Stand out in 2026

For your design interviews.

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Hi everyone,

Happy New Year! 🎉 Hope you had the best holidays!

Over the past few months, I’ve had several conversations with design students and junior designers on LinkedIn, including those preparing for internships, full-time roles, and, most often, design interviews.

What stood out to me was not a lack of talent. In fact, most of them had strong portfolios, thoughtful case studies, and a clear interest in building meaningful products. Yet, many of them shared the same concern:

“I’m not sure how to stand out anymore, especially now that everyone is using AI.”

Some were unsure whether mentioning AI tools in interviews would hurt their credibility. Others admitted they used AI extensively but struggled to explain how they did so without sounding as if they were outsourcing their thinking. A few didn’t use AI at all, worried that it would make their work feel generic or replace their design voice.

What became clear is that the challenge isn’t AI itself.
The challenge is knowing how to position yourself as a designer who thinks critically in an AI-assisted world.

Design interviews are changing. Interviewers are no longer just evaluating visual skills or polished mockups, but they’re paying close attention to how candidates think, structure problems, make decisions, and collaborate with tools, including AI.

This newsletter is an attempt to break that down from patterns I’ve observed across conversations, interviews shared by others, and how design teams are increasingly talking about AI in hiring.

In the sections below, I’ll explore how designers can stand out in interviews today by using AI intentionally, articulating their process clearly, and demonstrating judgment, not dependency.

Let’s get into it.

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1. What interviewers are actually looking for in the age of AI

While working on this newsletter, I spoke to a few hiring managers and design interviewers across startups and agencies. I asked them a simple question:

“Now that AI tools are everywhere, what actually makes a design candidate stand out in interviews?”

What surprised me was how consistent the answers were. No one talked about perfect screens, pixel-level polish, or being fluent in the latest AI tool. Instead, the expectations have quietly—but clearly—shifted toward something deeper.

Here are the patterns that came up again and again.

1. Clarity of thinking matters more than the final output

Interviewers are far less interested in what you design and far more interested in how you got there. They’re listening for things like:

- How you frame the problem before jumping to solutions
- How you deal with ambiguity instead of avoiding it
- How you make trade-offs when time, data, or context is limited

With AI speeding up execution, the final output is no longer the strongest signal. Your thinking process, especially under imperfect conditions, is what helps interviewers understand how you’d actually work on their team.

2. Designers who use AI transparently build more trust

One interviewer mentioned that candidates who openly say something like, “I used AI to explore a few directions” often come across as more confident than those who avoid mentioning it altogether. What stands out isn’t the use of AI itself, but:

- Knowing when it’s helpful
- Knowing when it’s not
- Being able to critique, refine, or reject what AI produces

AI is increasingly seen as a collaborator, and those who can explain how they worked with it rather than around it tend to build more trust.

3. Strong communication is now a core design skill

Several interviewers pointed out that two candidates can solve the same problem in very similar ways. The difference is almost always in how clearly they explain their thinking. They pay close attention to:

- How structured your explanations are
- Whether your assumptions are clear
- Whether your decisions follow a logical flow

In live interviews, especially, how you talk through your work often matters just as much as the work itself. The candidates who stand out are using AI not to replace their voice, but to strengthen it.

Which brings us to the first and most important shift in how designers should approach interview prep today.

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2. Treat AI as your interview prep partner

When preparing for design interviews, most candidates underestimate how much context they are expected to hold and articulate at once.

You are not just answering questions but you are expected to recall past projects, explain decisions, defend trade-offs, respond to critique, think out loud, adapt under pressure, and communicate clearly all in real time.

From my conversations with several design candidates, a recurring theme emerged: they knew their work, but struggled to retrieve and structure it under interview pressure.

Project details live in different places: portfolio decks, Figma files, Notion notes, old feedback, interview prep docs, half-written stories in your head.
During interviews, all of this context needs to come together instantly and that’s where most candidates freeze.

This is where AI can play a very specific role as a second brain that holds your interview context, challenges your answers, and simulates real interview conditions, before you ever sit across from a hiring manager.

Step 1: Create a dedicated ChatGPT Project for interview prep

Instead of using random chat threads, the first step is to create a single, persistent space where all your interview preparation lives.

In ChatGPT, go to the left sidebar and select “New project.”

Think of this Project as your personal interview room, one that remembers everything about you, your work, and the roles you are applying for.

