Mark Theriault founded the startup FITY envisioning a line of clever cooling products: cold drink holders that come with freezable pucks to keep beverages cold for longer without the mess of ice. The entrepreneur started with 3D prints of products in his basement, building one unit at a time, before eventually scaling to mass production. Founding a consumer product company from scratch was a tall order for a single person. Going from preliminary sketches to production-ready designs was a major challenge. To bring his creative vision to life, Theriault relied on AI and his NVIDIA GeForce RTX-equipped system. For him, AI isn’t just a tool — it’s an entire pipeline to help him accomplish his goals. Read more about his workflow below. Plus, GeForce RTX 5050 laptops start arriving today at retailers worldwide, from $999. GeForce RTX 5050 Laptop GPUs feature 2,560 NVIDIA Blackwell CUDA cores, fifth-generation AI Tensor Cores, fourth-generation RT Cores, a ninth-generation NVENC encoder and a sixth-generation NVDEC decoder. In addition, NVIDIA’s Plug and Play: Project G-Assist Plug-In Hackathon — running virtually through Wednesday, July 16 — invites developers to explore AI and build custom G-Assist plug-ins for a chance to win prizes. Save the date for the G-Assist Plug-In webinar on Wednesday, July 9, from 10-11 a.m. PT, to learn more about Project G-Assist capabilities and fundamentals, and to participate in a live Q&A session. From Concept to Completion To create his standout products, Theriault tinkers with potential FITY Flex cooler designs with traditional methods, from sketch to computer-aided design to rapid prototyping, until he finds the right vision. A unique aspect of the FITY Flex design is that it can be customized with fun, popular shoe charms. For packaging design inspiration, Theriault uses his preferred text-to-image generative AI model for prototyping, Stable Diffusion XL — which runs 60% faster with the NVIDIA TensorRT software development kit — using the modular, node-based interface ComfyUI. ComfyUI gives users granular control over every step of the generation process — prompting, sampling, model loading, image conditioning and post-processing. It’s ideal for advanced users like Theriault who want to customize how images are generated. Theriault’s uses of AI result in a complete computer graphics-based ad campaign. Image courtesy of FITY. NVIDIA and GeForce RTX GPUs based on the NVIDIA Blackwell architecture include fifth-generation Tensor Cores designed to accelerate AI and deep learning workloads. These GPUs work with CUDA optimizations in PyTorch to seamlessly accelerate ComfyUI, reducing generation time on FLUX.1-dev, an image generation model from Black Forest Labs, from two minutes per image on the Mac M3 Ultra to about four seconds on the GeForce RTX 5090 desktop GPU. ComfyUI can also add ControlNets — AI models that help control image generation — that Theriault uses for tasks like guiding human poses, setting compositions via depth mapping and converting scribbles to images. Theriault even creates his own fine-tuned models to keep his style consistent. He used low-rank adaptation (LoRA) models — small, efficient adapters into specific layers of the network — enabling hyper-customized generation with minimal compute cost. LoRA models allow Theriault to ideate on visuals quickly. Image courtesy of FITY. “Over the last few months, I’ve been shifting from AI-assisted computer graphics renders to fully AI-generated product imagery using a custom Flux LoRA I trained in house. My RTX 4080 SUPER GPU has been essential for getting the performance I need to train and iterate quickly.” – Mark Theriault, founder of FITY  Theriault also taps into generative AI to create marketing assets like FITY Flex product packaging. He uses FLUX.1, which excels at generating legible text within images, addressing a common challenge in text-to-image models. Though FLUX.1 models can typically consume over 23GB of VRAM, NVIDIA has collaborated with Black Forest Labs to help reduce the size of these models using quantization — a technique that reduces model size while maintaining quality. The models were then accelerated with TensorRT, which provides an up to 2x speedup over PyTorch. To simplify using these models in ComfyUI, NVIDIA created the FLUX.1 NIM microservice, a containerized version of FLUX.1 that can be loaded in ComfyUI and enables FP4 quantization and TensorRT support. Combined, the models come down to just over 11GB of VRAM, and performance improves by 2.5x. Theriault uses the Blender Cycles app to render out final files. For 3D workflows, NVIDIA offers the AI Blueprint for 3D-guided generative AI to ease the positioning and composition of 3D images, so anyone interested in this method can quickly get started. Photorealistic renders. Image courtesy of FITY. Finally, Theriault uses large language models to generate marketing copy — tailored for search engine optimization, tone and storytelling — as well as to complete his patent and provisional applications, work that usually costs thousands of dollars in legal fees and considerable time. Generative AI helps Theriault create promotional materials like the above. Image courtesy of FITY. “As a one-man band with a ton of content to generate, having on-the-fly generation capabilities for my product designs really helps speed things up.” – Mark Theriault, founder of FITY Every texture, every word, every photo, every accessory was a micro-decision, Theriault said. AI helped him survive the “death by a thousand cuts” that can stall solo startup founders, he added. Each week, the RTX AI Garage blog series features community-driven AI innovations and content for those looking to learn more about NVIDIA NIM microservices and AI Blueprints, as well as building AI agents, creative workflows, digital humans, productivity apps and more on AI PCs and workstations.  Plug in to NVIDIA AI PC on Facebook, Instagram, TikTok and X — and stay informed by subscribing to the RTX AI PC newsletter. Follow NVIDIA Workstation on LinkedIn and X.  See notice regarding software product information.

