Are You Building the Right Thing? Why User Insight Still Anchors AI-Native Design — Max Celko, Rapid Data

Max Celko’s path into product design leadership has taken him through journalism, innovation strategy, and user research, united by a consistent curiosity about how technology, markets, and human needs evolve. A common thread throughout his career has been his focus on identifying emerging opportunities, uncovering user needs, and translating insights into products and experiences that create tangible value. As his career progressed, he increasingly focused on shaping digital products directly, using user research to validate ideas and refining product experiences through continuous, evidence-based iteration. 

Now Director of Product Design at Rapid Data, a private equity-backed software company in the death care space, he leads design across both B2C and B2B products. He champions a user-centred design approach that combines quantitative and qualitative research, close cross-functional collaboration, and increasingly AI-driven ways of working.

What sparked your transition from journalism and innovation strategy into product design?

Max explains the common thread running through his career and why he wanted to move closer to product.

“I’ve always been driven by a curiosity about how technology and user needs evolve – and by the desire to turn those insights into products that solve real problems.
Journalism gave me the opportunity to explore emerging developments in technology, design, innovation, culture, and business. Innovation strategy built on that by helping organisations identify market opportunities and uncover user needs through research.
Over time, I realised that I didn’t just want to identify opportunities or develop concepts – I wanted to help build the products themselves. Product design gave me exactly that opportunity. It allowed me to take research and strategic thinking and translate them into experiences that could be launched, tested with users, continuously improved, and ultimately create real value.
In many ways, my career has been a progression from understanding change, to identifying opportunities, to shaping products that respond to those opportunities.”

What does your role at Rapid Data involve, and what excites you about it?

Max describes a role centred on understanding users, shaping better products, and helping teams make more informed decisions through research, collaboration, and AI. 

“At its core, my role is about making sure we build the right products for the right reasons. That starts with understanding our users – their needs, frustrations, and goals – and translating those insights into products that create value for both customers and the business.

A large part of my work involves bringing together evidence from user interviews, behavioural data, analytics, and customer feedback to build a complete picture of the customer experience. That requires bringing together insights from across the organisation. Product design isn’t something that happens in isolation; it’s a collaborative effort that involves product, engineering, sales, support, and onboarding.

Another important part of my role is improving how we work as an organisation. That means developing research and design processes that help teams collaborate more effectively and make better decisions. AI has become an increasingly important part of that. It helps us synthesise research, uncover patterns across multiple sources of customer feedback, and streamline design workflows. AI allows teams to spend more time solving problems and less time processing information.

What excites me most is seeing how user insights translate into better products. We invest a lot in understanding our customers, and it’s incredibly rewarding to see those insights turned into products that genuinely make people’s lives easier. The positive feedback we receive from users shows us that we’re making a real difference.”

How has AI reshaped your design and development workflow?

Max explains how AI has fundamentally reshaped his team’s design workflow, shifting from traditional design processes to an AI-assisted key screen approach.

“The biggest change is that AI has fundamentally reshaped the way we design and build products. The traditional workflow has effectively flipped. Instead of spending weeks creating concepts and prototypes in Figma before anything is built, we can now move directly into HTML prototyping, using AI as a design partner. This allows us to test ideas with users much earlier, gather feedback, and iterate more quickly.  

Our designers work from a shared design system that AI can access. Rather than manually designing every screen in Figma, they work in Claude to generate HTML prototypes. The designer remains in control throughout the process, guiding the AI and making the key design decisions. The prototypes aren’t always perfectly aligned with the design system, but that’s not an issue for user testing. When we introduce a new interaction or UI pattern, we create a single high-fidelity key screen in Figma that serves as the design reference for engineering. Developers then receive a working HTML prototype together with that key screen. We call this the key screen approach.

Engineering is evolving in a similar way, although AI plays a different role. AI can now generate significant parts of the code based on user stories, allowing developers to focus more on software architecture, reviewing the implementation, making technical decisions, and resolving complex issues. When the AI detects inconsistencies or ambiguities in the requirements, it flags them so they can be resolved together with product management before development continues.

Where do most organisations struggle with research, design, and implementation?

Max argues that the real challenge is balancing speed with product judgement – moving fast while staying focused on solving the right problems.

“The biggest challenge today is not building things quickly – it is making sure we are building the right things. With AI, it has become much easier and faster to develop and launch features. But the real question is whether those features solve meaningful customer problems and create value for the business. You could launch thirty features in a month, but if they don’t address real needs, you are simply adding complexity and making the user experience worse. Teams need to resist the temptation to build features simply because they can.

