Editor’s note: This blog is a part of Into the Omniverse, a series focused on how developers, 3D practitioners and enterprises can transform their workflows using the latest advances in OpenUSD and NVIDIA Omniverse. Simulated driving environments enable engineers to safely and efficiently train, test and validate autonomous vehicles (AVs) across countless real-world and edge-case scenarios without the risks and costs of physical testing. These simulated environments can be created through neural reconstruction of real-world data from AV fleets or generated with world foundation models (WFMs) — neural networks that understand physics and real-world properties. WFMs can be used to generate synthetic datasets for enhanced AV simulation. To help physical AI developers build such simulated environments, NVIDIA unveiled major advances in WFMs at the GTC Paris and CVPR conferences earlier this month. These new capabilities enhance NVIDIA Cosmos — a platform of generative WFMs, advanced tokenizers, guardrails and accelerated data processing tools. Key innovations like Cosmos Predict-2, the Cosmos Transfer-1 NVIDIA preview NIM microservice and Cosmos Reason are improving how AV developers generate synthetic data, build realistic simulated environments and validate safety systems at unprecedented scale. Universal Scene Description (OpenUSD), a unified data framework and standard for physical AI applications, enables seamless integration and interoperability of simulation assets across the development pipeline. OpenUSD standardization plays a critical role in ensuring 3D pipelines are built to scale. NVIDIA Omniverse, a platform of application programming interfaces, software development kits and services for building OpenUSD-based physical AI applications, enables simulations from WFMs and neural reconstruction at world scale. Leading AV organizations — including Foretellix, Mcity, Oxa, Parallel Domain, Plus AI and Uber — are among the first to adopt Cosmos models. Foundations for Scalable, Realistic Simulation Cosmos Predict-2, NVIDIA’s latest WFM, generates high-quality synthetic data by predicting future world states from multimodal inputs like text, images and video. This capability is critical for creating temporally consistent, realistic scenarios that accelerate training and validation of AVs and robots. In addition, Cosmos Transfer, a control model that adds variations in weather, lighting and terrain to existing scenarios, will soon be available to 150,000 developers on CARLA, a leading open-source AV simulator. This greatly expands the broad AV developer community’s access to advanced AI-powered simulation tools. Developers can start integrating synthetic data into their own pipelines using the NVIDIA Physical AI Dataset. The latest release includes 40,000 clips generated using Cosmos. Building on these foundations, the Omniverse Blueprint for AV simulation provides a standardized, API-driven workflow for constructing rich digital twins, replaying real-world sensor data and generating new ground-truth data for closed-loop testing. The blueprint taps into OpenUSD’s layer-stacking and composition arcs, which enable developers to collaborate asynchronously and modify scenes nondestructively. This helps create modular, reusable scenario variants to efficiently generate different weather conditions, traffic patterns and edge cases. Driving the Future of AV Safety To bolster the operational safety of AV systems, NVIDIA earlier this year introduced NVIDIA Halos — a comprehensive safety platform that integrates the company’s full automotive hardware and software stack with AI research focused on AV safety. The new Cosmos models — Cosmos Predict- 2, Cosmos Transfer- 1 NIM and Cosmos Reason — deliver further safety enhancements to the Halos platform, enabling developers to create diverse, controllable and realistic scenarios for training and validating AV systems. These models, trained on massive multimodal datasets including driving data, amplify the breadth and depth of simulation, allowing for robust scenario coverage — including rare and safety-critical events — while supporting post-training customization for specialized AV tasks. At CVPR, NVIDIA was recognized as an Autonomous Grand Challenge winner, highlighting its leadership in advancing end-to-end AV workflows. The challenge used OpenUSD’s robust metadata and interoperability to simulate sensor inputs and vehicle trajectories in semi-reactive environments, achieving state-of-the-art results in safety and compliance. Learn more about how developers are leveraging tools like CARLA, Cosmos, and Omniverse to advance AV simulation in this livestream replay: Hear NVIDIA Director of Autonomous Vehicle Research Marco Pavone on the NVIDIA AI Podcast share how digital twins and high-fidelity simulation are improving vehicle testing, accelerating development and reducing real-world risks. Get Plugged Into the World of OpenUSD Learn more about what’s next for AV simulation with OpenUSD by watching the replay of NVIDIA founder and CEO Jensen Huang’s GTC Paris keynote. Looking for more live opportunities to learn more about OpenUSD? Don’t miss sessions and labs happening at SIGGRAPH 2025, August 10–14. Discover why developers and 3D practitioners are using OpenUSD and learn how to optimize 3D workflows with the self-paced “Learn OpenUSD” curriculum for 3D developers and practitioners, available for free through the NVIDIA Deep Learning Institute. Explore the Alliance for OpenUSD forum and the AOUSD website. Stay up to date by subscribing to NVIDIA Omniverse news, joining the community and following NVIDIA Omniverse on Instagram, LinkedIn, Medium and X.