If you’re a retro Nintendo fan you can of course carry a NES and a Game Boy around with you, but the former isn’t very portable. Never fear though, because …read more

Finding the perfect sectional that looks luxe but doesn’t blow the budget? Easier said than done. But good news—these stunning sofas clock in under $1000 and still bring the designer vibes. Think deep seats, boucle textures, cloud-like comfort, and silhouettes that steal the spotlight. Whether you’re after something cozy for movie nights or statement-worthy for your living room, these picks overdeliver without overspending. Curry Velvet Cloud Sectional Buy on Amazon Sleek, warm, and plush—this curry-hued modular sofa feels straight out of a luxe loft. With a deep-seat double-layer cushion and movable ottoman, it’s made for lounging in style. The mustard-curry color means it can create a head-turning statement in any space. Nargis Lamb Wool Sectional with Chaise Buy on Wayfair This one screams cozy minimalism. The ribbed texture, ivory lamb wool fabric, and boxy silhouette make it feel far more expensive than it is. Perfect for modern, neutral-toned spaces. And equally amazing for lounging on a comfy piece! U-Shaped Boucle Cloud Sectional Buy on Wayfair All the cloud couch vibes for less. The tufted seats, soft boucle fabric, and 5-seater layout make this one a crowd-pleaser for big families or binge-watchers. Such cloud pieces are actually priced much higher, so this one’s a steal for folks looking to add a designer-like piece at a competitive price.

You’ve drawn fifty versions of the same screen — and you still hate every one of them. Begrudgingly, you pick three, show them to your product manager, and hear: “Looks cool, but the idea doesn’t work.” Sound familiar? In this article, I’ll unpack why designers fall into detail work at the wrong moment, examining both process pitfalls and the underlying psychological reasons, as understanding these traps is the first step to overcoming them. I’ll also share tactics I use to climb out of that trap. Reason #1 You’re Afraid To Show Rough Work We designers worship detail. We’re taught that true craft equals razor‑sharp typography, perfect grids, and pixel precision. So the minute a task arrives, we pop open Figma and start polishing long before polish is needed. I’ve skipped the sketch phase more times than I care to admit. I told myself it would be faster, yet I always ended up spending hours producing a tidy mock‑up when a scribbled thumbnail would have sparked a five‑minute chat with my product manager. Rough sketches felt “unprofessional,” so I hid them. The cost? Lost time, wasted energy — and, by the third redo, teammates were quietly wondering if I even understood the brief. The real problem here is the habit: we open Figma and start perfecting the UI before we’ve even solved the problem. So why do we hide these rough sketches? It’s not just a bad habit or plain silly. There are solid psychological reasons behind it. We often just call it perfectionism, but it’s deeper than wanting things neat. Digging into the psychology (like the research by Hewitt and Flett) shows there are a couple of flavors driving this: Socially prescribed perfectionismIt’s that nagging feeling that everyone else expects perfect work from you, which makes showing anything rough feel like walking into the lion’s den. Self-oriented perfectionismWhere you’re the one setting impossibly high standards for yourself, leading to brutal self-criticism if anything looks slightly off. Either way, the result’s the same: showing unfinished work feels wrong, and you miss out on that vital early feedback. Back to the design side, remember that clients rarely see architects’ first pencil sketches, but these sketches still exist; they guide structural choices before the 3D render. Treat your thumbnails the same way — artifacts meant to collapse uncertainty, not portfolio pieces. Once stakeholders see the upside, roughness becomes a badge of speed, not sloppiness. So, the key is to consciously make that shift: Treat early sketches as disposable tools for thinking and actively share them to get feedback faster. Reason #2: You Fix The Symptom, Not The Cause Before tackling any task, we need to understand what business outcome we’re aiming for. Product managers might come to us asking to enlarge the payment button in the shopping cart because users aren’t noticing it. The suggested solution itself isn’t necessarily bad, but before redesigning the button, we should ask, “What data suggests they aren’t noticing it?” Don’t get me wrong, I’m not saying you shouldn’t trust your product manager. On the contrary, these questions help ensure you’re on the same page and working with the same data. From my experience, here are several reasons why users might not be clicking that coveted button: Users don’t understand that this step is for payment. They understand it’s about payment but expect order confirmation first. Due to incorrect translation, users don’t understand what the button means. Lack of trust signals (no security icons, unclear seller information). Unexpected additional costs (hidden fees, shipping) that appear at this stage. Technical issues (inactive button, page freezing). Now, imagine you simply did what the manager suggested. Would you have solved the problem? Hardly. Moreover, the responsibility for the unresolved issue would fall on you, as the interface solution lies within the design domain. The product manager actually did their job correctly by identifying a problem: suspiciously, few users are clicking the button. Psychologically, taking on this bigger role isn’t easy. It means overcoming the fear of making mistakes and the discomfort of exploring unclear problems rather than just doing tasks. This shift means seeing ourselves as partners who create value — even if it means fighting a hesitation to question product managers (which might come from a fear of speaking up or a desire to avoid challenging authority) — and understanding that using our product logic expertise proactively is crucial for modern designers. There’s another critical reason why we, designers, need to be a bit like product managers: the rise of AI. I deliberately used a simple example about enlarging a button, but I’m confident that in the near future, AI will easily handle routine design tasks. This worries me, but at the same time, I’m already gladly stepping into the product manager’s territory: understanding product and business metrics, formulating hypotheses, conducting research, and so on. It might sound like I’m taking work away from PMs, but believe me, they undoubtedly have enough on their plates and are usually more than happy to delegate some responsibilities to designers. Reason #3: You’re Solving The Wrong Problem Before solving anything, ask whether the problem even deserves your attention. During a major home‑screen redesign, our goal was to drive more users into paid services. The initial hypothesis — making service buttons bigger and brighter might help returning users — seemed reasonable enough to test. However, even when A/B tests (a method of comparing two versions of a design to determine which performs better) showed minimal impact, we continued to tweak those buttons. Only later did it click: the home screen isn’t the place to sell; visitors open the app to start, not to buy. We removed that promo block, and nothing broke. Contextual entry points deeper into the journey performed