Tent Talks Featuring Kai Tran: Bridging Gaps: How AI Transforms Design Learning and Careers

[00:00:34] Chicago Camps: With AI integration becoming crucial in design, how do you see artificial intelligence reshaping the future of UX design, particularly for newcomers in the field?

[00:00:44] Kai Tran: The pace of AI advancements is staggering. Every few weeks, we see new updates to language models and innovations across various industries.

Almost every type of software or service I’m using has been AI integrated in some way, and just last week, Google announced Gemini, their AI model, being integrated into Google searches. This is huge, right? It impacts our tools, our work environment, significantly. I believe new designers entering the field are likely to feel overwhelmed.

I experienced this myself when I transitioned from marketing and visual design into UX. There were so many different programs, tools, conflicting advice that I often felt lost, and I dealt with a lot of imposter syndrome. This feeling is common among the junior and early career designers I’ve talked to. The explosion of AI and the constant news of layoffs, coupled with companies reporting improved outputs with smaller teams due to AI automation only intensifies the worry.

I want to share some interesting statistics to put things into context. According to the UX Design Institute, UX design openings were down by 71 percent from 2022 to 2023. On the other side, according to Theory Ventures, AI software companies are projected to grow 63 percent faster in 2024 compared to non AI companies.

All that is to say is that I encourage incoming UX designers not to lose hope. Economic instability and shifts are normal with drastic technological changes. By understanding how to incorporate AI into their workflows, and exploring AI tools enhances their competitiveness in the field, and they will position themselves advantageously in the long run.

I’m a really big fan of Jakob Nielsen’s writings and research on AI. He’s been super intrigued with the topic and encourages that the core principles of UX design are not being replaced, but are evolving with AI integration. He describes this as pancaking. UX is pancaking, and I’ll describe three main points of this concept.

One, AI lowers skill gaps and boosts seniority, providing everyone with a broader range of good enough skill. In the past, the ideal was the T shaped UX designer who specialized deeply in one area while only having basic skills in others. I think this is really scary for newcomers who feel like they have to figure it out.

They have to niche down while being super new at the same time. Almost like taking a gamble when you have to decide what to focus on. There’s this theory called the 10,000 hour rule, where to master a topic, you need to commit 10,000 hours. What if you choose the wrong specialization and you have to start all over?

For number two, the second point in the UX is pancaking is in contrast, the new ideal is becoming a UX unicorn or UX generalist with a wide range of skills covering the full UX process. It doesn’t become such a gamble when you have AI on your side to fill in your weak spots. Evidently, when one person can handle multiple tasks, It reduces communication overhead and company bureaucracy.

The third point is UX staff is spreading out across organizations in a flatter, less hierarchical way than the centralized UX team. This leads to fewer politics and more agile development. With the promise of new advancements, we’re seeing smaller teams be able to create faster and cheaper. I was surprised when I heard this.

MidJourney, which is an AI image generation company, is only 11 people on the team with $200 million in revenue, completely bootstrapped. With AI generated video creation becoming more of a reality, we are getting closer to an age of 5 million dollar movie studios versus 100 million dollar studios, which means more studios overall, and smaller teams, less communication overhead, less management, and more movies .

Jakob also explains that AI is changing both the products being designed and the workflow of the teams creating them. These changes are so significant that in 10 years, the UX landscape will be completely different. Teams will be smaller, more integrated with AI, and the traditional experience of senior UX professionals become less relevant, unless they adapt and gain hands on experience with AI enabled products.

So I would say for newcomers, this is actually an exciting opportunity by embracing AI and continually learning. They can become versatile UX generalists. And have a competitive edge and it won’t take 10,000 hours. There are designers who are both technically proficient and are able to see the bigger picture, making them more agile.

And I think there is still hope in this field. So I would say come all, you’re welcome. Don’t be too worried about AI hype.

[00:06:30] Chicago Camps: Could you share how your journey from print design to AI product design has influenced your approach to UX and what key lessons have proven most impactful?

