Bruce Yang is a Head of Product at Way2B1. Bruce led product management at Triumph and Forge, where he played a key role in strategizing mergers that led to successful IPOs.

Skillset of future product teams

Ana: Great. I must confess that I’m actually your fan because I really love your insightful posts on LinkedIn. Recently, you posted about how the talent stack is collapsing and how messy it’s become to create products in 2025. We know AI is the biggest driver of this change, but can we walk through how AI is actually changing how product teams operate? Like, what’s the impact at Way2B1?

Bruce: When I look at people and the outcomes we want—because we really want to focus on outcomes, what’s differentiated, and how to operate more effectively—I start by looking at the skills we have and the skills we need.

In most organizations pre-AI, everyone worked the same way: you had a bunch of designers who created a system from scratch. Since the system didn’t exist yet, they’d just put together a bunch of Figma files, do their best, then hand it off to engineering. Then there’s a really long feedback cycle—it takes three months to build, and only then does the designer get to actually interact with what they designed.

But inevitably, something gets lost in translation—or even if it’s a perfect copy, you realize the original design wasn’t quite right. Static mockups are really limiting because you can’t click around and see the flow of information or how a user interacts with the system.

So now, the skill set is different. We want to use real-code prototypes, where designers can click around and learn about the system as they use it. We can inject a lot of synthetic data to make it more realistic. For example, you design a CRM page with an “Organization” field in the top left, but in reality, users have 10 organizations or serve 100 clients—and suddenly your design doesn’t work anymore.

Designers need much more ability to “code”—and by that, I mean using AI to produce functional, iterative prototypes. That’s become really important. Also, the ability for engineers to deeply understand customers, work on product features, and do basic design work is much more important now.

So those traditional EPD or PDE (product, design, engineering) silos are all merging a little. Everyone will still have a specialty, but the boundaries are blurring.

Ways to transform an org into AI-native

Ana: It really sounds like stepping out of your comfort zone—embracing change and developing new skills. But it also affects the company’s processes and mindset. It’s not just about designers showing prototypes to customers and iterating—it feels like a broader cultural shift. And transformation is hard. It’s not a quantum leap—it’s a journey.

Some companies adopt technology top-down through leadership. Others evolve from the ground up. The top-down approach is faster but might face resistance or even sabotage. Evolution is slower and sometimes chaotic. What steps do you think companies should take to embrace this shift in how we build products?

Bruce: Fundamentally, you need a champion. Someone with enough influence to move things forward. If leadership doesn't eventually believe in a better path—even if it's not immediate—change won't happen.

If everyone is happy with the status quo, nothing will change. But if a company realizes that what they hope to be true isn’t real, then they become open to change. There are many ways to communicate that realization, but ultimately you do need to convince the executives.

They need to understand that this journey will be hard. Not everyone will come along. There will be disagreements. The value stack will shift. People who were once aligned may diverge. Eventually, someone may leave—or be ejected from the culture—if you can't get them aligned.

So yes, leadership is important, but as a change agent, you really have to do both—top-down and bottom-up. You want a slow-building crescendo where people start saying, “I’m playing with this; it’s helping me.”

That starts with one-on-one conversations. Over time, people start talking, and suddenly you look around and realize—wow, a lot of people are using AI and believe in the future.

But yes—it takes time. You need to know where to spend your energy. Who has influence? Who’s open to change? And who isn’t?

AI-centric culture and company policy

Ana: Yeah, that’s very wise. Can you also share your practical experience? What exact steps have you taken to create an environment where people can play with AI and feel safe doing so?

Bruce: Number one: you have to become an expert yourself. And when I say “expert,” I mean just more knowledgeable than those around you—enough to show them what’s possible.

One of the biggest misconceptions about AI is that it’s a switch. Either you’re using it or you’re not. And you hear a lot of people say, “I use ChatGPT, so I know what I’m doing,” or, “AI isn’t good—I tried it and it didn’t work.”

But there’s very little self-reflection. No beginner’s mindset. People rarely stop to think, “Maybe I’m not using it the right way.”

To me, AI is like a musical instrument. Nobody’s an expert right away. Over time, you have to learn how to play it—what works, what doesn’t. I have very smart friends dabbling in AI who said, “It just doesn’t give me what I want.” Then a month later, they discover a newer model—like GPT-4o or Claude—and suddenly it works way better.

Sometimes it’s as simple as using the wrong model because it’s the default. Most people don’t explore what’s out there—they don’t compare models, reasoning engines, or tools like Anthropic’s Claude. There’s a lot to learn.

Practically speaking, you have to know your craft. Show what’s possible. Share it freely.

From the bottom up, it’s about sitting with someone and saying, “Let’s do this together.” Show your process, ask them to show theirs, and compare outcomes. Often, even skeptics will say, “Yeah, I actually hated doing that task. AI made it easier. Now I can focus on the fun parts.”

From a leadership perspective, talk to the most senior person you can. Get alignment. In 2024, I saw CEOs saying, “We need to start doing AI.” Then they waited. By 2025, they realized nothing happened. The moment they start losing sales due to AI-powered competitors, it gets real.