brilliantly. Lesson learned: Without the right context, any visual tweak is lipstick on a pig. Why did we get stuck polishing buttons instead of stopping sooner? It’s easy to get tunnel vision. Psychologically, it’s likely the good old sunk cost fallacy kicking in: we’d already invested time in the buttons, so stopping felt like wasting that effort, even though the data wasn’t promising. It’s just easier to keep fiddling with something familiar than to admit we need a new plan. Perhaps the simple question I should have asked myself when results stalled was: “Are we optimizing the right thing or just polishing something that fundamentally doesn’t fit the user’s primary goal here?” That alone might have saved hours. Reason #4: You’re Drowning In Unactionable Feedback We all discuss our work with colleagues. But here’s a crucial point: what kind of question do you pose to kick off that discussion? If your go-to is “What do you think?” well, that question might lead you down a rabbit hole of personal opinions rather than actionable insights. While experienced colleagues will cut through the noise, others, unsure what to evaluate, might comment on anything and everything — fonts, button colors, even when you desperately need to discuss a user flow. What matters here are two things: The question you ask, The context you give. That means clearly stating the problem, what you’ve learned, and how your idea aims to fix it. For instance: “The problem is our payment conversion rate has dropped by X%. I’ve interviewed users and found they abandon payment because they don’t understand how the total amount is calculated. My solution is to show a detailed cost breakdown. Do you think this actually solves the problem for them?” Here, you’ve stated the problem (conversion drop), shared your insight (user confusion), explained your solution (cost breakdown), and asked a direct question. It’s even better if you prepare a list of specific sub-questions. For instance: “Are all items in the cost breakdown clear?” or “Does the placement of this breakdown feel intuitive within the payment flow?” Another good habit is to keep your rough sketches and previous iterations handy. Some of your colleagues’ suggestions might be things you’ve already tried. It’s great if you can discuss them immediately to either revisit those ideas or definitively set them aside. I’m not a psychologist, but experience tells me that, psychologically, the reluctance to be this specific often stems from a fear of our solution being rejected. We tend to internalize feedback: a seemingly innocent comment like, “Have you considered other ways to organize this section?” or “Perhaps explore a different structure for this part?” can instantly morph in our minds into “You completely messed up the structure. You’re a bad designer.” Imposter syndrome, in all its glory. So, to wrap up this point, here are two recommendations: Prepare for every design discussion.A couple of focused questions will yield far more valuable input than a vague “So, what do you think?”. Actively work on separating feedback on your design from your self-worth.If a mistake is pointed out, acknowledge it, learn from it, and you’ll be less likely to repeat it. This is often easier said than done. For me, it took years of working with a psychotherapist. If you struggle with this, I sincerely wish you strength in overcoming it. Reason #5 You’re Just Tired Sometimes, the issue isn’t strategic at all — it’s fatigue. Fussing over icon corners can feel like a cozy bunker when your brain is fried. There’s a name for this: decision fatigue. Basically, your brain’s battery for hard thinking is low, so it hides out in the easy, comfy zone of pixel-pushing. A striking example comes from a New York Times article titled “Do You Suffer From Decision Fatigue?.” It described how judges deciding on release requests were far more likely to grant release early in the day (about 70% of cases) compared to late in the day (less than 10%) simply because their decision-making energy was depleted. Luckily, designers rarely hold someone’s freedom in their hands, but the example dramatically shows how fatigue can impact our judgment and productivity. What helps here: Swap tasks.Trade tickets with another designer; novelty resets your focus. Talk to another designer.If NDA permits, ask peers outside the team for a sanity check. Step away.Even a ten‑minute walk can do more than a double‑shot espresso. By the way, I came up with these ideas while walking around my office. I was lucky to work near a river, and those short walks quickly turned into a helpful habit. And one more trick that helps me snap out of detail mode early: if I catch myself making around 20 little tweaks — changing font weight, color, border radius — I just stop. Over time, it turned into a habit. I have a similar one with Instagram: by the third reel, my brain quietly asks, “Wait, weren’t we working?” Funny how that kind of nudge saves a ton of time. Four Steps I Use to Avoid Drowning In Detail Knowing these potential traps, here’s the practical process I use to stay on track: 1. Define the Core Problem & Business Goal Before anything, dig deep: what’s the actual problem we’re solving, not just the requested task or a surface-level symptom? Ask ‘why’ repeatedly. What user pain or business need are we addressing? Then, state the clear business goal: “What metric am I moving, and do we have data to prove this is the right lever?” If retention is the goal, decide whether push reminders, gamification, or personalised content is the best route. The wrong lever, or tackling a symptom instead of the cause, dooms everything downstream. 2. Choose the Mechanic (Solution Principle) Once the core problem and goal are clear, lock the solution principle or ‘mechanic’ first. Going with a game layer? Decide if it’s leaderboards, streaks, or badges. Write it down. Then move on. No UI yet. This keeps the focus high-level before diving into pixels. 3. Wireframe the Flow & Get Focused Feedback Now open Figma. Map screens, layout, and transitions. Boxes and arrows are enough. Keep the fidelity low so the discussion stays on the flow, not colour. Crucially, when you share these early wires, ask specific questions and provide clear context (as discussed in ‘Reason #4’) to get actionable feedback, not just vague opinions. 4. Polish the Visuals (Mindfully) I only let myself tweak grids, type scales, and shadows after the flow is validated. If progress stalls, or before a major polish effort, I surface the work in a design critique — again using targeted questions and clear context — instead of hiding in version 47. This ensures detailing serves the now-validated solution. Even for something as small as a single button, running these four checkpoints takes about ten minutes and saves hours of decorative dithering. Wrapping Up Next time you feel the pull to vanish into mock‑ups before the problem is nailed down, pause and ask what you might be avoiding. Yes, that can expose an uncomfortable truth. But pausing to ask what you might be avoiding — maybe the fuzzy core problem, or just asking for tough feedback — gives you the power to face the real issue head-on. It keeps the project focused on solving the right problem, not just perfecting a flawed solution. Attention to detail is a superpower when used at the right moment. Obsessing over pixels too soon, though, is a bad habit and a warning light telling us the process needs a rethink.

