Modern Skill Stack is a podcast by Uxcel CEO Gene Kamenez. Real stories on how digital product professionals are keeping up with a constantly changing skills landscape.

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There’s a line Elizabete dropped about ten minutes into our conversation.

“You will not be replaced by AI as a designer. But designers who use AI might replace you.”

Easy to nod at. Easy to forget. What I kept circling back to was the mechanics, what it actually looks like when you’re using AI well, where most designers go wrong, and why Elizabete thinks the entire conversation about tools and prompts is already missing the point.

Elizabete founded Collectif Studio, a consultancy built around helping companies move from ambiguity to execution, specifically in the AI transition. Before that, over a decade as a UX and service designer. Startups. Large organizations. A stretch at Accenture Song, where design decisions carry real weight and the margin for messy thinking is thin. Her career moved through the UK, Germany, the UAE, and a meaningful period in Denmark, where she developed real grounding in co-design and facilitation. Those skills are now the core of how she approaches work and teaching.

She’s now a regular workshop facilitator at Uxcel. Her hands-on AI workshops sell out quickly, and consistently received 4+ rating. This is why I wanted her to walk me through what she actually teaches, why that structure, and what she wishes more designers understood right now.

This episode is brought to you by Uxcel.

Uxcel is a learning platform used by 500,000+ product professionals and 200+ organizations to build cross-functional skills across UX design, product management, and AI. Learn through short, gamified courses that fit into a working day, earn certifications, and build a portfolio with real-world project briefs.

Start learning at uxcel.com

You’ll learn:

• Why AI works best as an intern and fails badly as a director, and what that means for your design workflow

• How one team cut a 20-hour copywriting task down to 2 hours without sacrificing quality

• The “20% upfront” rule Elizabete uses before touching any AI tool

• Why mindset matters more than knowing the right prompts

• The workshop structure she uses to help designers overcome fear and build real AI habits, and the structure you can adapt for your own practice

Timestamps

• 00:00 Intro

• 01:17 Importance of strategic AI orchestration

• 03:38 Elizabete’s career journey

• 06:01 Transition from working 9-5 to starting a studio

• 07:12 How to use AI to reduce boring work

• 10:59 Spend the first 20% of AI time doing this

• 13:01 The importance of quality input

• 15:01 Live workshop walkthrough

• 22:43 Overcoming blockers in AI workflows

• 26:33 Final tips for designers using AI

• 27:29 Outro

My biggest takeaways

AI is a great intern and a terrible director

The framing that cracked this open for me: Elizabete doesn’t think about AI as a threat or a replacement. She thinks about it the way she’d think about a capable junior: someone who can execute a lot, but who absolutely should not be left in charge of decisions.

In Elizabete’s words:

“AI is a great intern and a terrible director. The decision making always stays with me or with the decision makers in different companies. It’s really about utilizing AI to give those boring tasks that you don’t want to do.”

Hand AI a vague prompt and expect it to figure out what you actually want, and you’re setting yourself up for mediocre output and real frustration. Treat it like an intern who needs a clear task, a defined scope, and honest feedback, and it becomes something you can actually rely on.

Try this next time: before you open any AI tool, spend a few minutes writing down what you actually want the output to look like. Not “help me with my research.” Something closer to: “I need three distinct user personas for a 30–45 year old audience who are lapsed gym members. Each persona should include a core motivation, a primary frustration, and a quote in first-person voice.” That shift in how you brief the tool changes everything you get back.

The real ROI isn’t time saved, it’s where that time goes

Elizabete shared a specific case: a team whose designers were spending around 20 hours on copywriting tasks. Necessary work, but not the kind that requires a UX professional’s judgment.

In Elizabete’s words:

“I helped the team speed up their process from 20 hours to two hours on copywriting. Give the task to AI, provide the right background information, and the team can spend their time on more valuable and strategic tasks.”

The number is definitely striking. But the more interesting part is what she says next, where the time goes. Getting 18 hours back means nothing if those hours just fill with other low-value work. The question worth asking first (before you touch any tool) is: what are the high-value activities your team is currently skipping because the tedious stuff is taking up most of the calendar?

