Prompt Engineering Patterns That Scale to Production

Stop hardcoding strings. Start engineering.

The String Concatenation Nightmare

Junior approach:

prompt = Hello  + user_name + , answer this:  + question

This is unreadable, untestable, and prone to injection attacks.

Pattern 1: Prompt Templates (Jinja2/Mustache)

Treat prompts like HTML templates.

You are a helpful assistant for {{ company_name }}.
Context:
{% for doc in documents %}
- {{ doc.content }}
{% endfor %}
Question: {{ question }}

This separates logic from content.

Pattern 2: Chain of Thought (CoT) Enforcement

Dont just hope the model reasons. Force it.

• Prompt: Think step by step. First, list the assumptions. Second, calculate the total. Third, output the final answer.
• Why: Improves math and logic performance by 30%+.

Pattern 3: Few-Shot Prompting (The Golden Rule)

The single best way to improve performance is to provide examples.

• Bad: Extract the entities.
• Good: Extract the entities. Example 1: Bob went to Paris - {Person: Bob, Location: Paris}. Now do: Jane went to Tokyo.

Pattern 4: Version Control

Prompts are code. They should be in Git.
prompts/sales_agent/v1.txt
prompts/sales_agent/v2.txt
Never change a prompt in production without a Pull Request.

Conclusion

Prompts are the source code of the AI. Treat them with the same respect you treat your Python or TypeScript.

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*Next: [Structured Outputs](/blog/structured-outputs-json-mode)*

How This Article Was Made

This article is a live example of the AI-enabled content workflow we build for clients.

Stage	Who	What
Research	Claude Opus 4.5	Analyzed current industry data, studies, and expert sources
Curation	Tom Hundley	Directed focus, validated relevance, ensured strategic alignment
Drafting	Claude Opus 4.5	Synthesized research into structured narrative
Fact-Check	Human + AI	All statistics linked to original sources below
Editorial	Tom Hundley	Final review for accuracy, tone, and value

The result: Research-backed content in a fraction of the time, with full transparency and human accountability.

Why We Work This Way

Were an AI enablement company. It would be strange if we didnt use AI to create content. But more importantly, we believe the future of professional content isnt AI vs. Human—its AI amplifying human expertise.

Every article we publish demonstrates the same workflow we help clients implement: AI handles the heavy lifting of research and drafting, humans provide direction, judgment, and accountability.

Want to build this capability for your team? Lets talk about AI enablement →

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