You can hear them saying, “I was on a sales call. We lost the sale to this AI feature.” And all the engineers go back and reply, “This feature isn't even real AI. It's so basic. It's only a wrapper around this” and blah, blah, blah. But it doesn't matter because you lost a sale. And then the CEOs are starting, “Okay, we have to do this. Like instead of suggesting it, I'm mandating it.” 

And if you look at something—even a company like Shopify, right? Shopify is a huge, very successful company. I think last year their CEO said, “We suggest everybody use AI.” And just about a month ago, they came out with a new policy that says you must use AI—AI is core to our features. You can never request more budget unless you’ve explained why AI can’t help you accomplish this. It’s going to be part of your performance review, right? This is going to be something that we accept as a culture. I think it’s very scary for people, but ultimately it’s both top-down and bottom-up. Even at our company, Way2B1, we’ve been talking about an AI policy, right? Having an explicit policy that the leadership all agrees on is also really important. It’s all these things that slowly get people on the same track.

How AI culture starts in a product org

Ana: I love so many parts of this discussion, but what resonates with me most is that change happens in both directions—and that stories have power. Being transparent about everyone’s experiments can really spark progress. When I hear that a colleague is exploring AI capabilities and sharing what they learn, it inspires me to do the same.

At Cieden, our journey began with a visionary CEO who’s also an enthusiast—playing around, leading by example, and showing his work to the company. That sparked interest in a few areas: maybe 2 – 5 % of the team became truly passionate about adopting new tools, but it didn’t spread widely until we took the next step: communicating the strategy. We acknowledged that AI is crucial—if we don’t adapt, we could fall out of the market. Even so, that announcement alone didn’t have a huge impact.

Real change came at the tactical level. We agreed on concrete next steps: team education, workshops, mentorship, and a hackathon (tomorrow!) where everyone will sit together, build something hands-on, and compare results. These are the practices we’re injecting into our process.

As an agency, we work with different companies. Some recognize the urgency and try to add new AI tools to their design workflows, but they can be rigid or unsure how to incorporate them. People also have personal excuses: “We don’t have time to make AI prototypes—we need to ship Figma files,” or “Our product manager doesn’t require it.” So there are barriers on both the personal and company levels.

What small experiment or next step would you recommend so companies can start incorporating AI tomorrow?

Bruce: What I love about what you said is that having the CEO—or any leader—bring people along is exactly the right approach. It’s hard, but it sets the company’s intention and direction.

On an individual level, people need to realize they must adapt. With my last hire, I decided that’s the last person I’ll ever bring on who isn’t AI-native—someone who uses AI for everything. The future belongs to people who leverage AI to be extraordinarily productive: faster, higher quality, doing things no one else can. I can’t go back to the old way.

If you’re about to retire, maybe this isn’t critical. But for anyone mid-career, change is here. When someone says they don’t have time, I get it—but the time you invest now will pay off forever. The best way to help is to sit with them while they work. You’ll see someone typing line by line in Google Sheets, and you can show them the formula that does it all in one go.

Praise also matters. From top down and bottom up, recognize and promote people who excel in the new world. If you claim to value AI skills, you must reward them—even over designers who may be stronger overall but don’t use AI. If you don’t follow through, you don’t really care.

At Way2B1 I’m always amazed: our designer builds clickable prototypes and mock-ups, and when we show customers, they say, “This is exactly what I wanted!” Often it’s not even my work—it’s the designer’s. Those prototypes end up in front of CEOs of billion-dollar companies who click around and love it. Designers don’t always realize how widely their work is shared. As leaders, we need to communicate that more clearly—I need to do better there too.

Ultimately, people must decide for themselves. From a company perspective, you want to bring as many people along as possible, but you can’t bring everyone. Pushing boundaries means, by definition, not everyone is on board. The real question is: who can come with us, and what kind of future do we want for our company?

Hiring builders, not roles

Ana: What are your thoughts on the defining skills companies should look for when hiring, and how do you find the right match?

Bruce: These days I’m focused less on specific roles and more on a vibe—call it values or culture. First, candidates must be curious: curious about new technologies and processes, but also hands-on with the tools and able to talk about them clearly. They need a real hunger to learn.

Whether you’re an engineer or a designer, my ideal interview looks like this: Let’s build an app. You’ll have one hour, and I’ll be nearby to answer questions. Create something simple—a to-do or checklist app. In that hour I can see where you lean on AI, where you don’t, and how you handle time pressure. I’ll watch you trade off quality versus speed and hear you think out loud about what the customer needs.

I’m hiring builders with deep expertise. A builder asks, How do I craft this?—like an artist. Designers, in particular, will become far more influential. People still treat designers as “the person who hands over a spec,” but the future is about artistry and emotion: taking what exists, combining it in a novel way, and shaping an experience customers will pay for. Designers naturally think that way.

So I’m looking across the board for builders: a builder with an eye for design, a builder with an eye for product, a builder who ships code.