The designers who thrive are the ones who were already solving problems

When I asked Elizabete whether job anxiety partly comes from losing the comfort of busy work, knowing exactly what you’re supposed to do each day, she didn’t soften it.

In Elizabete’s words:

“The skills that will be valued in the age of AI are really this critical thinking and problem solving. If you’ve always been a designer who solves problems, this is an amazing time for you because you can give all these more boring tasks to the AI. But if for the last year or so, or if you’re maybe a new designer coming in and you’re really focused more on the pixel pushing, then it’s the right time now to invest more into these problem-solving skills.”

This tracks with what I see on our side at Uxcel. The designers who feel most grounded about their futures aren’t the ones with the longest tool list. They’re the ones who can frame a problem clearly, who know what a good solution looks like before they’ve built anything, who can make judgment calls when the AI output is close but not quite there.

If you’ve built those skills, AI mostly just gives you more hours. If you haven’t, it makes the gap more visible.

Spend 20% of your AI time before you start

The sessions where AI frustrated Elizabete most were the early ones, before she worked out what was actually going wrong.

In Elizabete’s words:

“I learned how critical it is to spend the first 20% of your working time with AI to define what you want to get out of it and for what purpose. Whenever I work with a tool, it’s important to first define the right prompt, to really understand what I want to get out of it.”

Twenty percent sounds slow when you’re trying to move fast. But on a two-hour task, that’s 24 minutes of thinking before you type a single word into the tool. What does a good output actually look like? What context does the AI need that it won’t have by default? What would a bad output look like, so you can catch it?

Most people do the opposite. Open the tool, type something approximate, get something approximate back, spend an hour trying to salvage it. The 20% rule front-loads the thinking, and it’s counterintuitively faster.

To be honest, I’m still not sure I’ve fully adopted this habit. I know the rule but I find myself skipping it when I’m in a rush.

Mindset is the skill, tools are just the vehicle

The part of the workshop structure I found most interesting wasn’t which tools Elizabete chose or which prompts she favors. It was what she said the workshops are actually teaching.

She runs a two-task structure: an individual research exercise followed by a prototyping task, outputs from the first feeding directly into the second. Participants pick from three project clusters, a dating app, a food delivery product, a fitness app, enough creative distance from their day job to actually experiment without everything feeling high-stakes. After each task, the group shares what they built, how they prompted, what surprised them.

But when I asked what the workshop is really about:

In Elizabete’s words:

“This isn’t really about the prompts and the tools. Of course those matter, but it’s more about the mindset. Understanding what you can do with AI, and focusing on practical ways to improve your workflows instead of being blinded by the AI hype.”

I’ve seen enough designers running in place to know this is right. The hype creates a kind of paralysis: you feel like you should be using these tools, but you’re unsure which one, or for what, or whether the one you chose is already obsolete. The shift Elizabete is after is simpler than that: stop hunting for the perfect tool. Find one task in your current workflow that AI could lift off your plate. Do that one thing. Learn from it. Then do the next.

That’s how habit formation actually works. More durable than any prompt library.

“Garbage in, garbage out” — and why foundations matter more now, not less

There’s a version of the AI conversation I keep running into: now that AI can generate UI, draft copy, and synthesize research, strong foundations matter less. Just learn the right prompts.

Elizabete pushed back. So did I.

“It’s the garbage in, garbage out principle. If your input is garbage, the output will be garbage.”

If you don’t know what a well-structured persona looks like, you can’t tell when AI hands you a bad one. If you don’t understand what makes a prototype testable, you can’t brief the tool to build something useful. If you can’t recognize a strong research insight, AI-assisted synthesis just scales your confusion faster.

The designers getting the most out of these tools know enough to give good direction, and enough to evaluate what comes back. That’s a fundamentals story as much as an AI one. Maybe more.

A note from Gene

Every episode of this podcast starts with the same question: what’s the one skill you’re personally focused on right now? Elizabete’s answer was “strategic AI orchestration”. Not tools, not prompts, but learning how to look at a design workflow and understand where AI belongs and where it doesn’t.

That’s the same question Uxcel was built to help product professionals work through.