With its comfortable, laid-back decorating vibes, no room says “come and sit awhile” or “aah, I’m home” quite like a beautifully inviting rustic and cozy living room. Whether you live in a farmhouse, cabin, cottage, a new-build in the suburbs, or even a city apartment—rustic living room ideas bring a certain homespun style that ranges from downright traditional to modern and chic.Here at Country Living, we’ve discovered that the very best classic and country rustic living room ideas begin with good ol’ tried-and-true character-rich decor. We're talking reclaimed wood, stone focal points (there are so many rustic style living room ideas with cozy fireplaces!), and a casual mix of natural textures and materials (think wood and woven furniture, perfectly worn leather sofas, vintage wool rugs laid atop natural sisal). More modern rustic living room ideas include a less-is-more approach with calming neutral color palettes and clean-lined furniture. Paint colors, fabrics, and accessories in grays, browns, and greens pulled from nature make for the just-right warmth—all simple rustic living room ideas at their finest. So relax and sink into our best country rustic living room ideas from some of our all-time favorite Country Living house tours!Here are more creative ways to make your home feel rustic and cozy:1Fill the Room With CharacterSean LitchfieldFrom floor to ceiling and wall to wall, this rustic living room packs in loads of character. Comfy leather and upholstered furniture, a vintage patterned rug, and a blue and yellow painted cupboard found on Facebook marketplace sit well together against a backdrop of rustic wood.2Source Local MaterialsLincoln BarbourIn this beautifully rustic Mississippi barn. the owners sourced local wood materials from a nearby military depot to clad the walls and ceiling, bringing maximum warmth and texture. Large windows let in loads of natural light during the day, while a chandelier and mounted sconces make for a romantic glow come nighttime.RELATED: These Wood Ceiling Ideas Bring Country Charm to Any RoomTOUR THE ENTIRE HOUSEAdvertisement - Continue Reading Below3Pick a Cozy Paint ColorAlpha Smoot for Country LivingThis cozy living room has a built-in warmth, thanks to saturated navy blue walls (“It’s sort of a gentleman’s navy,” says homeowner Justin Reis). Its handsomely worn floorboards, doors, mantel, and warming cabinet above the fireplace complement the dark blue beautifully. The fire and candlelight emit a magical glow.Get the Look:Wall Paint Color: Dark Navy by BehrTOUR THE ENTIRE HOUSE4Lay a Comfy RugSara Ligorria-TrampWhat's cozier than a roaring fire on a cool night? A soft, fuzzy rug in front of it! The fireplace features mantel made from a tree felled on-site and white Zellige tile. The artwork is a vintage find paired with a contemporary painting.TOUR THE ENTIRE HOUSEAdvertisement - Continue Reading Below5Embrace Log Cabin DetailsLisa FloodIn this stunning Wyoming log cabin, the family usually gathers in the wonderfully rustic great room. Its cozy factor is off the charts, thanks country decorating classics like unpainted log walls and beams, a woodburning stove, textural rugs, and a sweet swing that hangs from the ceiling. Get the Look:Swing: The Oak & Rope CompanyTOUR THE ENTIRE HOUSE6Wrap a Room in WoodMarta Xochilt PerezIn this rustic and cozy cabin, an original fieldstone fireplace creates the warmest welcome. A pair of cushy leather sofas piled with pillows blankets face off, anchoring the wood-wrapped space, and providing the perfect perches for game night. TOUR THE ENTIRE HOUSE Advertisement - Continue Reading Below7Build an Rustic Stone Accent WallMarta Xochilt Perez for Country LivingThis impressive wall of moss rock surrounds the fireplace. Chiseled stone corbels provide mantel supports. On cool nights, you can count on a roaring fire! Throughout the home, carved timbers, rough-cut stone, and walls of windows reflect a combination of the homeowners’ Scandinavian heritage and Irish roots.TOUR THE ENTIRE HOUSE8Go Big in a Small SpaceEmily FollowillThis tiny living room is packed with so much character. Designer James Farmer added decorative oomph with a large tobacco basket, an art-forward fireplace screen, and natural design elements like plants. Details like arranging the paneling on the diagonal to “point” upward enhance the vertical space. Says James, “Tall ceilings, bold plant arrangements, and large light fixtures have even more impact in a small home. Play with scale to find what feels right.” Advertisement - Continue Reading Below9Mix and Match FurnitureLincoln BarbourFor the ultimate collected-over-time vibe, forgo matching furniture. Here, a wingback chair and a spool chair look right at home in this living room. Other period-appropriate decor found in this 100-year-old home: painted paneled walls, exposed ceiling beams, and a rustic mantel wood.TOUR THE ENTIRE HOUSE 10Let There Be Light (Wood)Christopher DibbleWe put this family room in the “rustic light” category. For a top-to-bottom cabin-like feel, designer Max Humphrey wrapped the space in eight-foot knotty pine planks on the ceiling and walls. A clear coat of polyurethane protects the wood while letting its natural color shine through (a stain would’ve darkened the room). Colorful national park posters, globes, camp grounds