How AI impacts design and engineering collaboration

Across my AI workshops, I’ve seen the same pattern emerging: code is quietly becoming a design tool. Vibe coding tools like Lovable and Claude Code let designers explore directions faster and prototype richer, more realistic experiences. When guided with taste and precision, they amplify—not replace—design judgment. I put together a short primer for designers curious to try it.

Let's talk about Design System. Our Design System isn’t just for humans anymore. It’s becoming the language machines use to build your products. AI Agents are going to dive deep into Design Systems, understand components, and generate real screens from it. ✨ If we structure our system clearly and consistently, our AI friends will build exactly what we want. 🧹 If it’s messy? They’ll improvise (We all have seen what happens when AI is creative) That’s why structure matters more than ever. The button in Figma should match the Button in code. Our layout tokens, color names, and spacing should follow a logic that a machine can use. So, is your Design System ready to welcome our robot overlords?

To designers who say “you can’t vibe-code a real product”: Check out anymark[.]co. I built it end-to-end with Replit (not affiliated). Is it beautiful? No. Is it bug-free? No. Does it have paying, happy customers? Yes. Many designers try a prototyping tool like Lovable, hit a wall, and conclude, “You can’t build a production-ready product with AI.” Here is the proof that you can. It’s likely a matter of time until you'll be pushing changes to production (as Intercom designers already do). Don’t let prototyping tools confuse you. Practice using heavier tools like Cursor and Claude Code (or even Replit).

Design used to start with sticky notes. Now it starts with AI. 🤖 Hear from Rachel Foster, Principal Product Designer, as she shares how AI tools are changing the way we design. They’re turning ideas into prototypes faster than ever and bringing designers, engineers, and product teams closer together. Discover how human creativity and AI are working side by side to shape the next era of design. 💡

🎨 The road to becoming a Creative Tech Lead (Lab 2: AI Prompt Visualizer) A deep dive into creative engineering. “What you feel when you write, you see moving.” Over the past weeks, I’ve been exploring how AI semantics and motion design can merge to create something poetic: a web experience that turns text into emotion-driven visuals — living gradients, gentle motion, and expressive grain — all reacting in real time to what you write. Built with React + Framer Motion + OpenAI, it analyzes your text’s emotional tone (joy, calm, nostalgia…) and transforms it into a visual mood — color, rhythm, and intensity. The result is not about generating images — it’s about feeling them. It’s a small step in my ongoing journey as a Creative Technologist, exploring how code, design, and emotion can speak the same language. You can explore it soon on my GitHub & portfolio 👇 DEMO: https://lnkd.in/eR5jByZ9 REPO: https://lnkd.in/e77XnA2u #CreativeTech #AI #MotionDesign #React #OpenAI #FramerMotion #EmotionalUX #GenerativeDesign #KevCoder

Heard of vibe coding? Then meet vibe designing — where AI helps you create the feel of your product, not just the function. 🎨 In this video, our CEO breaks it down: ✨ What vibe designing actually means ⚙️ How it differs from vibe coding 🧠 Why the editing experience (and multimodality) changes everything At Visily, we believe design should feel as natural as thinking — and that’s what vibe designing unlocks. 👇 Watch the full video to see how the future of design feels. #VibeDesign #VibeCoding #ProductDesign

Using tools like Cursor, Lovable, V0, Framer, Bolt, and Midjourney is quickly becoming non‑negotiable for hiring managers. We’re hearing this from them everyday yet still very few designers are spending enough time in them. You shouldn’t just take my word for it though. We started Double Diamond to get real insights from design leaders and amplify them so that designers anywhere can get access. So here’s the why, what, how on AI in design: - AI buys back time for the real work: end‑to‑end journeys, accessibility, systems—not just drawing wireframes. - Velocity is the culture: pre‑PMF spaces demand rapid, AI‑accelerated iteration; PMF areas still require rigor—top designers can do both. - Real prototypes > decks: small teams can prompt, iterate, and validate in days, then invest once there’s signal—tool fluency makes this possible. - The stack is converging: hybrids who can jump into code‑adjacent workflows (e.g., Cursor‑style) and get 80% to production are immediately valuable. - Strategic advantage: AI turns “trapped value” experiments into shippable wins in hours, informing the core product without roadmap drag. Get this and so much more from conversations that are happening in our Substack! Link in the comments! 

Prototyping used to start after design. Now it’s part of it. AI and tools like vibe coding are changing the timeline, letting teams explore ideas earlier and test what’s possible before things are fully baked. It’s redefining what “early design” looks like. I like how this shifts the focus from getting everything pixel perfect to getting closer to how the experience actually feels. Start low fidelity, get feedback fast, and learn before it costs you. The sooner we test, the sooner we get to the truth of what works. It’s exciting to see how fast this space is evolving. From AI-assisted prototyping to vibe coding, we’re watching the boundary between design and build disappear in real time.

Great session yesterday courtesy of Michael Riddering. Covered emerging AI practices from Henry Modisett, Pranathi Peri, and Nick Pattison. Chatted with 700 folks about Lovable, Vercel, Figma and others. Main takeaway: Designers should embrace and understand coding basics to stay relevant. #ai #aidesign #lovable #vercel #futureofdesign

I’ve noticed an interesting shift in how we build products. In the past, our workflow looked like this: Design → Code → Deploy We’d wait for polished mockups before a single line of code was written. But with AI tools accelerating how engineers code and iterate, it often looks more like: Code → Deploy → (Optional) Redesign → Code → Deploy again The initial design isn’t perfect, but that’s the point. By the time the designer steps in, there’s already usage data, feedback, and context.