We’ve built courses specifically on AI skills for product teams, structured to fit into a real working day. Five-minute lessons, practical exercises, real certifications you can point to.

Start learning at uxcel.com

And if you haven’t subscribed yet, Modern Skill Stack drops new episodes with practitioners working through these questions in real time. Subscribe on YouTube.

Resources and tools mentioned

Workshops:

• AI as a UX Co-Designer (Uxcel community workshop by Elizabete): https://luma.com/UxcelAIUXCoDesigner

• AI + Personas deep dive (upcoming Elizabete workshop): https://luma.com/UxcelAIUXPersonas

Where to find Elizabete:

• LinkedIn: https://www.linkedin.com/in/elizabete-staerfeldt/

• Collectif Studio: https://www.collectif.team/

• Uxcel workshops: https://luma.com/uxcel

Production and marketing by Uxcel. Interested in appearing on the Modern Skill Stack podcast? Reach out at partnerships@uxcel.com

What’s the one task in your current workflow you’d hand off to AI first, and what’s stopping you? Share it in the comments.

Cheers,
Gene

Modern Skill Stack

Real stories on how digital product professionals are keeping up with a constantly changing skills landscape. Hosted by Gene Kamenez, CEO of Uxcel.

Listen on YouTube.

I’ve been in rooms where a designer did more than anyone else on the project, and still walked out of the performance review empty-handed. Not because their work was weak, but because nobody knew it was theirs.

Oleksii Tkachenko has lived that exact story. He’s spent the years since figuring out how it happens and, more importantly, what to do about it.

Most recently he’s worked as a Senior Content Designer at Perk, where he focused on AI-powered assistant experiences. Before that, three years at Klarna: one of the most demanding content environments in European fintech, with complex payment products, strict regulatory constraints, and six or eight payment methods to maintain simultaneously.

He’s also an instructor at Uxcel, where he co-created the course Building Content Design Systems. Which means he spends a lot of time watching designers at all levels repeat the same mistakes he once made.

The one mistake that shows up the most? Working incredibly hard while staying almost completely invisible.

When I asked him when he first understood that a senior title doesn’t automatically come with influence, he recalled a specific performance review he had. He’d been supporting every PM on the team, fielding urgent ad hoc requests, staying across every project. Naturally, he assumed that level of effort and hard work would get him at least some recognition and praise. It didn’t. His manager’s response was something like: “Sounds good, but I didn’t see much.”

That gap between what you’re doing and what anyone actually knows you’re doing is what this conversation kept coming back to.

This episode is brought to you by Uxcel.

Uxcel is a learning platform used by 500,000+ product professionals and 200+ organizations to build cross-functional skills across UX design, product management, and AI. Learn through short, gamified courses that fit into a working day, earn certifications, and build a portfolio with real-world project briefs.

Start learning at uxcel.com

You’ll learn:

• Why doing more work often means less influence, and the logic gap behind it

• What the “ego trap” is, and why it keeps even experienced designers from being taken seriously

• What real influence actually looks like inside a product team (it’s not about title)

• The one workshop Oleksii runs every time he joins a new company

• A two-step playbook to start building visibility today, even if you feel like you’re starting from zero

• Why AI won’t replace your judgment, and why that’s the right thing to bet on

Timestamps

• 00:00 Intro

• 01:54 The importance of conversational design

• 04:50 Difference between conversational design and chatbot flows

• 07:34 Career journey from software engineering to content design

• 12:06 Robot vs. human design experience

• 14:44 How to get your first job in design

• 19:18 Understanding the gap between title and influence

• 27:35 Why emotional detachment is important for your career

• 32:24 What real influence looks like

• 37:01 Visibility and communication strategies

• 41:43 Playbook for building influence and visibility

• 46:39 Navigating the AI landscape in design

• 53:47 Promoting yourself and finding your advocates

• 55:45 Outro

My biggest takeaways

You can work yourself to exhaustion and still be invisible

Oleksii didn’t arrive at this through theory. He learned it during an actual performance cycle at Klarna covering multiple PMs, jumping on ad hoc requests, staying close to every product area. He assumed the hard work would speak for itself.

It didn’t.