[00:06:40] Kai Tran: I’d love to use some background on my journey.

I studied film in college. I didn’t have a lot of money or a decent camera, so I focused on digital art and 3D. When I graduated, I went into gaming cinematics. And then I transitioned more into game marketing. And then I had this opportunity that fell in my lap to work at a seasonal retail chain as a merchandising designer.

Their bread and butter was calendars. I don’t know the last time you’ve been to the mall, but you might remember those kiosks with calendars that would pop up closer to Christmas. They started moving into games and this was a big factor on why I was hired. They saw my niche skills in the gaming industry as something valuable.

I was the sole designer for over a thousand stores across the U. S. handling everything from print design, for store marketing materials, coupons, the billboard, to helping with the website, social media, and. The marketing videos that played in the food court areas. One of the key lessons I’ve carried over from this experience is the importance of understanding the end to end user journey.

AI products require a deep understanding of user flow, behaviors, and feedback loops, unlike non AI products, where we often focus on the happy path of the target user, AI design must account for many possibilities. However, the goal remains the same, ensuring users are happy and fulfilled. I believe that working on MMOs, massive multiplayer online games, honed this skill for me.

These games cater to diverse players with varying needs and there are conversation trees that branch out widely, but they still must converge at key points to maintain the game’s unity and storyline. Designing for AI is like a delicate puzzle, and I believe designers need to practice their strategic skills to tackle these challenges.

I meet a lot of designers intimidated by the word strategy, but strategy in design simply means having a plan to solve user problems by one, deeply understanding user needs, two, identifying how the unique capabilities of the technology such as machine learning can address these needs. And three, specifically for AI, envisioning and anticipating the future of AI experiences.

So we’ve currently unlocked large language learning models, and it’s really cool, but I believe that we’ve slapped on a bunch of chatbots for this, and there’s so much more that we can do to make these tool more usable and friendly, driving mass adoption. At this point, I don’t think my grandparents can pick up ChatGPT and know what to do.

And I do think that UX designers can help drive mass adoption. So overall, reflecting on my journey from print design to AI products, working in retail was incredibly immersive to the point that we were thinking about what should this store smell like? Should a calendar and game store smell like Christmas or candy?

As AI becomes more multimodal, meaning it can process and understand multiple types of inputs like text, images, audio, and even video, designers need to adopt a holistic approach creating an immersive end to end experience that goes beyond the screen.

[00:10:31] Chicago Camps: At Sprintfolio, you’ve helped accelerate the careers of many UX designers.

What are some of the most effective strategies you’ve employed in these design sprints to incorporate AI tools and methodologies?

[00:10:45] Kai Tran: At Sprintfolio, we believe in hands-on, project driven learning. One of the first things I encourage our designers to do is to find an AI project. There’s a lot of hype around AI these days, and having a case study involving an AI project does two key things.

One, it gives designers first hand experience with the unique nuances of AI, and two, it makes them stand out during interviews by providing interesting conversation points. Our core philosophy at Sprintfolio is that to become an AI competent UX designer, you need to design for an AI project, design with AI tools, and learn alongside AI.

We’ve integrated an AI UX mentor and assistant named Leo with our program. Leo is trained in UX principles and processes, and we’ve tuned him to be a Socratic teacher. Meaning he asks thoughtful questions to provoke deeper thinking before providing answers, which overall means less AI hallucination. He is trying to get an answer out of you first to get that context that he needs to respond more effectively.

So with the advancement of AI tools and AI UI design systems that are coming out, I truly believe designers have to really put in the reps for their problem solving skills and their thinking skills. Every week I host workshops on the design thinking process, highlighting which AI tools and methodologies work best at each phase.

For example, in the ideation phase, we might use AI tools that provide rapid prototyping ideas, based on user research data that you input. In the testing phase, AI can help stimulate user interactions to identify potential pain points, when you aren’t able to find those real users at that point, you can catch some of these things before you get that part.

