chatgpt-prompt-foundations
ITIAN ChatGPT Academy
Technology Simplified — Solutions That Work
Prompt Foundations
Learn a dependable structure for turning an idea into a clear request, then improve the result through review and conversation.
Learning Outcomes
By the end of this lesson, you should be able to:
Identify Five Prompt Parts
Recognise goal, context, requirements, format and review as a practical foundation.
Improve Vague Requests
Add the details that help ChatGPT understand the task without including unnecessary private information.
Choose a Useful Format
Request steps, a table, checklist, comparison or another structure suited to your purpose.
Review and Refine
Treat the first answer as a draft, check it and use follow-up prompts to correct or improve it.
The ITIAN G-C-R-F-R Framework
You do not need every part in every prompt. Use the framework as a checklist when the task deserves a careful result.
Goal
What should ChatGPT help you achieve?
Context
What background, audience or situation matters?
Requirements
What must be included, limited or avoided?
Format
How should the answer be organised and presented?
Review
What should be checked, clarified or improved next?
Anatomy of a Strong Foundation Prompt
Each line has a job. The labels are shown for teaching; natural wording is perfectly acceptable.
Example: Planning a Photography Practice Session
This prompt does not guarantee a perfect answer. It increases clarity and makes the result easier to evaluate.
Before and After Examples
The improved versions state the task, add relevant detail and request a usable structure.
Too Vague
The recipient, purpose, tone and required action are missing.
Improved
The task now has audience, purpose, tone, deadline, length and format.
Too Broad
The learner level, goal, time and lesson structure are unknown.
Improved
The answer can now match the learner, goal, scope and study format.
Interactive Prompt Laboratory
Build a complete foundation prompt. Everything is processed locally in your browser.
Six Useful Prompt Types
Use these as patterns, then add details relevant to your real task.
Explain
Learn a topic at the right level.
Explain [topic] for [audience]. Use [format] and include [examples].Draft
Create a starting version you will edit.
Draft [content] for [audience] with [purpose], [tone] and [length].Rewrite
Improve supplied text while preserving meaning.
Rewrite the text below to improve [quality]. Keep [important constraint].Compare
Evaluate realistic alternatives.
Compare [options] using [criteria]. Show trade-offs and recommend based on [goal].Plan
Turn a goal into staged action.
Create a [duration] plan for [goal], considering [resources and limits].Review
Find gaps and improvements.
Review [content] against [criteria]. Separate issues, strengths and recommended changes.Recommended: 16:9 • Captioned • Transcript supplied
Watch the Prompt Workshop
This future video will transform one vague request using the five-part framework, test the result and apply a follow-up prompt.
- Show every prompt in readable text.
- Explain why each detail was added.
- Review the answer instead of calling it perfect.
Practical Challenge: Build Three Prompts
Choose safe topics and complete all three. You may use the laboratory above.
0 of 8 completed — begin with an Explain prompt.
Common Prompting Mistakes
Too Little Information
Symptom: generic output.
Improvement: add the goal, relevant context and intended audience.
Too Many Tasks at Once
Symptom: incomplete or confused output.
Improvement: break a complex workflow into smaller conversational steps.
Only Saying What Not to Do
Symptom: uncertainty about the desired result.
Improvement: state the positive behaviour or format you want.
Treating the First Answer as Final
Symptom: missed errors and weak fit.
Improvement: review, verify and refine through follow-ups.
Knowledge Check
Answer all five questions, then check your result.
Official Sources and Further Reading
This lesson was reviewed against current first-party OpenAI guidance on 13 July 2026.
OpenAI Help Centre
- Prompt engineering best practices for ChatGPT — clarity, specificity, context, tone and iterative refinement.
- How to create a good prompt — clear tasks, right-sized requests and conversational improvement.
- Accuracy and reliability — checking important information and recognising confident errors.
Prompting techniques evolve, but clarity, relevant context, manageable tasks and careful review remain strong foundations.
Lesson Summary
The foundation to remember
- State the goal clearly.
- Add only the context that matters.
- Specify useful requirements and limits.
- Request a format suited to the task.
- Review, verify and refine the answer through conversation.