Design Workflow Optimization

🔮 How To Prioritize UX Work (Framework) (https://lnkd.in/eGQrPm2N), a very practical guide on how to choose and estimate the right level of research and UX work needed for a successful outcome of a project — along with the process to follow and UX estimates to set. Kindly shared by Jeremy Bird. 🤔 Planning is typically done for the delivery phase only. 🤔 Design, research, discovery, ideation are not planned. 🤔 Effort, estimates, roadmaps, capacity are rare for UX work. 🚫 Not every project needs the same level of research/design. ✅ Goal: set realistic expectations for UX work in a timeframe. Jeremy suggests to estimate research and design efforts separately, and across different dimensions: we assess research by mapping Risks and Problem Clarity. And we estimate design effort needed by mapping Risk and Level of Complexity: 🔮 Clarity: Low ↔ High New, unknown problems usually come with a lot of assumptions and very low clarity. Well-known problems with shared understanding in the team and some extensive research have higher degree of clarity. 🔥 Risk: Low ↔ High Some projects are relatively easy to roll back and they don't really affect business-critical workflows (low risk). Others are much more difficult to reverse and operate within users' key journeys (high risk). 🚀 Complexity: Low ↔ High Self-contained projects in well-understood workflows are typically straightforward (low complexity). Some projects that involve many systems, external dependencies, stakeholders scattered across teams with little existing knowledge (high complexity). ✅ We start by defining a problem to solve + business impact. ✅ Then, we shape desired user outcome and success criteria. ✅ Next, we assess design effort and research effort levels. ✅ Run a kickoff meeting to prioritize and decide the scope. ✅ Designers break down UX work, estimate it, add to Jira. Personally, I always find it remarkably difficult to estimate the effort for research or design work. Even after so many years, with 20–30% buffer, I’m often underestimating the little nuances, blockers, constraints and bottlenecks hidden away somewhere between complex dependencies and external stakeholders. One thing is certain though: considering risk early is a very, very effective way to guide UX work in the right direction. High risk always requires some level of research and discovery. And early prioritization helps UX teams focus their effort where they add most value — saving time on resources for projects that deliver value to users and businesses. Finally: I can highly recommend to consider John Cutler's Effort vs. Value curves (https://lnkd.in/evrKJUEy) for prioritization work as well. Much of the work isn’t completed once it's delivered. More often than not, it will significantly add to maintenance costs over time. We better account for it early. #ux #design

I left Microsoft to build foundations for graphic design systems. Today, design is still evaluated on vibes, not structure or correctness. So we approached this as a data problem first. We built a large-scale dataset of structured design compositions: each design represented as a hierarchy of elements (text, images, vectors) with explicit layout, typography, and constraints. Taste is personal and constantly evolving. So we built adaptive RL loops that learn from every edit, every rebrand, and every enterprise workflow. Most image models operate in pixel space, so edits require full regeneration. Our models operate in component space. The first model family we’re shipping focuses on editing: given any image → decompose it into independent layers (text, icons, backgrounds, shapes), all editable without breaking the rest. Instead of: prompt → image → prompt → image We enable: generate → decompose → edit → scale Try Lica with the link in the comments.

Don't need to comment, like, or connect. Download it. Read it. Use it. Learn with it. Over the last weeks I kept seeing the same pattern. Designers were curious about MCP, but stuck. The path was unclear. Setup felt intimidating. Real use cases were missing. So I built the Design MCP Adoption Toolkit. A practical guide for using MCP inside a real Figma workflow. No theory. No hype. Just execution. Inside you will find: → What MCP is in plain language. → The three MCPs that matter for design work. → The mental model for Anthropic Claude Code to Figma, OpenAI Codex to Figma, and Figma Console MCP by Southleft, LLC and TJ Pitre. → The full setup in nine clear steps. → Nine real workflows you can test this week: Accessibility audits. Ticket validation before handoff. Token migration. Multi platform component handoff. Component documentation generation and more. Our roles are evolving. We are moving closer to that old Webmaster model where design, systems, structure, and technology connect. The designer who understands systems and automation will have leverage. This toolkit is my contribution to that transition. Consume it. Test it. Break things. Ask questions. Explore your own use cases. These are exciting times, and we move faster when we learn together. If you build something interesting with it, share it. Concrete examples help the whole community level up.

