We’ve always wished for more hours in our day.

In a way, AI has given us that. It took over repetitive tasks that used to clog our calendars: writing meeting notes, status updates, specifications, user stories. All in a matter of minutes, right at our fingertips.

So why does it feel like we’re still falling behind?

Because instead of using that time for all the goals we once dreamed of, we’re using it to chase more. More features. More releases. More pressure.

We can do a lot more, a lot faster. So we do. Without pausing to ask: “Just because we can, does it mean we should?”

The cost of moving fast

A few years ago, launching a product in a week sounded absurd.

Now, tools like Lovable allow anyone to create an app in a matter of hours.

But the longer timelines pre-AI weren’t just due to technical constraints. Yes, coding took longer, but that time also gave us space to do research, ask important questions (to ourselves and to users), and reflect on the vision we were trying to build.

AI collapsed that cycle, and with it, some of that careful work disappeared.

We’re seeing the side effects: irrelevant features, duplicated ideas, decisions made without reflection. Seasoned product leader Priyanka Jain has been sounding the alarm. She writes that GenAI is “accelerating product teams—often at the cost of depth, reflection, and critical thinking.” Her concern is that “we’re not just thinking less deeply. We’re building things that all look the same.”

In another piece, she describes how teams are adopting AI-generated specs without challenging assumptions, treating the first output as final. But, as she says, “Execution isn’t insight. Automation is not strategy.”

We’re creating more, faster. But that speed is impacting quality. A McKinsey study found that AI increased productivity by 40%, but made clear that human judgment, validation and oversight are still critical to maintaining quality. This is especially true for junior PMs who “gained productivity at the expense of quality”.

This scenario shows just how essential leadership has become, especially when it comes to guiding junior PMs who now have powerful tools at their fingertips, but still need support thinking critically, making tradeoffs, and building with purpose.

Automation is easy, true leadership is not

We used to define good leadership by output: how fast things moved, how many meetings you unblocked, how many releases your team had. But AI is doing a decent job at all those things now.

So what’s left?

The hard stuff. The human touch. The real work.

In a recent conversation on Lenny’s podcast, Mike Krieger, CPO of Anthropic, listed three core skills product leaders need today:

1. The ability to work with both AI and humans
2. Strategic thinking
3. The ability to open others’ eyes to product potential

What stands out in the list is how human these skills are. They’re not about efficiency, they’re about connection, perspective, and helping teams do their best thinking in an increasingly automated world.

In the same conversation, Krieger mentions that a majority (80-90%) of Claude’s code is written by Claude itself.

That’s not just automation, it’s a complete redefinition of how work gets done.

When AI handles the bulk of execution, the role of humans isn’t to supervise tasks. It’s to guide direction, ensure quality, and make strategic, ethical decisions.

That raises new questions for leaders:

• How do we structure teams around thinking, not just shipping?
• What does it mean to create a culture of depth in a world of speed?
• How do we invest our time in people when AI gives us more of it?

If we waste this moment chasing output, we’ll miss the opportunity in front of us: to become better leaders than we’ve ever had time to be.

The CLEAR framework for human-centered leadership

So what does leadership look like in this new environment?

In my effort to become a better leader and coach others to do the same, I developed five principles to guide us toward being the leaders our teams need right now.

I call it the CLEAR framework because it helps leaders provide clarity to their teams in a time when ambiguity is everywhere.

C – Coach with intention

In the AI era, your job as a leader is less about managing and more about coaching.

Information is widely available, so your team doesn’t depend on you for it. What they need is context to make sense of that information, clarity on the path forward, and care throughout.

Replace check-ins with growth conversations focused on how people think, not just what they do. Get curious about what energizes each team member and align that energy with the problems you’re solving.

When AI frees up your time, reinvesting it in building people (not products or processes) is the right thing to do. That’s how you transform your team into stronger systems thinkers and more confident decision-makers.

L – Lead with vision

Execution speed is no longer a differentiator. With AI, everyone is fast.

But move fast without a clear direction and… congratulations: you’re the first one to arrive at the wrong place.

At a time where “everything is possible”, it matters even more to think deeply and carefully about the vision guiding every decision. That’s the difference between movement and progress.

Once you’ve defined the vision, paint a picture of it to your team in a way that’s exciting, human, and grounded in user needs. That will allow them to build that vision with you, not for you.

As you go, remember to constantly communicate the “why” behind your work. A shared purpose is proven to drive long-term value and greater employee satisfaction.

E – Empower systems thinking

AI is great at performing individual tasks. But seeing the bigger picture? That’s on you.

AI can’t think in ecosystems or see the friction between teams, second-order consequences, and the ripple effects of a rushed decision.

But you can – with the help of systems thinking.

This holistic approach to decision-making allows you to see your work as part of a larger whole, understanding how teams, tools, and decisions interconnect. With AI accelerating the speed at which everything happens, it’s more likely than ever that something will break.

Systems thinking increases your chances of catching it on time.

These five tips, all detailed in my previous article, help you develop a systems thinking approach:

• Zoom in and out intentionally to avoid blind spots
• Map the system to visualize how teams, tools, and workflows connect
• Ask about ripple effects to anticipate consequences
• Design for learning to benefit from feedback loops
• Make collaboration part of the process to surface risks and align efforts

A – Amplify team potential

When every tool is intelligent, your edge as a human is emotional intelligence.

How well you connect with the people on your team. How you understand each individual’s potential. How you adapt your leadership style accordingly.

If AI can take over tasks, leaders should take care of people.

Psychologically safe teams feel empowered to experiment, challenge convention, and grow. Not only does this benefit people, it also benefits the organization: Google’s Project Aristotle shows that the highest performing teams are the ones with the greatest psychological safety.

Be a leader who shows up consistently with empathy and integrity. That behavior spreads and becomes culture.

R – Reclaim your role as the thinker

Smart as it can be, AI is like any other tool: the minute you can’t function without it, you’re doing something wrong.

AI does a great job at replacing humans in repetitive tasks and exploring broad solution spaces. But it can’t replace our judgment and critical thinking. The humans using the tool should still be the ones thinking deeply, creatively and ethically.

As a leader, make it a priority to help your team use AI wisely, in a way that empowers human creativity instead of replacing it. AI should be a partner, never a crutch.

What kind of leader do you want to be?

AI has given us time back, but it hasn’t told us what to do with it. That’s still our job.

We can choose to fill that space with more of the same, or we can pause to reflect and start leading with more clarity, empathy, and intention than we’ve ever had the chance to.

The best product leaders won’t be the fastest.

They’ll be the ones who know when to slow down, while helping everyone else do the same.