My design workflow looks different now.

Brainstorming → Claude
Breaking down UI references → Gemini
Wireframes → Lovable
Working prototypes → Antigravity

What used to take days now takes hours.

I'm not using AI to replace my design thinking. I'm using it to move faster so I can spend more time on the decisions that actually matter.

The designers who figure this out early are going to be very hard to compete with 🤔

What's in your AI stack right now?

AI tools are everywhere right now.

But some of them don’t actually fit into real design workflows.

So instead of listing everything I’ve tried,
I broke down the 9 top AI tools I actually use in my UX workflow, from idea to prototype to code.

Not hype.
Not theory.
Just what’s working for me right now.

One thing I’ve learned:

AI doesn’t replace design thinking.
It removes friction so you can focus on what actually matters.

#AItools #AI #UXDesign #Designworkflow

I used AI design tools every day for 60 days.
No hype. Just real work.

Tested:
→ Figma Make
→ Google Stitch
→ Framer AI
→ Claude skills

Used them on actual product flows — not fake concepts.

What worked 👇
— Instant first drafts ⚡
— Quick layout ideas
— Helped when I was stuck
— Decent starting copy

What didn’t 👇
— No real user understanding
— Breaks flows beyond 1–2 screens
— Zero product thinking
— No consistency across screens

Here’s where it got frustrating:

I wasn’t designing anymore.
I was fixing.

And worse — I was fighting code 👨‍💻
instead of thinking about actual design problems.

Faster output… ⚡
but slower progress.

That’s when it clicked 💡

AI is great at generating screens.
But product design is about decisions.

Now I use it for:
— Quick drafts
— Exploring directions

And I keep the thinking:
— What problem matters
— Why this flow exists

AI won’t replace designers.
But it will expose the ones who don’t think.

Use it as a tool.
Not as your brain.

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

Best AI design tools in 2026 - these are the 7 AI tools I use to run my design studio every single day. Not demos, not sponsored picks - real tools that ship real client work.

I tested over 50 AI design tools and narrowed it down to 7 that cover every part of the web design workflow: ideation, layout, assets, visuals, design, building, and the one tool that connects everything together. Each tool earned its spot by surviving real client projects at my studio, Klime.

When I use AI in my design work, I’m not outsourcing my thinking. I’m speeding up the parts of the process where speed is actually valuable, generating options, exploring directions, getting a quick read on structure, so I can spend more time on the parts where my judgment matters. That’s a meaningful difference.

I use Claude for research. I’ve trained it over time to understand the tone and voice of the products I work on. When I save a screenshot of something that inspired me, I send it over and it helps me remember why I saved it, what the design is actually doing, and how it connects to whatever I’m building now. That’s not impressive. It’s just useful.

I’ve also given it instructions for UX writing — the tone, the constraints, who the users are. When it gives me copy suggestions, I don’t paste them straight in. I read them against the product’s voice and ask whether they’re actually clear for the user. Sometimes I run tests to find out.

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 👍

We need to decide:
Is AI here to make our work faster
or to replace the work we do?

I use AI regularly in my workflow —
to explore ideas, speed up tasks, and meet deadlines more efficiently.

And yes — with the right context,
it can even help identify edge cases, bugs, and gaps.

But that’s the key:
AI works best when it’s guided.
It still relies on human understanding of:
• Context
• Dependencies
• Product thinking
• Real-world constraints

Without that, outputs and timelines can look efficient —
but fall short in reality.

AI is a powerful tool to accelerate the way we work.

But building meaningful products still requires
human judgment, collaboration, and experience.

Humans shouldn’t compete with AI —
we should learn how to direct it effectively.

💬 How are you using AI in your workflow today — as support or substitution?

#UXDesign #ProductDesign #UserExperience #ArtificialIntelligence #AIinDesign #SoftwareDevelopment #FutureOfWork #DesignThinking #TechTrends

These tools are powerful, but each one only works well when you know exactly what job to give it.

I’ve been using AI tools as a core part of my design workflow. Here’s what actually works and what doesn’t.

ChatGPT: My content partner. Great for UI copy, microcopy variations, and translating engineer-speak into user-speak.

Figma Make: Good at generating initial wireframes and scaffolding a starting flow. The frustrations: credit limits are brutal and burn fast when iterating (which is… the entire point of design). It struggles with large context, you need to feed it bite-sized chunks. No plan mode like VS Code, so you can’t orchestrate a multi-screen flow strategically. For these reasons, it’s much easier to go from Figma Make to VS Code than the other direction.

Figma: Still the source of truth. After Make generates a starting point, I always move into Figma to manually refine. AI-generated layouts need a human hand- spacing, hierarchy, consistency.

VS Code + Claude: Where designs come to life. Like Figma Make, works best with focused prompts, not massive context dumps. But the speed is transformative. Things that used to require a developer friend and a weekend now take an afternoon.

Google Stitch: Strong at generating polished visual UI and great for design system exploration. But the content and UX structure is consistently weak- page hierarchy, flow logic, information architecture all need significant rework. Better for visual inspiration than building experiences.

Updated stack as a designer using ai to streamline my workflows; for those that find it useful.

AI tech stack: Claude (research, strategy assistant), Claude Code (coding), Figma Make (prototyping), v0 (structural explorations), Vercel (hosting), Nano Banano Pro (image gen), Notion (second brain), Shadcn & Tailwind (styling)