Using LLMs to generate, critique, and refine UX design directions, IA, flows, and wireframes
Use LLMs as an active design thought partner to plan and generate initial UX/UI and website directions, information architecture, user flows, screen lists, navigation models, page structures, site maps, and wireframes from ambiguous briefs; ask clarifying questions before generation; and refine promising concepts through a fast generate-review-iterate loop before detailed Figma work begins.
Why the human is still essential here
The designer must define the problem, user goals, and constraints; judge quality; rearrange architecture; validate tradeoffs and edge cases; approve the plan before generation; and decide what direction deserves further work. AI helps unblock exploration and structure, but it does not own product judgment, UX accountability, or final flow decisions.
How people use this
User flow & IA ideation
Use an LLM to propose multiple user flows, information architectures, and edge cases for a feature, then the designer selects and refines the most viable direction.
ChatGPT / ClaudeRapid wireframe variations from prompts
Generate and iterate low-fidelity wireframe/layout options from a short product brief to compare alternative screen structures before rebuilding the chosen version in design tools.
Uizard / Galileo AINavigation model options
AI proposes different menu, tab, or sidebar structures so the designer can compare information architecture directions quickly.
v0 / RelumeNeed Help Implementing AI in Your Organization?
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Related Prompts (4)
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Plan smarter with more context in Make
Plan mode
Plan mode is a new opt-in mode that helps you shape that direction before generation starts. Make takes a look at your project, asks a few clarifying questions, and drafts a plan you can edit, refine, and approve before anything gets built.
It's most useful for complex workāmulti-section layouts, detailed specs, design importsāwhere getting aligned upfront leads to noticeably better results. For simpler prompts, you can skip it and build directly.
Turn it on via the dropdown in the prompt box or the /plan command. Because plan mode does extra work upfront, it uses more AI credits than a standard buildāyou'll see an estimate before you commit.
Web search & fetch
Make can now pull live context from the web mid-build. Search broadly or fetch a specific URL to ground builds in current content. Tool-call approvals let you review before anything enters your session.
Queued messages
Stack follow-up instructions while Make is still generating. Edit or delete them before they commit, and they'll send automatically once the current build finishes.
My design workflow looks different now.
My design workflow looks different now.
Brainstorming ā Claude
Breaking down UI references ā Gemini
Wireframes ā Lovable
Working prototypes ā 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 š¤
What's in your AI stack right now?
9 Top AI Tools I Use For My UX Workflow
AI tools are everywhere right now.
But some of them donāt actually fit into real design workflows.
So instead of listing everything Iāve 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 whatās working for me right now.
One thing Iāve learned:
AI doesnāt 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.
I used AI design tools every day for 60 days.
No hype. Just real work.
Tested:
ā Figma Make
ā Google Stitch
ā Framer AI
ā Claude skills
Used them on actual product flows ā not fake concepts.
What worked š
ā Instant first drafts ā”
ā Quick layout ideas
ā Helped when I was stuck
ā Decent starting copy
What didnāt š
ā No real user understanding
ā Breaks flows beyond 1ā2 screens
ā Zero product thinking
ā No consistency across screens
Hereās where it got frustrating:
I wasnāt designing anymore.
I was fixing.
And worse ā I was fighting code šØāš»
instead of thinking about actual design problems.
Faster output⦠ā”
but slower progress.
Thatās when it clicked š”
AI is great at generating screens.
But product design is about decisions.
Now I use it for:
ā Quick drafts
ā Exploring directions
And I keep the thinking:
ā What problem matters
ā Why this flow exists
AI wonāt replace designers.
But it will expose the ones who donāt think.
Use it as a tool.
Not as your brain.
I recently tried designing a website with AI as the starting point.
I recently tried designing a website with AI as the starting point.
The idea was intentionally simple and generic:
a camping / camperāfriendly 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 thatās 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.
Thatās 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.
Itās a powerful tool if you know when to use it and when to step away.
And thatās probably the most important design skill today.
#AI #UXdesign #UIdesign #DesignToday
Best AI Design Tools in 2026 - The Complete Stack for Web Designers
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.
Designers and AI: The Honest Conversation Weāre Not Having
When I use AI in my design work, Iām not outsourcing my thinking. Iām 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. Thatās a meaningful difference.
I use Claude for research. Iāve 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 Iām building now. Thatās not impressive. Itās just useful.
Iāve also given it instructions for UX writing ā the tone, the constraints, who the users are. When it gives me copy suggestions, I donāt paste them straight in. I read them against the productās voice and ask whether theyāre actually clear for the user. Sometimes I run tests to find out.
How I actually use AI in product design.
How I actually use AI in product design.
Most teams are using AI to move faster.
Thatās not the hard part.
The hard part is not making the product worse in the process.
Hereās 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 Iām not asking it what the experience should be.
Thatās still on me.
2. I treat the first output as a draft, not the answer:
AI gives you something that looks right.
Thatās the danger.
Spacing might be fine. Flow might be off. Edge cases are missing.
If you donāt know what āgoodā looks like, youāll 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 itās loose, you just get cleaner-looking chaos.
4. I use it to explore, not finalise. Itās great for:
⢠Trying directions quickly
⢠testing layout approaches
⢠getting out of a blank state
⢠But the final 20% still needs taste.
That hasnāt changed.
The shift isnāt that AI is designing for you.
Itās that itās 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 ā not just the flashy demos I'm seeing on socials š
We need to decide:
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 ā
to explore ideas, speed up tasks, and meet deadlines more efficiently.
And yes ā with the right context,
it can even help identify edge cases, bugs, and gaps.
But thatās the key:
AI works best when itās guided.
It still relies on human understanding of:
⢠Context
⢠Dependencies
⢠Product thinking
⢠Real-world constraints
Without that, outputs and timelines can look efficient ā
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 shouldnāt compete with AI ā
we should learn how to direct it effectively.
š¬ How are you using AI in your workflow today ā as support or substitution?
#UXDesign #ProductDesign #UserExperience #ArtificialIntelligence #AIinDesign #SoftwareDevelopment #FutureOfWork #DesignThinking #TechTrends