Most portfolios blend into one another. Out of every 100, only a few genuinely stand out. The format, structure, and depth of thinking in many portfolios are often superficial. They rarely showcase work in a structured problem-solving narrative, leaving it unclear why the work was created as it was. Also, many folios are underdesigned and don’t reflect their creators’ ethos or thinking. They come across as just another folio, or worse, a slideshow. Your work should reflect who you aspire to be as a creator. If time has been a barrier, take the opportunity to create work that showcases your intent, passions, and talents. This is the single best investment you can make in yourself. You only get a moment to stand out. So make it count. A portfolio is more than just a layout. It’s a narrative. Create a clear story about your work, explaining why it is interesting, how it works, and where it is effective. Personalise it. Make it compelling. Discuss each project’s significance and why it works for its intended audience. Avoid regurgitating the brief. Highlight what makes your work distinct and showcase that. Display only your very best work. Articulate your creative approach and what makes you an engaging collaborator. Guide people, explaining what sets you apart and be explicit about what you offer and how you could enrich a studio or relationship. Research the places you wish to work with; this understanding will help you know what you’ll gain from them and what they will gain from you. If you were hiring, why should you be chosen? Imagine you’re hiring. Is it clear why they should choose you? View your portfolio as if you were someone outside the industry. Would they understand it? Review fifty portfolios of your peers. Identify recurring trends, tricks, derivative work, or traits that cause you to blend into the crowd. Address these issues. Look at great agencies to see how they present their work. And it is worth repeating: if you haven’t yet created work you love, take the time to do it now. + A decent basic structure for projects: Create context: Clearly define the problem and how your idea addresses it. Instantly prove it works: Nail the idea in a single killer slide. Highlight the ‘Wow’ factor: Emphasise what makes your work uniquely impressive. Prove resilience: Illustrate how your idea handles challenges. Show unexpected applications: Demonstrate versatility and creativity by stretching your concept. Explain audience resonance: Articulate why your work resonates with its intended audience. Present a vision: Outline how your approach could evolve. Quality over quantity: Focus on fewer but more potent ideas. Create memorable names: Make your concepts sticky and easy to recall. Be authentic: Include only work that you genuinely believe in. End powerfully: Conclude with a strong executive summary that leaves a lasting impression. This approach ensures your portfolio stands out, not just blends in. _

Workflow design is the next language of creativity. At Adobe MAX, Adobe introduced two new workflow design tools: Firefly Creative Production for Enterprise and an upcoming system called Project Graph. Both use node-based interfaces that visualize and connect Adobe’s growing suite of Creative Cloud APIs. Project Graph takes it a step further. It allows workflows to be packaged, shared, and customized - essentially turning them into reusable, photoshop plugins. Node-based design isn’t new. Tools like ComfyUI, n8n, and Langflow have been building this space for a while, helping consolidate the rapidly expanding universe of AI capabilities. But this is the first time a major creative software company has fully embraced this approach and targeted it at the creative community. The baseline skill set for digital creatives is about to change. Those who can design automated, modular workflows will soon outpace those who can’t. Can’t wait to get hands-on with these and see what’s possible. #AdobeMAX #AI #CreativeTechnology #WorkflowDesign #Automation

Freepik Spaces Lists let you design, automate, and scale AI-powered creative workflows in one place, turning a single idea into dozens of outputs without jumping between tools. In this advanced Freepik Spaces tutorial, we walk you through how to build end-to-end workflows that generate logos, mockups, image variations, and videos automatically. What you’ll learn in this video: 👉 How Freepik Spaces workflows and nodes work together 👉 Turn one input into multiple variants using Lists 👉 Use assistant nodes to auto-improve prompts with built-in LLMs 👉 Generate industry-aware mockups without manual prompting 👉 Create image variations, storyboards, and videos in bulk 👉 Build scalable systems for agencies, freelancers, and creators This is perfect for designers and creators who want to move beyond manual execution and start building high-leverage AI workflows that save time, cut costs, and scale output effortlessly. You'll find the full video link in the comments.

This might be the most slept-on way to use AI creative tools. It’s called Spaces by Freepik. Spaces is a node based canvas. So you can connect text, image, and video nodes together to build a visual AI workflow. For example, let’s say I wanna make the perfect image of Michael Jordan dunking over a Lamborghini. Before, I’d have to type a text prompt and manually generate 10 different versions, while tweaking the style description every time. But Spaces lets me set up a workflow with 10 different branches that automatically runs this process for me. You can see, I click once, and automatically have 10 different image outputs from all the best image models. When you rig up multiple of these chains together, you basically create an entirely automated system for generating visuals. All we have to do is drop in a single line of text from our script, and this workflow spits out 5 AI generated videos, in our desired style, that are all ready to go in just a few minutes. This type of workflow was super difficult to build before, but with Spaces it’s much much easier. And the beauty of these workflows is that once you build them, you can share a link so that any other users, like your editors, can redownload the entire workflow on their side, in a single click. I think these visual canvases are going to be the future of how people use AI creative tools. Because they make the process feel less like work and more like a video game. If you wanna try this out, check out Spaces on Freepik. Follow Kane K. for more AI creative tips. #ai #artificialintelligence #tech #technology #freepikpartner #design #marketing #aidesign #animation #motiongraphics #productmarketing