In Oleksii’s words:

“There is this huge gap in logic, thinking that working so much means everyone knows you’re working so much. What happened to me. I didn’t have enough time to socialize anything. I didn’t have enough time to present anything or even document anything. It was mostly me knowing I do so much and then hoping that everyone automatically knows about this. But everyone was like, oh, really? What exactly did you do? People don’t know. And you don’t need to assume they do.”

There’s a second layer to it. Because he was constantly in execution mode, he started missing planning meetings. Skip one, and the pattern locks in fast. People stop expecting you there. Slowly, he became what he calls “an executioner”: someone carrying out decisions made by others instead of shaping them. Senior in title only.

The uncomfortable truth is simple: visibility isn’t a byproduct of hard work. It’s a separate function. Treat it like one, or your output fades into the background despite how good it is.

The ego trap: designers assume their value is obvious to everyone

Why do so many capable designers end up in this position? Oleksii traces it to something he calls the “ego trap”, a deeply held assumption that designers are the heroes of every project, and that everyone else already recognizes what they bring.

He references the book “Why Design Is Hard”, which he says pins this dynamic precisely. The frustration designers feel when they’re overlooked isn’t random, but comes from a specific false premise.

In Oleksii’s words:

“We as designers very often have this strong ego trap in our mind, thinking that the designer is usually the hero. Basically the most important person who comes in and saves the project. We automatically assume that everyone understands our value. But it’s funny to assume that, because we have fewer designers in the world than product managers and other roles.”

A COO who never explained their contributions would be invisible too, regardless of their impact. Same logic applies to a senior designer.

It’d be wrong to say this is just ego. Think of it more as a structural blind spot: designers spend years in places where design’s value is assumed. Then they join organizations where it is not, and then be surprised when their work does not get recognized.

The fix isn’t to become someone who performs self-promotion constantly, but accepting that communicating your value is part of the job. Not a game of politics on top of the work. Part of the actual work.

Real influence starts before the work begins

When Oleksii strips away title and politics, his definition of real influence comes down to one question: are you in the room when the initial decision gets made?

Not the room where someone hands you a brief. The room where the brief gets written.

In Oleksii’s words:

“Number one (and it really is number one) is being involved when the initial decision is made about a project. Being part of the planning is part of your influence, because that’s where you can push through a project you’ve been thinking about, or question a project that has no real design support. The scary part is that you have to take responsibility. You have to say, “Yes, we need to do this because of this and this.” That’s where you become senior. That’s where you act as a senior.”

The second dimension is relationships across disciplines. Oleksii says he understood this too late: designers need to build genuine working relationships with PMs and engineers, not just other designers. That will help you speak in planning conversations about what’s technically feasible in a realistic timeline. That skill compounds over time and turns you into someone people consult.

The third dimension is team growth. Be the person who educates the broader organization about design. Run internal sessions. Help PMs grasp what they’re actually getting when a designer is involved. When your team’s value is understood across the org, that understanding attaches to you personally.

As Oleksii puts it: “Influence is about trust. If you have trust from a certain group of people, you have influence over whatever they’re making.”

Visibility is about business impact, not effort

Designers who know they should be more visible often still get it wrong. They show up to the all-hands, walk through every step of their process, explain how difficult the content system was to build and leave people impressed but unclear on why any of it mattered.

That’s the distinction Oleksii draws between activity-based visibility and impact-based visibility.

In Oleksii’s words:

“The right visibility is about making sure that when you present what you’ve done, you explain why you did it and what benefit it brings to the company in terms of money or how it helps other teams be more productive. When we built the email system at Klarna, one obvious benefit was consistency in how we spoke to customers. But the bigger win was for the operations team. Instead of writing new content every time Klarna launched in a new country, they could take the ready-made templates, handle any local regulatory requirements, and go. They spent less time on it. That’s what I presented: good for the business, and less work for you.”

Notice the reframe: not “here’s what I built and why it was technically demanding.” But “here’s what changed for you because this exists.”

Even if your project doesn’t have measurable outcomes yet, you still need to speak up. Don’t invent impact. Share a realistic estimate of how it will help the business or other teams. When PMs hear it framed that way, they stop thinking about your task list and start thinking: I want that person on my project.

