AI for Product Managers: Your New Junior PM?

You know, it’s funny. Just the other day I was wrestling with a particularly thorny product problem – you know the kind, where the market research is a mess, the user feedback is contradictory, and you’re starting to feel like you’re wandering in the wilderness. Then, it hit me. What if I had a little help? Not another PM on the team (though that would be nice!), but something… different. That’s when I started experimenting with AI.

Now, before you start picturing robots taking over your job (and my job!), let me clarify: AI isn’t here to replace us. Instead, think of it as your new junior PM, a super-smart assistant who can help you with some of the heavy lifting. It’s like having a tireless intern who can crunch data, generate ideas, and even write decent documentation. Who wouldn’t want that?

But just like any junior PM, you can’t just let AI run wild. You need to guide it, give it direction, and always, always double-check its work. Remember, AI is a tool, and like any tool, it’s only as good as the person using it.

The AI-Powered PM Workflow

So, how can you actually use AI in your day-to-day work as a PM? Here’s a simple workflow I’ve been playing around with:

Research: Start by asking your AI assistant questions about the topic you’re working on. I’ve been using a RAG-based AI model for this, which can access and process information from a variety of sources. It’s like having a research team at your fingertips! Need to know the latest trends in mobile gaming? Just ask. Curious about the competitive landscape for productivity apps? Your AI assistant has you covered.

Assumptions: Next, have your AI assistant help you create a list of assumptions about your product or market. This can be a great way to identify potential risks and opportunities. For example, are you assuming that your target users are tech-savvy millennials? Or that your product will be primarily used on mobile devices? Get those assumptions out in the open and start testing them.

Problem Statement: Once you’ve validated your assumptions (more on that later!), use your AI assistant to analyze the results and draft a problem statement. This will help you focus your efforts and ensure you’re solving the right problem. A clear problem statement is like a compass, guiding you towards the right solution.

Competitors: Now it’s time to see what else is out there. Ask your AI assistant to find competitors or examples of solutions for the problem you’re tackling. This can give you valuable insights into what works, what doesn’t, and where the opportunities lie.

Feature Analysis: Have your AI assistant analyze the competitor list and identify the features they offer. This can help you identify gaps in the market and opportunities for differentiation. What are your competitors doing well? Where are they falling short? This information can be gold for your product strategy.

MVP Scoping: Finally, use your AI assistant to help you scope out an MVP. Based on the features you’ve identified and the probability of them solving the problem, your AI assistant can help you prioritize and create a roadmap for your product. Think of it as your AI assistant helping you build the leanest, meanest version of your product possible.

A Word of Caution (and Excitement!)

Now, before you run off and start delegating everything to your AI assistant, remember: AI is a powerful tool, but it’s not a magic bullet. It’s still important to use your own judgment, experience, and intuition. Think of AI as your co-pilot, not your autopilot.

But here’s the exciting part: AI has the potential to free us from some of the more tedious and time-consuming tasks, allowing us to focus on what we do best: understanding our users, crafting amazing products, and bringing those products to market.