Prompt Engineering: The next PM superpower

As Product Managers (PMs), we often juggle a dozen tasks at once—prioritizing features, aligning stakeholders, gathering user insights, and communicating across teams. Imagine having an intelligent assistant by your side that can summarize reports, brainstorm features, generate user stories, or even help with competitive analysis—within minutes. That’s the power of using Large Language Models (LLMs) like ChatGPT. But to truly harness this power, one critical skill is required: prompt engineering.

Let’s explore what prompt engineering is, why it matters, and how it can be a game-changer for every Product Manager.

What is Prompt Engineering?

Prompt engineering is the process of crafting effective prompts—basically, instructions—for AI models like ChatGPT, Gemini, or Claude to get the outcome you desire. Think of it as giving step-by-step instructions to a new baker to bake a cake. If you just say, “Bake a cake,” you’ll likely get something vague. But if you specify the flavor, layers, frosting, and baking time, the results will be far more accurate.

In the world of AI, a prompt is not just a question or command. It's a combination of context, clarity, and direction that guides the AI to produce helpful and actionable results.

Why Is Prompt Engineering So Important?

The quality of your output from an AI tool depends directly on the quality of your prompt. A vague prompt often leads to a generic or incomplete response, while a specific and well-structured prompt generates focused and insightful answers.

Let’s look at an example:

• Less Effective Prompt: “What are the events happening in San Francisco?”

• More Effective Prompt: “What are the major public events or festivals happening in San Francisco during the weekend of March 29th–30th, 2025?”

The second prompt gives a clearer time frame and context, helping the AI provide a more accurate and relevant response.

For PMs, where every insight and minute matters, this level of specificity can save hours of research or content creation.

Best Practices of Prompt Engineering

There are four key principles to crafting effective prompts: Clarity, Context, Precision, and Persona.

1. Clarity

Make your prompt easy to understand. Avoid jargon, complex phrases, or sentence structures.

Example:

Instead of "Help with product stuff for next week.”

Try: “Create a bulleted list of key product development tasks to be completed for the mobile app release next week.”

2. Context

LLMs work best when they understand the background. Provide relevant information to help generate better outputs.

Example: Summarize this user feedback for our fitness tracking app. Users are mostly concerned about inaccurate step counts and lack of integration with smartwatches.”

3. Precision

Specify the format, tone, and expected outcome.

Example: Write a professional email to the design team summarizing feedback from the latest user testing session. Use a friendly and collaborative tone.”

4. Persona

Define the role you want the AI to play. This helps in tailoring the response.

Example: As a senior UX researcher, write a summary of the top 3 usability issues found during our beta testing phase.”

How Is Prompt Engineering Useful to a Product Manager?

Now let's see how a PM can use prompt engineering in their day-to-day work. Here are a few real-world examples:

1. Market Research and Competitive Analysis

Prompt: “Act as a product analyst. Compare the features of our food delivery app with DoorDash and Uber UberEats, focusing on user experience, loyalty programs, and delivery speed.”

You can use the results to identify gaps, validate your roadmap, or prepare for stakeholder meetings.

2. Creating User Stories and Acceptance Criteria

Prompt: Write three user stories and corresponding acceptance criteria for a new feature that allows users to schedule video calls in our HealthCare app.”

This can be a starting point before refining with your engineering team.

3. Crafting Clear Communications

Prompt: “Write a concise email message to the UAT (User Acceptance Testing) team informing them that the new login feature will be delayed by two days due to Quality Assurance (QA) testing issues.”

It saves time and ensures your message is well-crafted.

4. Brainstorming New Features

Prompt: As a product innovation coach, suggest five unique features that could improve user retention for a language learning app. ”You can get fresh perspectives and accelerate ideation sessions.

5. Summarizing Long Documents

Prompt: Summarize the key insights from this 10-page customer feedback document into a bulleted list of pain points and opportunities.”

Imagine how much time this could save before a sprint planning meeting.

6. Writing Product Requirement Document (PRD) or Feature Specs

Prompt: Create a draft Product Requirements Document for a mobile feature that tracks users’ carbon footprint based on their travel data. Use a formal structure: overview, goals, features, metrics, and risks.”

This can be used as a draft, and further content can be built upon it.

Examples of Prompt Engineering Tools

Langchain , PromptBase, Helicone.ai , Dust

You can also experiment with prompts using: ChatGpt, IBM Watsonx.ai

Conclusion

Prompt engineering is not just a technical skill—it’s a strategic advantage for Product Managers. In a world where time is limited and expectations are high, using AI tools can improve productivity. But to unlock their full potential, you need to speak their language, and that begins with writing great prompts.

Just like you wouldn’t walk into a stakeholder meeting without a plan, don’t approach AI without a clear prompt. Mastering this skill can amplify your productivity, enhance decision-making, and help you focus on what truly matters—building great products. So, the next time you’re staring at a blank page or racing against a deadline, try crafting a smart prompt.