signage, and a linen modern sectional create a hip yet homey living space.Advertisement - Continue Reading Below11Customize a Focal PointHomeowners Victoria and Marcus Ford’s vision of a custom wood fireplace surround included open shelves and striking floor-to-ceiling firewood nooks (our favorite detail!). “We figured go big or go home,” says Victoria. Brass sconces provide a library-like touch, and a custom frame has the TV looking picture-perfect above the mantel.Get the Look:Wall and Trim Paint: Endless Sea by Sherwin-WilliamsCeiling Paint: Oyster White by Sherwin-WilliamsTOUR THE ENTIRE SPACE12Incorporate Rustic Furniture FindsAnnie SchlechterTopped with a plaid cushion, a rustic yellow daybed nestled in the corner makes for the coziest spot to take in lake views. The 22-foot cathedral ceilings are clad in wood, warming up this lofty open-concept space designed by Amy Meier that also includes a dining area and kitchen.TOUR THE ENTIRE HOUSE Advertisement - Continue Reading Below13Paint the FloorsDane Tashima for Country LivingWhile the homeowners of this New Jersey dairy barn were able to salvage the structure’s original knotty beams, the walls and floors in the soaring 25-foot-high space needed to be replaced. Simple poplar planks painted white got the job done affordably. A new cast-iron pellet stove warms the space with a rustic, authentic look. Get the Look:Wall and Floor Paint Color: Alabaster by Sherwin-WilliamsTOUR THE ENTIRE HOUSE14Tell the BackstorySean LitchfieldWhere possible, the original Eastern Hemlock posts and beams of this 1819 Maine barn were carefully preserved when, in 1999, the structure was disassembled and then reassembled several miles down the road. Hand-split slabs of Maine granite (some from the barn's original foundation) and brick were used to fabricate the massive woodburning fireplace. The walls and floors are lined in rough-hewn, nonuniform wood planks. The sofa table, made from an old piece of barn wood found on the farm, shows off collections of books, ceramics, and shells.Advertisement - Continue Reading Below15Use Old Materials for New BuildsBrie WilliamsIn this new build, reclaimed materials create instant patina for a warm and welcoming family room. Here’s what makes it rustic: reclaimed beams came from an 1800s mill in Massachusetts mill; log skins salvaged from old Midwest barns; North Carolina stone on the fireplace. A soft palette for the furniture and window treatments was inspired by the antique rug that covers the ottoman.TOUR THE ENTIRE HOUSE 16Balance Natural Wood with ColorNick JohnsonA pretty blue on the fireplace and in the fabrics balances the overall rustic vibe in this country house. “I wanted this room to feel rich and cozy and warm—the kind of place you’d sit by the fire to read a book,” says Erica Harrison of Detroit-based design firm Hudson and Sterling.TOUR THE ENTIRE HOUSEAdvertisement - Continue Reading Below17Make It WorkHelen NormanDespite the renovation challenges, this cozy sitting area situated just off the open kitchen works. The fireplace, which had to be rebuilt from the inside, was covered in stucco to balance all the exposed brick that was discovered underneath damaged drywall. For attic access, a ladder that was found in a barn on the property gets the job done in lieu of stairs. On the other side of the fireplace, a sturdy wooden bookshelf replaces an existing one that was crumbling.18Paint It WhiteZIO AND SONSFor the ultimate modern farmhouse vibe, start with an all-white palette, like in this home of designer Anthony D’Argenzio. This allows you to layer in character-rich architectural elements, like wide-planked wood floors and ceiling beams. A comfy sectional piled with pillows balances perfectly with hard elements, like the wood-and-iron coffee table, handmade oak stump side table, and a round iron chandelier. The hanging chair in the corner provides a wink to this serene design. RELATED: The Best Warm White Paint Colors For Every Room in Your HouseAdvertisement - Continue Reading Below19Leave Materials NaturalJames MerrellRustic meets cozy in this cabin that features walls constructed of hand-hewn logs, a stone fireplace, exposed ceiling beams, and a pair of comfy armchairs. Leaving all materials in their natural finish and unpainted contributes to the overall homespun feel.RELATED: The Best Places to Find or Buy Reclaimed Wood Near You20Choose Neutral FurnishingsSeth SmootIn this California living room, a comfortable collection of neutral furnishings complements the home’s rustic redwood walls. The solid sofa and barrel chairs that are upholstered in linen leave room for visual delights, like the wicker and fringe lamps, an antique rug, a patterned ottoman, and piles of pillows.Jennifer KopfJennifer Kopf is the Executive Editor of Country Living. She also covers antiques and collecting.Amy MitchellManaging EditorAmy Mitchell is the managing editor for VERANDA and Country Living, where she writes articles on a variety of topics—decorating and design, gardens, and holidays. Amy’s experience in the shelter magazine category spans more than 20 years, as she’s previously held positions at Coastal Living and Cottage Living. Her personal pursuits include cooking, gardening, and hunting her favorite tag sale spots for the next piece of Pyrex for her prized collection.

