Prompting for Dummies
A Beginner’s Guide to Not Suck at ChatGPT
Hello frens,
Let’s be real. Most people suck at prompting.
They open ChatGPT, type something like “write me a resume” or “teach me cybersecurity,” and then get mad when it spits out corporate oatmeal.
That’s not the model’s fault.
That’s your prompt.
The good news? You don’t need to be a “prompt engineer.”
You just need to understand one simple structure that gets 80 percent of the results with 20 percent of the effort.
The 80/20 Rule of Prompting
ChatGPT doesn’t “think”. It predicts.
It completes your sentence based on how clear you are.
If you give it chaos, it’ll mirror chaos.
If you give it structure, it’ll deliver insight.
You don’t need 40-line prompt templates or “ultimate master prompts” that try to do 30 things at once. Those bloated walls of text are the equivalent of shouting instructions at a waiter in four languages — confusing, unnecessary, and extremely likely to come back wrong.
Good prompting is lean, intentional, and layered.
And it starts with a framework that actually works.
The CARF Framework
Context → Action → Result → Format
This is the backbone of every good prompt.
It’s simple enough for anyone to learn and powerful enough to scale across anything you do — personal, professional, or technical.
Step 1: Context
Tell it who it is, who you are, and what’s going on.
Without context, ChatGPT guesses tone, expertise, and purpose — and it usually guesses wrong.
Bad: “Write a message to my boss.”
Good: “You are an HR professional helping me write a respectful message to my boss to request time off next week without sounding lazy.”
Why it works: Context gives the model its identity and mission.
Step 2: Action
Tell it exactly what to do.
Bad: “Help me plan my day.”
Good: “Prioritize my tasks by urgency and energy level, assuming I have four hours of deep focus time and a few errands.”
Why it works: The model understands your constraints and decision logic.
Step 3: Result
Tell it the goal or outcome you want.
Bad: “Give me fitness advice.”
Good: “List three bodyweight workout plans I can do in 30 minutes each, focused on strength and consistency.”
Why it works: You’re defining the finish line, not just the topic.
Step 4: Format
Tell it how to deliver the output.
Bad: “Give me healthy lunch ideas.”
Good: “Give me five healthy lunch ideas in a table with columns for ingredients, prep time, and calorie range.”
Why it works: Format tells the model how to package the result so you can actually use it.
Full CARF Example
“You are a productivity coach helping me plan tomorrow.
Look at the list of things I need to do and group them into Deep Work, Admin, and Personal categories.
Then prioritize each group in order of importance and suggest when I should do them based on energy level.
Return the result as a clean checklist with time blocks.”
Context (who + why), Action (what to do), Result (goal), Format (structure).
That’s it. Simple, repeatable, and effective.
Why Master Prompts Are Trash
Everyone’s chasing the “master prompt.”
You know the ones: 2,000 words of “You are an elite expert who must respond using empathy, data-driven reasoning, markdown tables, motivational tone, and 19 adjectives.”
That stuff looks impressive in screenshots, but in practice it’s useless.
AI doesn’t need a novel. It needs clarity.
Master prompts try to do too much, and when you stack fifty constraints, the model just averages them out, and you end up with bland, middle-of-the-road mush.
If you want precision, stack small prompts, not big ones.
Think in layers: one for role, one for task, one for output, one for polish.
That’s how you get adaptive, controllable responses.
One-Shot Prompting is Overhyped
Everyone loves to talk about “one-shot prompting.”
It sounds clean. Fire off one perfect prompt, get one perfect answer.
In reality? It rarely works.
For novel, creative, or complex tasks, multi-shot prompting wins every time.
You’re not talking to a vending machine; you’re building a feedback loop.
The more context you layer and the more you refine, the sharper your results.
When One-Shot Prompting Actually Works
To be fair, one-shot prompting isn’t bad. It’s just overused.
It’s perfect for simple, predictable, low-risk outputs where the structure never changes:
Converting a resume to plain text like at PlainTextResume.com
Generating a grocery list based on ingredients
Formatting an email into professional tone
Creating basic templates like social posts or blurbs
If the problem is clear and the output predictable, one-shot works.
But if the task involves nuance, decision-making, or human context — that’s where multi-shot prompting becomes non-negotiable.
CARF Works Everywhere
You can use CARF for anything:
Career:
“You are a cybersecurity hiring manager. Review my resume and tell me what’s missing for a Tier 1 SOC Analyst role. Return feedback as a three-column table.”
Fitness:
“You are a certified personal trainer. Build me a four-week bodyweight routine I can do at home with no equipment. Show weekly progression in a table.”
Cooking:
“You are a chef. Turn the ingredients in my fridge into a two-day meal plan under 2,000 calories per day. Return a shopping list and prep guide.”
Life Planning:
“You are a financial coach. Help me decide between paying off debt or investing, assuming I have $1,000 per month to allocate. Write it as a simple pros and cons list.”
The Takeaway
Prompting isn’t about memorizing tricks or pretending to be an engineer.
It’s about communicating clearly.
Skip the bloated master prompts.
Stop worshiping one-shot perfection.
Think in layers. Iterate. Refine.
If you can master the CARF framework (Context, Action, Result, Format) you can get professional-grade output from AI in minutes instead of hours.
The game isn’t about writing the longest prompt.
It’s about writing the right one.
That’s all for now. Next time, I’ll show you how I do intermediate prompting with categories and lists for ultra detailed, long form, structured outputs.
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Until next time!
Much love,
Evan Lutz (BowTiedCyber)