Productside Stories

Product and Design Collaboration: AI Can’t Judge

Featured Guest:

Jared Hall-Dugas | Lead UX Designer at National Grid
09/09/2026

Summary

In this episode of Productside Stories, Rina Alexin sits down with Jared Hall-Dugas, a design leader with over 20 years of experience across defense, entertainment, and utilities, to unpack where the lines between product and design are blurring, and where they are not.

Jared shares his non-traditional path from engineering into UX, explains how AI has unlocked the ability to turn ideas into interactive prototypes faster than ever, and explores what that speed actually costs when judgment leaves the room. He introduces the Pinocchio problem: AI-generated outputs that look polished, functional, and ready to ship, but have no electricity inside. Somebody in the room still has to say so, and that somebody needs domain expertise.

The conversation moves through role compression versus role amplification, the cultural work of moving a 50,000-person regulated organization toward AI adoption, the non-negotiable moment where design must be in the room, and what it looks like when product and design work arm-in-arm rather than stepping on each other’s territory.

Jared’s closing message is worth sitting with: designers are just as uncertain and just as scared about all of this as product managers are. That shared uncertainty is where the collaboration starts.

Key Takeaways

Judgment is the job now.

  • Jared can look at ten AI-generated prototypes and tell you which one will land and why. That call is not automatable yet. He argues judgment is the thing product and design both get paid for, and it is the last thing AI will be able to replace.

The output looks done. It isn’t.

  • Buttons that go nowhere. Data that doesn’t reconcile. Jared calls it a Pinocchio problem: the shop window looks ready to open, and there’s no electricity inside. Somebody in the room has to say so, and saying so requires real domain expertise.

Where cutting design out gets expensive.

  • Design belongs in the room from day one. If that’s impossible, Jared names the non-negotiable: the moment discovery converges into a defined solution. Skip it there and you’re rewriting later, for the same reason you need an engineer before you’ve committed to a feature that doesn’t exist in your stack.

Role compression isn’t the answer. Leverage is.

  • The early 2026 conversation around one person doing three jobs is shifting. Companies are starting to ask: how do I amplify the expertise I already have rather than compress it? One person magnified beats two people merged into one.

AI culture moves through pockets of proof.

  • Inside a large, regulated organization, Jared’s approach is zero-agenda monthly meetings where people can say “I don’t know what I’m doing”, and a steady stream of small wins shown to leadership that demonstrate what AI can actually produce. Fear turns to curiosity when people see it work.

Chapters

  • 00:00:00 – Introduction to Jared Hall-Dugas
  • 00:01:37 – Jared’s Non-Traditional Path into UX and Design
  • 00:02:53 – How AI Is Changing the Design Process
  • 00:04:08 – The Impact of AI on Product Requirements and Roles
  • 00:05:40 – What Should Remain Human in Design and Product Work
  • 00:06:51 – The Importance of Judgment and Expertise
  • 00:07:56 – Detecting Gaps and Ensuring Quality with AI
  • 00:09:34 – Balancing Speed and Quality in AI-Driven Work
  • 00:11:03 – The Evolving Nature of Roles and Team Dynamics
  • 00:13:22 – Creating Safe Spaces for AI Conversations in Organizations
  • 00:15:03 – The Shift from Fear to Opportunity with AI
  • 00:16:03 – The Societal and Organizational Adaptation to AI
  • 00:18:16 – Role Compression Versus Leverage of Expertise
  • 00:19:39 – Managing Security, QA, and Boundary Setting in AI Projects
  • 00:26:45 – The Importance of Early Involvement of Design in Product Development
  • 00:29:23 – Collaboration Between Product and Design in Early Stages
  • 00:35:34 – Building Strong Relationships Between Product Managers and Designers
  • 00:36:47 – Final Thoughts and How to Connect with Jared

Why Listen to This Episode?

