How product managers can use AI to work more efficiently
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TLDR
- AI is changing how we manage products and come up with new ideas, giving us new tools to work faster and be more creative.
- AI can help in many parts of making a product, from research to writing product plans and documents.
- To use AI well in product management, we need to know how to ask it questions (called prompt engineering), balance AI ideas with human know-how, and always double-check AI’s work.
- AI can make tasks faster, but it’s important to keep people involved and use AI to help, not replace, our usual ways of working.
- The future of product management will involve using more AI tools, like advanced language models and creating fake data for testing. We’ll need to keep learning as AI keeps getting better.
Introduction
In this episode, I’m interviewing Brian Collard, an expert in managing big projects and plans for global companies. Brian has been working for 15 years in different industries like finance, healthcare, and technology. We’re talking about how artificial intelligence (AI) is changing the way we manage products and come up with new ideas.
As people who manage products, lead teams, or come up with new ideas, we’re right in the middle of this AI revolution. We need to figure out how to use AI to make products that customers will love, while also dealing with all the new things AI brings to the table.
Before using AI, check your organization’s policy to make sure you’re in compliance. Be careful when using AI, especially with sensitive information.
AI in the Product Development Lifecycle
Discovery and Research Phase
Large language models can come up with ideas, but always keep humans in the loop. AI is a great way to augment the discovery process, but it won’t completely replace traditional research methods.
Brian recommends a three-step formula for prompting AI:
- Input: provide context
- Create scaffolding: understand typical processes that industry experts use
- Output: the output from the AI is now more valuable to you because you have documented the inputs and processes that created it
Creating Product Briefs with AI
One area where Brian sees significant promise is in the creation of product briefs. He shares that product managers are reporting efficiency gains of around 50% when using AI to assist in drafting these important documents. AI can help with:
- Rapid generation of initial draft product briefs
- Assistance in structuring briefs with key components
- Increased output and iterations
Brian notes that while AI can significantly speed up the process of creating product briefs, these documents often require nuanced understanding and strategic thinking. He advises using AI as a starting point, but always reviewing and refining the output to ensure it aligns with product strategy and organizational goals.
Artificial Intelligence and Hallucinations
Large language models can hallucinate, or make up information, such as links that do not exist. Brian recommends the tool Perplexity.ai, which removes hallucinations and brings in real-time information. He also recommends that we trust but verify when using information from AI.
Mastering Prompt Engineering for Product Managers
Brian gives some tips for talking with AI tools, or prompt engineering.
The Importance of Context
Brian explains that when we use AI tools, we need to give them clear background information. This helps the AI understand exactly what we’re working on and what we need.
Chain of Thought Prompts
Brian introduces the idea of chain of thought prompts. This means guiding the AI through a series of steps. It’s especially useful for complex tasks.
For example, “Here are three product ideas. Based on these ideas, please give me another one.”
Logical Reasoning Prompts
Encourage AI to use logical reasoning by giving it examples or frameworks. This can be particularly helpful for tasks like figuring out market size or making financial projections.
For example, “Given a particular market size and capture rate, how many sales do I need to break even?”
You can get similar results by including the words, “think step by step,” in your prompt.
Tips for Prompts
You can ask the AI model, “How would you improve this prompt?”
The AI tends to remember the beginning and end of a prompt. Instead of providing one long prompt, provide a series of short prompts, asking the AI to refine its response each time.
For example, begin with an outline of a product brief, and then ask the AI to fill in the sections. This also helps make your work more defensible in front of an executive, because you can explain how you created it.
Brian recommends the tool Superpower GPT, which allows you to run a series of prompts (a prompt chain) all at once.
Market Research Techniques
Brian explains how AI is revolutionizing market research, offering new ways to gather and analyze data. He mentions using tools like Perplexity.ai for real-time information gathering and fact-checking.
Persona Generation
AI can help create more detailed and data-driven user personas, including the generation of synthetic personas based on market trends and user data.
Needs and Requirements Documentation
AI can assist in documenting and organizing product requirements, including automated extraction of requirements from various sources.
SWOT and PESTLE Analysis
AI tools can enhance traditional strategic analysis frameworks like SWOT and PESTLE analysis.
AI as a Complement to Traditional Methods
Brian emphasizes the importance of viewing AI as a complement to, rather than a replacement for, traditional product management methods. He discusses the use of synthetic data and personas, and the importance of balancing AI insights with direct customer interaction.
Best Practices for Using AI in Product Management
Brian shares several best practices for integrating AI into product management workflows:
- Treat AI as a collaborative tool
- Break down complex prompts
- Leverage advanced AI tools
- Adopt a “trust and verify” model
Conclusion
In this episode, we’ve explored with Brian Collard how bringing AI into product management offers significant opportunities for innovation and efficiency. Brian reminds us that AI is a tool, not a replacement for human expertise. The most successful product managers will be those who can effectively combine AI-driven insights with their own experience, intuition, and strategic thinking.
Useful links:
Innovation Quote
“I haven’t failed. I just found 10,000 ways the product hasn’t work yet.” – based on a quote from Thomas Edison
Application Questions
- How can you bring AI tools into your current product development process to work more efficiently without losing quality?
- Which specific areas of your product management work could benefit most from AI help, and what challenges might you face when starting to use AI in these areas?
- How can you make sure you keep a good balance between AI-driven insights and traditional customer research in your product strategy?
- What skills and training might your product management team need to effectively use AI tools in your work?
- How can you set up a system to double-check AI-generated insights that fits with how your organization makes decisions?
Bio
Brian Collard has 15 years of experience in managing strategic project portfolios for global organizations. He has proven success across multiple industries including finance, healthcare, and technology. Brian holds a degree in engineering and an advanced business degree and is the co-founder of the St. Louis PDMA chapter.
Thanks!
Thank you for taking the journey to product mastery and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.
