The great merge

If you’ve been reading this newsletter for any length of time, then you’ve heard me highlight in various ways how AI is shaping how we design and build great experiences.

This past week week, my team at StealthX and I spent some time jamming on a recent article from Suff Syed, The Design Leaders Are Lying to You. It tackles how the craft of design is being reshaped by AI and what that means for the people doing the work. He questions how organizations and teams need to evolve to stay ahead of the curve with design. Pretty interesting read and prompted a lot of good discussion on the team.

Also, this week I dropped the latest episode of the Building Great Experiences podcast with Justin O’Connor, an AI leader in the advisory practice at KPMG who is also building an AI-native platform reimagining how dev teams actually get work done. (Listen on Spotify or watch on YouTube).

Each of these perspectives connected the same dots from different angles. And what is emerging for me is a simple truth: design and engineering are blending into an overlapping discipline focused on outcomes, not outputs.

From pixels to outcomes

For years UX has often been viewed as how something looks, feels, and functions on a screen. That era is over.

The future of designing experiences is about creating outcomes, not interfaces. The value is shifting from screens to orchestrating systems that deliver results across every touchpoint including people, processes, policies, data, and technology.

UX and software engineering aren’t dying, but focusing on designing/building the interface is. The real value now lives beneath the interface, where decisions happen, and where humans, agents, and systems collaborate in real time.

Suff Syed highlighted how most leaders are still optimizing old playbooks instead of evolving them. He’s right. The interface is no longer the product. It’s a thin layer sitting on top of an intelligent layer of agents and AI. Folks who only focus on what’s visible will be left behind.

Rio Longacre, a friend and former colleague of mine said it perfectly in his recent Medium article: “Agents won’t just assist us. They’ll be the interface.” The design challenge is shifting from arranging buttons to defining behaviors, relationships, and trust patterns between humans and AI.

Employee experience is a competitive advantage

In the age of AI, employee experience will become just as important as customer experience.

This was one of the biggest topics from my discussion with Justin. He put it simply: “Happy developers create happy customers. Happy customers create happy investors.”

Employee experience is a business differentiator. It determines how fast teams can move, how confidently they can experiment, and how efficiently they can bring value to market.

But, tooling alone doesn’t make a great employee experience. Culture does. Justin sees it firsthand in his advisory work at KPMG and we see it constantly at StealthX. Most AI projects fail not because the technology doesn’t work, but because the culture isn’t ready.

AI maturity begins with literacy, trust, and psychological safety. Before organizations start deploying AI, they need to teach teams what these systems can do, how they behave, and where they shouldn’t be used.

If teams skip that step, fear and resistance take over. People don’t like being forced to change what they don’t understand. But when teams are included early, when they can experiment safely and see value for themselves, they start pulling for change instead of being pushed into it.

That’s why our mantra at StealthX continues to be “Create a pull, not a push.” Make the change magnetic.

Long live generalists. Death to silos.

AI has commoditized individual skills like research, visual design, and prototyping. BUT what AI can’t replace is human judgment, problem/opportunity framing, and the ability to align people around outcomes.

The most valuable designers and engineers in the next decade will be the ones who can see across boundaries and understand both the human and system problem/s.

Justin and I talked about how the best organizations are scaling knowledge, not headcount. The goal isn’t to hire more designers and developers. It’s to raise up teams without silos who use AI and automation to amplify their expertise and bring out the best in one another to deliver real value.

The future belongs to people who can connect customer needs, business strategy, and system architecture and communicate across all three.

The era of orchestration

We’re in what Justin called the age of orchestration, a period where agents, data, and workflows are finally starting to connect.

Until now, most AI adoption has been isolated. Chatbots in one place, automation tools in another, analytics elsewhere. But over the next few years, we’ll see these converge into cohesive systems that handle full processes end to end.

This is where design and engineering come together. The best teams will work together to build the backbone (orchestration layer, APIs, MCP servers, and agents) AND shape the experience layer that keeps the system usable, trustworthy, and human-centered.

The next frontier is interoperability, connecting systems so they can reason and act together intelligently. Interoperability is a fancy way of saying that different systems can talk to each other and actually understand what’s being said.

Right now, most tools and platforms live in their own bubbles. Your CRM knows one thing, your BI or analytics tools know another, and your AI agent doesn’t know either.. unless someone builds a bridge between them.

Interoperability is about building those bridges so data, logic, and actions can flow smoothly from one place to another without manual work or translation. Think of it like this. Without interoperability, your team spends time copying and pasting between apps. With interoperability, systems share what they know automatically so everything is working off the same playbook and collaborating in real time. When one learns something new, the others can act on it.

It’s the difference between a collection of tools and an intelligent ecosystem.

Principles for building in this new era

Here’s how we’re approaching building great experiences in the age of AI at StealthX and how we’re guiding clients to do the same:

1. Start at the end. Define the jobs-to-be-done (i.e., what is your user/customer/employee ultimately trying to accomplish) and measurable outcomes before jumping into solutions.

2. Design the service, not just the screen. Include people, process, policy, data, and technology in the scope of design.

3. Prove before you promise. Lead with small proofs of concept or future-vision demos that de-risk decisions and build belief.

4. Deliver with maturity in mind. Meet teams where they are and design stepping stones that move them from foundational systems to intelligent ones.

5. Use AI as a force multiplier. Apply AI in research, prototyping, and workflow automation, but keep humans responsible for ethics, judgment, and taste.

6. Build safety and ethics into the system. Privacy, explainability, bias, and governance aren’t side notes. They’re design requirements.

Putting this into action

Here are a few ways to start putting these ideas to work:

• Run a cross-functional mapping session: Bring cross-functional team members into one room. Map a single customer journey and identify where automation or AI could amplify outcomes.

• Prototype fast, learn faster: Pick one “boring” problem everyone agrees on and workshop how AI can help you solve it. Document/record the before and after, share the results, and let curiosity spread naturally.

• Raise literacy together: Host internal learning sessions where team members learn basic AI concepts, experience principles, and empathy-building techniques.

• Make outcomes visible: Replace feature counts and velocity charts with metrics that show impact on time-to-value, customer satisfaction, or customer LTV (lifetime value).

Wrapping up

We’re entering a post-surface era of experience design where success depends on how well humans, agents, and systems collaborate. There are still tons of questions and things to figure out as we enter this era, things like:

1. How deep is "deep enough" on AI literacy/education/training?

2. What does the experience look like when agents are interacting with other agents?

3. What org and process changes are needed to get the most value from AI?

4. What are the right metrics to measure?

I truly believe that the people who understand systems thinking and human experience, will be the ones who define this next chapter.

Justin said it best, “We’re moving from building software to building systems that build software.”

That’s the frontier we’re walking into. The next few years will reward teams that invest in culture, literacy, and empathy as much as code and craft. Because in the end, great experiences will always come down to trust, clarity, and care.

Onward & upward,
Drew

P.s. If we haven’t met yet, hello! I’m Drew Burdick, Founder and Managing Partner at StealthX. We work with brands to design & build great customer experiences that win. I share ideas weekly through this newsletter & over on the Building Great Experiences podcast. Have a question? Feel free to contact us, I’d love to hear from you.