This is why design and user research are becoming increasingly interconnected. They always have been, but as product cycles accelerate, understanding users, aligning with business goals, and making evidence-based decisions becomes  more critical than ever.”

How will the relationship between product, design, and research evolve over the next three to five years?

Max sees the boundaries between disciplines becoming increasingly fluid, with AI introducing a new dimension to product design.

“The boundaries between product, design, research, and engineering will become increasingly fluid. Instead of separate cycles of discovery, design, implementation, and testing, these disciplines will move towards one continuous process of understanding problems, creating solutions, and learning from users.
Design will become even more closely integrated with continuous insight and research. Depending on the maturity of the design system, teams may increasingly design through AI or directly in code. This allows designers to spend less time producing deliverables and more time focusing on guiding the process, evaluating outcomes, and ensuring the experience remains useful and intuitive.

At the same time, we need to think about a new AI layer in product experiences. In the past, we designed user journeys and flows around screens and interactions. Now we also have to consider how AI influences the experience and how we can create value through intelligent functionality. This represents a fundamentally new dimension of user experience design: designing intelligent behaviour is becoming as important as designing interfaces. 

Looking further ahead, interfaces will become more fluid and adaptive. Today, personalisation is mostly about tailoring existing content and experiences—whether by curating content on platforms like TikTok or Instagram or by adapting software interfaces to individual users. The next evolution could be personalised creation: generating content, experiences, and even interfaces based on your preferences, needs, and context.”

What have you learned about building genuinely collaborative teams?

Max explains why successful collaboration starts with a shared goal – and the mindset he values most when building a design team.

“The most important thing is creating a shared understanding of the problem you’re trying to solve. Once teams are aligned around the customer, the desired outcome, and the value you’re trying to create, collaboration becomes much easier. A big part of my role is facilitating those conversations across product, engineering, customer success, sales, and other teams, making sure everyone understands how their work contributes to the same goal.

When hiring, the specific skills depend on the role, but I’m generally looking for people who take ownership rather than simply execute. I want designers who can explain the reasoning behind their decisions, evaluate whether they achieved the intended outcome, and reflect on what they would do differently next time. That ability to think critically, learn continuously, and understand the broader context behind design decisions is far more important than simply producing great screens.”

What one question should every product leader ask before launching?

Max distils his product philosophy into one simple question that guides every product decision.

“The question I always ask is: Are we building the right thing? In other words, are we solving a real customer problem, and does solving that problem also create value for the business? If the answer to both is yes, then we’re building something worth investing in.”

Join the Conversation: The Ortus Club’s Executive Network

As Max Celko’s perspective shows, the pressures facing design and product leaders, from AI-native workflows to the discipline of shipping only what truly matters, are rarely navigated in isolation. As cycles accelerate and the boundaries between research, design, and development dissolve, leaders increasingly rely on candid peer dialogue to pressure-test their approaches and learn how others are adapting.

At The Ortus Club, we host curated executive roundtables that bring together senior leaders facing exactly these challenges. Step beyond the hype around AI and design tooling, and join the kind of open, high-value conversations that connect emerging capability to real user and business outcomes.

Frequently Asked Questions

Q: What is the key screen approach to product design?

A: It is a workflow where designers use AI to create HTML prototypes based on an established design system. High-fidelity Figma screens are created only when a genuinely new interaction or UI pattern is required, with both then handed over to development.

Q: How is AI changing the relationship between design, research, and product management?

A: AI is bringing design, research, and product management into one continuous, interconnected work stream. As teams build and iterate faster, design becomes increasingly interconnected with user research and discovery rather than remaining a separate phase.

Q: What is the difference between personalisation as curation and as creation?

A: Curation personalises which existing content a user sees, as social platforms do with feeds. Creation goes a step further by generating new content – or even entirely new interfaces – tailored to a user’s preferences, needs, and context.

Q: What is the most important question to ask before launching a feature?

A: The first question should be: “Are we building the right thing?” In practice, that means asking whether the feature solves a real customer problem and whether solving that problem creates meaningful value for the business.

Q: What quality should leaders look for when hiring designers?

A: The ability to take ownership of design decisions, explain the rationale behind them, and assess whether they achieved the intended outcome – rather than simply executing design work.