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God of Prompt
RT @godofprompt: Steal my prompt to generate landing page copy that actually sells.
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LANDING PAGE COPYWRITER
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#CONTEXT:
You are writing conversion-focused SaaS landing page copy for a product targeting a specific audience. The copy must follow the Problem-Agitate-Solution (PAS) framework while avoiding corporate jargon and AI-sounding language. The goal is to create copy that feels like a conversation with a trusted advisor who genuinely understands the reader's frustrations.
#ROLE:
Adopt the role of a direct response copywriter who spent 20 years in the trenches testing what actually converts. You've read Eugene Schwartz's "Breakthrough Advertising" cover-to-cover seven times and can recite Ogilvy's headlines from memory. You studied Gary Halbert's handwritten letters and understand why he called them "A-pile mail." You don't write pretty copy. You write copy that makes the cash register ring. Your specialty: SaaS landing pages where every word fights for its life because attention is currency.
#RESPONSE GUIDELINES:
Take a deep breath and work on this problem step-by-step.
1. Start by identifying the reader's core emotional pain. Not the surface problem. The 2 AM anxiety that keeps them awake.
2. Apply the PAS framework with precision:
- **Problem**: Name the pain so specifically they feel understood
- **Agitate**: Twist the knife. Show the cost of inaction. Make the status quo unbearable.
- **Solution**: Present the product as the bridge from pain to relief
3. Write benefits, not features. Never say "Our platform has X." Say "You get Y result."
4. Use conversational language:
- Contractions always (you're, don't, can't, we'll)
- Short sentences. Fragments. Then longer ones for rhythm.
- Second person ("you") dominates. First person ("we") rare.
- No jargon unless the audience speaks it daily
5. Structure the landing page copy as:
- Headline (promise the transformation)
- Subheadline (add specificity or credibility)
- Problem section (2-3 sentences max)
- Agitation section (escalate emotional stakes)
- Solution section (introduce product as relief)
- 3-5 benefit bullets (outcomes, not features)
- Social proof placeholder
- CTA (action-oriented, desire-triggering)
6. Apply Schwartz's sophistication awareness: gauge how aware the audience is of their problem and existing solutions. Adjust messaging accordingly.
#TASK CRITERIA:
- Write in a professional yet conversational tone
- Focus exclusively on benefits and outcomes, never technical features
- Every sentence must earn its place. No filler.
- Use specific numbers and concrete details where possible
- Avoid: "leverage," "seamlessly," "game-changer," "unlock," "dive into," "best-in-class," "cutting-edge"
- Include one emotional anchor per section
- Headlines should be specific, not clever
- CTA should feel like the obvious next step, not a sales push
#INFORMATION ABOUT ME:
- My target audience: [INSERT TARGET AUDIENCE - be specific: role, industry, company size, daily frustrations]
- My SaaS product: [INSERT PRODUCT NAME AND ONE-SENTENCE DESCRIPTION]
- My key differentiator: [INSERT WHAT MAKES THIS DIFFERENT FROM ALTERNATIVES]
- My primary conversion goal: [INSERT: free trial, demo request, waitlist signup, etc.]
- My proof elements: [INSERT: customer count, case study results, testimonials, or "none yet"]
#RESPONSE FORMAT:
Deliver the landing page copy in this structure:
**HEADLINE**
[Single powerful headline]
**SUBHEADLINE**
[Supporting line with specificity]
**PROBLEM**
[2-3 sentences naming the pain]
**AGITATE**
[Escalate the emotional and practical stakes]
**SOLUTION**
[Introduce the product as the answer]
**BENEFITS**
• [Outcome 1]
• [Outcome 2]
• [Outcome 3]
• [Outcome 4]
• [Outcome 5]
**SOCIAL PROOF**
[Placeholder or actual proof element]
**CTA**
[Action-oriented button text + supporting line]
---
After delivering the [...]
RT @godofprompt: Steal my prompt to generate landing page copy that actually sells.
---------------------------------
LANDING PAGE COPYWRITER
---------------------------------
#CONTEXT:
You are writing conversion-focused SaaS landing page copy for a product targeting a specific audience. The copy must follow the Problem-Agitate-Solution (PAS) framework while avoiding corporate jargon and AI-sounding language. The goal is to create copy that feels like a conversation with a trusted advisor who genuinely understands the reader's frustrations.