The main strength that I believe a UX designer can bring into the realm of AI tools is that designers now have the ability to take part in engineering. Specifically, prompt engineering. A good rule of thumb is understanding that the output of a chat is dependent on the quality and context given in the input.

We as UX designers have this special opportunity where instead of writing a line of code, we can clearly instruct the model on its mission by writing a prompt. And the strange thing about training a model on the entire corpus of human text is that It takes on our quirkiness. Even using a smiley face emoji can increase its performance.

So I do believe the average designer’s prompt writing ability can be better than an engineer with practice. Our extensive experience distilling complex user requirements and clearly communicating needs is a strength. But it also means we need to get comfortable learning about the technical execution and studying the model development process.

This is why I highly recommend designers to look under the hood of understanding the basics of language learning models. It’s important for us not to treat it like the Wizard of Oz and be aware of its constraints and biases. So by coupling AI tools and methodologies with a strong foundation and the principles, we empower our designers to innovate and excel.

We’ve had a content designer successfully land a contract at Meta, and she was exceptional at leveraging AI in her work. She took part of our first AI focused design sprint and received a notable recognition from it. As more websites integrate AI chatbots into their systems, I see that there will be a greater need for conversational designers, and this is a way for the non visual designers to really take part of the UX process.

[00:15:01] Chicago Camps: For professionals looking to transition into UX design, what advice would you give about incorporating AI projects into their portfolios, and what skills should they emphasize to potential employers?

[00:15:14] Kai Tran: For professionals transitioning into UX design, incorporating AI projects into their portfolios can be a significant advantage.

Like I mentioned earlier, there’s a lot of hype. It makes an interesting interview conversation. This experience demonstrates their ability to work with cutting edge technology and showcases their adaptability and forward thinking minds. Here are a few tips.

One, again, start with real projects. Iron managers can tell the difference between a fresh out of bootcamp designer versus a designer in the field. And that difference is between a hypothetical passion project and real projects with real impact. Often startup projects don’t have huge budgets allocated for user research. Highlighting how you use AI to handle these constraints and how it was used to solve specific design problems and improve user experience is very important for the startups that are popping up.

For career transitioners, I highly recommend leveraging your pre existing experience and expert subject matter to stand out. During the pandemic, we saw so many educators move into UX and work on UX for tools for educators because they intimately understood their users. The successful AI projects that we are going to see in the future are the ones that are understanding which industries that they can get into. So that expert knowledge is going to be key in standing out among competition.

Two, showcase data driven decisions. Employers value designers who can make informed decisions based on data. Include examples of how you use AI to analyze user data, how it saved you time, AKA the startup’s budget, and how it influenced your design choices.

Three, emphasize key skills, focus on skills such as user research, prototyping, and usability testing. Additionally, highlight any experience with AI tools and technologies. Have you dabbled with ChatGPT, DALI, MidJourney? Don’t forget to put these in your resume. They seem really fun and novel, but they are skills.

Four, continuous learning. Demonstrate your commitment to continuous learning by mentioning any courses, certifications, or workshops you’ve attended. This shows potential employers that you are proactive and dedicated to staying current with industry trends. You can also share insights from these learnings and how they influenced your design approach.

Five, find collaborative projects. Highlight any collaborative projects where you worked with cross functional teams, including data scientists and developers. This demonstrates that you can work in a multidisciplinary environment and leverage AI from other team members. For example, you could discuss a project where you collaborated with developers to develop an AI driven recommendation engine.

If you can’t find a real project, you can envision how you can add AI to a project. If you’re wanting to work for a specific company, showing them a solution that speaks to their needs and the potential to grow will really make you stand out.

And then six, ethical considerations. Address the ethical implications of AI in your portfolio.

If you’re using data from there and not real user research, it’s okay. Just say that. The fact that you can recognize the difference is important. Show that you are aware of issues like data privacy, bias, and the importance of human oversight. I think when ChatGPT first came out, it didn’t have that little notice at the bottom that says, ChatGPT can make mistakes, check important information.

There were cases where some lawyers were actually using the things from there in real court cases that affected people’s lives. Those few little warnings that you put in your design can make a huge impact on your users.

