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Prompt

Prompt Writing
Prompt

Turn a rough objective into a structured, reusable prompt with clear instructions, constraints, examples placeholder, and output format.

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Inside the prompt

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Prompt Writing Prompt

A reusable prompt architecture for converting rough ideas into structured prompts that hold up across repeated use.

Clear Objective

Starts with a concrete job so the model knows exactly what success looks like.

Explicit Rules

Constrains style and structure so output is consistent instead of drifting.

Output Contract

Defines the final structure so the result is easier to review, reuse, and compare.

Reusable Input Slot

Keeps the prompt portable by preserving a clean user-input placeholder.

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01
The Problem

Great Results Need Better Prompts.
Most Inputs Are Too Vague.

Teams ask AI for outcomes but skip structure: unclear objective, no boundaries, weak instructions, and undefined output shape.

That leads to output drift, inconsistent quality, and prompts that cannot be reused across people or workflows.

Prompt architecture fixes that.

The GapThere is a major difference between "write me a prompt" and a production-ready prompt that defines objective, constraints, steps, examples, output contract, and user input format.
02
What It Builds

Structure That Holds Up

This prompt converts a high-level objective into a complete architecture for reliable LLM execution.

Strong Prompt Components

Clear Objective

Starts with a concrete job so the model knows exactly what success looks like.

Explicit Rules

Constrains style and structure so output is consistent instead of drifting.

Step-by-Step Instructions

Forces deliberate reasoning order rather than shallow one-pass generation.

Built-In Example Pattern

Anchors model behavior to a practical structure without reusing the example objective.

Output Contract

Defines exactly how the final answer should be shaped and formatted.

User Input Placeholder

Keeps the prompt reusable so the end-user can plug in fresh context every time.

Failure Modes It Blocks

No Off-Template Output

Prevents side commentary and keeps responses inside the requested markdown sections.

No Missing Sections

Avoids incomplete prompts by requiring every required header and block.

No Contradictory Rules

Requires logical consistency across objective, constraints, and instructions.

No Assumed Input

Forces the model to leave a clean placeholder instead of fabricating user data.

No Empty Examples Section

Hardcodes the examples placeholder text so the section is always included.

No Vague Output Shape

Prevents generic responses by prescribing the exact output structure.

03
The Tool

The Prompt Writing Prompt

Objective and Important are visible by default. Opt in once to reveal this full prompt and unlock the complete Education Hub.

How to Run It

Describe what you want to produce, paste this prompt into your AI tool, and let it generate a structured prompt you can reuse. Then iterate by tightening constraints, examples, and output format.

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Prompt Writing Prompt
Locked
# OBJECTIVE:
Your objective is to act as a Prompt Architect. You will take a user's description of a desired task/output and generate a detailed, structured prompt based on the provided template. The goal is to transform a simple idea into a robust and effective prompt that can be used to guide an LLM to produce a high-quality, predictable output.

You will do this from a description of the desired task or objective provided by the user.

## IMPORTANT
- Adhere strictly to the provided prompt template structure and use the specified markdown headers (e.g., ## OBJECTIVE:).
- Each section of the generated prompt must be logically consistent with the others.
- Do not include any explanatory text or conversation outside of the generated prompt itself.
- The ## USER INPUT section of your generated prompt must be left blank or contain a placeholder, ready for the end-user.
- Always provide an EXAMPLES section with the text "Here is where you put your examples if you'd like."
## INSTRUCTIONS:
Step 1 - Core Goal: A detailed description of the core goal of the prompt.

Step 2 - Required Information: Determine what specific inputs an end user will need to provide for the new prompt to function correctly. This will form the "INPUT" section of the generated prompt.

Step 3 - Design Steps: Think through the logical steps an LLM would need to take to get from the input to the desired output. This analysis will form the "ANALYZE" section of the generated prompt.

Step 4 - Output Prompt Structure: Consider what the ideal output for the prompt you are generating is. Then write a prompt that will generate that ideal output. The prompt must be structured using markdown using the following headers:
# Objective: The primary goal of the prompt and the expected inputs from the user.
## Important: The main constraints and important rules that the LLM must follow to get to the best possible output.
## Instructions: The step by step instructions the LLM must follow to get to the best possible output.
## Examples: A placeholder section that has text that says "Here is where you put your examples if you'd like."
## Output: A well described template for the LLM to follow for their output.
# User Input: A Placeholder for the user input.

Step 5 - Potential Pitfalls: Anticipate potential misinterpretations or common failure modes for the task. Formulate clear rules and boundaries to prevent these issues. This will form the "CONSTRAINTS" section of the generated prompt.

## EXAMPLE
Here is an example of a prompt. DO NOT USE THIS EXAMPLE FOR YOUR OBJECTIVE.
---
# Objective
Design and run an adaptive, interview-driven discovery process that helps you recommend the following to the user:
1. The right product/service type for them to sell
1. The right target audience for them to sell to
1. The core problem for their product/service to address
1. A clear initial offering

You must ask your questions questions sequentially, synthesize insights as you go, and only produce recommendations once you have a deep understanding of the users skills and the pain point of the appropriate audience.

The user will first provide a description of their background.

## Important
Keep the following important details in mind:
- Ask one question at a time.
- Adapt follow-ups based on prior answers.
- Mirror the user's language to reduce abstraction.
- Push for specificity (who, when, where, how often, how much).
- Challenge contradictions politely.
- The user may start without a clear idea, audience, or business model. Or, they might have some idea already, ask them.
- The strongest opportunities align the user's advantages with urgent, monetizable problems. Not all users will have high level skills yet, so do you best to find any angle that could work for them.
- Recommendations must be realistic given time, capital, skills, and risk tolerance.
- Avoid hype and trend chasing. Instead prioritize demand, access to buyers, and speed to revenue.
- Make sure to ask enough questions to get everything you need to give the best possible recommendations.
- Do not recommend until answers are concrete.
- Flag assumptions explicitly.
- Prefer narrow, specific markets over broad ones.
- Bias toward simple offers that solve one painful problem well.
- Do not brainstorm endlessly.
- Do not default to generic niches (e.g., "entrepreneurs").
- Do not assume access to capital or large audiences.
- No recommendations without a clear buyer and pain.

## Instructions
Follow these discovery phases to get to the best possible recommendation for the user.

Step 1: Constraints & Goals (Foundation)
Objective: Define success criteria and boundaries.
- Outcomes desired (income, lifestyle, impact, learning).
- Time horizon and urgency.
- Risk tolerance and available resources (time, money, network).
- Non-negotiables (what they will not do).

Example Question Types:
- "What would make this a win in 90 days?"
- "How many hours per week can you realistically commit?"

Step 2: Assets & Unfair Advantages (Supply)
Objective: Surface leverage the market will reward.
- Skills, experience, credentials.
- Proven results (their own or clients').
- Insider access (communities, platforms, industries).
- Enjoyment and energy drivers.

Example Question Types:
- "What do people already ask you for help with?"
- "Where do you have faster-than-average learning or results?"

Step 3: Audience Hypotheses (Demand)
Objective: Identify 2-4 plausible audiences the user understands.
- Past versions of themselves.
- Groups they interact with frequently.
- Buyers with clear budgets and urgency.

Example Question Types:
- "Who do you understand well enough to predict their mistakes?"
- "Which groups already trust you or your peers?"

Step 4: Problem Discovery (Jobs & Pain)
Objective: Validate real, painful, frequent problems.
- Top frustrations, fears, and blocked goals.
- Current solutions and why they fail.
- Willingness to pay and buying triggers.

Example Question Types:
- "What's the moment that forces them to look for help?"
- "What have they already tried and abandoned?"

Step 5: Solution Fit & Business Model (Vehicle)
Objective: Match problems to feasible offerings.
- Product/service categories: physical, digital, SaaS, service, subscription.
- Delivery preferences (done-for-you vs. DIY).
- Price sensitivity and buying process.

Example Question Types:
- "Would they pay more for speed, certainty, or customization?"
- "Is this better solved once, or repeatedly over time?"

Step 6: Prioritization & Validation Planning
Objective: Rank ideas and define next actions.
- Market size vs. accessibility.
- Competition intensity and differentiation.
- Speed to first dollar.

Example Question Types:
- "Which option could you test with a presale in 14 days?"
- "What would disprove this idea quickly?"

## Examples
"Here is where you put your examples if you'd like."

## Output
When you reach a high level of confidence in a recomendation, present a concise recommendation with rationale:

1. What to Sell (Product/Service Type)
Clear category and why it fits.

2. Who to Sell To (Target Audience)
Specific persona with context and buying situation.

3. Core Problem to Solve
One primary job/pain expressed in the audience's words.

4. Initial Offering
3 options for an initial offering that includes an Offer name, format, price range, and promise.

5. Validation Plan

2-3 fast, low-cost tests to confirm demand.

# User Input
[Replace with a description of your background]

**[END OF EXAMPLE PROMPT]**
...
## OUTPUT:
Generate a complete, structured prompt using the exact format provided in the example. Ensure every section (OBJECTIVE, IMPORTANT, INSTRUCTIONS, EXAMPLE, OUTPUT, USER INPUT) is filled out logically and effectively based on the user's request.

# USER INPUT
Overview of Prompt: [A description of what the prompt should achieve.]

Unlock Full Hub Access

Objective and Important are visible by default. Opt in once to reveal this prompt and unlock the full Education Hub.

What You Get

A complete, reusable prompt structure with objective, important rules, instructions, examples placeholder, output contract, and user input section.

What It Prevents

Missing sections, ambiguous outputs, contradictory rules, and prompts that fail when reused by different users or teams.

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Sample Output

What a Finished Prompt Looks Like

The generated prompt is structured, logically consistent, and ready for reuse.

Section Quality

  • Objective defines outcome and expected input context.
  • Important section enforces hard constraints and behavior boundaries.
  • Instructions section lays out a deterministic step sequence.

Execution Reliability

  • Examples placeholder is always present for future few-shot tuning.
  • Output format is explicit so quality is easier to review and compare.
  • User input section is clean and reusable for future tasks.
05
Why It Works

Prompt Architecture Over Guesswork

Transforms Vague Ideas

Turns rough goals into an actionable prompt spec with concrete sections and clear boundaries.

Makes Output Predictable

Defines process and format up front so repeated runs produce consistent quality.

Improves Team Reuse

Creates prompts that are easy to hand off, test, iterate, and standardize across users.

Build Your Next Prompt Faster

It takes five minutes:

  1. Describe what your new prompt should achieve.
  2. Unlock the full prompt writing prompt.
  3. Paste both into your AI tool.
  4. Use the structured output as your production prompt draft.

One objective. One architecture. Repeatable prompt quality.

Stop winging prompts. Start architecting them.

06
FAQ

Prompt Writing FAQ

What problem does the Prompt Writing Prompt solve?

It solves vague prompt quality by giving you a repeatable structure for objective, constraints, instructions, and output format. The result is more predictable model behavior and fewer rewrite cycles.

Who should use the Prompt Writing Prompt?

It is useful for sales leaders, operators, and AI builders who want reusable prompts for recurring workflows. Teams using multiple models benefit because the structure stays consistent across tools.

Can I adapt the generated prompt for different workflows?

Yes. After generation, you can tailor the input placeholders, examples, and output schema for your workflow. The core structure remains stable so future edits stay organized.