One of the most frustrating parts of early-stage design?
You spend more time managing tools than testing ideas.
I’d have SketchUp open for massing, GIS for overlays, and Excel for calculations - all running at once. It was clunky, slow, and completely broke my design flow.
Recently, I tried Giraffe Technology on a project, and it turned out to be one of the most useful upgrades to my workflow.
🚀 I tested three different design options in one sitting.
No switching tools. No reformatting. No waiting.
Here’s what stood out:
✅ Instant site analysis with contextual overlays
✅ Real-time solar radiation and shadow studies
✅ Rapid conceptual designs with built-in flexibility
✅ Live yield and area metrics
✅ Export-ready reports
✅ Seamless collaboration with team members
My personal favorites?
👉 The Site Analysis Annotations : it pulled together zoning, setbacks, and overlays in one neat layer.
👉 And the Solar Radiation Tool - gave me intuitive, visual insights that usually take hours to compile.
If you’re working on anything that involves early-stage planning or site strategy, Giraffe Technology is worth exploring.
✨ Watch the tutorial attached to see how I used it.
🛠️ AI coding skills might become one of the biggest opportunities for Design Systems.
Jakub Krehel shared his open-source /better collection with four new Claude skills focused on improving interfaces. At first glance, they're built for developers. But after looking at them, I couldn't stop thinking about how valuable this approach could be for design systems. Also inside Figma as a component.
The new skills review accessibility, layout, interface quality, and product writing. Instead of generating something from scratch, they analyze an existing interface, identify issues, and suggest improvements. That shift is what makes them interesting.
Some of the new additions include:
🔹 /better-accessibility to identify accessibility issues and recommend fixes.
🔹 /better-layout to improve spacing, hierarchy, responsiveness, and visual structure.
🔹 /better-writing to make product copy clearer and more consistent.
🔹 /better-interface to combine every skill into a complete interface review.
What caught my attention isn't the implementation. It's the mindset.
I've seen countless AI tools focused on creating UI faster. I rarely see AI focused on improving existing interfaces. That's a much harder problem, and arguably a more valuable one for mature products.
Now imagine bringing this concept into Figma. Instead of asking AI to generate a screen, designers could run specialized review skills directly on the canvas to detect inconsistent spacing, missing accessibility requirements, weak visual hierarchy, design system violations, or opportunities to simplify components before handing designs to engineering.
To me, that's where AI becomes truly collaborative. Not replacing design decisions, but acting like an experienced design reviewer that's available whenever you need a second opinion.
I believe this "review-first" approach will become one of the next big directions for AI in design tools.
Would you rather use AI to generate interfaces from scratch, or to review and improve the ones you've already designed? Drop your comment below! 👇
🔗 Jakub Krehel's GitHub: https://lnkd.in/dDw3Ca5Q#AI#Figma#DesignSystems#ProductDesign#UX#Accessibility#DesignOps#InterfaceDesign#ArtificialIntelligence#OpenSource
## Unlock Seamless Client-Designer Collaboration! 🔥
Granting your clients access to Figma can revolutionize your design workflow by fostering collaboration and transparency. Clients can interact with the design in real-time, providing immediate feedback and enabling quick adjustments. 🛠️ This accelerates the iteration process and ensures the final product aligns perfectly with the client's vision. 🎨
### Benefits:
**Real-Time Feedback:** Clients can instantly share their thoughts, speeding up the iteration process. 💬
**Enhanced Transparency:** Clients can monitor progress and understand the rationale behind design decisions. 👀
**Improved Communication:** Direct comments on the design minimize misunderstandings and streamline discussions. 📣
### Challenges:
**Potential Over-Involvement:** Clients might make their own changes, potentially disrupting the design process. 🚫
**Learning Curve:** Some clients may need time to get accustomed to Figma, possibly slowing the initial phase. ⏳
**Boundary Setting:** Establishing clear guidelines is essential to prevent unintentional alterations that could lead to confusion. 🛑
Overall, providing clients access to Figma can be a game-changer. However, setting clear boundaries and conducting regular check-ins are crucial for a smooth and productive design journey. ✅
#ui
I tried 10+ AI prototyping apps. Only one stood out.
Here's why:
Don't sleep on this tool.
I tried the usual suspects (Lovable, Stitch, Make, Bolt, v0, etc.) But when I found Magic Patterns, I stopped looking.
It had everything I needed for collaborative, AI-powered prototyping, especially in the early stages of the design process.
Everyone’s debating which AI prototyping tool generates the best UI designs or code.
Or they're showing off a random vibe coded app.
But I think the real opportunity for product teams is being overlooked.
Early-stage collaborative AI prototyping is where the magic happens. Fast exploration, shared context, real momentum.
