AI-assisted design research, briefs, strategy, competitor context, user-flow planning, and project scoping

A few years ago, if someone had told me that AI would become a part of almost every design project I worked on, I probably would have laughed. Like many designers, I believed great products came from creativity, empathy, and experience — not algorithms.

Then I started experimenting.

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.

I’m a web designer and I use AI.

Not to design for me. Trust me, I’ve tried.

I find AI amazing for things like researching a client’s target audience.

Or organizing my client meeting notes, so I can find the info I need later.

So I'm not anti-AI at all.

But there are things I’m pretty sure I’ll never hand over to it.

One of them is messaging.

I know coaches who:
- opened ChatGPT
- told it a bit about themselves
- asked it to write their homepage copy

And it gives them something that sounds like every other coach on the internet.

AI can only work with what you give it.

That's why it's so important to know what your website needs to say first.

If you don't, you'll likely end up with generic copy that does nothing to show potential clients why you're the right coach for them.

🔴 If you're struggling to write your website copy, my Coach Website Blueprint might be more useful to you than ChatGPT.

It’s a free 31-minute video course breaking down the messaging framework I use with my clients.

Head here to get it:
https://lnkd.in/gr2B7nGx

I presented my custom AI design workflow to our design team two weeks ago. #ClaudeDesign launched 𝙩𝙬𝙤 𝙙𝙖𝙮𝙨 𝙡𝙖𝙩𝙚𝙧 and had a lot of overlap with what I built. I sat on this post for a while. 🧘‍♀️

Decided to share because building it taught me something about where custom workflows are still optimal (for now).

𝘢𝘭𝘪𝘦𝘯𝘦 𝘾𝘭𝘢𝘶𝘥𝘦 𝘿𝘦𝘴𝘪𝘨𝘯 𝘸𝘪𝘯𝘴
Seed of an idea → something “good enough” to move a conversation forward, fast. Built-in sketch tool (hey, that’s the “digital napkin” concept), consistent format, easy to share and comment on. For early ideation, it’s genuinely convenient.

𝘢𝘭𝘪𝘦𝘯𝘦 𝘘𝘶𝘴𝘵𝘰𝘮 𝘴𝘬𝘪𝘭𝘭𝘴 𝘸𝘪𝘯
𝘄𝘩𝘦𝘯 𝘪𝘵 𝘴𝘵𝘢𝘳𝘵𝘴 𝘣𝘦𝘧𝘰𝘳𝘦 𝘨𝘦𝘯𝘦𝘳𝘢𝘵𝘪𝘰𝘯. My workflow begins with /𝘣𝘳𝘪𝘦𝘧-𝘤𝘳𝘦𝘢𝘵𝘪𝘰𝘯, a live or async brainstorm between me and AI that builds a comprehensive project context before anything gets made. In async mode, AI generates a questionnaire based on the problem area, the team discusses and answers it in a working session, then we bring the answers back to Claude Code and AI picks up from there. That context carries forward into every skill downstream.

𝘾𝘰𝘮𝘱𝘰𝘯𝘦𝘯𝘵 𝘧𝘪𝘥𝘦𝘭𝘪𝘵𝘺. Claude Design rebuilds components as HTML files rather than pulling from the actual codebase I uploaded, which sometimes isn't 1-to-1 with the actual design system — missing states, missing components, approximate spacing. Custom skills can go deeper, connecting to your real design system components and anti-patterns, so what comes out actually matches your product styles and adheres to your design system better.

𝘏𝘩𝘦 𝘴𝘺𝘴𝘵𝘦𝘮 𝘭𝘦𝘢𝘳𝘯𝘴 — or at least, starts to. Every time I run /𝘥𝘪𝘳𝘦𝘤𝘵-𝘩𝘪𝘧𝘪 and flag what's off, the anti-patterns file updates. The goal is for team decisions and feedback to feed back in the same way, still figuring out that part. But even the early version compounds.

That’s the thinking behind this experiment: how my custom skills actually chain together across the double-diamond design process.
/𝘣𝘳𝘪𝘦𝘧-𝘤𝘳𝘦𝘢𝘵𝘪𝘰𝘯 → /𝘤𝘳𝘦𝘢𝘵𝘦-𝘥𝘦𝘤𝘬 → /𝘮𝘪𝘥-𝘵𝘰-𝘩𝘪𝘧𝘪 𝘰𝘳 /𝘥𝘪𝘳𝘦𝘤𝘵-𝘩𝘪𝘧𝘪 → /𝘪𝘵𝘦𝘳𝘢𝘵𝘦 → /𝘤𝘰𝘥𝘦-𝘵𝘰-𝘧𝘪𝘨𝘮𝘢 → /𝘢𝘥𝘥-𝘵𝘰-𝘴𝘺𝘴𝘵𝘦𝘮
Each skill's output is the next skill's input. Human checkpoint and decision making at every stage. Also, you don't have to use all the skills. Already have a brief? Start at exploration. Already have hi-fi? Jump to /𝘪𝘵𝘦𝘳𝘢𝘵𝘦.

Check the 3min video below for the highlights of my walkthrough. 👇

Claude Design is genuinely great, but a custom workflow can be tuned to your methodology, your design system, your rhythm in ways a general tool can't, at least not yet. Until it fully closes the gaps (and I believe it will), there's room for each of us to systematize how we work with AI, not just adopt it.