Once inside the Project, the most important step is defining how this AI should behave.

Step 2: Give AI context

I’ve noticed candidates saying, “AI didn’t really help me prepare.” It’s usually because they treated it like a search engine or an answer generator. They asked vague questions, got vague responses, and walked away with surface-level confidence that quickly collapsed in a real interview.

Every Project includes an Instructions section.
This is where you tell the AI who it is and how it should interview you. Instead of vague prompts, be explicit.

Use this prompt:

"I am preparing for a design interview and want to use AI as a thinking and preparation partner, not as a shortcut for answers.

I’m applying for a [UX / UI / Product / Visual] Designer role at a [startup / scale-up / enterprise] company. The company primarily works on [mobile apps / SaaS platforms / consumer products / B2B tools], and the role emphasizes user-centered problem solving, clear decision-making, and impact-driven design rather than just visual output.

My current experience level is [student / junior / mid-level], and I want to prepare in a way that reflects realistic expectations for this level—while still showing strong potential, structured thinking, and growth mindset.

I want you to act as a senior design interviewer, mentor, and interview preparation partner. Your role is to:

- Think like an interviewer who has conducted many real design interviews
- Evaluate my responses the way an interviewer would (clarity, reasoning, depth, and trade-offs)
- Help me structure my thoughts, not write answers for me
- Ask probing follow-up questions when my thinking is unclear or shallow
- Point out gaps in logic, assumptions, or missing considerations
- Help me articulate why I made certain design decisions, not just what I did

When responding, prioritize:
- Problem framing and understanding user needs
- Decision-making under constraints (time, business goals, tech limitations)
- Trade-offs and alternative approaches
- Clear communication and storytelling
- Real-world design thinking rather than textbook definitions

Do not give generic or overly polished “perfect” answers. Instead, guide me to think, refine, and improve my own responses—similar to how a strong interviewer or mentor would during real interview preparation."

Step 3: Feed the project your complete context

Now comes the part most candidates skip — and the part that makes the biggest difference.

Your AI interviewer can only challenge you properly if it knows your work.

Use the “Add files” option inside the Project and upload everything relevant, such as:

• Your portfolio PDF

• Case study decks

• Resume

• Project write-ups

• Design critiques you’ve received

• Job descriptions you are applying for

• Notes from past interviews

• Even screenshots of Figma flows exported as PDFs

A useful mindset shift here is this:
almost everything you need to prepare for interviews already exists as text.

Once uploaded, the Project begins to understand:

• your design process

• your strengths and gaps

• patterns in your decision-making

• the kinds of projects you tend to talk about

Step 4: Use AI to deconstruct the job description

Now that the bot has the whole context and your previous work, you can put your current JD and ask it to deconstruct to understand better.

A job description is not just a list of skills it’s a compressed signal of the problems the team is trying to solve, the gaps they’re hiring for, and the type of designer they need right now. When candidates fail to unpack this, they often prepare for the wrong interview.

Using AI to deconstruct the job description helps you move beyond “Do I qualify?” to “What are they actually evaluating when they talk to me?”

Open the project and put this prompt along with the JD to help you understand it better:

"Here is the job description for the design role I’m applying to.
I want you to analyze it as a senior design interviewer or hiring manager, not as a keyword scanner. Assume this role receives many applications and interviews candidates regularly.

Please break the job description down into the following:

1. Core skills and competencies they are likely evaluating
- Distinguish between must-have skills vs. nice-to-have skills
- Identify both explicit requirements and implied expectations
- Call out design skills, soft skills, and business/product thinking separately

2. Types of interview questions I should realistically expect
- Portfolio walkthrough questions
- Case study or whiteboard challenge themes
- Behavioral and situational questions
- Follow-up questions that probe depth, not surface-level answers

3. Signals a strong candidate would demonstrate during interviews
- What interviewers would listen for in answers
- Behaviors, language, and mindset that indicate seniority or readiness
- Red flags or weak signals candidates often show unintentionally

Frame your analysis in a practical, interview-focused way so I can clearly understand what the interview is actually testing, not just what the job description says on paper."

Step 5: Clarify your own design story

Most interviews don’t fail because a candidate’s work is weak. They fail because the interviewer can’t form a clear picture of who this designer is and where they’re heading.

When candidates talk through their experience, it often sounds like a collection of disconnected projects and if you clarify your design story, it gives the interviewers the context.

Here’s a prompt to use: