Running design reviews, flow checks, accessibility reviews, and pre-launch UX audits on Figma files

How do I use AI as a product designer?

I've recently started experimenting with AI in my work to speed up the process. I primarily use Claude Cowork and recently started trying out Claude Design. I'd like to share what I liked:

1. Checking the task for completeness. When we're talking about a product task that results in a specific mockup or flow, it's important that the task is described as thoroughly as possible, as the outcome directly depends on the designer's immersion in the context. That's why running the task through AI and challenging the product designer can significantly change the final outcome.

2. Task planning. I often work on large projects where tasks need to be decomposed, otherwise they're quite difficult to approach. Claude is great for breaking these tasks down into stages and subtasks, which become milestones that are understandable for both you and your team.

3. Conducting quick research at the initial stages of the task. Previously, it was necessary to spend a considerable amount of time defining user segments, jobs to be completed, and so on. Now, it's all done in one or two prompts, and you immediately receive a significant amount of research that helps you immerse yourself in the context of the task.

4. Mobbin's MCP integration into Claude. It opens up a wealth of opportunities, for example, a quick and detailed analysis of direct and indirect competitors, finding killer features, analyzing application flow, and suggesting proposals for your own product. This greatly accelerates the initial immersion in tasks because it immediately provides sufficient context for what's happening in the market.

5. Highlighting weaknesses and analyzing what has been accomplished. For example, you're reworking a flow to improve it and asking Claude to analyze it and compare it with competitors' flows on Mobbin. Typically, 30-40% of the insights turn out to be quite useful, while the rest either miss the point of the interface or provide information that's valid outside the context of the product.

6. Finding missed corner cases. When you're designing a completely new section of the interface that hasn't existed before, it really helps you understand whether you've missed anything; the development team will definitely be grateful for it.

I'd say Claude is now a great work assistant and fits perfectly into anyone's workflow. It allows me to significantly speed up previously time-consuming stages, allowing me to focus on what's most important: high-level planning, polishing mockups and UI work, more time on micro-animations, and ensuring the interface is responsive to user interactions.

This is what working with AI in design feels like…


Most designers approach AI like a shortcut.
That’s the wrong mental model.

AI is not here to reduce effort.
It’s here to expand thinking capacity.


When I integrate AI into my workflow, a few shifts happen:

• I stop thinking in single solutions and start thinking in systems of possibilities
• I move from “what should I design?” to “what are the 10 better ways this could exist?”
• I spend less time executing and more time questioning assumptions
• I validate ideas earlier, instead of polishing the wrong direction

AI becomes a pressure-testing layer for my decisions.


A practical lens on using AI effectively:

Instead of asking:
“Give me a UI for this”

Ask:
“What are 5 fundamentally different ways to solve this problem?”

Instead of:
“Write microcopy”

Ask:
“What would confuse a first-time user here?”

Instead of:
“Generate a wireframe”

Ask:
“What are the edge cases I’m missing?”


The advantage is not speed.

The advantage is better questions → better decisions → better outcomes.

Designers who treat AI as a generator will stay average.
Designers who treat AI as a thinking partner will move ahead quickly.


If you’re looking to bring this level of thinking into your team or workflow, I conduct practical workshops and training sessions on AI for design.

📩 Reach out to collaborate or schedule a session.

And if you want the prompt to generate this image, drop a like and comment “PROMPT”.

How I actually use AI in product design.

Most teams are using AI to move faster.
That’s not the hard part.
The hard part is not making the product worse in the process.

Here’s how I actually use AI in product design right now.

1. I use AI for structure, not decisions:

Layouts, variants, responsive states.
Anything repetitive.

That used to take hours. Now it takes minutes.
But I’m not asking it what the experience should be.
That’s still on me.

2. I treat the first output as a draft, not the answer:

AI gives you something that looks right.
That’s the danger.
Spacing might be fine. Flow might be off. Edge cases are missing.

If you don’t know what “good” looks like, you’ll ship it anyway.

3. I stay close to the system:

Design systems matter more now, not less.
Tokens, constraints, patterns.
If the system is solid, AI outputs improve.

If it’s loose, you just get cleaner-looking chaos.

4. I use it to explore, not finalise. It’s great for:

• Trying directions quickly
• testing layout approaches
• getting out of a blank state
• But the final 20% still needs taste.

That hasn’t changed.

The shift isn’t that AI is designing for you.
It’s that it’s removing the parts of design that were never the point.

Less time pushing pixels.
More time deciding what actually matters.

Most people will use this to skip thinking.
The advantage is using it to think better, faster.

Curious how others are actually using this in real workflows — not just the flashy demos I'm seeing on socials 👍

I used to spend hours on briefs, planning, and file setup before designing.

Now, my AI-powered design workflow takes me from idea to design in 4 steps:

Step 1: Voice → Structured brief

I do a 2-3 min voice brain dump using Whisper Flow. It captures everything and sends it to Notion. No typing, no formatting. Just talk and it's documented.

Step 2: Brief → Tasks → Daily focus

Notion AI then breaks the brief into tasks and keeps everything in one dashboard: tasks, notes, docs, links and even daily todos. No app switching, no scattered files. Stays focused without oversight.

Step 3: Layout → Final design

Figma Make generates initial layouts quickly. I pull in styling from my library so everything stays on-brand. Then I continue polishing it in Figma: typography, spacing, alignment and all the details that make it feel polished.

Step 4: Design → Critique

Before calling it done, I screenshot and drop it into Claude. It analyzes layout pros and cons, identifies ambiguous language, and reduces wordiness so the message is sharp.

This is how I use AI to work smarter and faster while keeping creative decisions in human hands.

What does your AI workflow look like? I'd love to hear what's working for you 👇

AI didn’t change what I design. It changed how I design.

Over the past several months, my design process hasn’t just evolved — it’s been fully restructured. My AI tool stack isn’t something I use occasionally; it is an operational layer embedded into my day-to-day and across discovery, ideation, prototyping, validation, and delivery.

This article outlines how I structure projects using AI models — primarily Claude and ChatGPT — alongside specialized tools such as Figma Make and Amplitude.