Still a lot to explore for future experiments: one-click wireframe ↔ hi-fi switching, converting prototyping code → production, tighter design system compliance, and more.

Curious what gaps you're working around with Claude Design or anything else. Leave your comments!

I've been sharing a lot about AI-powered product design workflows — what I try, what I actually use in my own work, and what sticks.

Every time I post, someone asks for tutorials or a deeper walkthrough. So I finally put it all in one place.

The guide covers everything I've tested so far - design workflow across 7 modules:
→ UX Research & Synthesis → UX Strategy & Methodology → Visual & UI Design → Content & Copy → Handoff & Documentation → Design Systems (coming soon) → Claude Skills

If you've been curious about how to bring AI into your design practice in a way that's actually useful, this is for you.

Link in the comments 👇

As a designer in tech, keeping up with AI news these days feels like Drake and Josh trying to keep up with that sushi belt.

Scrolling through social feeds in the tech community right now feels like walking down the street during an earthquake. Posts are unsettling, overwhelming, and make me feel so behind on all the new trends and workflows that I’ll never catch up. Sometimes I want to bury my head in the sand and not pay attention (which I’ve done plenty over the last few years).

But recently, I’ve found some positivity and fun working with AI. I’ve developed strategies for keeping my footing in this ever-changing industry, and I’m sharing them here, hoping they’ll help other designers who are overwhelmed and don’t know where to start.

AI isn't replacing my work, its expanding it


The last year completely changed how I work as a designer:
I’ve upskilled. Expanded what I offer. Sharpened my approach. Reduced my timelines.

And honestly grown more in the last year than the previous 5 combined.

What’s wild is not just the growth, it’s what I’m now able to offer solo.

Things I never imagined doing on my own:

1. Video and animation
Now a huge part of my work
Social content, paid ads, ecommerce
High-end pack shots and scroll stopping motion

2. Website development
From brand guidelines to wireframes to fully functioning sites

3. App prototyping
Taking ideas from rough concepts to something founders can actually show investors

4. AI-generated brand asset systems
Hundreds of on-brand visuals and videos for campaigns and content

5.Deep research and strategy
Competitive landscapes and creative direction baked into the work

The reality is simple

AI has pushed me into full E2E creative

Strategy → Brand → Execution → Rollout

All done in weeks, not months

At a fraction of what a mid-sized agency would cost

Here’s the stack I actually use daily:
• Nano Banana 2
For hyper-real product, lifestyle, and model imagery

• Kling 3.0
Best for controlled, high-quality video and animation

• Grok
More experimental, looser creative outputs

• Loveable
For prototyping apps, websites, and product ideas

• ChatGPT
Prompting, structuring ideas, research
• Canva
Client-ready templates and presentations

• Figma
Web design, structure, and handoff

• Adobe Illustrator
Still the core for logos and vector work

Year one of freelancing has been a bit mad
Can’t wait to see what year two looks like...

Which AI tool has made the biggest impact on how you work as a designer?
What changed your workflow the most, not just your speed?

#AI #designer #AIdesigner #branding #freelance #creative

I decided a while ago to not use AI to create designs at the agency.

We’ve tried it. Some parts of the process are cool.  But we’re creating human-to-device connection here.

And our designs come from our ideas which come from our conversations with you.

I’ll continue using AI as a tool for planning, parts of building and testing.  But when it comes to design, AI-use will be minimal if at all.

Design is not something I’m looking to delegate to AI right now.

I recently tried designing a website with AI as the starting point.

The idea was intentionally simple and generic:
a camping / camper‑friendly website.
A topic where AI should perform well.

I started the process the right way not with visuals, but with thinking.
I talked with ChatGPT about the project:
- what problem the website should solve
- what kind of experience I wanted to create
- the goals of the business
- who the users are and what they expect

The result was surprisingly good.
AI helped me structure my thoughts and turn them into a clear design brief something that usually takes quite some time. That part genuinely pushed me forward.

I then took this input and moved it into an AI web design tool, expecting the visuals to naturally follow.

And that’s where things became… tricky.

The result was okay, but very generic.
I tried refining it with more prompts, more instructions, more iterations but instead of getting better, it slowly became constrained and messy. The design started to feel stuck.

So I stopped.

I took the AI-generated design and moved into Figma, this time designing manually, without AI.
That’s where everything clicked again. I refined layouts, hierarchy, spacing, interactions and finally reached a result I was happy with.

My takeaway?
AI can push you very far, very fast especially in:
- problem framing
- structuring requirements
- defining goals and constraints

But when it comes to design decisions, clarity, and nuance, AI can also slow you down or trap you in generic solutions.

AI is not a replacement.

It’s a powerful tool if you know when to use it and when to step away.
And that’s probably the most important design skill today.

#AI #UXdesign #UIdesign #DesignToday

My AI workflow I use to 10x my design work:

1. Inktrail.ai - For brainstorming, understanding PRDs, conducting market and competitor research and creating user flows

2. variant.com - To curate a moodboard of design directions and UI flows

3. figma.com/make - The HTML and CSS code that aligns to my need from the moodboard and curate a complete prototyping

4. figma.com - For creating the design artifacts, aligning with brand standards and design system

Inktrail.ai - To write the UX copies for the designs

Worthy of mention; windsurf.com - Creats a design.md file and implement the UI on frontend level.

This workflow cuts my design time from days to hours and still maintain the same level of quality.

Designers should perform human oversight and not manual work.

What’s your own process?

Repost to help a designer from your network.