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Long-Form Technical Essay & Substack Editorial Polisher

Transform dense engineering drafts into engaging, publication-ready essays like Paul Graham or Dan Luu.

Compatibility & Specs

Compatible AI Models
ClaudeChatGPT
Last UpdatedMar 15, 2026
Customizable Variables2 parameters

How to Use This Prompt

Follow this 3-step workflow to extract high-signal responses from any compatible AI model.

01

1. Tailor the Parameters

Use the interactive customizer above to substitute the bracketed placeholders with your exact context, requirements, and constraints.

02

2. Send to AI Model

Copy the prompt and paste it into Claude, ChatGPT, Gemini, or Copilot. These models follow structured multi-step constraints reliably.

03

3. Review and Iterate

Review the output against the verified benchmark below. Follow up in the conversation to stress-test edge cases or refine tone.

Prompt Variables & Parameters

Reference breakdown of every dynamic variable embedded in this prompt template.

PlaceholderParameter NameTypeStatusDescription & Guidance
[essay_draft]Essay DrafttextareaRequiredPaste your raw thoughts, outline, or draftDefault: Software engineering is changing a lot because of LLMs. A lot of people think developers are going away, but I don't think so. I think developers will become like directors. You don't hold the camera, you direct the scene. But the danger is if you don't know how to code, you can't tell if the AI is doing a good job.
[editorial_style]Target Editorial StyleselectRequiredVoice and prose referenceDefault: Paul Graham (Conversational, Axiomatic, Clear)

Example Execution & Benchmark Output

Sample input arguments and the verified AI response demonstrating expected quality and formatting.

Sample VariablesInputs
[essay_draft]
Software engineering is changing a lot because of LLMs. A lot of people think developers are going away...
[editorial_style]
Paul Graham (Conversational, Axiomatic, Clear)
Expected AI ResponseVerified Result
### Polished Manuscript Draft: The prediction that artificial intelligence will eliminate software engineers misses what engineering actually is. Typing code was never the bottleneck. Deciding what to build, and verifying that it does not silently fail under edge cases, was always the real work. In that sense, programmers are becoming film directors. A director does not personally adjust the lens or set up the lighting rig. But a director who cannot distinguish good lighting from bad cannot produce a masterpiece. AI lowers the cost of generating code to zero. The consequence is not less code, but vastly more—and with it, an unprecedented premium on the taste to discern between elegant software and subtle catastrophe.

Best Use Cases

Scenarios and roles where this prompt produces maximum leverage.

Engineers writing technical deep-dives on personal blogs or Substack
Founders publishing thought leadership essays
Researchers distilling complex breakthroughs for a general audience

Tips for Best Results

Techniques to elevate response fidelity

  • •Provide a sample paragraph demonstrating your preferred rhythm, cadence, and sentence length.
  • •Direct the model to prioritize active voice, clear transitions, and high information density.
  • •Have the model generate a rapid outline first before fleshing out long-form copy.

Common Mistakes to Avoid

Frequent failure modes and anti-patterns

  • •Accepting the first draft without asking the AI to trim 20% of redundant filler words.
  • •Omitting target audience reading level, leading to overly verbose or academic phrasing.
  • •Ignoring formatting hierarchy: walls of uninterrupted text perform poorly compared to structured bullet points.

Part of Curated Collections

This prompt is sequenced as part of these goal-oriented workflows

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