The practical playbook: be in the room, speak the language, protect your time

Oleksii’s playbook for building visibility and influence comes down to three moves.

The first one he does at every new company without exception. He starts by running a “ways of working” workshop with his team.

In Oleksii’s words:

“The top thing I do when I join a new company is run a ‘ways of working’ workshop. We talk about how they previously worked with content design. Maybe they never did. How do they understand the role? At what stage do they think I should be included? And when they say they think I should be included somewhere after planning, I say: “Can you include me here instead? This is why, and here I can impact the product much better.” That workshop helps you actually be at the right place at the right time.”

This works because it makes the inclusion conversation explicit from day one. People aren’t leaving you out maliciously. They genuinely don’t know how or when you need to be involved. This approaches teaches them, before the pattern of exclusion has a chance to set in.

The second move is speaking in business language consistently. Not design language. Language that connects your work to outcomes other people care about delivered in formats that is familiar to them. Slack updates after releases. A standing slot at the Friday all-hands. A one-pager for the PM who prefers to get information that way. The goal is to become a regular, expected signal, not a one-off presentation.

The third move is protecting time to track your own impact. It’s the first thing that gets dropped when things get busy. If you never go back and check what your last release actually did, you have nothing concrete next time. You end up, as Oleksii puts it, “really busy but very disconnected from the product.”

Two steps to start building influence today

When I asked Oleksii what someone who feels competent but invisible should do first (not next quarter or after the next review, but today), he said: self-promotion and finding an advocate.

In Oleksii’s words on self-promotion:

“Start small. Make a Slack post about what you just released and why it matters. Sometimes even your own content design team doesn’t know what you did. So start there. Then post in the broader design channel. Then go to the design all-hands. Build outward from there. The key is making it a repeatable experience, not a one-off, so people come to expect your updates.”

And on finding your first advocate:

“The second thing is my favorite, because when I give this advice it always works. Find the people who will be your first advocates. Don’t go to work tomorrow trying to make everyone understand and respect you all at once. Start with one PM, perhaps someone who already sees some value in content design but isn’t fully sure yet. Work closely with them. Explain your value. Then communicate publicly: ‘Me and this PM did this, and here are the business outcomes.’ The more advocates like that you build (especially PMs, because they’re part of planning), the more you’ll have people saying, “We need a content designer in the room.” Those people become your biggest allies.”

Both steps share the same logic: start small, build outward, let the effect compound. You’re not on a mission to change the entire organization’s understanding of design in one presentation. You’re on a mission to find one person who gets it (or is at least close to it), work on something together, and use that as a foundation.

The PM detail matters specifically. Oleksii isn’t saying find a friend. He’s saying find someone who sits in planning, and whose endorsement puts you in the conversations that decide what gets built. That’s where influence lives.

AI will take part of your job, but not the part that matters most

Oleksii has a more personal stake in this question than most. He’s been directly affected as he lost his job because of AI. So when he said he’s not worried, it brought some relief.

His argument is that AI is already taking parts of the job. In some cases, that includes writing tasks that designers truly enjoyed. But what it leaves behind is the judgment, the evaluation, and the ability to recognize that an output is or isn’t good. And that is precisely what years of real-world experience and studying builds.

In Oleksii’s words:

“AI will never substitute your judgment. People use AI and say, “Look, I’m a designer now” or “I’m a filmmaker.” But those people haven’t gone through the process of learning in university or real experience in tech companies. They don’t have the same judgment. That’s why they show a trailer and say, “Look at this great thing I did.” But if you had judgment built on real experience, you would recognize that the output isn’t really that great. Judgment is our thing. For a really, really long time, that part belongs to us.”

He also makes a point specific to content designers: prompting is writing. The people who can give AI the clearest, most precise instructions are the same people who’ve spent years thinking carefully about language. And in an AI-augmented workflow, that’s not nothing.

His vision for the junior content designer of the near future isn’t someone replaced, but someone AI-native who will handle more strategic UX work while AI offloads execution tasks that used to consume most of their day.

A note from Gene

The skills that make you good at your craft and the skills that make you visible inside an organization are two different skill sets.

What Oleksii described is a common trap in product careers: working hard, staying helpful, then realizing nobody noticed. His solution is to do the second half of the job, the part most people don’t even realize is part of the job.

If you want to work on communicating your value, connecting work to business outcomes, and operating effectively across disciplines, start by learning skills to support that.

We have 40+ courses across UX, PM, and AI skills, including Oleksii’s own course on Building Content Design Systems. Lessons are short and fit your working day. Track your progress, get certified and build skills your team will notice.

Start for free at uxcel.com.

Resources and tools mentioned

Books:

• Why Design Is Hard by Scott Berkun with Bryan Zug: scottberkun.com/why-design-is-hard/

Tools:

• ChatGPT: chatgpt.com

• Gemini: gemini.google.com

• Claude: claude.ai

Where to find Oleksii Tkachenko

• LinkedIn: linkedin.com/in/tkachenko-oleksii

• Building Content Design Systems course: uxcel.com/courses/building-content-design-systems

Production and marketing by Uxcel. Interested in appearing on the Modern Skill Stack podcast? Reach out at partnerships@uxcel.com

What’s the biggest thing stopping you from being more visible at work right now?

Cheers,
Gene

Modern Skill Stack — Real stories on how product professionals are keeping up with a constantly changing skills landscape. Hosted by Gene Kamenez, CEO of Uxcel.

Listen on YouTube.

I sat down with Florian Boelter, a Staff Product Designer at Juro, a legal-tech platform serving in-house legal teams, where he has spent 3 years leading AI adoption across the design organization. Outside his day job, he runs Open Doors, a community that connects junior designers with job opportunities, portfolio feedback, and hiring insights every week. His sell-out workshops on AI in UX and vibe coding for designers on Uxcel consistently rate above 4.5.

What makes Florian’s perspective different is that he sits at three intersections most designers don’t: building AI features inside a real product, experimenting with AI tools to build his own side projects, and advising hundreds of junior designers on how to break into the industry right now.

So when I asked him what skill he’s personally focused on learning today, his answer wasn’t what I expected.

This episode is brought to you by Uxcel.

Uxcel is a learning platform used by 500,000+ product professionals and 200+ organizations to build cross-functional skills across UX design, product management, and AI. Learn through short, gamified courses that fit into a working day, earn certifications, and build a portfolio with real-world project briefs.

Start learning at uxcel.com

What you’ll learn

• Why a staff product designer is doubling down on fundamental UX skills, not AI tools right now

• The three-layer AI skill stack for designers and PMs in 2026: from table stakes (LLMs) to interesting (vibe coding tools) to advanced (Cursor, Claude Code), and which tier you actually need

• How AI in products is shifting from sloppy to truly embedded features, and what that means for how you design them

• What happened when Florian pitched AI-assisted design system work at Juro in 2023, and why the engineers moving to Cursor six months later changed everything

• The exact portfolio gap separating junior designers landing roles at cool companies from those who keep getting ghosted

• Why the product triad of design, PM, and engineering is getting closer, and the cross-functional skill that’s driving it

Timestamps

• 0:00 Introduction

• 5:00 The importance of design fundamentals

• 9:49 Role of AI in design and user experience

• 13:34 Building AI features: necessity or nice-to-have

• 19:05 Misconceptions about AI in design

• 22:28 Do designers need to learn to code?

• 25:06 The role of systems thinking in design

• 27:20 Empowering the product triad

• 31:21 AI tools and skills bare minimum

• 34:21 Building internal tools with AI

• 45:22 Leading AI adoption in organizations

• 51:27 Which designers are thriving vs. which are struggling right now

• 56:38 The importance of foundational skills

• 1:02:19 Advice for staying relevant in design

• 1:04:22 Outro

My biggest takeaways

The differentiator with AI isn’t an AI skill, it’s what you can imagine

When I asked Florian what skill he’s personally focused on right now, I expected him to name a tool or a model. Instead, he said typography, color, and composition. Not because he lacks confidence with AI (after all, he’s been building with it since the early days) but because he’s identified where the real gap will open up.

