I spent 6 months collecting and testing production-grade prompt templates. Here are the ones that actually work.
Why Most Prompt Templates Fail
Most prompts you find online are demo-quality. They work in a clean test case. They fall apart in production with real user input, edge cases, and messy data.
These templates are different. They're battle-tested.
Classification Template
Use when: categorizing text into predefined categories.
You are a [domain] classifier. Given input text, classify it as one of: [categories].
Rules:
- Return only the category name
- If uncertain, return "UNCERTAIN"
- Never invent new categories
Input: [user input]
Category:
JSON Extraction Template
Use when: pulling structured data from unstructured text.
Extract from the following text and return ONLY valid JSON matching this schema:
[schema]
Rules:
- Return ONLY JSON, no explanation
- If data is missing, use null
- If text doesnt contain the field, omit it
Text: [user input]
JSON:
Summarization Template
Use when: condensing long documents.
Summarize the following text in exactly 3 sentences.
Rules:
- First sentence: the main topic
- Second sentence: key findings or points
- Third sentence: most important takeaway
Text: [user input]
Summary:
Code Review Template
Use when: getting an LLM to review code.
Review this code for [purpose].
Rules:
- Be specific about issues found
- Rate severity: CRITICAL/WARNING/SUGGESTION
- Provide actionable fix for each issue
- If no issues, say "No issues found"
Code:
[code]
Review:
Error Explanation Template
Use when: explaining errors to non-technical users.
You are a technical writer. Translate this error message into plain English.
Rules:
- Explain what happened in 1-2 sentences
- Explain what the user should do in 1-2 sentences
- Be direct, not apologetic
Error: [error message]
Plain English:
Get All 47 Templates
I packaged all 47 production prompt templates into a template pack. Copy-paste into your project:
LLM Prompt Engineering Template Pack — £29
47 templates, organized by use case, with usage notes for each.
The Key Pattern
Good prompts have three things:
- Role — who the LLM is acting as
- Constraints — what it can and cannot do
- Output format — exactly what you want back
Most templates you find skip #2. That's why they fail in production.
The 47 templates in this pack all have explicit constraints. That's what makes them production-ready.
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