Unlocking the Power of Prompt Engineering in Product Management

We’re living in a technological wild west. Fears of people losing jobs, new AI innovations happening on a daily basis… It’s more important now than ever to stay ahead of the curve and apply this tech in your workflow so that you don’t get left behind.

What is prompt engineering?

Prompt engineering is the fine art of designing and refining prompts to extract the most value from AI models like GPT-4. This practice is gaining a ton of buzz in it’s ability to support in ideation, research, analysis, communication, and planning. Below are 10 of prompt engineering use cases for product management, complete with specific examples that'll have you stand out from your peers:

1. Feature brainstorming

Gain an edge when it comes to ideation for your next product roadmap. Prompt engineering can help, just ask the AI model to "List 10 innovative features for an e-learning platform targeting college students," and watch your feature list grow before your eyes.

1. Market research

Stay ahead of the game with AI-powered market research. Simply use a prompt like, "Summarize the top five competitors in the project management software market and their key features," and let the AI be your trusty sidekick in conquering the competition.

1. Customer feedback analysis

Turn customer feedback into a treasure trove of insights with prompt engineering. Use a prompt like, "From the given customer feedback data, identify the top five recurring issues and suggest potential solutions," and become the customer-whisperer you've always dreamed of being.

1. User persona creation

Get up close and personal with your target audience using AI-generated user personas. Give a prompt like, "Create a user persona for a 30-year-old female freelance graphic designer using a project management tool," and let AI be your matchmaker.

1. Writing user stories

In my opinion, one of the greatest benefits of ChatGPT is it’s ability to free up more time by tackling busy work such as user story creation. Here’s a sample prompt you can try: "Write a user story for a project manager who wants to track the progress of multiple projects at once,". Obviously, the quality of output is determined by how specific your prompt is to the feature you are building out, so make sure to do your due diligence.

1. Roadmap planning

Not only can AI support you with writing definitions for your stories, it can also be your sounding board for prioritication. I’d never trust ChatGPT without my own assessment, however the following prompt can save you a few hours by getting you started: "Prioritize the following features for a fitness app based on user demand and market trends: social sharing, workout tracking, and diet plans,".

1. Risk assessment

Prompt engineering can be your ace in the hole for identifying and assessing potential risks in your product development process. Try a prompt like, "Analyze potential risks and their impacts associated with integrating third-party APIs into our e-commerce platform,". This is obviously not a comprehensive prompt, but if you take the time to document the full scenario or paste your latest project tracking notes, you’d be surprised how helpful LLMs can be for this task.

1. Design critique

Give your UI/UX design a touch of brilliance with AI-powered feedback based on best practices and usability heuristics. Use a prompt like, "Evaluate the usability and visual design of this mobile app prototype for a meal planning service,”. Will this replace your UI team? No (thankfully). However, it can shorten turnaround time and take some effort off their plate in a pinch.

1. Product pitch

Weaving enthralling product pitches or elevator speeches is a breeze with AI assistance. Just use the prompt, "Write a 30-second elevator pitch for a new task management app targeting small business owners," and charm your target audience with your product's captivating story. As in the above examples, the more data you provide the AI tool, the more high quality the response will be.

1. Changelog and release notes

Last but not least, prompt engineering can help you generate optimized and informative changelog entries or release notes for product updates. Try a prompt like, "Write release notes for version 2.0 of our time-tracking software, highlighting the new features and improvements." You’ll need to feed the AI tool some documentation, but you’ll save hours of busy work.

All in all, these tactics for using AI models like ChatGPT are far from replacing Product Managers and other technology leaders. However, they are extremely valuable at reducing the time spent on tasks and can free up your time for more high impact work.

How else are you using LLMs like ChatGPT in your work systems? Comment below, I’d love to hear from you.