3 Reasons why Magic Patterns excels at this:
1. Live AI prototyping with others = game changer
Magic Patterns lets you invite people to a shared canvas. Review and interact with multiple prototypes in one view. Fork, remix, and build on ideas instantly. It’s multiplayer AI prototyping done right, perfect for my AI design sprint workshops. And perfect for product teams to rally around a problem and explore ideas.
2. Front-end focus, no backend noise
You can explore flows and concepts fast, without getting distracted by databases or logic. Many of the hyped AI tools are focused on vibe coding complete apps. But for early-stage work you just need to quickly explore multiple ideas, iterate, get alignment, and test for feedback. For this purpose, Magic Patterns is exactly what I needed.
3. Thoughtful features that speed up your flow
Magic Patterns is perfect for first-time AI prototypers. The beginner friendly interface and useful features like "Presets," "Inspiration," and "Polish", make it easy for anyone to experiment with purposeful ideas.
Bonus Reason:
Don't mistake Magic Patterns for a basic AI UI tool. There are advanced features and smart workflows I’ll show you that make this the most valuable tool I’ve added to my design process in years.
I’m hosting a FREE live walkthrough next week where I’ll demo exactly how I use Magic Patterns inside my AI Design Sprint workshops, including best practices and the frameworks I’ve used in real sessions. This is a glimpse into how design, product, and engineering will work together in the AI era. Once you see it in action, you’ll want to run your next workshop this way.
Come hang out. It’s going to be fun, useful, and maybe even a little magical. 🪄
Spots are limited. Drop “magic” in the comments or DM me to reserve your spot.
🧠 Double Diamond in the AI Era
AI has a huge impact on how we build things. And it changes the very foundation of any design process—double diamond.
But despite popular beliefs, AI isn't here to eliminate the double-diamond; it's here to stretch it, compress it, and sometimes even loop it in surprising ways.
The fundamentals of good design haven't changed: We still explore broadly, narrow down, experiment, and ship.
But how we do it is evolving quickly.
Think of it like this: Before AI, the double-diamond felt like a marathon-long research cycle, slow iteration, heavy execution work. Today, it's more like a high-speed circuit: fast insights, and strong focus on implementation (rapid prototyping) and validation which leads to constant learning, and tighter human judgment loops.
Here is a quick overview of the new double diamond with helpful AI tools:
🔍 1. Discover (AI-Accelerated Research)
Before AI: in-depth interviews, manual note-taking, and long synthesis cycles.
With AI:
✓ AI-assisted desk research & competitive scans
✓ Auto-summarized interviews (using tools like Condens, Dovetail, Notion AI)
✓ Sentiment & theme extraction
✓ Rapid user persona hypotheses
✓ Problem-space simulation (prompting ChatGPT or Claude, "act like a surgeon, what would frustrate you here?")
Outcome changes: You get to insights faster, but you still need to do validation, interpretation, and framing.
AI = speed + pattern surfacing, not necessarily user understanding.
🎯 2. Define (AI-Enhanced Framing & Strategy)
Before AI: Manual synthesis, slow reframing.
With AI:
✓ AI helps cluster themes (tools Condens, Dovetail)
✓ Drafts JTBD, opportunity map, problem statements
✓ Runs "counterfactual thinking" prompts (e.g., prompting ChatGPT "what if the constraint disappeared?")
But it won't tell you which problem you should focus on first and foremost; humans decide which problem matters.
✨ 3. Develop (AI Co-Creation)
Before AI: Sketch → wireframe → prototype → code
With AI:
✓ AI generates first drafts of flows, UI states, microcopy (tools like Figma First Draft or Framer Wireframer)
✓ AI transforms sketches → wireframes → polished UI
✓ Design tokens, DS components surfaced instantly
✓ Interactive prototypes auto-built (using tools like Figma Make)
AI will help you move faster, but it's up to you to strategically choose solution direction, consider UX nuance, constraints, quality bar, and manage innovation guardrails.
✅ 4. Deliver (AI-Integrated Execution)
Before AI: final polish, dev handoff, QA.
With AI:
✓ Design → code translation (tools like Cursor or Vercel v0)
✓ GPT agents catch accessibility issues/errors
✓ AI QA: heuristic review, friction detection
✓ Real-time versioning & code-sync design systems
The designer becomes more editor/conductor than pixel-pusher.
👉 Join my free 30-min workshop, “Vibe design with AI” on January 15: https://lnkd.in/ebMepq69#AI#design#UX#UI
The Designer's Toolbox: Must-Have Tools for Every Stage of the Process
Designing is a journey from concept to creation, and having the right tools can make all the difference. Here's a peek into my toolbox, packed with essentials for every stage of the process.