In this thought-provoking episode, you’ll gain:

  • A sharper answer to “what part of my role is safe” that isn’t wishful thinking
  • A test for spotting AI output that looks finished and isn’t, before it reaches a VP
  • The one point in your process where a designer is non-negotiable, and the language to argue for it
  • A repeatable way to move AI culture inside a slow, regulated, 50,000-person organization

Jared’s closing line is the one worth sitting with: your designer is just as unsure about all of this as you are.

 

Introduction

Rina Alexin | 00:00:00 – 00:01:37

Hi everyone, and welcome to Productside Stories, the podcast where we reveal the very real and raw lessons learned from product leaders and thinkers all over the world. I’m your host, Rina Alexin, CEO of Productside.

Today I’m talking with Jared Hall-Dugas, a design leader with over 20 years of experience across defense, entertainment, and utilities. From building interactive worlds at Warner Bros. to designing mission-critical tools for the US Air Force, to now serving as lead UX designer at National Grid. He is also finding time to help individuals and organizations build real capability with AI through Strong with AI.

Today we’re going to talk about where the lines between product and design are blurring, and where they’re not. We’ll tackle what should stay human as AI takes on more of our grunt work, and how we can actually strengthen the relationship between product and design. I’m excited for today’s conversation. Welcome, Jared.

Jared Hall-Dugas | 00:01:06

Hey Rina, thank you so much. I really appreciate you giving me this time and I’m happy to chat.

Jared’s Non-Traditional Path into UX and Design

Rina Alexin | 00:01:37 – 00:02:53

Jared, I always love to bring different voices onto this podcast. Sometimes product managers get very familiar with their own world and their own challenges. It’s so important for us to hear from the people we collaborate with the most, and that means design. So I’d love to hear your story first. How did you end up choosing UX and design as your career path?

Jared Hall-Dugas | 00:01:47 – 00:02:53

For me it’s a non-traditional path. I started with an engineering degree, wanted to write code, and got into the video game world on small teams early on. I remember being with a group of engineers who would come in the next day having already done two weeks’ worth of work. They’d stayed up until three in the morning because they were completely absorbed by it. And I realized that wasn’t me. I did the work. I enjoyed the problem. But it wasn’t something I ate, slept, and drank.

I started gravitating toward design around that time. Going into video games, design became the thing that kept me up at night, whether it was a game mechanic, a quest, a UI challenge, figuring out how to arrive at the right solution for a problem. That passion for it has carried me through the last twenty years.

How AI Is Changing the Design Process

Rina Alexin | 00:02:45 – 00:02:53

And now with AI, I think it’s changing the game for a lot of us. How has it really changed design for you specifically?

Jared Hall-Dugas | 00:02:56 – 00:04:08

For me specifically, it comes down to access. I came from a non-traditional art background. I didn’t start with a UI artist degree. The barrier for me was always that next step: getting an idea out of my head and onto a screen in an interactive form. I’ve had the concepts, I’ve had the thoughts, I’ve known what I wanted to build. But actually constructing it was the friction.

AI has unlocked those doors. I can now go build the thing. I can try it. I can see what it actually looks like in an interactive form. Getting something from idea to working prototype is about ten times faster now. That shift has been enormous for how I work.

The Impact of AI on Product Requirements and Roles

Rina Alexin | 00:03:42 – 00:04:08

And that’s really the point we’re trying to get at today. You’re describing how you can take an idea out of your head and now actually have a tool to help you build and execute it. The same thing is happening in product, where product managers can now design with AI directly. So do you think AI is actually changing what product needs from design?

Jared Hall-Dugas | 00:04:15 – 00:05:40

Yeah, for sure. And I think that’s the scary part for all of us. Engineers are feeling it too. All three sides of the product triad are feeling that uncertainty around: is my role changing? I don’t know. What was my role for the last twenty years, and what is it going to be in six months, two years, five years? Nobody has any idea.

