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Issue #18: Build your own Prompt Writer.

TL;DR

AI output quality depends heavily on the prompt.
Most people struggle because writing strong prompts takes time.
A simple solution is to build a Prompt Writer project inside Claude or ChatGPT.
Upload prompting resources and system instructions.
Then describe the task you want, and the system generates the optimized prompt for you.

1. The Hidden Skill Behind Good AI

Every week someone tells me:

“AI gave me a terrible answer.”

Sometimes that’s true.

But more often the problem isn’t the AI.

It’s the prompt.

Think about it this way.

If you give a vague assignment to an employee, you usually get a vague result. AI is exactly the same. The clearer the task definition, the better the output.

The difference between:

“Write a marketing email”

and

“Write a short email to HVAC business owners explaining why Google Ads leads are dropping and how better targeting fixes it”

is massive.

The model hasn’t changed.

The instruction has.

2. Prompting Is Not Guesswork

A lot of people think prompting is just trial and error.

It’s not.

There are actually well studied prompting frameworks used in AI research and model development.

Things like:

Role prompting
Few-shot prompting
Chain of thought reasoning
ReAct workflows
Persona prompting

If you want the deeper explanation of these approaches, I wrote a full guide here:

The Complete Guide to Prompting Frameworks
https://kuware.com/blog/the-complete-guide-to-prompting-frameworks-standardized-and-experimental-approaches/

That article walks through the structured ways AI researchers design prompts.

But here’s the catch.

Understanding the theory does not automatically make writing prompts easier in real life.

3. The Real Problem: Nobody Has Time to Craft Perfect Prompts

In theory we would love to craft perfect prompts every time.

Define the role.
Add examples.
Set constraints.
Structure the output.
Explain the reasoning path.

But in real business workflows?

Nobody has time for that.

You just want AI to help with something quickly.

And this is exactly why I built something I call a Prompt Writer.

4. The Idea: Let AI Write Your Prompts

Instead of manually building perfect prompts every time, you can create a small AI workspace that generates them for you.

Prompt Writer uses:

OpenAI prompting documentation
Anthropic Claude best practices
Google Gemini prompting guides
academic research on prompt engineering

When you describe the task you want AI to perform, Prompt Writer creates a structured prompt optimized for the target model.

Even better.

It explains why the prompt was written that way.

So you gradually learn better prompting while using it.

If you want the full walkthrough, the blog explaining the system is here:

Stop Wrestling With AI: Build Your Own Prompt Writer Instead
https://kuware.com/blog/build-your-own-prompt-writer

5. The Practical Setup

The implementation is surprisingly simple.

Create a project in Claude or ChatGPT.

Then upload a small set of prompting resources and system instructions.

Those files act as the knowledge base for your prompt generator.

The resources I use include:

Prompt Writer system instructions
Claude prompting best practices
Gemini prompting guide
The Prompt Report (academic survey of prompt engineering)

Once these are inside the project, you now have a prompt-generation workspace.

Instead of writing full prompts yourself, you simply describe what you need.

Example:

“Create a prompt for Claude to analyze a sales transcript and identify objections.”

Prompt Writer produces the optimized prompt automatically.

6. One More Useful Feature

You can also specify which LLM the prompt is for.

Why does that matter?

Because models behave slightly differently.

Claude prefers clearer reasoning structures.
GPT models often respond well to explicit formatting instructions.
Gemini sometimes prefers different prompt layouts.

Prompt Writer adjusts the structure based on the model you choose.

So you get prompts optimized for:

ChatGPT
Claude
Gemini
or other models

7. Why This Matters for Businesses

Many companies are experimenting with AI.

But most teams still rely on random prompts.

That leads to inconsistent results.

When you standardize prompting inside your organization, two things happen:

AI outputs become far more reliable
Teams learn faster

The difference between casual AI use and structured AI workflows often comes down to this layer.

Prompting.

8. The Bigger Lesson

Over the last few issues we’ve been talking about AI architecture layers.

Models
Inference
Routing
Interfaces

Prompting is another layer most people overlook.

It’s the instruction layer.

And if you improve that layer, every AI system you use suddenly performs better.

Not by changing the model.

But by changing the instructions.

Thanks for reading Signal Over Noise,
where we separate real business signal from AI noise.

See you next Tuesday,

Avi Kumar

Founder: Kuware.com

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