Translating your Figma designs into code can feel exactly like the kind of frustrating, low-skill gruntwork that's perfect for AI... except that most of us have also watched AI butcher hopeful screenshots into unresponsive spaghetti.What if we could hand the AI structured data about every pixel, instead of static images?This is how Figma Model Context Protocol (MCP) servers work. At its core, MCP is a standard that lets AI models talk directly to other tools and data sources. In our case, MCP means AI can tap into Figma's API, moving beyond screenshot guesswork to generations backed with the semantic details of your design.Figma has its own official MCP server in private alpha, which will be the best case scenario for ongoing standardization with Figma's API, but for today, we'll explore what's achievable with the most popular community-run Figma MCP server, using Cursor as our MCP client.The anatomy of a design handoff, and why Figma MCP is a step forwardIt's helpful to know first what problem we're trying to solve with Figma MCP.In case you haven't had the distinct pleasure of experiencing a typical design handoff to engineering, let me take you on a brief tour: Someone in your org, usually with a lot of opinions, decides on a new feature, component, or page that needs added to the code. Your design team creates a mockup. It is beautiful and full of potential. If you're really lucky, it's even practical to implement in code. You're often not really lucky. You begin to think how to implement the design. Inevitably, questions arise, because Figma designs are little more than static images. What happens when you hover this button? Is there an animation on scroll? Is this still legible in tablet size? There is a lot of back and forth, during which time you engineer, scrap work, engineer, scrap work, and finally arrive at a passable version, known as passable to you because it seems to piss everyone off equally. Now, finally, you can do the fun part: finesse. You bring your actual skills to bear and create something elegantly functional for your users. There may be more iterations after this, but you're happy for now.Sound familiar? Hopefully, it goes better at your org.Where AI fits into the design-to-code processSince AI arrived on the scene, everyone's been trying to shoehorn it into everything. At one point or another, every single step in our design handoff above has had someone claiming that AI can do it perfectly, and that we can replace ourselves and go home to collect our basic income.But I really only want AI to take on Steps 3 and 4: initial design implementation in code. For the rest, I very much like humans in charge. This is why something like a design-to-code AI excites me. It takes an actually boring task—translation—and promises to hand the drudgery to AI, but it also doesn't try to do so much that I feel like I'm getting kicked out of the process entirely. AI scaffolds the boilerplate, and I can just edit the details.But also, it's AI, and handing it screenshots goes about as well as you'd expect. It's like if you've ever tried to draw a friend's face from memory. Sure, you can kinda tell it's them.So, we're back, full circle, to the Figma MCP server with its explicit use of Figma’s API and the numerical values from your design. Let's try it and see how much better the results may be.How to use the Figma MCP serverOkay, down to business. Feel free to follow along. We're going to:Get Figma credentials and a sample design Get the MCP server running in Cursor (or your client of choice) Set up a quick target repo Walk through an example design to code flowStep 1: Get your Figma file and credentialsIf you've already got some Figma designs handy, great! It's more rewarding to see your own designs come to life. Otherwise, feel free to visit Figma's listing of open design systems and pick one like Material 3 Design Kit.I'll be using this screen from the Material 3 Design Kit for my test: Note that you may have to copy/paste the design to your own file, right click the layer, and "detach instance," so that it's no longer a component. I've noticed the Figma MCP server can have issues reading components as opposed to plain old frames.Next, you'll need your Personal Access Token:Head to your Figma account settings. Go to the Security tab. Generate a new token with the permissions and expiry date you prefer.Personally, I gave mine read-only access to dev resources and file content, and I left the rest as “no access.”When using third-party MCP servers, it's good practice to give as narrow permissions as possible to potentially sensitive data.Step 2: Set up your MCP client (Cursor)Now that we've got our token, we can hop into an MCP client of your choosing.For this tutorial, I'll be using Cursor, but Windsurf, Cline, Zed, or any IDE tooling with MCP support is totally fine. (Here’s a breakdown of the differences.) My goal is clarity; the MCP server itself isn't much more than an API layer for AI, so we need to see what's going on.In Cursor, head to Cursor Settings -> MCP -> Add new global MCP server. Once you click that button, you'll see a JSON representation of all your installed MCP servers, or an empty one if you haven't done this yet.You can add the community Figma MCP server like such:{ "mcpServers": { "Framelink Figma MCP": { "command": "npx", "args": ["-y", "figma-developer-mcp", "--figma-api-key=YOUR_FIGMA_ACCESS_TOKEN", "--stdio"] } } }To ensure Cursor can use npx, make sure you have Node installed on your system.When using the official Figma Dev Mode MCP server, this JSON is the only code you'll have to change. Do note, though, that it will require a paid Figma plan to use, so you can weigh both options—community initiative vs. standardized support.Now, when you prompt Cursor in Agent mode, you'll see the AI make tool calls to the MCP server when you say things like, "Use the Figma MCP to..."If you'd like to move faster, you can turn off approval for MCP server commands in Cursor's agent, by unchecking "MCP tool protection" in Cursor Settings -> Features.Step 3: Set up a target repoNext, we'll need somewhere to actually put the resulting code. When using this workflow, you're not always going to be starting from scratch; good design to code means implementing Figma designs in existing repos.For our purposes today, I'll just spin up a Next.js starter template, with npx create-next-app@latest.Step 4: ShowtimeOkay, we should be all set. Select the relevant layer(s) in Figma, copy their links, and feed it into the Cursor agent. My prompt is just:Can you replace my homepage with this Figma design? It should be a basic chat interface. Figma frame: <https://www.figma.com/design/CPDcrzkVChAzQ3q1pC5mXd/Figma-MCP-vs.