But it’s also exciting. I think for all of us it’s leaning in. Trying to understand what parts still hold true and what parts are shifting. The ride we’re on is moving fast enough that the only productive response is to pay close attention to both.

What Should Remain Human in Design and Product Work

Rina Alexin | 00:05:14 – 00:05:40

So let’s dig into what you just said about what stays true. Because I think if we rely too much on AI, we might be putting ourselves in more dangerous situations than we’re even aware of. What do you think the designer role should retain, even as AI takes on some parts of it?

Jared Hall-Dugas | 00:05:44 – 00:06:51

It’s still evolving, but right now the “why” is still the most important part. Why is this good? Why is this prototype better than that one? I hesitate to use the word judgment because it’s been thrown around a lot, but it’s exactly that: the judgment between two options is the thing that still holds true.

You can show me ten different prototypes. I can still tell you which one is probably going to be more successful and explain why. I can talk through it in a way that connects to real user outcomes. And AI cannot replace that right now. There is just no way.

The Importance of Judgment and Expertise

Rina Alexin | 00:06:21 – 00:06:51

I want to unpack that, because I agree with you. Judgment is being talked about constantly right now, and I think it’s because it really is core to what should remain human. AI doesn’t have judgment. It sounds like it does, and that’s actually the problem: if you don’t know better, an AI output can look completely right when it isn’t. So how do you catch that gap between what looks polished and what actually has problems underneath?

Jared Hall-Dugas | 00:06:57 – 00:07:56

I think a lot of it comes down to the experts in the room catching what they can see. I literally did this today: we were showing a prototype to a VP and they were excited about it, thought it was really solid. But you have to maintain those checkpoints where you say: “Wait, the data here isn’t quite right. We still need to build the real thing behind this.”

I keep calling it a Pinocchio-to-real-boy scenario. The prototype looks like a store ready to open. You look through the windows and everything seems in place. But there’s no electricity yet. It’s still on the human, whether product, engineering, or design, to bring their expertise to the table and say: “Hold on. Those buttons aren’t actually functional. That’s just decoration.” Because a lot of times prototypes get generated and the moment someone starts actually interacting with them as a real tool, they find that half the interface is just visual. The functionality isn’t there yet.

Detecting Gaps and Ensuring Quality with AI

Rina Alexin | 00:07:42 – 00:07:56

That “who catches it” question is important. When teams are trying to move faster than ever, who is actually responsible for catching the gaps in AI output?

Jared Hall-Dugas | 00:08:09 – 00:09:34

It’s still the experts. It’s still the people in the room. It’s just that they have to stay sharp and stay honest about what they’re seeing. The Pinocchio analogy applies to everything: AI-generated images where the actor changes face between scenes, prototypes where the buttons don’t work, data outputs where the numbers look right but don’t match reality.

The expertise question also matters when you’re outside your domain. I went down a rabbit hole early on, excited about Claude Code, and tried to build a research tool that would help scientists find patterns in healthcare and aging data. Fundamentally, the concept was sound. But I don’t know anything about pharmaceutical development or RNA research. When I produced the prototype, I had no idea whether it was pointing toward something genuinely useful or something completely worthless. That was the moment where I realized: expertise matters. You can’t go build a solution in a domain you don’t understand and trust the output just because it looks convincing. Someone who has spent twenty years thinking about that problem would catch things I’d never even know to look for.

Balancing Speed and Quality in AI-Driven Work

Rina Alexin | 00:09:47 – 00:11:03

So the tension you’re describing is real: designers, product managers, engineers are all feeling newly empowered by AI tools, and that’s true. But the blurring of roles was already happening before AI showed up. Has it gotten worse, and what do we actually do about it?

Jared Hall-Dugas | 00:10:47 – 00:11:03

I think it’s okay. I really do. I got worried about it early, back when AI was first hitting and everyone was asking whether roles were going to disappear overnight. But I think this is, ultimately, natural human psychology: we want to belong to our roles, our teams, our disciplines. And so what we’re doing now is trying to redefine ourselves.