Building product strategy with AI at the core

Ana: We may have drifted a bit, but this still gets to how companies can stand out. Merely adding AI isn’t enough; what really differentiates you is deep understanding and proper use of it. It’s not just “we have speech-to-text” or an auto-summary. True AI-native products have AI at their core, not as a bolt-on module.

Bruce: In the end, everything comes back to sales—that’s the key metric. So every company has to stay laser-focused on sales, but to do that you need real strategy.

Planning vs. strategy

Planning is what you can control: resources, roadmap, feature order. It feels safe because you set the schedule. Too often we mistake that plan for “strategy.” Strategy, however, is about trying to influence what you can’t control—especially the customer. You can’t make a customer give you money. All you can do is present something so compelling that they choose to pay.

You also can’t control how the outside world sees you. When someone mentions Cieden, do they think “low-cost provider,” “highest quality,” or “AI leader”? You can’t dictate that perception any more than I can force everyone to believe I’m the handsomest guy in the room. What you can do is act: dress better, work out, improve your craft. Over time those actions influence how people see you.

If you don’t like your current results—sales, brand perception, customer mix—your strategy has to change, because strategy is simply the collection of things you actually do. Change your actions, change the outcome.

Where AI fits

AI unlocks entirely new strategies—new ways to earn attention, create value, and convince customers to pay. For instance, before we worked with you, I spoke to another design firm about generating a library of assets. I asked if they could use AI to create and refine those assets. Their answer was basically, “We don’t do that.” No curiosity, no willingness to explore.

Imagine instead that everyone thought of Cieden this way:

“Need an AI-powered experience—fast and high-quality? Want your prospects to test a real, emotionally engaging app instead of just a Figma mock-up? Call Cieden.”

That’s strategy in action: using AI at the core to shape how customers perceive you and, ultimately, why they buy.

Everyone’s biased – align them

Ana: We’ve talked a lot about strategy as a way to win clients—that’s the external part. But how do you communicate that strategy to the team?

Bruce: If you’re still searching for a product–market fit, it’s tough to communicate strategy because you don’t truly have one yet. Every customer call becomes an exercise in discovery. We show prospects ideas, observe their reactions, have different types of conversations, and note what resonates.

For example, we used to position ourselves around internal efficiency: “We’ll streamline your operations.” Recently I realized our customers care even more about their customers. So I started testing a new message:

“You love your clients and want to give them a priceless experience. We can help you do that in ways no one else can—turning a first touchpoint into lasting trust.”

When I say that, people perk up.

Two practices help align the team:

1. Customer quotes. I record every customer conversation. Everyone sees the same raw input instead of filtering it through their own bias.
2. Clear boundaries. Paint the picture of who we are and who we’re not. For us, the sweet spot is the intersection of a great client experience and seamless hand-off to the company’s internal systems. Focusing on just one side isn’t enough.

Data will matter even more in an AI-driven future. Code keeps getting cheaper, but personalization—powered by unique data connections—becomes the differentiator.

Ana: That’s why communicating vision matters. If everyone can influence product decisions, they’ll pull in different directions unless the vision narrows the brainstorming.

Bruce: Exactly. Repetition is crucial—everyone should be able to say the same core message. Right now, if I asked each group lead—customer success, engineering, product, design— I’d get different answers. We have to fix that.

At the team level we set outcome-based goals, not implementation details:

• “A user must be able to create a task in ≤1 second.”
• “Provide a multimodal way (voice, text, image) to create multiple items at once.”

How the team achieves those outcomes is up to them: prototype broadly, then prune what doesn’t work. I call it prototype and prune.

Building an AI Center of Excellence

Ana: Focusing on outcomes—and the problem or opportunity we’re addressing—makes sense. We have to wrap up, but could you share concrete steps product leaders can take tomorrow to start operationalizing AI in their teams?

Bruce: Step one is using it yourself, right? After that you really have to start helping the team, and that’s where it gets tricky.

A few things help—some of them your company is already doing. First, company-wide hackathons with a specific theme are great. Second, set up a center of excellence: every two weeks the team meets to share their AI experiences. The goal is for people to contribute their own stories, because when a product person talks about AI in engineering it doesn’t land the same way it does when an engineer says it. You need diverse perspectives.

It’s one thing for a designer to say, “You engineers should use AI for design— you’ll be fine.” The engineers may think, Okay, you don’t know engineering. But when another engineer says, “I use AI like this, here are the questions I ask, and the design turns out great,” suddenly everyone thinks, If it’s possible for you, it’s possible for me.

So establish a forum where people can discuss, share information, and celebrate wins. Remember: people avoid risks. If I write a document with AI and my boss reacts with, “Uh, this was written with AI,”—even without criticism—I’ll stop doing it or hide it. Create a culture that celebrates AI use and pushes it forward.

Individually, just keep getting better. When you deliver experiences others can’t match, people notice, pay attention, and talk about it.

Ana: Thank you for this inspiring conversation and all the practical advice people can use. I really enjoyed it.

Bruce: Awesome. Thanks for inviting me—maybe we’ll do a part two in the future.

Ana: I hope so. Thank you!

Bruce: Bye-bye.

Ana: Bye.