When I'm in the brainstorming phase, Miro is my go-to. Its infinite canvas and collaborative features make idea generation a breeze. Whether sketching out concepts or collaborating with team members, it's the perfect digital whiteboard.
Moving on to wireframing, Figma stands out. It's intuitive and powerful, allowing for real-time collaboration. The ability to prototype within the same environment speeds up the workflow, and its vast library of plugins is a designer's dream.
For the actual design work, I can't recommend Adobe Creative Cloud enough. Adobe XD for UI/UX, Photoshop for detailed graphics, and Illustrator for vector designs – it's a suite that covers all bases. The seamless integration between these tools ensures that transitioning from one to another is smooth and efficient.
Finally, when it's time for the final execution, tools like InVision for prototyping and user testing are indispensable. They help in gathering feedback and ensuring that the design not only looks good but functions perfectly.
These tools have been game-changers for me, enhancing creativity and productivity. What are your favorite design tools?
#webdesign#graphicdesign#designthinking#uiux#creativity#designprocess#digitaldesign#designinspiration#creativeworkflow#designers
🚀 Level up your prototyping workflow:
How to share multiple versions of your vibe-coded prototype
Working on a complex prototype and need to show stakeholders different variations? Or running A/B tests with users?
Here's a game-changer I just set up for our team:
The problem: You're iterating on a prototype but need to keep the "stable" version accessible while testing new ideas. Or you want to run user research comparing two approaches.
The solution: Deploy each Git branch to its own unique URL.
Now our prototypes live at:
main → primary "stable" prototype URL
variant-a → /variant-a/
variant-b → /variant-b/
Why this matters for designers:
✅ Stakeholder reviews. Use the Github desktop app to switch between versions — "Here's the current version, and here's what we're exploring"
✅ User research — Run proper A/B tests with different participants seeing different URLs
✅ Iteration without fear — Experiment on a branch without breaking what's already working
✅ Documentation — Each variation has a permanent, shareable link
The setup takes minutes using GitHub Actions. Once configured, every time you push changes to a branch, it automatically deploys to its own URL. This setup works particularly well at companies with security restrictions on teams that already use Github.
Showing always beats telling.
If you're a designer working with code-based prototypes, this workflow is a must-have. Happy to share the technical setup if anyone's interested!
Also curious — what tools or workflows have changed how you share work with stakeholders?
𝗬𝗼𝘂𝗿 𝗱𝗲𝘀𝗶𝗴𝗻𝗲𝗿 𝗶𝘀 𝗯𝘂𝘀𝘆. 𝗬𝗼𝘂𝗿 𝘀𝗽𝗿𝗶𝗻𝘁 𝘀𝘁𝗮𝗿𝘁𝘀 𝗠𝗼𝗻𝗱𝗮𝘆. 𝗬𝗼𝘂 𝗻𝗲𝗲𝗱 𝗮 𝗺𝗼𝗰𝗸𝘂𝗽 𝗻𝗼𝘄.
𝗜'𝘃𝗲 𝘁𝗲𝘀𝘁𝗲𝗱 𝟮𝟬+ 𝘁𝗼𝗼𝗹𝘀. 𝗧𝗵𝗲𝘀𝗲 𝟲 𝗮𝗿𝗲 𝘁𝗵𝗲 𝗼𝗻𝗲𝘀 𝗜 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘂𝘀𝗲 𝗶𝗻 𝘀𝗽𝗿𝗶𝗻𝘁 𝗽𝗹𝗮𝗻𝗻𝗶𝗻𝗴 𝘁𝗼 𝗴𝗼 𝗳𝗿𝗼𝗺 𝗶𝗱𝗲𝗮 𝘁𝗼 𝘃𝗶𝘀𝘂𝗮𝗹 𝗶𝗻 𝘂𝗻𝗱𝗲𝗿 𝟮𝟬 𝗺𝗶𝗻𝘂𝘁𝗲𝘀 — 𝗻𝗼 𝗱𝗲𝘀𝗶𝗴𝗻 𝗱𝗲𝗴𝗿𝗲𝗲 𝗻𝗲𝗲𝗱𝗲𝗱:
🧠 𝗨𝗶𝘇𝗮𝗿𝗱 — Type a feature description or upload a rough sketch. Done. Editable wireframes in seconds. I use this when an idea is still half-baked but I need something to react to.
🎨 𝗩𝗶𝘀𝗶𝗹𝘆 — My go-to for stakeholder alignment. Business-friendly, no Figma overwhelm, and exports cleanly for the design team to polish later.
⚡ 𝗨𝗫𝗣𝗶𝗹𝗼𝘁 — Built for PMs who care about UX. Generates multi-screen flows, spots friction before handoff, and gives you design critiques without needing a designer in the room.