That process needs to happen together. All three sides of the triad need to be open and honest and say: “I don’t know what I’m doing here yet. I’m figuring this out.” Because all the processes we’ve built, agile, waterfall, everything, were defined around a reality that is fundamentally shifting. We used to track work because getting it delivered was the bottleneck. Now work gets delivered at the speed of light. So what are we tracking? That’s the real question.

The Evolving Nature of Roles and Team Dynamics

Rina Alexin | 00:12:21 – 00:13:22

How have you navigated that change on your own team?

Jared Hall-Dugas | 00:12:27 – 00:13:22

For me it’s about showing up. Being present and able to participate in whatever is happening. I’m at a 50,000-person company with a lot of bureaucracy and regulatory constraints. The mandate from leadership is: adopt AI, make AI happen. And I think there’s a natural tendency to just solve that problem for your own team in isolation and move on.

What I’ve tried to do instead is bring people together to actually have the conversation. What does AI adoption actually mean here? Which tools are right for which people? Any time someone has wanted to talk about AI, I’ve said yes. Let me be in that room. Let me help figure this out together.

Creating Safe Spaces for AI Conversations in Organizations

Rina Alexin | 00:13:35 – 00:15:03

Is there a structured agenda you follow in those conversations?

Jared Hall-Dugas | 00:13:39 – 00:15:03

Not really, and that’s intentional. I think people are scared and they don’t know what to do. At a company like ours, we’re a little further back in the AI adoption curve, moving more carefully. And a lot of the early conversations were people just wanting to say: “I don’t know what’s going on. What am I supposed to do?”

So I started holding two different monthly meetings with literally zero agenda. The purpose is just to have a place to talk about AI. Because I genuinely believe there are a lot of people who just need that space.

Over time the conversations have shifted. It started as fear, as: “Are we all going to lose our jobs?” And now it’s evolved into people bringing tools they’re working with, sharing something cool they built, asking specific questions about a weird thing that happened, passing around books and podcasts. It’s become about sharing, which is exactly where it should go. The goal was never to be the single voice. It was to create a place where people feel they can ask questions.

The Shift from Fear to Opportunity with AI

Rina Alexin | 00:15:52 – 00:16:03

There was clearly a pretty significant change for the people you were helping in your organization, a real shift from “I’m going to lose my job” to “this is cool and it can help me.” What clicked for them?

Jared Hall-Dugas | 00:16:20 – 00:16:03

I think it was the same thing that clicked for a lot of people generally. Back around December and January, it felt like a shock moment. Like COVID. There were predictions of massive layoffs in weeks. And once that didn’t happen at that scale and pace, people calmed down a little. They said: okay, this isn’t an instantaneous total disruption. This is a big technological change that’s going to take time to fully develop.

And once people calmed down, the question shifted from “what’s going to happen to me” to “what can I actually do with this?” The genie is not going back in the bottle. This is not a fad. So people started trying to figure out how to adapt rather than how to resist.

The Societal and Organizational Adaptation to AI

Rina Alexin | 00:17:31 – 00:18:16

Earlier in the year there was a lot of talk about whether one person could do the job of three. Role compression was a real conversation in many organizations, and in some places it still is. But I’m also seeing a shift where instead of compressing roles, companies are asking: how do I increase the leverage of the people I already have? One person magnified rather than two people compressed into one. Are you seeing that as well?

Jared Hall-Dugas | 00:18:34 – 00:18:16

Yes, definitely. And I’m trying to actively champion that perspective. I think it’s important for us as employees to fight for it. Companies are always going to look for ways to lower costs and increase efficiency. That’s just how it works. But I think it’s equally important for us to say: we have the ability to augment that. We have expertise that AI can amplify, not replace.

And when you think about it from a team perspective: if a small, unified group of people is injecting AI into their work together, the results are exponential. The power of the combination is huge. We can do so much, so much faster as a strong, functioning team working with AI than any one of us could accomplish solo, with or without the tools.

