Prompt Engineering Course
Industry Frameworks
In real companies, prompts are not written casually.
They follow frameworks.
Frameworks make prompts reliable, reusable, auditable, and scalable across teams.
Why Industry Uses Prompt Frameworks
Without structure, prompts break when:
- Models change
- Inputs vary
- Users ask unexpected questions
Frameworks solve this by enforcing consistency.
What Is a Prompt Framework?
A prompt framework is a repeatable structure that defines:
- What information goes in
- How instructions are ordered
- How outputs are constrained
Think of it as an API contract for language models.
The CORE Prompt Framework
One commonly used industry pattern is:
- Context
- Objective
- Rules
- Expected Output
Each section has a clear purpose.
Context
Context sets the environment and background.
You are an AI assistant helping customer support agents
for an e-commerce platform.
This tells the model where it operates.
Objective
The objective defines the task.
Your task is to generate a polite, accurate response
to customer refund requests.
Objectives remove ambiguity.
Rules
Rules control behavior.
Follow company refund policy.
Do not promise actions you cannot perform.
Keep responses under 150 words.
This prevents risky outputs.
Expected Output
Output format ensures consistency.
Respond in a friendly tone.
Use bullet points if listing steps.
End with an offer for further help.
This standardizes responses across users.
Why Frameworks Beat Ad-Hoc Prompts
Framework-based prompts:
- Scale across teams
- Are easier to debug
- Work well with APIs
Ad-hoc prompts do not survive production environments.
Frameworks in Real Departments
Different teams use different frameworks:
- Support teams focus on safety and tone
- Data teams focus on structure and accuracy
- Engineering teams focus on determinism
Prompt frameworks adapt to business goals.
How Learners Should Practice Frameworks
Practice by:
- Breaking prompts into sections
- Testing each section independently
- Refining rules based on failures
This builds system-level thinking.
Common Industry Mistakes
- Writing long prompts without structure
- Mixing objectives and rules
- Not defining output clearly
These mistakes cause unstable systems.
Practice
Why do industry prompts need structure?
What is the purpose of rules in a prompt framework?
What problem do output definitions solve?
Quick Quiz
Which framework section sets the environment?
What makes prompts production-ready?
Which section ensures response consistency?
Recap: Industry frameworks turn prompts into reliable, scalable systems used across real organizations.
Next up: Building prompt systems — combining multiple prompts into one coordinated workflow.