Traditional surrogate-based design optimization (SBDO) is hitting a wall, especially with high-dimensional, complex designs. In this new paper, Dr. Namwoo Kang presents a next-gen framework using generative AI, integrating three key models: - Generative model (design synthesis) - Predictive model (performance estimation) - Optimization model (iterative or generative) Rather than optimizing directly in a high-dimensional design space (x), the workflow introduces a low-dimensional latent space (z) learned via generative models. ➡️ z → x → y z = latent variables x = CAD geometry y = performance (drag, stress, etc.) This means we’re no longer hand-coding design parameters or doing trial-and-error with simplified surrogate models. 🧠 Why this matters: - Parametric modeling is no longer a bottleneck - Complex shapes are learned directly from CAD - Dynamic and multimodal performance data (1D, 2D, 3D) can be used - Near real-time optimization is possible #AI #GenerativeDesign #CAE #DesignOptimization

ABM tech. It's tempting to chase the latest shiny tool, right? But I've learned that features alone don't win. Integration does. Think of it like building a kitchen. You could have the best oven, fridge, and stove. But if they don't work together, you'll have a mess. I've seen companies with many ABM tools, but the data doesn't connect, and the teams can't collaborate, resulting in not so good ABM results. The key is a unified platform. I mean one that connects your CRM, marketing automation, intent data, and personalization tools. Imagine this... Your intent data shows a target account is researching your solution, and your CRM automatically picks that up and updates this account's profile. Then, your marketing automation triggers a personalized email while your sales team gets real time alerts. That's what I mean by integration. And that's power. It's like having a GPS for your #ABM strategy. You know exactly where you are and where you're going. Of course, this requires careful planning. Start with your data. 👉🏾Where does it live?  👉🏾How does it flow?  👉🏾Which systems need to talk to each other? Tools like Zapier or Workato can help with these integrations. They can connect disparate systems and automate workflows. But don't forget the human element. Your teams need to be aligned. They need to understand how the tech stack works. They need to use it effectively. #b2bmarketing #marketingstrategy

I experimented with a workflow that combines Gravity Sketch, mixed reality, and Runway's Gen-3 video-to-video AI and got some impressive results, here is what I did: 🚀 Step 1: Using Gravity Sketch in VR, I designed stasis tubes with humanoid figures inside. I placed these models throughout my hallway, integrating them into the real space, using mixed reality mode on my Meta Quest 3 headset. 🎥 Step 2: I filmed myself walking through this mixed reality set, holding a 3D object, capturing my real environment with the 3D models layered in. This gave a first-person view of the scene, as if I were navigating through an alien ship. 🧪 Step 3: Finally, I ran the footage through Runway’s Gen-3 video-to-video AI, using prompts to transform the scene into a space marine navigating an alien ship, complete with eerie stasis tubes and ambient sound effects to drive the atmosphere home. A fast, intuitive way to pre-visualize complex scenes that would otherwise take much longer to design and film traditionally. What this means for creative workflows: 🔹Advanced Storyboarding: With mixed reality, you can set up rough models and get a realistic sense of scale and positioning. You can actually walk through you scene, interacting with it and capturing raw footage directly. 🔹 Quick Pre-Visualization: Using video-to-video genAI, this rough footage can quickly be transformed into something more. It’s a great way to experiment with looks, check in with your client vision, and even lighting before diving into final production. 🔹 Future-Ready Workflows: As video-to-video AI improves, this workflow won’t just be for pre-viz. We’re looking at a future where you could create final-quality outputs straight from this setup, acting out scenes in a mixed reality environment while the AI enhances and polishes everything in real time. Moving towards final generated outputs vs rendered. This opens up a lot of possibilities. You could set up a mixed reality scene, interact with it, and create an entire short film without needing a massive crew or extensive post-production. For now, it’s a powerful way to prototype, storyboard, and explore creative concepts quickly and intuitively. ❓Curious about how mixed reality and AI could transform your creative process? Let’s connect-I’d love to share more insights and explore how these tools can push your projects to the next level.