Managing Security, QA, and Boundary Setting in AI Projects

Rina Alexin | 00:19:52 – 00:26:45

Has AI ever actually made you slower?

Jared Hall-Dugas | 00:19:56 – 00:22:00

Yes. Absolutely. I’ve taken wrong turns and gone down rabbit holes. The biggest example for me was early in my exploration. I got so excited about Claude Code that I was building prototypes in every direction. I heard someone talk about how AI might be able to transform the healthcare and longevity space, and I thought: that’s fascinating. I could try to build something for that.

So I went down this whole path of trying to build a research tool that would gather data about aging and health, apply pattern recognition, and help scientists surface hypotheses. Fundamentally, as a concept, it’s not crazy. But I know nothing about pharmaceutical development, RNA research, or any of the underlying science. When I produced the website, I had no way to evaluate whether it was pointing toward something genuinely useful or just telling someone to eat more vegetables. There was no knowledge base to evaluate the output against.

That was the moment I really understood: expertise matters. I can’t go solve a domain I don’t understand just because I have access to powerful tools. Someone who has spent twenty years thinking about a problem will catch things I will never even know to look for.

Rina Alexin | 00:22:27 – 00:26:45

Speaking of complex, regulated environments: you’re at National Grid, a large utility with significant security and regulatory constraints. And with AI security incidents in the news regularly, how are you thinking about QA and boundary setting in that context?

Jared Hall-Dugas | 00:25:28 – 00:26:45

It sounds like a broken record at this point, but it really is the expertise question again. I can vibe code something all day. Product can make it look compelling for the business and get people excited. But without an engineer who actually knows what they’re talking about looking at the security architecture, if you skip that step, that’s where the public embarrassment happens. For a utility like National Grid, protecting electricity and gas infrastructure, that’s a non-starter.

The message I keep repeating is: we still need an engineer here. We cannot jump to the next stage just because something looks great and everyone’s excited to ship it. And I actually think this is where product and design work well together: we can catch that moment quickly. We can be the voices that say yes, this looks great, everybody wants this to be real, but we still have to go through the rigor. We have to make sure there are safeguards, that it’s protected, that it’s not going to expose something we’ll regret.

The cultural approach in a conservative organization has been showing, not just telling. We presented to a VP this week with a complicated data problem that AI is genuinely well suited to. When they saw what it could actually produce for them, they were excited. I think a lot of AI adoption in large organizations happens through those pockets of proof: here’s what it can do, here’s what it produced, here’s what we had to do to make it safe. Multiply enough of those moments and the culture starts to move.

The Importance of Early Involvement of Design in Product Development

Rina Alexin | 00:26:39 – 00:29:23

At the start of this conversation, I asked whether AI is changing what product needs from design. Let me flip it: are the requirements of design on product changing? Do you need something different from product management than you did before?

Jared Hall-Dugas | 00:27:05 – 00:29:23

I don’t think it’s fundamentally different, but it’s more urgent. Designers have always wanted to be chewing on the problem from the beginning. That’s what we do. We want to understand the problem space deeply before we start building.

What I see in a lot of organizations is product defining the problem, developing a solution space, and then bringing that solution to design and saying: let’s start moving forward. And I think that’s exactly where things go wrong. Design needs to be there from day one, as much as is humanly possible, for two reasons:

First, it helps us understand the problem better ourselves, which makes our contribution more valuable.

Second, it lets us challenge the solution direction early, when it’s still cheap to change. We can say: “Is this the right solution? Or are there five others that might be just as good or better?” And with AI now, we can get to that answer much faster. I can show you ten prototypes in the time it used to take to build one. So the earlier we’re in the room, the more of that speed advantage we can actually put to work.