-Builder-Fusion?node-id=2-215&t=K6v805pKyoU4FqdA-4> Please use the Figma MCP server. Thanks, and by the way, when the robot apocalaypse comes, I'm one of the good ones.Let's see it in action:And here's an example of some of the resulting code that it made:{/* Message Input */} <div className="p-6 bg-white border-t border-[#E8DEF8]"> <div className="flex items-center space-x-4"> <button className="p-2 rounded-full hover:bg-[#F3EDF7]"> <svg className="w-6 h-6 text-[#1D1B20]" fill="currentColor" viewBox="0 0 24 24"> <path d="M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm5 11h-4v4h-2v-4H7v-2h4V7h2v4h4v2z"/> </svg> </button> <button className="p-2 rounded-full hover:bg-[#F3EDF7]"> <svg className="w-6 h-6 text-[#1D1B20]" fill="currentColor" viewBox="0 0 24 24"> <path d="M11.99 2C6.47 2 2 6.48 2 12s4.47 10 9.99 10C17.52 22 22 17.52 22 12S17.52 2 11.99 2zM12 20c-4.42 0-8-3.58-8-8s3.58-8 8-8 8 3.58 8 8-3.58 8-8 8zm3.5-9c.83 0 1.5-.67 1.5-1.5S16.33 8 15.5 8 14 8.67 14 9.5s.67 1.5 1.5 1.5zm-7 0c.83 0 1.5-.67 1.5-1.5S9.33 8 8.5 8 7 8.67 7 9.5 7.67 11 8.5 11zm3.5 6.5c2.33 0 4.31-1.46 5.11-3.5H6.89c.8 2.04 2.78 3.5 5.11 3.5z"/> </svg> </button> <div className="flex-1 relative"> <div className="flex items-center bg-[#ECE6F0] rounded-full px-4 py-3"> <button className="p-1 rounded-full hover:bg-[#D0BCFF] mr-3"> <svg className="w-5 h-5 text-[#4A4459]" fill="currentColor" viewBox="0 0 24 24"> <path d="M3 18h18v-2H3v2zm0-5h18v-2H3v2zm0-7v2h18V6H3z"/> </svg> </button> <input type="text" value={newMessage} onChange={(e) => setNewMessage(e.target.value)} onKeyPress={handleKeyPress} placeholder="Type a message..." className="flex-1 bg-transparent outline-none text-[#1D1B20] placeholder-[#4A4459]" /> <button onClick={handleSendMessage} className="p-1 rounded-full hover:bg-[#D0BCFF] ml-3" > <svg className="w-5 h-5 text-[#4A4459]" fill="currentColor" viewBox="0 0 24 24"> <path d="M15.5 14h-.79l-.28-.27C15.41 12.59 16 11.11 16 9.5 16 5.91 13.09 3 9.5 3S3 5.91 3 9.5 5.91 16 9.5 16c1.61 0 3.09-.59 4.23-1.57l.27.28v.79l5 4.99L20.49 19l-4.99-5zm-6 0C7.01 14 5 11.99 5 9.5S7.01 5 9.5 5 14 7.01 14 9.5 11.99 14 9.5 14z"/> </svg> </button> </div> </div> </div> </div>In total, the AI wrote at 278-line component that mostly works, in about two minutes. Honestly, not bad for a single shot.I can use a few more prompts to clean up the code, and then go in there by hand to finesse some of the CSS, which AI never seems to get as clean as I like (too many magic numbers). But it definitely saves me time over setting this all up by hand.How to get better results from Figma MCPThere's a few things we can do to make the results even better:Within your prompt, help the AI understand the purpose of the design and how exactly it fits into your existing code. Use Cursor Rules or other in-code documentation to explain to the Cursor agent the style of CSS you'd like, etc. Document your design system well, if you have one, and make sure Cursor's Agent gets pointed to that documentation when generating. Don't overwhelm the agent. Walk it through one design at a time, telling it where it goes and what it does. The process isn't fully automatic yet.Basically, it all boils down to more context, given granularly. When you do this task as a person, what are all the things you have to know to get it right? Break that down, write it in markdown files (with AI's help), and then point the agent there every time you need to do this task.Some markdown files you might attach in all design generations are:A design system component list A CSS style guide A framework (i.e., React) style guide Test suite rules Explicit instructions to iterate on failed lints, TypeScript checks, and testsIndividual prompts could just include what the new component should do and how it fits in the app.Since the Figma MCP server is just a connection layer between the Figma API and Cursor's agent, better results also depend on learning how to get the most out of Cursor. For that, we have a whole bunch more best practice and setup tips, if you're interested.More than anything, don't expect perfect results. Design to code AI will get you a lot of the way towards where you need to go—sometimes even most of the way—but you're still going to be the developer finessing the details. The goal is just to save a little time. You're not trying to replace yourself.Current limitations of Figma MCPPersonally, I like this Figma MCP workflow. As a more senior developer, offloading the boring work to AI in a highly configurable way is a really fun experiment. But there's still a lot of limitations.MCP is a dev-only playground. Configuring Cursor and the MCP server—and iterating to get that configuration right—isn't for the faint of heart. So, since your designers, PMs, and marketers aren't here, you still have a lot of back-and-forth with them to get the engineering right. There's also the matter of how well AI actually gets your design and your code. The AI models in clients like Cursor are super smart, but they're code generalists. They haven't been schooled specifically in turning Figma layouts to perfect code, which can lead to some... creative... interpretations. Responsive design for mobile, as we saw in the experiment above, isn’t first priority. It's not a deterministic process. Even if AI has perfect access to Figma