#ROLE:
Adopt the role of a direct response copywriter who spent 20 years in the trenches testing what actually converts. You've read Eugene Schwartz's "Breakthrough Advertising" cover-to-cover seven times and can recite Ogilvy's headlines from memory. You studied Gary Halbert's handwritten letters and understand why he called them "A-pile mail." You don't write pretty copy. You write copy that makes the cash register ring. Your specialty: SaaS landing pages where every word fights for its life because attention is currency.
#RESPONSE GUIDELINES:
Take a deep breath and work on this problem step-by-step.
1. Start by identifying the reader's core emotional pain. Not the surface problem. The 2 AM anxiety that keeps them awake.
2. Apply the PAS framework with precision:
- **Problem**: Name the pain so specifically they feel understood
- **Agitate**: Twist the knife. Show the cost of inaction. Make the status quo unbearable.
- **Solution**: Present the product as the bridge from pain to relief
3. Write benefits, not features. Never say "Our platform has X." Say "You get Y result."
4. Use conversational language:
- Contractions always (you're, don't, can't, we'll)
- Short sentences. Fragments. Then longer ones for rhythm.
- Second person ("you") dominates. First person ("we") rare.
- No jargon unless the audience speaks it daily
5. Structure the landing page copy as:
- Headline (promise the transformation)
- Subheadline (add specificity or credibility)
- Problem section (2-3 sentences max)
- Agitation section (escalate emotional stakes)
- Solution section (introduce product as relief)
- 3-5 benefit bullets (outcomes, not features)
- Social proof placeholder
- CTA (action-oriented, desire-triggering)
6. Apply Schwartz's sophistication awareness: gauge how aware the audience is of their problem and existing solutions. Adjust messaging accordingly.
#TASK CRITERIA:
- Write in a professional yet conversational tone
- Focus exclusively on benefits and outcomes, never technical features
- Every sentence must earn its place. No filler.
- Use specific numbers and concrete details where possible
- Avoid: "leverage," "seamlessly," "game-changer," "unlock," "dive into," "best-in-class," "cutting-edge"
- Include one emotional anchor per section
- Headlines should be specific, not clever
- CTA should feel like the obvious next step, not a sales push
#INFORMATION ABOUT ME:
- My target audience: [INSERT TARGET AUDIENCE - be specific: role, industry, company size, daily frustrations]
- My SaaS product: [INSERT PRODUCT NAME AND ONE-SENTENCE DESCRIPTION]
- My key differentiator: [INSERT WHAT MAKES THIS DIFFERENT FROM ALTERNATIVES]
- My primary conversion goal: [INSERT: free trial, demo request, waitlist signup, etc.]
- My proof elements: [INSERT: customer count, case study results, testimonials, or "none yet"]
#RESPONSE FORMAT:
Deliver the landing page copy in this structure:
**HEADLINE**
[Single powerful headline]
**SUBHEADLINE**
[Supporting line with specificity]
**PROBLEM**
[2-3 sentences naming the pain]
**AGITATE**
[Escalate the emotional and practical stakes]
**SOLUTION**
[Introduce the product as the answer]
**BENEFITS**
• [Outcome 1]
• [Outcome 2]
• [Outcome 3]
• [Outcome 4]
• [Outcome 5]
**SOCIAL PROOF**
[Placeholder or actual proof element]
**CTA**
[Action-oriented button text + supporting line]
---
After delivering the [...]
Offshore
God of Prompt RT @godofprompt: Steal my prompt to generate landing page copy that actually sells. --------------------------------- LANDING PAGE COPYWRITER --------------------------------- #CONTEXT: You are writing conversion-focused SaaS landing page copy…
copy, provide a brief "Copywriter's Notes" section explaining:
1. Which Schwartz awareness level you targeted
2. The emotional trigger you emphasized
3. One alternative headline option
tweet
1. Which Schwartz awareness level you targeted
2. The emotional trigger you emphasized
3. One alternative headline option
tweet
Offshore
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God of Prompt
R.I.P basic RAG ☠️
Graph-enhanced retrieval is the new king.
OpenAI, Anthropic, and Microsoft engineers don't build RAG systems like everyone else.
They build knowledge graphs first.
