
The Vague Question:
"What are some ways to improve our email open rates?"
Your Instruction
Strong Instruction Example
"List 5 tactics to improve email open rates for a B2B SaaS newsletter with 10,000 subscribers and a current 18% open rate. For each tactic, provide: the name, a one-sentence explanation, and expected improvement percentage. Prioritize tactics that can be implemented within one week."
Goal:Improve email open rates
Output:List of 5 tactics with name, explanation, and expected improvement
Constraints:B2B SaaS, 10K subscribers, 18% current rate, one-week implementation
Self-Assessment
Research Scenario 2 of 3
The Vague Question:
"Can you explain machine learning?"
Your Instruction
Strong Instruction Example
"Write a 200-word explanation of machine learning for a marketing professional with no technical background. Use an analogy from everyday life. Avoid jargon. End with one practical example of how ML is used in digital advertising."
Goal:Explain machine learning
Output:200-word explanation with analogy and practical example
Constraints:Non-technical audience, no jargon, marketing context
Self-Assessment
Technical Scenario 3 of 3
The Vague Question:
"How do I make my code faster?"
Your Instruction
Strong Instruction Example
"Review this Python function that processes a CSV file with 100,000 rows. Identify the top 3 performance bottlenecks and suggest specific optimizations for each. Format your response as a numbered list with: the bottleneck, why it's slow, and the optimized code snippet."
Goal:Identify and fix performance bottlenecks
Output:Numbered list with bottleneck, explanation, and code fix
Constraints:Python, CSV processing, 100K rows, top 3 only
Self-Assessment

Remember: There's no single "right" answer - the goal is to practice being specific. Compare your version to the example and notice what you included or missed.

Reflect

What Did You Learn?

Guided Reflection

Take a moment to consider these questions:

  • 1Which part of the G.O.C. framework do you find hardest to specify?
  • 2How might this skill change how you use AI in your work?
  • 3What question do you ask AI frequently that you could convert to an instruction?

Key Takeaways

  • Questions invite vague answers; instructions produce useful outputs
  • Every instruction should specify Goal, Output format, and Constraints
  • Being specific upfront saves time iterating on unhelpful responses
Your Learning Journey

The Bloom Journey

You're in the "Grow" stage - building foundational skills through deliberate practice.

Seed
Discovery
Grow
Foundations
Flourish
Application
Thrive
Mastery
Radiant
Leadership
Lab 1 of 5 in Practice Studio You're learning the foundational skill of prompt engineering - transforming questions into precise instructions.
Previous Lab Return to Practice Studio Next: Spot the Hallucination
Lab 1 of 5 complete

Ready for More Practice?

Continue building your skills with the next lab, or explore the full Practice Studio.

Next: Spot the Hallucination View All Labs