[00:19:40] Chicago Camps: Having been at the forefront of design innovation and mentoring nearly 200 design sprints, what are some unexpected challenges and rewards you’ve encountered while guiding new talents in leveraging AI?

[00:19:52] Kai Tran: In terms of challenges, one of the biggest hurdles I’ve faced is related to my own journey into UX design. Since I’m relatively new to UX design, there’s a bit of a double edged sword here. Even though I felt like I’ve utilized the skill within UX design in my ten years of professional design work, I didn’t officially call myself one and I never really got to go through an entire cycle.

I think testing was not really part of my workflows in the past. So some designers might question my capability to guide them, given my shorter tenure in the field. On the other hand, this freshness allows me to relate to their challenges intimately as I’ve recently navigated many of them myself.

Balancing this while trying to run a business has been incredibly demanding. My co-founders and I have poured countless hours into experimenting with different approaches of running design sprints, determining how many people should be involved, how long the sprints should last to balance speed and depth, and what constraints should we impose to foster creativity while maintaining focus?

I couldn’t run Sprintfolio without leveraging AI myself. Our mission when we started, and it still continues, is that we wanted to address the exorbitant fees that some programs charge unemployed junior UX designers. But at the same time, we couldn’t sustain our operations for free. And we certainly tried.

Eventually, I had to prove that I could follow my own advice, upscale and secure a UX job, both for social proof and out of necessity to keep this thing going. Throughout the year and a half we were building Sprintfolio, I applied to 29 jobs, faced 14 rejections, and finally got hired at USAA. This experience taught me resilience and the importance of iterative improvement both in business and personal growth.

One crucial lesson I try to impart to all the designers that go through Sprintfolio is to take a strategic approach to job application. It’s tempting to apply to hundreds of jobs out of desperation, but it’s far more effective to step back and assess what you’ve learned from the batches of applications you’ve sent.

What did you do different each batch? What worked? What didn’t? How can you improve? Improving your portfolio and deepening your understanding of your learnings is vital. This growth mindset, embracing iterative design and iterative learning is key to achieving the goals that you set out for yourself.

In terms of rewards, one of the most fulfilling aspects of mentoring is Witnessing the transformation of designers as they integrate AI into their work. It starts off feeling really silly and you don’t know what you’re doing and you feel like you’re breaking things or it’s just a useless amount of time. But when they finally start to soak in the learnings and become confident in their skills to replicate these results over and over again, and also to push through the ambiguity of an open canvas is incredibly rewarding.

Many come in feeling intimidated, But as they start to understand and use it, they genuinely start glowing and like picking up speed, finishing projects faster, getting more stuff done. And it’s a very awesome transformation to be part of. Another rewarding aspect is seeing the impact of our program on designers careers.

We’ve had designers go on to continue working with the projects they’ve done in our program, or join design agencies of our mentors. When a designer lands a job or successfully complete the project that they’re proud of, it’s incredibly gratifying. It validates our approach and the value of practical hands on learning.

Finally, the collaborative environment we foster leads to really meaningful professional relationships. As mentors, we learn as much from our designers as they do from us. We currently have this super cool design project for an open source tool for developers called Idrinth/api-benchmark. It’s a tool that helps developers in measuring and monitoring their API response times.

The lead designer of this product is a software developer transitioning into UX. She’s using her preexisting knowledge of software development to help build a bridge between designers who want to understand developers better and vice versa.

We’ve had another product where a law student transitioning into UX is collaborating with a lawyer, being guided by a legal animation consulting firm founder, who was also a developer.

And they built a tool to help incarcerated people and their families get access to resources more readily. I call these projects “Serendipity in Action.” And it’s fun to be that matchmaker that has the stars aligning and finding the right people to get this wonderful project off the ground.

I’m really excited about the future of Splintfolio. We are getting close to wrapping up our public beta and having a showcase presentation day with the client. So I’m excited to see their work. And I feel really lucky to be able to see projects come to life and people grow from it.