The Future of Product Management

How AI is Transforming Product Management and Teams

This blog post is based on articles and videos from Lenny Rachitsky and Claire Vo, who inspired me and taught me much about the Product discipline. These thoughts are the result of their teachings and based on their work.

Product management is undergoing a revolution. AI is no longer a buzzword or a far-off promise, it’s here, reshaping our work. This transformation isn’t just an operational shift, it’s a strategic need. As Product Leaders, CEOs and Founders, we all know that a great Product is not about solving today’s problems. It’s about envisioning what customers will need in 3, 5, or even 10 years, and building the foundation for that future. This applies not only to the Product but also to you, the company and the teams creating it. So to strive in this new environment we need to ask ourselves, are we and our teams getting equipped for tomorrow’s challenges? Are we getting ready to thrive in a decade shaped by exponential technological change? Individuals, teams and companies that will succeed tomorrow are those whose leaders are enabling them to adapt and innovate, but most of all coaching them in that direction.

Reinventing the Process

As Claire Vo brilliantly summarized in her talk on “Lenny & Friends Summit 2024,” product development is a time-intensive and complex endeavour. As Product Managers, we dedicate weeks to crafting, revising, and refining product strategies that align with our company’s vision, customer needs, competitor analysis and market trends. Translating these strategies into clear, actionable plans requires significant effort—distilling input from stakeholders, synthesizing user research, and prioritizing a deluge of ideas and feedback into a cohesive strategy to then create some Product Requirement Document (PRD). From there, we spend additional time breaking down requirements into bite-sized tasks, meticulously organizing them into tools like Trello or Jira for effective tracking and team alignment. But even with a strong roadmap in hand, progress is often hampered by bottlenecks in the design and engineering phases, even for the smallest prototypes or proofs of concept. We frequently encounter delays as we wait for wireframes or prototypes from design teams, essential deliverables that shape the early stages of testing and iteration.

Manually analyzing and prioritizing all this information is no small task, and it often feels like a race against time to ensure that our decisions are informed by the most critical insights.

AI transformed this process. Nowadays, you can dump your ideas and context on any LLM to outline the core of your product strategy, and in under an hour of focused effort, you can refine the output of the LLM into a polished strategy and roadmap. If you’re working on a product with historical data and real customers or if you’re interviewing your first leads, you can quickly harvest insights with AI, effortlessly integrating those into your Product Strategy and Roadmap, freeing you from hours of manual analysis. More than that you can easily consolidate information from tools like Intercom (with customer support queries) and Apple Store and Google Play Store (with review). You can generate functional prototypes with top-notch UX/UI in a couple of hours using tools like V0 and Cursor, ready to be shared for feedback, eliminating weeks-long iteration periods. This is a new reality with faster, and data-driven progress.

As you start learning to create prompts, feeding the models the relevant inputs such as your vision, data, customer insights, etc, you will power up the utility of the LLM.

Literally what once took us weeks to do, can now be taken care of in less than a day of work.

Think about this: If AI can do this now, what will it achieve in a few months with improved models, better agents, and richer data? The speed and quality improvements are exponential.

The AI Power up

The product teams of the future will look vastly different. To prepare for this I love to think about three mental models shared by Claire:

1. Automate: yourself as much as possible to speed up your work. AI is powerful enough to handle repetitive tasks with unmatched efficiency. From drafting documents to analysing customer feedback, automation will allow you to focus on strategic work.
2. Learn: expand your skills. AI tools are a gateway to skill up you and your team. You might not have a developer, or a designer free to help you create a proof of concept, or you might not have a data analyst to do some queries to your database, but you can use AI to do the work yourself. Tools like V0 allow you to quickly create beautiful functional prototypes, Cursor allows you to create a backend without coding, and The Wren allows you to query an SQL database effortlessly. What is your excuse?
3. Leverage: Great leaders build not just their own skills but also their teams and company. Teach your team to use AI effectively, nurture the habit of discovering new things and sharing, and a culture of reinforcing experimentation with AI, give the example yourself.

Why is this critical, you ask?

Right now we have a reality with small Product Teams, with a few engineers, a UX/UI specialist, and in very few cases a data analyst. As we progress I believe this will change dramatically, the nature of teams will evolve into a dynamic blend of highly independent, focused humans and AI agents, each with distinct capabilities and limitations. For Product Leaders, this shift demands a recalibration of traditional management approaches to account for the unique strengths and constraints of both humans and AI Agents. Understanding the cost of opportunity becomes paramount—PMs must evaluate where human creativity, empathy, and intuition can deliver unparalleled strategic value while leveraging AI for its unmatched speed, scalability, and precision in data processing and routine tasks. Decisions about resource allocation, task delegation, and prioritisation will need to factor in the adaptability and evolving capabilities of AI systems and humans.

Product Leaders will need to ensure that Humans and AI agents complement each other rather than stifle innovation.

Communication strategies will also shift, as PMs craft workflows where human team members and AI agents collaborate seamlessly—whether through enriched interfaces or enhanced decision support tools. Agile, Waterfall and SCRUM will probably crumble in this new unparallel reality where the paradigm is completely changing. Embracing this hybrid workforce and thriving in this new landscape will require a relentless focus on adaptability, continuous upskilling, and experimentation. To maximize strategic impact, PMs must become fluent in leveraging AI as a core component of their teams, consistently iterating and optimizing how tasks are distributed to meet both short-term outcomes and long-term vision.

As you probably are already suspecting, adding to this complexity is the evolving role of PMs themselves. As AI tools increasingly enable high-speed prototyping, coding, and design, Product Managers are no longer just facilitators or strategists; they need to become highly valuable individual contributors. With AI-powered tools levelling the playing field, PMs are expected to “get their hands dirty” by directly engaging in tasks traditionally reserved for designers, developers, and data analysts. And the other way around is also true! Writing code, designing user flows, and deploying initial iterations will become integral parts of the PM supported by an AI toolkit. AI will empower individuals to execute at speed and scale, and agents will free them for the most strategic bits, where I believe creativity, empathy and human intuition will play critical roles.

What to Avoid

While the potential is enormous, AI is not without its pitfalls. As you embrace this new paradigm, there are several traps that we need to avoid:

• Minimal usage: Don’t get comfortable with minimal use. Use AI for more than ideation—it can create near-final outputs with minimal refinement.
• Stagnation: Don’t rely on today’s tools as a crutch. Stay ahead by continuously exploring the next generation of AI capabilities. Stay ahead, think about how you want your team to operate in a 10-year interval and iterate on that as you research.
• Overlooking Human Insight: AI can accelerate processes, but it cannot replace your vision, creativity, empathy or intuition. Balance automation with your inputs and learn.

Embrace the Evolution

The era of AI-driven product management is not a distant horizon—it’s here. For Product Leaders, CEOs and Founders, this is an unparalleled opportunity to reimagine not just your product but the very fabric of your teams. The question isn’t whether AI will transform your product discipline—it’s whether you’ll seize this transformation to lead your company into the future. By adopting AI now, you’re not just staying competitive, you’re building the foundation for sustained innovation and success.