Prompt Patterns That Work Across Any LLM (2025 Edition)

Although models differ in scale, training, and cost, one principle holds true: good prompts outperform bad ones. In 2025, the field of prompt engineering has matured beyond trial-and-error. Analysts and practitioners have identified repeatable “patterns”—prompt structures that reliably improve performance regardless of the model.

These patterns are not shortcuts. They are frameworks, much like templates in business writing. They reduce uncertainty, save time, and increase the odds of a useful output.

Why Prompt Patterns Matter

• Universality: They work across Claude, ChatGPT, Gemini, Mistral, and others.

• Efficiency: A reusable structure saves hours of rewriting.

• Scalability: Teams can standardise prompts for consistent results.

Think of them as recipes. Different chefs (models) may season differently, but the dish turns out well if the recipe is solid.

7 Prompt Patterns That Work Everywhere

1. Role + Task + Format

Assign the AI a role, define the task, and specify the output format.

• Example: “You are a business consultant. Write a SWOT analysis for OpenAI. Present as a 4-row table.”

2. Step-by-Step Reasoning (“Chain-of-Thought Lite”)

Encourage structured reasoning without overcomplicating.

• Example: “List your reasoning in numbered steps before giving the final answer.”

3. Few-Shot with Examples

Show two examples, then ask for a third.

• Example: “Here are two great cold email templates. Write a third in the same style.”

4. Constraints-First

Specify hard limits upfront.

• Example: “Summarise this report in exactly 150 words. No bullet points.”

5. Critic + Creator

Ask the AI to generate, then critique its own work.

• Example: “Draft a headline. Then list three weaknesses and improve it.”

6. Persona Simulation

Make the AI “think” as a different expert.

• Example: “Pretend you are Steve Jobs presenting the iPhone for the first time. Write the opening speech.”

7. Multi-Perspective Prompt

Force diversity of output.

• Example: “Explain the impact of AI regulation from the perspective of a CEO, a policymaker, and a consumer.”

Applying Patterns in Real Scenarios

• Marketing: Persona simulation can mimic customer voices.

• Education: Step-by-step reasoning helps students understand processes.

• Research: Constraints-first ensures concise abstracts.

• Business Strategy: Multi-perspective prompts surface blind spots.

The Limits of Patterns

Patterns provide scaffolding, not guarantees. Weak data, vague tasks, or unrealistic expectations still lead to poor results. As with any framework, human judgment remains critical.

Conclusion

In 2025, prompt patterns have become the building blocks of effective AI use. Whether writing code, summarising reports, or generating ideas, these seven patterns cut through randomness and create consistency.

The next step for beginners is simple: test them. Take one task you do every week—emails, reports, or presentations—and run it through at least three of these patterns. The improvement will speak for itself.