Collaboration Between Product and Design in Early Stages

Rina Alexin | 00:28:07 – 00:35:34

Product management can’t include every stakeholder in every part of the process. But for design and engineering specifically, I think the missing piece is often understanding the problem space. Even when designers can’t be in every voice-of-customer research session, having a debrief afterward to share the thinking and bring them along for the journey matters a lot.

And I’m reflecting on something you said earlier: as product managers are using AI to do more vibe prototyping themselves, they may actually be bypassing the designer even more in the earlier stages. That feels faster in the moment, but over time it means losing the rich context that makes collaboration work. So where should product and design really be collaborating more, especially in those earlier activities?

Jared Hall-Dugas | 00:29:42 – 00:35:34

More is better. A better product comes out of being interlocked from the beginning. You’ve got two sets of eyes looking at the same problem from a product perspective and a design perspective at the same time, and that’s genuinely valuable.

Thinking about it through the lens of prompting: everyone has realized you need to take time to craft a good prompt before you just say “make me the coolest thing.” You have to define the what, the why, the how, and really articulate the problem before you get a useful result. If a product manager and a designer are crafting that prompt together, solving the framing together, the output is going to be so much stronger because it’s being seen from two sides of the same coin.

The specific point where design must be involved, if there’s a non-negotiable: it’s the moment when problems become solutions. That transition from discovery to definition, from understanding the problem space to converging on a direction, is where design’s superpower is. If you don’t have a designer in that room at that moment, you’re going down one path instead of evaluating multiple. And you’re setting yourself up for the same kind of costly rework that happens when you haven’t talked to an engineer before defining feasibility: you build a whole thing and then find out you don’t have the technology to support it, or the user experience doesn’t actually solve the original problem.

The designer’s role at that stage is almost like a chief of staff to the president: that voice on your shoulder that keeps asking “have you thought about this?” and “have you considered this alternative?” It can feel like it’s slowing things down. But it’s what keeps you from going too far down the wrong path before you’ve spent real money on it.

Building Strong Relationships Between Product Managers and Designers

Rina Alexin | 00:35:29 – 00:36:47

We’ve covered a lot about the product and design collaboration. But I want to ask a final question about the relationship itself. As we’re navigating friction, nervousness about roles, and trying to redefine what we each own: what advice would you give a product manager who wants to build a genuinely strong relationship with their UX and design team?

Jared Hall-Dugas | 00:36:05 – 00:36:47

I think it starts with understanding that we’re the same kind of scared. We are just as worried about job roles, about the future, about what all of this means, about how much is our responsibility and how much isn’t, as product managers are.

When product and design are looking at each other across role boundaries, it can feel like: “You’re doing my job” or “I’m doing yours.” But what I’ve seen in my history, when it really works, is that it becomes arm-in-arm lockstep. You stop worrying about who owns what and start thinking about the shared mission. And that’s when you get really cool things happening and products that everybody is genuinely proud of.

So my advice: go in knowing that your designer is just as frightened and just as uncertain about what all of this means. You’ll probably find a sympathetic ear and a friend who will make the work easier. More empathy, less territory.

Final Thoughts and How to Connect with Jared

Rina Alexin | 00:37:12 – 00:38:19

I think we can all have more empathy for our teammates and remember that we’re all trying to accomplish the same goals. That’s a really important message to end on. Jared, I really enjoyed this conversation. Thanks for wrestling with these hard questions with me. How can our listeners follow you or get in touch?

Jared Hall-Dugas | 00:37:33 – 00:38:19

LinkedIn is the best place to find me. I post there most often and have links to everything else from my profile. There really are no other Jared Hall-Dugases out there, so searching the name should get you there quickly.

Rina Alexin | 00:37:50 – 00:38:19

We will also include a link to Jared’s LinkedIn on the episode page. Thank you all for listening to another episode of Productside Stories. If you enjoyed today’s conversation, please don’t keep it to yourself. Share it with a friend and subscribe so you don’t miss a future episode. I’m Rina Alexin, and from all of us at Productside: let’s do product better, together