In Florian’s words:

“If I can prompt AI to do something, it’s not a matter of the output itself that’s produced. It’s more a matter of what I can actually imagine and how I can describe what needs to go in. So the output eventually becomes something nice and novel. That’s why I’m trying to mostly focus on scaling up in craft; because I otherwise feel quite capable in the AI department already.”

This is the clearest framing I’ve heard of why craft matters more, not less, in an AI-assisted workflow. You’re not competing with the tool. You’re competing with other people who are also using the tool, and the gap between them is the quality of their vision and the vocabulary they use to direct it. When everyone can generate, the one who can imagine well and describe precisely wins.

The action step here is counterintuitive: if you feel behind on AI skills, stop and check whether a foundation problem is underneath that. Florian argues that fixing the foundation pays a higher return than chasing the next tool.

LLM fluency is table stakes. Vibe-coding tools are where it gets interesting.

Florian draws a clean line between what’s mandatory and what’s still emerging. Using ChatGPT, Claude, or Gemini to accelerate day-to-day work (e.g. summarizing user feedback, drafting copy, getting quick context on something) that’s no longer optional for designers or PMs, or frankly for anyone in a knowledge-work role.

In Florian’s words:

“A basic command of ChatGPT, Claude, or Gemini — I feel like that’s definitely a mandatory skill that even goes beyond design into non-tech jobs at this point. But the more interesting place is where AI is embedded in areas and functions where you can’t even see it’s AI. It’s just helping you get the job done. That’s where the complexity is, and that’s where it’s actually getting interesting.”

The practical split Florian recommends: once LLMs are part of your daily workflow, the next layer is picking one higher-level tool such as Lovable, Figma Make, or similar, and spending a focused weekend with it. Build something you’re actually concerned with at work. The goal isn’t to launch anything. It’s to understand what’s possible before you need to explain it to anyone else.

Beyond that, the tools diverge by role. If you work heavily on design systems, tools like Claude Code and Cursor are already mature enough to be worth the investment. If you’re in brand or visual design, image generation models have a flat learning curve and are already producing professional-grade output when guided by someone who knows what “good” looks like.

AI in products has moved past the GPT-wrapper era, and most teams are behind the shift

Three years ago, “adding AI to your product” meant slapping a chat interface on top of an API call. Florian watched that era play out, saw the gap between expectation and reality, and thinks about it as a designer who was on the receiving end of feature requests that weren’t yet buildable.

That era is closing. The products getting it right now are ones where AI is embedded at the workflow level, where you can’t even see it’s AI, because it’s just removing friction from the thing you were already trying to do. Florian points to Intercom’s Finn as the clearest example: it started as a wrapper, took years of infrastructure work to mature, and is now genuinely capable.

The trap Florian flags is the assumption that “we have a capable model, so we can ship something capable.” The infrastructure underneath still takes time to build right. He draws a parallel to the cloud migration era of the early 2010s, when the technology existed but companies couldn’t flip overnight. The AI transition is faster, but not instantaneous.

For designers, the practical implication is that understanding AI systems at a conceptual level, what an LLM can and can’t do, what agents are actually orchestrating, how guardrails work, makes you a significantly more effective design partner on these features. You don’t need to understand how to build them. You need to understand enough to design around their real behavior, not their idealized version.

Systems thinking is the non-technical skill that unlocks AI-assisted building

One of the more useful moments in our conversation came when Florian described what actually enabled him to vibe-code things that work, not just things that look like they work. The answer wasn’t learning to code. It was systems thinking.

In Florian’s words:

“The one thing that for me unlocked all of that and enabled me to bug-fix things I would never be able to write myself is systems thinking. Understanding how the systems that AI is building for me work on a high level. Without that, I don’t know that I need a function to do this and that. I need to understand what the front end and back end are, what’s happening in my database, what happens if I need to change something there. Those concepts, if you know those, you’re good to go.”

This is a useful reframe for anyone who’s felt blocked by vibe-coding tools when things go wrong. You don’t need to write the code. You need to understand the structure well enough to describe what’s broken and what you want instead. That’s a different skill that is closer to systems design than engineering and it’s one that designers and PMs already have more of than they often realize.