🖼️ 𝗙𝗶𝗴𝗺𝗮 𝗔𝗜 — FigJam AI generates user flow diagrams from a prompt, and the design side can auto-write placeholder copy, suggest layouts, and bridge directly to dev handoff. I reach for this when I'm collaborating closely with a designer.
🤝 𝗠𝗶𝗿𝗼 𝗔𝗜 — Turns your discovery sticky notes and diagrams into basic UI layouts. Zero context switching if Miro is already your planning home.
🔧 𝗚𝗼𝗼𝗴𝗹𝗲 𝗦𝘁𝗶𝘁𝗰𝗵 (𝗳𝗿𝗲𝗲 𝗯𝗲𝘁𝗮, 𝗚𝗼𝗼𝗴𝗹𝗲 𝗟𝗮𝗯𝘀) — Free. Prompt in, Figma file and frontend code out. Still rough but already in my rotation.
The real unlock isn't speed. It's earlier alignment.
𝗪𝗵𝗲𝗻 𝘆𝗼𝘂 𝘄𝗮𝗹𝗸 𝗶𝗻𝘁𝗼 𝘀𝗽𝗿𝗶𝗻𝘁 𝗽𝗹𝗮𝗻𝗻𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗮 𝘃𝗶𝘀𝘂𝗮𝗹 𝗶𝗻𝘀𝘁𝗲𝗮𝗱 𝗼𝗳 𝗮 𝟯-𝗽𝗮𝗴𝗲 𝗣𝗥𝗗, 𝘁𝗵𝗲 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻 𝘀𝗵𝗶𝗳𝘁𝘀. 𝗟𝗲𝘀𝘀 "𝘄𝗵𝗮𝘁 𝗮𝗿𝗲 𝘄𝗲 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴?" 𝗠𝗼𝗿𝗲 "𝗵𝗼𝘄 𝗱𝗼 𝘄𝗲 𝗺𝗮𝗸𝗲 𝘁𝗵𝗶𝘀 𝗯𝗲𝘁𝘁𝗲𝗿?"
🎬 Behind the Scenes of SWEG (AI fridge we built in < 5 hours)
Having experimented with a lot of vibe coding tools, I was curious how Figma Make would compare. The biggest unlock? Collaborative prompting.
Just like Figma revolutionized co-design, Figma Make lets multiple people co-prompt. David and I quickly fell into a rhythm: while I entered one prompt, he engineered the next one. This made us faster and let us divide and conquer — I fine-tuned functionality while he focused on the visual design.
Other features that stood out:
👆 Selection tool → lets you target specific elements when prompting, giving the LLM much-needed clarity.
🎨 Insert designs → no more generic “AI slop” placeholders; we dropped in David’s custom fridge art to personalize SWEG.
⏪ Revert mode → when the AI went off-track, we could roll back like hitting a checkpoint in a video game.
Takeaway? Figma Make isn’t just another AI prototyping tool — it’s rethinking how we collaborate with AI. And for builders like us, that unlock is huge.
Before Figma, collaboration was… painful for a lot of creatives, especially if you were in web or UI design.
The vibe was endless email attachments, conflicting file versions, and the dreaded, “Is this the latest file?”
Design collaboration used to feel like a solo sport with too many players. Then Figma came along and showed us that collaboration doesn’t have to be painful.
Real-time collaboration transformed the process into a true team effort—and it made me a better team player.
Here’s how Figma revolutionized the way I work with others:
1️⃣ Real-time edits
Gone are the days of “waiting your turn” with the file.
➔ Figma lets the whole team work on the same design simultaneously.
➔ No bottlenecks. No delays. Just seamless collaboration.
2️⃣ Version history
Every single change is logged, so:
➔ If someone moves a layer into oblivion, you can restore the previous version in seconds.
➔ No more panic attacks when things go wrong—just a sigh of relief.
3️⃣ Team libraries
Shared components and styles mean everyone’s working from the same toolkit.
➔ The result? Consistency across designs and fewer headaches for developers.
4️⃣ Commenting features
No more “I think I emailed you about that last week.”
➔ Comments stay directly on the design, eliminating miscommunication.
➔ Feedback is centralized, clear, and actionable.
Collaboration isn’t just about tools—it’s about how those tools make the process smoother and more enjoyable for everyone involved.
Figma has been a game-changer for me, turning chaos into clarity.
💡 How has Figma improved collaboration for your team? 🤔💭👇
#FigmaFriday#teamwork#uxdesign#graphicdesign#projectmanagement#work#collaboration
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👋 Hi, I'm Dane—I share daily design tools & tips.
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