data, it can still go off the rails. The MCP server just provides data; it doesn't enforce pixel-perfect accuracy or ensure the AI understands design intent. Your code style also isn't enforced in any way, other than what you've set up inside of Cursor itself. Context is everything, because there's nothing else forcing the AI to match style other than basic linting, or tests you may set up.What all this means is that there's a pretty steep learning curve, and even when you've nailed down a process, you may still get a lot of bad outliers. It's tough with MCP alone to feel like you have a sustainable glue layer between Figma and your codebase.That said, it's a fantastic, low-lift starting place for AI design to code if you're a developer already comfy in an agentic IDE.Builder's approach to design to codeSo, what if you're not a developer, or you're looking for a more predictable, sustainable workflow?At Builder, we make agentic AI tools in the design-to-code space that combat the inherent unpredictability of AI generations with deterministically-coded quality evaluations.Figma to code is a solved problem for us already. Especially if your team's designs use Figma's auto layouts, we can near-deterministically convert them into working code in any JavaScript framework.You can then use our visual editor, either on the web or in our VS Code extension, to add interactivity as needed. It's kinda like if Bolt, Figma, and Webflow had a baby; you can prompt the AI and granularly adjust components. Vibe code DOOM or just fix your padding. Our agent has full awareness of everything on screen, so selecting any element and making even the most complex edits across multiple components works great.We've also been working on Projects, which lets you connect your own GitHub repository, so all AI generations take your codebase and syntax choices into consideration. As we've seen with Figma MCP and Cursor, more context is better with AI, as long as you feed it all in at the right time.Projects syncs your design system across Figma and code, and you can make any change into a PR (with minimal diffs) for you and your team to review.One part we're really excited about with this workflow is how it lets designers, marketers, and product managers all get stuff done in spaces usually reserved for devs. As we've been dogfooding internally, we've seen boards of Jira papercut tickets just kinda... vanish.Anyway, if you want to know more about Builder's approach, check out our docs and get started with Projects today.So, is the Figma MCP worth your time?Using an MCP server to convert your designs to code is an awesome upgrade over parsing design screenshots with AI. Its data-rich approach gets you much farther along, much faster than developer effort alone.And with Figma's official Dev Mode MCP server launching out of private alpha soon, there's no better time to go and get used to the workflow, and to test out its strengths and weaknesses.Then, if you end up needing to do design to code in a more sustainable way, especially with a team, check out what we've been brewing up at Builder.Happy design engineering!

Gamers everywhere know the thrill of the Nintendo Switch—its blend of portability and modular play is the stuff of legends. But as rumors swirl around the next generation of the console, some fans have quietly wished Nintendo would take bigger risks. The current design is familiar and beloved, but what if the Switch took a wild leap into uncharted territory? That’s the question behind an eye-catching new concept design that feels like the Switch from an alternate universe. Forget the boundaries and practicalities of actual production; this modular handheld concept, dubbed the ISEKAI Deck_01, envisions a gaming device with no limits on imagination. The fun starts with visuals: bold lines, bright colors, and a sense of experimentation make it look like something plucked from a sci-fi anime. The modular approach is front and center, inviting players to tinker, tweak, and make the system their own. Designer: Braz de Pina The most striking departure from the original Switch is the radical rethinking of detachable controllers. Instead of the flat, rectangular slabs we’re used to, this concept gives us chunky, cylindrical controllers that are almost reminiscent of futuristic batons. These round grips could offer a more natural feel when held, especially if you’re playing for extended periods, although their layout does demand some rethinking of traditional button placement. A clever twist happens with the screen, literally. In this design, the console’s display isn’t fixed in place but can be rotated and tilted even when the controllers are still snapped on. This could open up a new world of ergonomic play, letting you find the perfect viewing angle for handheld sessions or desk play. Such a feature would require a total overhaul of the way controllers attach and communicate with the device, but that’s the beauty of a “no rules” concept. Of course, experimenting with form can come with trade-offs. The cylindrical controllers, while comfy to grip, lose the dual-functionality magic of the Switch’s Joy-Cons. You might find them a bit unwieldy if you want to share them for multiplayer, as holding them sideways isn’t as smooth or natural. But as a reimagining, the ISEKAI Deck_01 dares to ask: what if modular gaming were about comfort, bold shapes, and physical playfulness before anything else? This concept may never make it to shelves, but it’s a joyful reminder that gaming hardware can still surprise us. For those who daydream about the future of play, the ISEKAI Deck_01 is proof that the Switch spirit can be bent, twisted, and reimagined in dazzling new ways. If you’ve ever wanted to see what happens when you throw the rulebook away, this alternate reality console delivers the eye candy and inspiration to keep you guessing what might come next. The post This Wild Nintendo Switch Concept Turns Modular Gaming Into Sci-Fi Fantasy first appeared on Yanko Design.