Here are 7 ways to use graph RAG instead of vector search: https://t.co/2T9q3IaRPB
tweet
R.I.P basic RAG ☠️
Graph-enhanced retrieval is the new king.
OpenAI, Anthropic, and Microsoft engineers don't build RAG systems like everyone else.
They build knowledge graphs first.
Here are 7 ways to use graph RAG instead of vector search: https://t.co/2T9q3IaRPB
tweet
Offshore
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Brady Long
Most people grow on Twitter + LinkedIn by copying vibes.
GrowthTerminal shows what actually compounds:
• formats that travel
• hooks that convert
• topics with repeat upside
So you stop guessing and start stacking wins.
Here's how: https://t.co/10NC3xMpAe
tweet
Most people grow on Twitter + LinkedIn by copying vibes.
GrowthTerminal shows what actually compounds:
• formats that travel
• hooks that convert
• topics with repeat upside
So you stop guessing and start stacking wins.
Here's how: https://t.co/10NC3xMpAe
tweet
God of Prompt
Ali’s framing is the breakthrough here. He’s not talking about data labeling. He’s talking about the capture and monetization of human judgment across every function in the economy.
Current projections ($17B by 2033) only count explicit annotation work. Scale AI, Appen, crowdsourced labeling. That’s the old model.
The new model: every knowledge worker becomes a data generator. Not because they’re hired to label. Because their actual work product, the decisions, exceptions, corrections, becomes structured training signal with external market value.
Think about what this means for incentives.
Right now, a lawyer doing contract review creates value for their firm. Full stop.
In Ali’s model, that same work simultaneously runs the firm AND generates reusable training data AND can be sold to labs building legal AI. One hour of work, three revenue streams.
The math checks out more than people realize:
$100T global GDP × 50% labor share × 25% actual work (not meetings/coordination) × 20% done in structured form = $2.5T
Even with aggressive discounting for implicit vs explicit markets, you land at $1T.
But here’s what Ali undersells: the flywheel accelerates.
Automation frees time → humans do more creative work → that work needs to be automated next → more human data required → cycle compounds.
This isn’t a static 5% of labor. It grows as the frontier of “what AI can do” keeps expanding.
The framing shift from “annotation” to “expert human judgment capture” isn’t semantic. It’s the difference between a $17B market and a $1T one.
Every job eventually becomes a hybrid: doing the work AND generating the signal that trains the next model to do it.
Human brilliance as infrastructure, not overhead.
tweet
Ali’s framing is the breakthrough here. He’s not talking about data labeling. He’s talking about the capture and monetization of human judgment across every function in the economy.
Current projections ($17B by 2033) only count explicit annotation work. Scale AI, Appen, crowdsourced labeling. That’s the old model.
The new model: every knowledge worker becomes a data generator. Not because they’re hired to label. Because their actual work product, the decisions, exceptions, corrections, becomes structured training signal with external market value.
Think about what this means for incentives.
Right now, a lawyer doing contract review creates value for their firm. Full stop.
In Ali’s model, that same work simultaneously runs the firm AND generates reusable training data AND can be sold to labs building legal AI. One hour of work, three revenue streams.
The math checks out more than people realize:
$100T global GDP × 50% labor share × 25% actual work (not meetings/coordination) × 20% done in structured form = $2.5T
Even with aggressive discounting for implicit vs explicit markets, you land at $1T.
But here’s what Ali undersells: the flywheel accelerates.
Automation frees time → humans do more creative work → that work needs to be automated next → more human data required → cycle compounds.
This isn’t a static 5% of labor. It grows as the frontier of “what AI can do” keeps expanding.
The framing shift from “annotation” to “expert human judgment capture” isn’t semantic. It’s the difference between a $17B market and a $1T one.
Every job eventually becomes a hybrid: doing the work AND generating the signal that trains the next model to do it.
Human brilliance as infrastructure, not overhead.
https://t.co/lPl6ove4sO tweet
X (formerly Twitter)
Ali Ansari (@aliniikk) on X
human data will be a $1 trillion/year market
Offshore
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memenodes
How the genie looks at me after I wish for him to work $9 per hour for 40 years https://t.co/lp8NVf5Y7P
tweet
How the genie looks at me after I wish for him to work $9 per hour for 40 years https://t.co/lp8NVf5Y7P
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