His practical threshold: surface-level tools like Lovable require no visible code. If you want to go deeper into Cursor or Claude Code territory you need a working model of front-end vs. back-end, basic data flow, and what a component actually is. That’s learnable without an engineering degree.

The portfolios making Florian feel imposter syndrome share one pattern

Florian runs Open Doors, a weekly newsletter where he spotlights early-career design portfolios. He sees hundreds. And across all the different paths, university, bootcamps, self-taught, he’s identified a consistent pattern in the ones that are landing jobs at cool companies versus the ones that aren’t.

In Florian’s words:

“The people combining solid fundamentals with AI experimentation are the ones going through the roof. Those are the portfolios that make me feel imposter syndrome. The people that are struggling are the ones rushing the fundamentals, treating them as a box to check rather than a foundation to build on. Once the foundation is solid, throw AI in the mix — build something in Lovable, make it cool, post it. That’s the sequence that’s working.”

The market has shifted dramatically from a decade ago, when demand was high enough that basic portfolios could get you in the door. That’s no longer true. Hiring managers in 2026 expect typography and color to be done well, but that’s the bare minimum, not what gets you hired. Florian is direct: if you don’t meet that bar yet, the answer is to stop applying and reinvest in the foundation. Then, once it’s solid, AI amplifies what you’ve built rather than exposing what’s missing.

AI is a multiplier. Applied to strong fundamentals, it produces work that stands out. Applied before the fundamentals are there, it surfaces the gaps faster and more visibly.

AI adoption inside teams is a change-management problem, not a technology problem

Florian’s experience leading AI adoption at Juro offers a grounded view of what this actually looks like inside a real organization that’s generally open to change, had genuine friction to solve, and that still moved slowly at first.

In Florian’s words:

“Back when I started, I was sitting there with early GPT trying to write scripts and it kept failing. If I’d brought that anywhere, no one would have said ‘great, let’s have you push code now.’ But things evolved. And eventually people higher up came to me because they’d seen what I was doing. You want to be ready for that moment. And a lot of this isn’t work-unrelated. You can try it during work and call it an experiment.”

His advice for people who haven’t started yet: the window of “I’ll get to it” is closing. Four years after ChatGPT became publicly available, still not having daily usage of these tools is a real gap. Not a catastrophic one, but a meaningful one. Start with the thing that’s actually mandatory (LLM fluency), then move outward from there at a pace that doesn’t create burnout.

And for people already using these tools: the recognition that they’re imperfect is a feature, not a bug. Knowing where they fail and what they’re not good at is what makes you effective at using them where they do work.

A note from Gene

I started Uxcel because I know what it’s like to want to level up and have no accessible path to do it. When I began designing in 2010, the options were expensive courses that required you to fly to London, or bootcamps that cost five to ten grand. Neither of which was remotely accessible for most people.

What Florian said at the end of our conversation meant a lot to me: that when junior designers ask him where to start, Uxcel is now his default recommendation. Not because it’s the easiest option, but because it goes deep when depth is needed, it’s repeatable, and it doesn’t require you to bet three years or thousands of dollars on an outcome.

If you’re a designer or PM trying to close skill gaps, whether in craft, AI, or the cross-functional skills that are becoming more valuable as the triad gets closer, we’d love to help.

Sign up for Uxcel here.

Resources and tools mentioned

Tools discussed:

• Lovable — AI-assisted web app builder; Florian’s recommendation for first vibe-coding experiments

• Figma Make — Figma’s AI prototyping layer

• Cursor — AI-powered IDE for designers working on code-heavy workflows

• Claude Code — Anthropic’s agentic coding environment

• Midjourney — Image generation; recommended for visual/brand designers

• Intercom Fin — Referenced as a model of AI-native product evolution done right

Where to find Florian:

• LinkedIn: www.linkedin.com/in/florian-boelter/

• Open Doors Newsletter: www.opendoorscareers.com

Production and marketing by Uxcel. Interested in appearing on the Modern Skill Stack podcast? Reach out at partnerships@uxcel.com

What pattern do you see in your own team? Are people doubling down on fundamentals, on tools, or trying to do both at once? Drop a comment below.

Cheers,
Gene