Productboard x Intercom: Product Craft When AI Changes the Stakes

Reflections from a San Francisco meetup with product leaders.

When product leaders gathered at Intercom’s office in January for an in-person meetup, the conversation quickly moved beyond tools or trends. Instead, it zeroed in on a more foundational question facing product teams in 2026. 

What does strong product judgment look like when AI makes it dramatically easier to ship?

The discussion featured Hubert Palan, Founder and CEO of Productboard, in conversation with Archana Agrawal, President of Intercom, building Fin. While both leaders have spent years building software companies before the rise of large language models, their exchange reflected how deeply the product role is being reshaped by AI.

The takeaway was not that AI diminishes product craft. It actually does the opposite. As the cost of building drops, the responsibility to choose well increases. Velocity stops being the differentiator. Judgment is.

Durable Differentiation Requires Context, Empathy & Clarity

Early in the conversation, Hubert framed product craft as a discipline rooted in empathy and clarity. The work starts long before a feature exists. It begins with understanding who a product is for, what they are struggling with, and why that struggle matters enough to warrant a solution.

AI does not remove this responsibility. In many ways, it exposes whether teams have done this work well. When it becomes possible to generate designs and even production-ready code in days, any lack of clarity shows up quickly. Teams either realize they are solving a real problem, or discover they have built something impressive that does not meaningfully help customers.

“I think that the reason why most products suck is not because we aren’t able to ship fast. Agents are helping us ship faster than ever before. It’s because we’re not shipping the right things.”

— Hubert Palan, Founder & CEO, Productboard

This shift surfaced repeatedly throughout the conversation. With speed at their fingertips, product teams are now constrained by how clearly they can define the problem they are trying to solve. Without that clarity, speed only accelerates misalignment.

Access to models and infrastructure is broadly shared. So, if everyone can build similar features, what actually sets products apart?

The answer: context.

Teams can achieve sustained differentiation if they understand a specific domain deeply enough to design workflows that lead to better decisions and better outcomes. To have such deep domain knowledge, you need empathy and clarity.

Hubert used building the world’s best car as an example. When asked to design one, many AI systems immediately produce a list of features. What they do not do is ask who the car is for, what job it needs to perform, or what trade-offs matter in that context. Without those questions, some features are ultimately meaningless. And the most important features remain unknown.

AI can generate outputs quickly, but it does not decide which inputs matter. Product leaders still need to define the audience, constraints, and intent behind what is being built. That framing is what allows AI to become useful rather than generic.

GTM Alignment Requires New Operating Models

The acceleration of product change also reshapes how go-to-market teams operate. Traditional enablement models assumed predictable roadmaps and infrequent launches. That rhythm breaks down when products evolve continuously.

“When teams are going through the change management of using these new products and interfaces, they are also reliant on deep partnership that the domain experts can give them on how adoption can help them completely change their businesses.”

— Archana Agrawal, President, Intercom, building Fin

Archana shared how Intercom has responded by organizing around smaller, more adaptive teams tied closely to specific product areas. Learning happens more asynchronously, and PMs are more directly involved in customer-facing conversations. Enablement becomes an ongoing loop rather than a scheduled event.

Productboard has seen similar dynamics. As product velocity increases, static decks and one-time trainings lose effectiveness. What remains stable are a few core anchors: who the product serves, how it is positioned, and what differentiates it. Everything else becomes more fluid.

Human connection plays an outsized role here. PMs spending time with sales and support teams, shared immersion moments, and hands-on collaboration help maintain alignment when documentation alone cannot keep up.

Creating Focus Time: Product’s New Secret Weapon 

Strategy has always required focus and trade-offs. What AI changes is not the need for those trade-offs, but the forces that used to enforce them.

Historically, teams were constrained by cost. Engineering cycles, headcount, and UI complexity made prioritization unavoidable. In an agentic world, many of those constraints recede. New use cases can be supported without new interfaces or heavy infrastructure. Ideas that once sat in the backlog as long-term bets suddenly feel within rach.

The problem shifts from scarcity to abundance. When almost anything feels possible, the hardest question becomes what should exist at all. Without clear boundaries, products risk losing their shape. Customers struggle to understand what a product is really for, even if it can technically do many things.

This is where focus becomes an active responsibility for product leaders. 

As agentic workflows make it easier to expand into adjacent use cases, maintaining a coherent mental model for users becomes a strategic discipline. Focus is no longer enforced by cost. It has to be enforced by intent, positioning, and clear decision-making. According to Hubert, this thinking directly informed how Productboard approached building Spark. Not as a way to do more, but as a way to help teams make better decisions about what matters. 

For product leaders and teams, that responsibility shows up in how close they stay to the work itself. In a landscape where tools and workflows change rapidly, the ability to absorb new information and adapt becomes non-negotiable. Hubert spoke about staying deeply involved, even as a CEO. Sitting with teams, reviewing early discovery, and understanding how AI systems are actually being used provides the context needed to guide decisions without micromanaging. With dedicated focus time, leadership shifts away from directing output toward shaping judgment.

At the organizational level, Productboard has tried to reinforce that focus by protecting time for exploration. Initiatives like Spark’d Fridays create space for teams to experiment and share what they learn. The goal is not experimentation for its own sake, but visible momentum that helps teams align on what is worth pursuing and what is not.

The Enduring Role of Product Judgment

AI is changing how products are built, but it is not changing why product judgment matters. If anything, it raises the stakes. 

When shipping becomes easier, every decision carries more weight. Products reflect the clarity or confusion of the teams that build them. Tools can accelerate execution, but they cannot replace taste, empathy, or responsibility for outcomes.

For product leaders navigating this era, the work looks less like chasing speed and more like sharpening intent. The teams that succeed will be the ones who stay grounded in customer reality, making deliberate trade-offs and using AI to amplify judgment rather than bypass it.

Watch the full conversation on Product Craft in the Age of AI.

And explore how Productboard Spark enables high-performing product teams.