Slow Down to Speed Up: Jake McKee’s Guide to AIX (A Chat with Cross-Functional Experts)

Dianna Deeney interviews Jake McKee to explore AI Experience Design (AIX), the practice of designing relationships between humans and intelligent AI systems, and how it’s reshaping product development in today’s rapidly advancing technological landscape.

In this eye-opening conversation, Jake draws a powerful parallel between today’s AI transformation and the digital transformation of the early 2000s. The key difference? Scale and speed. While the early web had natural boundaries, AI presents an almost limitless frontier advancing at breathtaking pace. This creates unique challenges for product teams caught between executive demands for AI innovation and the practical realities of implementation. Jake explains how this pressure often leads to a predictable cycle of over-reliance followed by algorithm aversion before teams eventually find balance.

Rather than viewing AI as a replacement for human capabilities, Jake advocates for seeing it as a “creative and critical partner” that enhances our thinking and processes. He shares practical examples of how product teams can thoughtfully integrate AI – from using it to test early concepts against customer data to employing it as a collaborative ideation tool. Throughout our discussion, Jake emphasizes that successful AI integration depends on maintaining human relationships at the center of product development, not pushing customers further away behind technological barriers.

This interview is part of our series, “A Chat with Cross Functional Experts”. Our focus is speaking with people that are typically part of a cross-functional team within engineering projects. We discuss their viewpoints and perspectives regarding new products, the values they bring to new product development, and how they’re involved and work with product design engineering teammates.

About Jake

Jake McKee is a veteran community strategist and experience designer with more than two decades of experience helping companies like LEGO, Apple, and Southwest Airlines build deeper relationships with their most passionate customers. Today, he helps organizations navigate AI transformation through the emerging discipline of AI Experience Design (AIX)—the practice of designing how humans relate to intelligent systems. Jake is the founder of Jake McKee Consulting and the creator of AIX Sessions a unique monthly event series designed for candid, senior-level conversation about community, product, and AIX strategy.

Jake and Dianna talk about

Comparing AI transformation to the digital transformation of the early 2000s, but with greater speed and fewer boundaries.
Understanding the “over-reliance and algorithm aversion curve” in AI adoption.
Using AI as a creative and critical thinking partner rather than a replacement for human judgment.
Developing critical and creative thinking skills as essential capabilities for the AI era.
Considering the social contracts and relationship dynamics created by new AI tools.
Looking beyond quarterly business results to build sustainable, ethical AI solutions.

Perhaps Jake’s most counterintuitive yet valuable advice is simple: slow down. “Slow is smooth, and smooth is fast,” he quotes from fighter pilot wisdom. By taking time to consider the deeper implications of AI implementation – from social contracts to ethical considerations to long-term impacts – teams can actually achieve better, more sustainable results than those rushing to implement AI for quarterly gains.

Introducing AIX

The emergence of AI Experience Design (AIX) marks a pivotal moment in how we conceptualize the relationships between humans and intelligent systems. As Jake McKee explains in our recent discussion, AIX represents the practice of designing how humans relate to intelligent systems—a discipline that extends far beyond mere user interfaces or conversational design elements.

We’ve done it before, but not at this pace and scope

One of the most striking analogies McKee offers is comparing our current AI transformation to the digital transformation of the late 1990s and early 2000s. Back then, businesses rushed to establish web presences without fully understanding what they were building or why—much like today’s executive mandates to “add AI” to products and services without strategic purpose. However, there’s a crucial difference: while web technologies had inherent boundaries and limitations, AI presents an almost boundless frontier of possibilities, advancing at unprecedented speed. This combination of velocity and scope creates both tremendous opportunity and significant risk.

Our psychological patterns about AI

The psychological patterns emerging around AI adoption are particularly fascinating. McKee describes what researchers call the “over-reliance and algorithm aversion curve”—a cycle where users initially place excessive trust in AI systems, then become disillusioned upon discovering limitations or problems, leading to complete avoidance before gradually returning to a more balanced relationship. This pattern mirrors many organizational approaches to AI implementation, where initial enthusiasm gives way to frustration when expected transformations don’t materialize overnight.

AI and product design

Perhaps the most valuable insight for engineers and designers is McKee’s perspective on AI as a “creative and critical partner” rather than a replacement for human judgment or customer engagement. He shares an illuminating personal example of using AI to refine his newsletter content—not by blindly accepting generated outputs, but by engaging with the system as a collaborative thinking partner. This approach harnesses AI’s strengths while maintaining human creativity and discernment at the center of the creative process.

For product development teams, McKee emphasizes that AI should enhance rather than replace customer involvement. He challenges the traditional “black box” approach to product development, where customer research happens only at the beginning and validation stages, advocating instead for continuous customer participation throughout the creation process. AI tools can facilitate this engagement when used thoughtfully—for instance, by creating proprietary systems trained on customer data that allow engineers to test concepts and ideas rapidly before investing in full prototypes.

How to approach AI innovation

The most compelling advice McKee offers comes in the form of a counterintuitive recommendation: slow down. In an age where AI appears to accelerate everything, deliberately slowing our processes can lead to better outcomes. As he quotes the fighter pilot axiom, “slow is smooth, and smooth is fast.” This principle suggests that taking time for thoughtful implementation ultimately produces superior results more efficiently than rushing through half-formed applications of technology. In practical terms, this means carefully considering customer needs, ethical implications, and long-term relationships rather than pursuing quarterly achievements at the expense of sustainable innovation.

The social dimensions of AI integration represent another crucial consideration. McKee’s anecdote about encountering someone wearing a conversation-recording device highlights the emerging questions around consent, transparency, and social norms as AI technologies become more pervasive in our daily interactions. These considerations extend beyond technical specifications into the realm of relationship design—a domain that requires empathy, ethical awareness, and human-centered thinking.

What can you do today?

Next Steps for Engineers:

Exercise Your Critical Thinking Skills: Go beyond purely technical solutions and apply critical thinking to understand broader impacts. Jake’s discussion about bridging creative and engineering, and his focus on user experience, inherently highlights the importance of critical thinking to solve problems from a holistic perspective, not just a technical one. This includes understanding the “why” behind decisions and anticipating challenges.
Think of AI Adoption in Terms of AIX (AI Experience), Keeping People First: Jake explicitly introduces and champions the concept of AIX, or the AI Experience, stressing that AI solutions must be designed with the human user at the center. For engineers, this means moving beyond just the functionality of AI to consider its usability, ethical implications, and the overall impact on the people interacting with it. It’s about designing AI that genuinely augments human capabilities and improves user interaction, rather than simply automating tasks.