“Wait, can users actually add products to the cart?”Every prototype faces that question or one like it. You start to explain it’s “just Figma,” “just dummy data,” but what if you didn’t need disclaimers?What if you could hand clients—or your team—a working, data-connected mock-up of their website, or new pages and components, in less time than it takes to wireframe?That’s the challenge we’ll tackle today. But first, we need to look at:The problem with today’s prototyping toolsPick two: speed, flexibility, or interactivity.The prototyping ecosystem, despite having amazing software that addresses a huge variety of needs, doesn’t really have one tool that gives you all three.Wireframing apps let you draw boxes in minutes but every button is fake. Drag-and-drop builders animate scroll triggers until you ask for anything off-template. Custom code frees you… after you wave goodbye to a few afternoons.AI tools haven’t smashed the trade-off; they’ve just dressed it in flashier costumes. One prompt births a landing page, the next dumps a 2,000-line, worse-than-junior-level React file in your lap. The bottleneck is still there. Builder’s approach to website mockupsWe’ve been trying something a little different to maintain speed, flexibility, and interactivity while mocking full websites. Our AI-driven visual editor:Spins up a repo in seconds or connects to your existing one to use the code as design inspiration. React, Vue, Angular, and Svelte all work out of the box. Lets you shape components via plain English, visual edits, copy/pasted Figma frames, web inspos, MCP tools, and constant visual awareness of your entire website. Commits each change as a clean GitHub pull request your team can review like hand-written code. All your usual CI checks and lint rules apply.And if you need a tweak, you can comment to @builderio-bot right in the GitHub PR to make asynchronous changes without context switching.This results in a live site the café owner can interact with today, and a branch your devs can merge tomorrow. Stakeholders get to click actual buttons and trigger real state—no more “so, just imagine this works” demos.Let’s see it in action.From blank canvas to working mockup in five promptsToday, I’m going to mock up a fake business website. You’re welcome to create a real one.Before we fire off a single prompt, grab a note and write:Business name & vibe Core pages Primary goal Brand palette & toneThat’s it. Don’t sweat the details—we can always iterate. For mine, I wrote:1. Sunny Trails Bakery — family-owned, feel-good, smells like warm cinnamon. 2. Home, About, Pricing / Subscription Box, Menu (with daily specials). 3. Drive online orders and foot traffic—every CTA should funnel toward “Order Now” or “Reserve a Table.” 4. Warm yellow, chocolate brown, rounded typography, playful copy.We’re not trying to fit everything here. What matters is clarity on what we’re creating, so the AI has enough context to produce usable scaffolds, and so later tweaks stay aligned with the client’s vision. Builder will default to using React, Vite, and Tailwind. If you want a different JS framework, you can link an existing repo in that stack. In the near future, you won’t need to do this extra step to get non-React frameworks to function.(Free tier Builder gives you 5 AI credits/day and 25/month—plenty to follow along with today’s demo. Upgrade only when you need it.)An entire website from the first promptNow, we’re ready to get going.Head over to Builder.io and paste in this prompt or your own:Create a cozy bakery website called “Sunny Trails Bakery” with pages for: • Home • About • Pricing • Menu Brand palette: warm yellow and chocolate brown. Tone: playful, inviting. The restaurant is family-owned, feel-good, and smells like cinnamon. The goal of this site is to drive online orders and foot traffic—every CTA should funnel toward "Order Now" or "Reserve a Table."Once you hit enter, Builder will spin up a new dev container, and then inside that container, the AI will build out the first version of your site. You can leave the page and come back when it’s done.Now, before we go further, let’s create our repo, so that we get version history right from the outset. Click “Create Repo” up in the top right, and link your GitHub account.Once the process is complete, you’ll have a brand new repo.If you need any help on this step, or any of the below, check out these docs.Making the mockup’s order system workFrom our one-shot prompt, we’ve already got a really nice start for our client. However, when we press the “Order Now” button, we just get a generic alert. Let’s fix this.The best part about connecting to GitHub is that we get version control. Head back to your dashboard and edit the settings of your new project. We can give it a better name, and then, in the “Advanced” section, we can change the “Commit Mode” to “Pull Requests.”Now, we have the ability to create new branches right within Builder, allowing us to make drastic changes without worrying about the main version. This is also helpful if you’d like to show your client or team a few different versions of the same prototype.On a new branch, I’ll write another short prompt:Can you make the "Order Now" button work, even if it's just with dummy JSON for now?As you can see in the GIF above, Builder creates an ordering system and a fully mobile-responsive cart and checkout flow.Now, we can click “Send PR” in the top right, and we have an ordinary GitHub PR that can be reviewed and merged as needed.This is what’s possible in two prompts. For our third, let’s gussy up the style.If you’re like me, you might spend a lot of time admiring other people’s cool designs and learning how to code up similar components in your own style.Luckily, Builder has this capability, too, with our Chrome extension. I found a “Featured Posts” section on OpenAI’s website, where I like how the layout and scrolling work. We can copy and paste it onto our “Featured Treats” section, retaining our cafe’s distinctive brand style.Don’t worry—OpenAI doesn’t mind a little web scraping.You can do this with any component on any website, so your own projects can very quickly become a “best of the web” if you know what you’re doing.Plus, you can use Figma designs in much the same way, with even better design fidelity. Copy and paste a Figma frame with our Figma plugin, and tell the AI to either use the component as inspiration or as a 1:1 to reference for what the design should be.(You can grab our design-to-code guide for a lot more ideas of what this can help you accomplish.)Now, we’re ready to send our PR. This time, let’s take a closer look at the code the AI has created.As you can see, the code is neatly formatted into two reusable components. Scrolling down further, I find a CSS file and then the actual implementation on the homepage, with clean JSON to represent the dummy post data.Design tweaks to the mockup with visual editsOne issue that cropped up when the AI brought in the OpenAI layout is that it changed my text from “Featured Treats” to “Featured Stories & Treats.” I’ve realized I don’t like either, and I want to replace that text with: “Fresh Out of the Bakery.”It would be silly, though, to prompt the AI just for this small tweak. Let’s switch into edit mode.Edit Mode lets you select any component and change any of its content or underlying CSS directly. You get a host of Webflow-like options to choose from, so that you can finesse the details as needed.Once you’ve made all the visual changes you want—maybe tweaking a button color or a border radius—you can click “Apply Edits,” and the AI will ensure the underlying code matches your repo’s style.Async fixes to the mockup with Builder BotNow, our pull request is nearly ready to merge, but I found one issue with it:When we copied the OpenAI website layout earlier, one of the blog posts had a video as its featured graphic instead of just an image. This is cool for OpenAI, but for our bakery, I just wanted images in this section. Since I didn’t instruct Builder’s AI otherwise, it went ahead and followed the layout and created extra code for video capability.No problem. We can fix this inside GItHub with our final prompt. We just need to comment on the PR and tag builderio-bot. Within about a minute, Builder Bot has successfully removed the video functionality, leaving a minimal diff that affects only the code it needed to. For example: Returning to my project in Builder, I can see that the bot’s changes are accounted for in the chat window as well, and I can use the live preview link to make sure my site works as expected:Now, if this were a real project, you could easily deploy this to the web for your client. After all, you’ve got a whole GitHub repo. This isn’t just a mockup; it’s actual code you can tweak—with Builder or Cursor or by hand—until you’re satisfied to run the site in production.So, why use Builder to mock up your website?Sure, this has been a somewhat contrived example. A real prototype is going to look prettier, because I’m going to spend more time on pieces of the design that I don’t like as much.But that’s the point of the best AI tools: they don’t take you, the human, out of the loop.You still get to make all the executive decisions, and it respects your hard work. Since you can constantly see all the code the AI creates, work in branches, and prompt with component-level precision, you can stop worrying about AI overwriting your opinions and start using it more as the tool it’s designed to be.You can copy in your team’s Figma designs, import web inspos, connect MCP servers to get Jira tickets in hand, and—most importantly—work with existing repos full of existing styles that Builder will understand and match, just like it matched OpenAI’s layout to our little cafe.So, we get speed, flexibility, and interactivity all the way from prompt to PR to production.Try Builder today.

The farmhouse, Flint Farm, in North Hertfordshire, was in poor condition with a number of unsympathetic additions that had altered its character over the years. Will Gamble Architects was appointed to restore and extend it for a young couple who wanted to transform it into their long-term family home and improve the house’s relationship with its garden and wider farmyard setting. While the original brief had been to replace an existing conservatory with a new extension, the practice encouraged the client to extend by integrating an adjacent barn into the envelope of the reworked house, changing the way the property was used.Advertisement Existing unsympathetic extensions were removed and the internal layout was reconfigured, with a new linking element added between the barn and farmhouse. The series of internal spaces that has been created is designed to retain the character of the historic listed property. Architect’s view The barn was sensitively restored and converted into an informal living space. Its timber-framed structure was refurbished and left exposed to celebrate the historic fabric of the barn and the craftsmanship of its original construction. A contemporary picture window with parts of the historic timber frame exposed within its reveals frames a view of the garden, as well as the barn’s unique structure. The extension, that links both barn and farmhouse, is deliberately contemporary in appearance to ensure that the historic buildings remain legible. It’s low-rise, built into the sloping garden and particularly lightweight in appearance. Floor-to-ceiling glass sits on a plinth of semi-knapped flint, rooting the intervention into the garden. A ribbon of black steel, with shallow peaks and troughs hovers above. The form of this ribbon draws inspiration from the distinctive black timber-clad gables that characterise the farmhouse and the surrounding outbuildings of the old farmstead. Internally the addition’s structure is exposed, much like the historic timber framed structure of the farmhouse and the barn. The interiors are tactile, defined by texture and pattern and inspired by the characteristics of the old farmstead. Miles Kelsey, associate, Will Gamble ArchitectsAdvertisement Client’s view We bought the farmhouse as a family home to move out of our two-bed flat in north London. Will visited the farmhouse with us whilst we were working through the purchase to understand what we were looking to do and went on to support us through each stage. The farmhouse was a combination of the original 16th century timber-framed building that had been added to with unattractive, unusable, and poorly planned extensions that meant the house was completely disconnected from the garden. Will and Miles transformed the whole house including moving the front door, converting an adjacent barn and building the modern extension as our kitchen and dining room that makes the best of the garden and views. The process that Will and Miles ran was a perfect balance of what we wanted, Sophie’s specific tastes and creativity combined with the benefit of the architects views and what they have done before. What really stood out to us was the way they worked with the council during the planning process so we got consent for almost everything we wanted, expressing their own views but ensuring we were always leading the process and the attention to detail during the build stage. Overall we are incredibly happy with what Will and Miles helped us create and the way they led us through the whole process.   Source:Will Gamble Architects Project data Location North Hertfordshire Start on site April 2023 Completion February 2025 Gross internal floor area 320m2 Form of contract or procurement route JCT MW Building Contract. Design-Bid-Build Architect Will Gamble Architects Client Private Structural engineer Axiom Structures Principal designer Will Gamble Architects Main contractor Elite Construction

June 5, 20254 min readThe Trump-Musk Fight Could Have Huge Consequences for U.S. Space ProgramsA vitriolic war of words between President Donald Trump and SpaceX CEO Elon Musk could have profound repercussions for the nation’s civil and military space programsBy Lee Billings edited by Dean VisserElon Musk (left) and President Donald Trump (right) seemed to be on good terms during a press briefing in the Oval Office at the White House on May 30, 2025, but the event proved to be the calm before a social media storm. Kevin Dietsch/Getty ImagesFor several hours yesterday, an explosively escalating social media confrontation between arguably the world’s richest man, Elon Musk, and the world’s most powerful, President Donald Trump, shook U.S. spaceflight to its core.The pair had been bosom-buddy allies ever since Musk’s fateful endorsement of Trump last July—an event that helped propel Trump to an electoral victory and his second presidential term. But on May 28 Musk announced his departure from his official role overseeing the U.S. DOGE Service. And on May 31 the White House announced that it was withdrawing Trump’s nomination of Musk’s close associate Jared Isaacman to lead NASA. Musk abruptly went on the attack against the Trump administration, criticizing the budget-busting One Big Beautiful Bill Act, now navigating through Congress, as “a disgusting abomination.”Things got worse from there as the blowup descended deeper into threats and insults. On June 5 Trump suggested on his own social-media platform, Truth Social, that he could terminate U.S. government contracts with Musk’s companies, such as SpaceX and Tesla. Less than an hour later, the conflict suddenly grew more personal, with Musk taking to X, the social media platform he owns, to accuse Trump—without evidence—of being incriminated by as-yet-unreleased government documents related to the illegal activities of convicted sex offender Jeffrey Epstein.On supporting science journalismIf you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.Musk upped the ante further in follow-up posts in which he endorsed a suggestion for impeaching Trump and, separately, declared in a now deleted post that because of the president’s threat, SpaceX “will begin decommissioning its Dragon spacecraft immediately.” (Some five hours after his decommissioning comment, tempers had apparently cooled enough for Musk to walk back the remark in another X post: “Ok, we won’t decommission Dragon.”)Dragon is a crucial workhorse of U.S. human spaceflight. It’s the main way NASA’s astronauts get to and from the International Space Station (ISS) and also a key component of a contract between NASA and SpaceX to safely deorbit the ISS in 2031. If Dragon were to be no longer be available, NASA would, in the near term, have to rely on either Russian Soyuz vehicles or on Boeing’s glitch-plagued Starliner spacecraft for its crew transport—and the space agency’s plans for deorbiting the ISS would essentially go back to the drawing board. More broadly, NASA uses SpaceX rockets to launch many of its science missions, and the company is contracted to ferry astronauts to and from the surface of the moon as part of the space agency’s Artemis III mission.Trump’s and Musk’s retaliatory tit for tat also raises the disconcerting possibility of disrupting other SpaceX-centric parts of U.S. space plans, many of which are seen as critical for national security. Thanks to its wildly successful reusable Falcon 9 and Falcon Heavy rockets, the company presently provides the vast majority of space launches for the Department of Defense. And SpaceX’s constellation of more than 7,000 Starlink communications satellites has become vitally important to war fighters in the ongoing conflict between Russia and U.S.-allied Ukraine. SpaceX is also contracted to build a massive constellation of spy satellites for the DOD and is considered a leading candidate for launching space-based interceptors envisioned as part of Trump’s “Golden Dome” missile-defense plan.Among the avalanche of reactions to the incendiary spectacle unfolding in real time, one of the most extreme was from Trump’s influential former adviser Steve Bannon, who called on the president to seize and nationalize SpaceX. And in an interview with the New York Times, Bannon, without evidence, accused Musk, a naturalized U.S. citizen, of being an “illegal alien” who “should be deported from the country immediately.”NASA, for its part, attempted to stay above the fray via a carefully worded late-afternoon statement from the space agency’s press secretary Bethany Stevens: “NASA will continue to execute upon the President’s vision for the future of space,” Stevens wrote. “We will continue to work with our industry partners to ensure the President’s objectives in space are met.”The response from the stock market was, in its own way, much less muted. SpaceX is not a publicly traded company. But Musk’s electric car company Tesla is. And it experienced a massive sell-off at the end of June 5’s trading day: Tesla’s share price fell down by 14 percent, losing the company a whopping $152 billion of its market value.Today a rumored détente phone conversation between the two men has apparently been called off, and Trump has reportedly said he now intends to sell the Tesla he purchased in March in what was then a gesture of support for Musk. But there are some signs the rift may yet heal: Musk has yet to be deported; SpaceX has not been shut down; Tesla’s stock price is surging back from its momentary heavy losses; and it seems NASA astronauts won’t be stranded on Earth or on the ISS for the time being.Even so, the entire sordid episode—and the possibility of further messy clashes between Trump and Musk unfolding in public—highlights a fundamental vulnerability at the heart of the nation’s deep reliance on SpaceX for access to space. Outsourcing huge swaths of civil and military space programs to a disruptively innovative private company effectively controlled by a single individual certainly has its rewards—but no shortage of risks, too.

A Peloton perched in the living room. A set of weights on the bedroom floor. Some wellness products have a way of making their presence known. But even the smaller things—think daily supplements, mushroom tinctures, herbal teas—can slowly start to sprawl out everywhere. With the rise and awareness of holistic health habits, wellness routines that rival your skincare shelf, and obsessions like ProteinTok—a whole corner of the internet dedicated to everything protein—you might find that wellness has taken over your kitchen. Suddenly, your blender is battling for space with the hydration powders, collagen tubs, and stacks of snack bars. If you don’t have a place to properly store it all, your kitchen can start to be more overwhelming than calming. But with thoughtful design, proper planning, and smart storage solutions, you can integrate it all into your home in a way that feels serene and seamless. We asked designers and wellness experts how they manage their ever-expanding collection of products and design their kitchens with well-being in mind.Consider An Appliance GarageTessa NeustadtGreen cabinet doors conceal the appliances in this kitchen by Interior Archaeology.“For things that need to be in reach and on the counter, we put everything in an appliance garage,” shares Lynn Kloythanomsup of Landed Interiors and Homes. By that she means is a built-in cabinet or nook—typically integrated into the cabinetry—that features a door that lifts, rolls, or swings open and shut to conceal bulky appliances. Designer Hollie Velten of Spaces by Hollie Velten is also a fan of this feature and notices more clients requesting it. “A custom appliance garage allows things like tea supplies to be accessible for entertaining but hidden for everyday use.”It’s not just designers who advocate for this intentional placement—wellness experts themselves are just as mindful of it. “Our juicer must be on the countertop to make juicing as effortless as possible but other appliances are fine tucked away,” says health coach and nutritionist Daphne Javtich of Doing Well. Kerrilynn Pamer of Cap Beauty echoes this: “I keep my juicer on the counter, I have a Nama, and it’s pretty discreet even though it's large. Everything else, I keep behind doors.”Think Beyond The Main KitchenStacy Zarin GoldbergThis auxiliary kitchen by Kate Abt Design makes a perfect spot for wellness essentials.One luxury feature on the rise? Auxiliary kitchens, also known as dirty kitchens. “When designing for clients, we almost always have the ‘family’ or ‘show’ kitchen and then a second kitchen where the real cooking happens,” says Eric Egan of Eric Egan Interior Design. “This is much like in a restaurant show kitchen, where you see them finishing the meals, but you don't see the prep work or the clean up, all of which happens in the background.” Designer Sarah Barnard of Sarah Barnard Design has also seen an increase in the request of auxiliary kitchens and loves them because they “provide concealed storage for juicers, blenders, dehydrators, and food processors.” While two kitchens might not be realistic for everyone, if you have access to a nice-sized pantry or closet nearby, that’s an ideal spot to corral it all, as well. Rethink Unused SpacesKEVIN MIYAZAKIRemove the booze, bring in the blender, and this liquor cabinet, in a library designed by Kate Marker, could be a wellness station.Speaking of ideal spots for wellness, consider transforming underutilized spaces like liquor cabinets or part of a mudroom into a wellness hub. “We don't find that too many of our clients have a liquor cabinet or use a bar anymore,” shares Kloythanomsup. “So that area can be repurposed as a wellness area.” While you're repurposing it, consider where you can plug in all those wellness appliances. “Clients are also asking us to design technology-stations, so they have multiple areas to hide their technology and free their view of cords and distractions,” Velten says. Get In The ZoneEmma Farrer//Getty ImagesA dedicated tea zone.If you are going to dedicate counter space to your wellness routine, whether it’s a juicing zone, smoothie station, a hydration corner—keep things arranged in groups or zones. “I keep the bulk of my supplements and remedies in a large, shallow pullout drawer in the kitchen,” Javitch shares. “I find this is the easiest way to organize and find products quickly. And you don't have to remove some to get to others.”“I love setting up thoughtful, dedicated zones, like a wellness drawer with teas, vitamins, and tinctures all in one place, or a water station with a glass water pitcher, reusable bottles, and electrolytes,” shares Blakey. Keeping similar items together allows products to stay top of mind and prevents them from getting lost in the shuffle. Contain YourselfCourtesy Holly BlakeyA pantry organized by Holly Blakey of Breathing Room Home.While baskets are a no-brainer for kitchen organization, designers and experts say that’s for good reason, advising homeowners not to overlook them—and to keep the materials as natural as possible. “Wooden bins are another favorite way to add warmth and style while keeping items grouped,” Blakey says. Velten seconds the idea of rush baskets or wooden bins, “We try to push living finishes as much as we can because with proper care, material that came from the earth just vibrates differently.” No matter how many products you use or how dialed-in your routine may be, “wellness becomes part of the daily flow when your space helps you follow through on your intentions,” says Blakey. For that reason, says Javitch, “I always keep a few small baskets in our cabinets with products I often grab for like the kids' sunblock stick or their multivitamin gummies.”Show Off Your Stash Thomas LeonczikHollie Velten designed this kitchen to keep essentials on view. The alternative to hiding things away? Showing them off! “We worked with a client who described her kitchen goals as ‘California health kitchen,’” shares Velten. “We actually removed the upper cabinets to create an easy-to-access corner of shelving to hold glass jars and sustainable practices for her teas, herbs, spices, tinctures, and other food prep essentials.” After all, some items deserve to be seen—not only from an aesthetic perspective but also to prompt daily use and consistency. “I’ll usually keep my essential daily products on a pretty wood tray on the kitchen counter,” Javtich shares.If you are going to keep things out in the open, Bay Area-based organizer of Breathing Room Home Holly Blakey, says clarity is key. “I swear by glass containers for food storage, not just for sustainability, but because they help you know what you have and when you can clearly see your items, you’re more likely to use them before they expire.”Plus, this keep-it-all-out method a way to incorporate your personal preferences and add a little personality into your kitchen. “Sometimes well-kept essentials really only bring more joy and utility when out in the open,” Velten adds. 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Last year, China saw a boom in foundation models, the do-everything large language models that underpin the AI revolution. This year, the focus has shifted to AI agents—systems that are less about responding to users’ queries and more about autonomously accomplishing things for them.  There are now a host of Chinese startups building these general-purpose digital tools, which can answer emails, browse the internet to plan vacations, and even design an interactive website. Many of these have emerged in just the last two months, following in the footsteps of Manus—a general AI agent that sparked weeks of social media frenzy for invite codes after its limited-release launch in early March.  These emerging AI agents aren’t large language models themselves. Instead, they’re built on top of them, using a workflow-based structure designed to get things done. A lot of these systems also introduce a different way of interacting with AI. Rather than just chatting back and forth with users, they are optimized for managing and executing multistep tasks—booking flights, managing schedules, conducting research—by using external tools and remembering instructions.  China could take the lead on building these kinds of agents. The country’s tightly integrated app ecosystems, rapid product cycles, and digitally fluent user base could provide a favorable environment for embedding AI into daily life.  For now, its leading AI agent startups are focusing their attention on the global market, because the best Western models don’t operate inside China’s firewalls. But that could change soon: Tech giants like ByteDance and Tencent are preparing their own AI agents that could bake automation directly into their native super-apps, pulling data from their vast ecosystem of programs that dominate many aspects of daily life in the country.  As the race to define what a useful AI agent looks like unfolds, a mix of ambitious startups and entrenched tech giants are now testing how these tools might actually work in practice—and for whom. Set the standard It’s been a whirlwind few months for Manus, which was developed by the Wuhan-based startup Butterfly Effect. The company raised $75 million in a funding round led by the US venture capital firm Benchmark, took the product on an ambitious global roadshow, and hired dozens of new employees.  Even before registration opened to the public in May, Manus had become a reference point for what a broad, consumer‑oriented AI agent should accomplish. Rather than handling narrow chores for businesses, this “general” agent is designed to be able to help with everyday tasks like trip planning, stock comparison, or your kid’s school project.  Unlike previous AI agents, Manus uses a browser-based sandbox that lets users supervise the agent like an intern, watching in real time as it scrolls through web pages, reads articles, or codes actions. It also proactively asks clarifying questions, supports long-term memory that would serve as context for future tasks. “Manus represents a promising product experience for AI agents,” says Ang Li, cofounder and CEO of Simular, a startup based in Palo Alto, California, that’s building computer use agents, AI agents that control a virtual computer. “I believe Chinese startups have a huge advantage when it comes to designing consumer products, thanks to cutthroat domestic competition that leads to fast execution and greater attention to product details.” In the case of Manus, the competition is moving fast. Two of the most buzzy follow‑ups, Genspark and Flowith, for example, are already boasting benchmark scores that match or edge past Manus’s.  Genspark, led by former Baidu executives Eric Jing and Kay Zhu, links many small “super agents” through what it calls multi‑component prompting. The agent can switch among several large language models, accepts both images and text, and carries out tasks from making slide decks to placing phone calls. Whereas Manus relies heavily on Browser Use, a popular open-source product that lets agents operate a web browser in a virtual window like a human, Genspark directly integrates with a wide array of tools and APIs. Launched in April, the company says that it already has over 5 million users and over $36 million in yearly revenue. Flowith, the work of a young team that first grabbed public attention in April 2025 at a developer event hosted by the popular social media app Xiaohongshu, takes a different tack. Marketed as an “infinite agent,” it opens on a blank canvas where each question becomes a node on a branching map. Users can backtrack, take new branches, and store results in personal or sharable “knowledge gardens”—a design that feels more like project management software (think Notion) than a typical chat interface. Every inquiry or task builds its own mind-map-like graph, encouraging a more nonlinear and creative interaction with AI. Flowith’s core agent, NEO, runs in the cloud and can perform scheduled tasks like sending emails and compiling files. The founders want the app to be a “knowledge marketbase”, and aims to tap into the social aspect of AI with the aspiration of becoming “the OnlyFans of AI knowledge creators”. What they also share with Manus is the global ambition. Both Genspark and Flowith have stated that their primary focus is the international market. A global address Startups like Manus, Genspark, and Flowith—though founded by Chinese entrepreneurs—could blend seamlessly into the global tech scene and compete effectively abroad. Founders, investors, and analysts that MIT Technology Review has spoken to believe Chinese companies are moving fast, executing well, and quickly coming up with new products.  Money reinforces the pull to launch overseas. Customers there pay more, and there are plenty to go around. “You can price in USD, and with the exchange rate that’s a sevenfold multiplier,” Manus cofounder Xiao Hong quipped on a podcast. “Even if we’re only operating at 10% power because of cultural differences overseas, we’ll still make more than in China.” But creating the same functionality in China is a challenge. Major US AI companies including OpenAI and Anthropic have opted out of mainland China because of geopolitical risks and challenges with regulatory compliance. Their absence initially created a black market as users resorted to VPNs and third-party mirrors to access tools like ChatGPT and Claude. That vacuum has since been filled by a new wave of Chinese chatbots—DeepSeek, Doubao, Kimi—but the appetite for foreign models hasn’t gone away.  Manus, for example, uses Anthropic’s Claude Sonnet—widely considered the top model for agentic tasks. Manus cofounder Zhang Tao has repeatedly praised Claude’s ability to juggle tools, remember contexts, and hold multi‑round conversations—all crucial for turning chatty software into an effective executive assistant. But the company’s use of Sonnet has made its agent functionally unusable inside China without a VPN. If you open Manus from a mainland IP address, you’ll see a notice explaining that the team is “working on integrating Qwen’s model,” a special local version that is built on top of Alibaba’s open-source model.  An engineer overseeing ByteDance’s work on developing an agent, who spoke to MIT Technology Review anonymously to avoid sanction, said that the absence of Claude Sonnet models “limits everything we do in China.” DeepSeek’s open models, he added, still hallucinate too often and lack training on real‑world workflows. Developers we spoke with rank Alibaba’s Qwen series as the best domestic alternative, yet most say that switching to Qwen knocks performance down a notch. Jiaxin Pei, a postdoctoral researcher at Stanford’s Institute for Human‑Centered AI, thinks that gap will close: “Building agentic capabilities in base LLMs has become a key focus for many LLM builders, and once people realize the value of this, it will only be a matter of time.” For now, Manus is doubling down on audiences it can already serve. In a written response, the company said its “primary focus is overseas expansion,” noting that new offices in San Francisco, Singapore, and Tokyo have opened in the past month. A super‑app approach Although the concept of AI agents is still relatively new, the consumer-facing AI app market in China is already crowded with major tech players. DeepSeek remains the most widely used, while ByteDance’s Doubao and Moonshot’s Kimi have also become household names. However, most of these apps are still optimized for chat and entertainment rather than task execution. This gap in the local market has pushed China’s big tech firms to roll out their own user-facing agents, though early versions remain uneven in quality and rough around the edges.  ByteDance is testing Coze Space, an AI agent based on its own Doubao model family that lets users toggle between “plan” and “execute” modes, so they can either directly guide the agent’s actions or step back and watch it work autonomously. It connects up to 14 popular apps, including GitHub, Notion, and the company’s own Lark office suite. Early reviews say the tool can feel clunky and has a high failure rate, but it clearly aims to match what Manus offers. Meanwhile, Zhipu AI has released a free agent called AutoGLM Rumination, built on its proprietary ChatGLM models. Shanghai‑based Minimax has launched Minimax Agent. Both products look almost identical to Manus and demo basic tasks such as building a simple website, planning a trip, making a small Flash game, or running quick data analysis. Despite the limited usability of most general AI agents launched within China, big companies have plans to change that. During a May 15 earnings call, Tencent president Liu Zhiping teased an agent that would weave automation directly into China’s most ubiquitous app, WeChat.  Considered the original super-app, WeChat already handles messaging, mobile payments, news, and millions of mini‑programs that act like embedded apps. These programs give Tencent, its developer, access to data from millions of services that pervade everyday life in China, an advantage most competitors can only envy. Historically, China’s consumer internet has splintered into competing walled gardens—share a Taobao link in WeChat and it resolves as plaintext, not a preview card. Unlike the more interoperable Western internet, China’s tech giants have long resisted integration with one another, choosing to wage platform war at the expense of a seamless user experience. But the use of mini‑programs has given WeChat unprecedented reach across services that once resisted interoperability, from gym bookings to grocery orders. An agent able to roam that ecosystem could bypass the integration headaches dogging independent startups. Alibaba, the e-commerce giant behind the Qwen model series, has been a front-runner in China’s AI race but has been slower to release consumer-facing products. Even though Qwen was the most downloaded open-source model on Hugging Face in 2024, it didn’t power a dedicated chatbot app until early 2025. In March, Alibaba rebranded its cloud storage and search app Quark into an all-in-one AI search tool. By June, Quark had introduced DeepResearch—a new mode that marks its most agent-like effort to date.  ByteDance and Alibaba did not reply to MIT Technology Review’s request for comments. “Historically, Chinese tech products tend to pursue the all-in-one, super-app approach, and the latest Chinese AI agents reflect just that,” says Li of Simular, who previously worked at Google DeepMind on AI-enabled work automation. “In contrast, AI agents in the US are more focused on serving specific verticals.” Pei, the researcher at Stanford, says that existing tech giants could have a huge advantage in bringing the vision of general AI agents to life—especially those with built-in integration across services. “The customer-facing AI agent market is still very early, with tons of problems like authentication and liability,” he says. “But companies that already operate across a wide range of services have a natural advantage in deploying agents at scale.”

When people talk about UX, it’s usually about the things they can see and interact with, like wireframes and prototypes, smart interactions, and design tools like Figma, Miro, or Maze. Some of the outputs are even glamorized, like design systems, research reports, and pixel-perfect UI designs. But here’s the truth I’ve seen again and again in over two decades of working in UX: none of that moves the needle if there is no collaboration. Great UX doesn’t happen in isolation. It happens through conversations with engineers, product managers, customer-facing teams, and the customer support teams who manage support tickets. Amazing UX ideas come alive in messy Miro sessions, cross-functional workshops, and those online chats (e.g., Slack or Teams) where people align, adapt, and co-create. Some of the most impactful moments in my career weren’t when I was “designing” in the traditional sense. They have been gaining incredible insights when discussing problems with teammates who have varied experiences, brainstorming, and coming up with ideas that I never could have come up with on my own. As I always say, ten minds in a room will come up with ten times as many ideas as one mind. Often, many ideas are the most useful outcome. There have been times when a team has helped to reframe a problem in a workshop, taken vague and conflicting feedback, and clarified a path forward, or I’ve sat with a sales rep and heard the same user complaint show up in multiple conversations. This is when design becomes a team sport, and when your ability to capture the outcomes multiplies the UX impact. Why This Article Matters Now The reason collaboration feels so urgent now is that the way we work since COVID has changed, according to a study published by the US Department of Labor. Teams are more cross-functional, often remote, and increasingly complex. Silos are easier to fall into, due to distance or lack of face-to-face contact, and yet alignment has never been more important. We can’t afford to see collaboration as a “nice to have” anymore. It’s a core skill, especially in UX, where our work touches so many parts of an organisation. Let’s break down what collaboration in UX really means, and why it deserves way more attention than it gets. What Is Collaboration In UX, Really? Let’s start by clearing up a misconception. Collaboration is not the same as cooperation. Cooperation: “You do your thing, I’ll do mine, and we’ll check in later.” Collaboration: “Let’s figure this out together and co-own the outcome.” Collaboration, as defined in the book Communication Concepts, published by Deakin University, involves working with others to produce outputs and/or achieve shared goals. The outcome of collaboration is typically a tangible product or a measurable achievement, such as solving a problem or making a decision. Here’s an example from a recent project: Recently, I worked on a fraud alert platform for a fintech business. It was a six-month project, and we had zero access to users, as the product had not yet hit the market. Also, the users were highly specialised in the B2B finance space and were difficult to find. Additionally, the team members I needed to collaborate with were based in Malaysia and Melbourne, while I am located in Sydney. Instead of treating that as a dead end, we turned inward: collaborating with subject matter experts, professional services consultants, compliance specialists, and customer support team members who had deep knowledge of fraud patterns and customer pain points. Through bi-weekly workshops using a Miro board, iterative feedback loops, and sketching sessions, we worked on design solution options. I even asked them to present their own design version as part of the process. After months of iterating on the fraud investigation platform through these collaboration sessions, I ended up with two different design frameworks for the investigator’s dashboard. Instead of just presenting the “best one” and hoping for buy-in, I ran a voting exercise with PMs, engineers, SMEs, and customer support. Everyone had a voice. The winning design was created and validated with the input of the team, resulting in an outcome that solved many problems for the end user and was owned by the entire team. That’s collaboration! It is definitely one of the most satisfying projects of my career. On the other hand, I recently caught up with an old colleague who now serves as a product owner. Her story was a cautionary tale: the design team had gone ahead with a major redesign of an app without looping her in until late in the game. Not surprisingly, the new design missed several key product constraints and business goals. It had to be scrapped and redone, with her now at the table. That experience reinforced what we all know deep down: your best work rarely happens in isolation. As illustrated in my experience, true collaboration can span many roles. It’s not just between designers and PMs. It can also include QA testers who identify real-world issues, content strategists who ensure our language is clear and inclusive, sales representatives who interact with customers on a daily basis, marketers who understand the brand’s voice, and, of course, customer support agents who are often the first to hear when something goes wrong. The best outcomes arrive when we’re open to different perspectives and inputs. Why Collaboration Is So Overlooked? If collaboration is so powerful, why don’t we talk about it more? In my experience, one reason is the myth of the “lone UX hero”. Many of us entered the field inspired by stories of design geniuses revolutionising products on their own. Our portfolios often reflect that as well. We showcase our solo work, our processes, and our wins. Job descriptions often reinforce the idea of the solo UX designer, listing tool proficiency and deliverables more than soft skills and team dynamics. And then there’s the team culture within many organisations of “just get the work done”, which often leads to fewer meetings and tighter deadlines. As a result, a sense of collaboration is inefficient and wasted. I have also experienced working with some designers where perfectionism and territoriality creep in — “This is my design” — which kills the open, communal spirit that collaboration needs. When Collaboration Is The User Research In an ideal world, we’d always have direct access to users. But let’s be real. Sometimes that just doesn’t happen. Whether it’s due to budget constraints, time limitations, or layers of bureaucracy, talking to end users isn’t always possible. That’s where collaboration with team members becomes even more crucial. The next best thing to talking to users? Talking to the people who talk to users. Sales teams, customer success reps, tech support, and field engineers. They’re all user researchers in disguise! On another B2C project, the end users were having trouble completing the key task. My role was to redesign the onboarding experience for an online identity capture tool for end users. I was unable to schedule interviews with end users due to budget and time constraints, so I turned to the sales and tech support teams. I conducted multiple mini-workshops to identify the most common onboarding issues they had heard directly from our customers. This led to a huge “aha” moment: most users dropped off before the document capture process. They may have been struggling with a lack of instruction, not knowing the required time, or not understanding the steps involved in completing the onboarding process. That insight reframed my approach, and we ultimately redesigned the flow to prioritize orientation and clear instructions before proceeding to the setup steps. Below is an example of one of the screen designs, including some of the instructions we added. This kind of collaboration is user research. It’s not a substitute for talking to users directly, but it’s a powerful proxy when you have limited options. But What About Using AI? Glad you asked! Even AI tools, which are increasingly being used for idea generation, pattern recognition, or rapid prototyping, don’t replace collaboration; they just change the shape of it. AI can help you explore design patterns, draft user flows, or generate multiple variations of a layout in seconds. It’s fantastic for getting past creative blocks or pressure-testing your assumptions. But let’s be clear: these tools are accelerators, not oracles. As an innovation and strategy consultant Nathan Waterhouse points out, AI can point you in a direction, but it can’t tell you which direction is the right one in your specific context. That still requires human judgment, empathy, and an understanding of the messy realities of users and business goals. You still need people, especially those closest to your users, to validate, challenge, and evolve any AI-generated idea. For instance, you might use ChatGPT to brainstorm onboarding flows for a SaaS tool, but if you’re not involving customer support reps who regularly hear “I didn’t know where to start” or “I couldn’t even log in,” you’re just working with assumptions. The same applies to engineers who know what is technically feasible or PMs who understand where the business is headed. AI can generate ideas, but only collaboration turns those ideas into something usable, valuable, and real. Think of it as a powerful ingredient, but not the whole recipe. How To Strengthen Your UX Collaboration Skills? If collaboration doesn’t come naturally or hasn’t been a focus, that’s okay. Like any skill, it can be practiced and improved. Here are a few ways to level up: Cultivate curiosity about your teammates.Ask engineers what keeps them up at night. Learn what metrics your PMs care about. Understand the types of tickets the support team handles most frequently. The more you care about their challenges, the more they'll care about yours. Get comfortable facilitating.You don’t need to be a certified Design Sprint master, but learning how to run a structured conversation, align stakeholders, or synthesize different points of view is hugely valuable. