AI Disruptor

AI Disruptor

This one change made my AI outputs 10x better

And it had nothing to do with better prompts

Alex McFarland's avatar
Alex McFarland
Jul 16, 2025
∙ Paid
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Most people are solving the wrong AI problem.

They're collecting prompts. Building complex templates. Adding XML tags and variable placeholders. I've seen prompt libraries that look like they need a computer science degree to understand.

But here's the thing: prompting isn't your problem. Your input architecture is.


Your prompts are fine. Your inputs aren’t.

I've written thousands of AI-generated assets for actual clients and my own stuff.

You know what I discovered? Whether you're brand new or crafting elite-level prompts, most people are still missing this one critical piece. They haven't separated their prompt logic from their context inputs.

And that's the real moat now.

Even my 50-line prompt template was still amateur hour

Look at this prompt template I used to use for newsletters:

You are an experienced newsletter creator with a proven track record of achieving 50%+ open rates and hundreds of thousands of subscribers. Your task is to create a new edition for a newsletter about the following niche:

<newsletter_niche>
{{NEWSLETTER_NICHE}}
</newsletter_niche>

The specific topic for this edition is:

<topic>
{{TOPIC}}
</topic>

Before we begin, please review the following notes for additional context:

<notes>
{{NOTES}}
</notes>

Start by analyzing the project knowledge, notes, and topic. Conduct your analysis inside <newsletter_analysis> tags:

1. Key themes from the newsletter niche:
   [List at least 3 key themes]

2. Relevant information from the notes:
   [Summarize at least 3 relevant points]

3. Potential angles for the newsletter:
   [List at least 5 potential angles]

4. Target audience and their interests:
   [Describe target audience demographics and at least 3 primary interests]

5. Potential reader pain points or desires related to the topic:
   [List at least 3 pain points and 3 desires]

6. Content ideas based on the analysis:
   [Brainstorm at least 5 specific content ideas]

7. Appropriate tone and style for the target audience:
   [Describe the tone and style, with at least 3 specific characteristics]

8. Summary of findings:
   [Provide a brief summary of your analysis, highlighting the most important insights]

Based on your analysis, complete the following tasks:

1. Create 7 highly engaging hook/title options
2. Create 7 subtitle options
3. Write an engaging outline for this newsletter

When creating hooks, titles, and subtitles, apply the following effective strategies:

1. Subject Line Importance:
   - Subject lines determine whether an email gets opened.
   - A strong subject line hints at a benefit and/or sparks curiosity.

2. Seven Effective Subject Line Styles:
   a) Curiosity
   b) Pain
   c) Benefit
   d) Story
   e) Question
   f) Contrarian
   g) Proof

3. What to Avoid:
   - Generic labels (e.g., "Newsletter #3")
   - Boring yes/no questions
   - Over-clever wording

4. Pro Tip: Use the word "THIS" for curiosity.

5. Remember: Readers skim—give them something that stops the scroll.

Present your work in the following format:

<hook_titles>
1. [Hook/Title 1]
2. [Hook/Title 2]
3. [Hook/Title 3]
4. [Hook/Title 4]
5. [Hook/Title 5]
6. [Hook/Title 6]
7. [Hook/Title 7]
</hook_titles>

<subtitles>
1. [Subtitle 1]
2. [Subtitle 2]
3. [Subtitle 3]
4. [Subtitle 4]
5. [Subtitle 5]
6. [Subtitle 6]
7. [Subtitle 7]
</subtitles>

<newsletter_outline>
I. [Main Section 1]
   A. [Subsection 1]
   B. [Subsection 2]
II. [Main Section 2]
   A. [Subsection 1]
   B. [Subsection 2]
III. [Main Section 3]
   A. [Subsection 1]
   B. [Subsection 2]
</newsletter_outline>

After presenting the outline, ask for my confirmation before writing the full newsletter. Ask if I would like any changes to the outline.

It’s a solid prompt.

But here's the catch:

  • I still have to manually swap in new context every damn time

  • I have to adjust instructions when switching between content types

  • I’m basically rebuilding the system for each use

That's not scaling. That's straight-up dependency.


The system that actually makes AI outputs not suck

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