Advancing Your Product Career in an AI World

Advancing Your Product Career in an AI World

In 2013, Brian wrote his now legendary blog post, How to Become a Customer Acquisition Expert. In short, the post focuses on enhancing your skillsets by adopting a "T" shape approach.

In any role, such as product or marketing, it's crucial to have a broad understanding of key topics. This wide knowledge base helps you grasp the entire discipline, providing context, aiding in strategic comprehension, and linking the functional strategy to the company's overall strategy. It makes you a versatile player.

However, it's equally important to delve deeply into a specific topic. Aim to position yourself among the top 10% of professionals in a particular skill or topic within your field.

That framework became a core pillar of our Product Strategy program and has remained sound advice to this day…

Now with the rise of AI, does anything about this framework change? And is AI PM going to be a thing?

Well, we had a special edition of Unsolicited Feedback with Brian Balfour and Fareed Mosavat this week, and they discussed this very topic.

To save you some time, we’ve summarized the key takeaways below, but if you’d like to see the conversation for yourself, please watch it here!

And, for more Unsolicited Feedback, sign up for our mailing list here, and get ready for Season 2 on Feb 20! 🙂

How AI Is Affecting Your Product Career:

🔮 Future proofing your career has a 2-3 year horizon. 🔮

“I've had many conversations where people delve into AI futurist predictions, trying to anticipate what it's going to be like when the ‘AI takes over.’ For practical purposes, in managing your career, the longer the time horizon, the lower the probability that your predictions will be correct. This is not an effective way to manage your career and decide your next steps. It's more beneficial to narrow your focus to the next year or two, being open and willing to consistently change and evolve.” - Brian

💡 The key to future-proofing your career? Stay adaptable. 💡 The tech landscape is ever-evolving, and so should you.

🎯 We think the AI PM specialization will be important, at least for the next few years. 🎯

Top-Down and Bottom-Up are two different approaches in product management. In the Top-Down approach, we identify a customer problem and figure out a solution for it. With Bottom-Up, we start with what the technology can do and then decide how to use it. Lately, Top-Down product management has been dominant, but when new technological frontiers like AI emerge, the Bottom-Up approach gains importance.

For this reason, Brian predicts that AI Product Management will be prominent for at least the next few years. Why?

Creating products with AI 1) demands new skills and knowledge to solve problems because it requires understanding what AI is capable of and how it works, and 2) necessitates different approaches and development processes. For instance, traditional customer feedback on design prototypes doesn't work with AI products. The feedback you get is often contingent on what the AI produces for the customer.

🧠 Understanding how AI works is critical, but coding not so much. 🧠

Understanding AI technology is crucial, particularly to be able to build products Bottom-Up. You don't need to be a coding whiz, but grasping what AI can and can't do will help you leverage it effectively. And, the only way to do this is to tinker, play, and experiment.🔧

🦐 Small Teams do Big Things. 🦐

We need to rethink our career ladders, focusing on increasing complexity rather than the number of people we manage. The rise of AI will lead to smaller, more efficient teams, pushing PMs to focus more on strategic problem-solving and less on people management

🌶️ Middle managers are at risk. 🌶️

Roles are changing. Instead of focusing on project management, entry-level positions will now need to understand complex customer problems.

Middle management roles might disappear as smaller teams gain more capabilities. What can middle managers do in this situation? It is time to start branding yourself as a super IC (individual contributor).

📈 Focus on outcomes. 📈

The future of product management will be about managing complex problems. It's not just about using AI to automate tasks, but about leveraging AI to deliver better outcomes for customers.

"When I think about product management, a lot of it can feel like spinning your wheels. This isn't to say that it's not hard work or valuable, but tasks like writing user stories, entering things into Jira, prioritizing bugs, ensuring the right engineers are working on the right things at the right time can be time-consuming. Then there's the taste, the craft, the hard problems of determining whether this solves a customer problem or a business problem. Those things will be harder to abstract or replace, at least with the current state of AI tools." - Fareed

🚝 Right now, AI is still in Systems 1 Thinking, but that might change 🚝

Today, AI excels at immediate, type one thinking. For instance, if I ask you what's two times two, you'll instantly respond with four. This doesn't require actual mathematical calculations in your head or working through the steps of a problem.

However, if I ask you what's 132 times 84 divided by three, you'd need to sit down and think it through. This is where AI currently falls short, although it is improving rapidly.

You can view this as a spectrum from type one to type two thinking, with type two representing complex, strategic problems. Essentially, the more steps involved in strategic thinking, the less proficient AI currently is, which is where you can add value.

And, don’t miss Season 2 of Unsolicited Feedback, launching Feb 20!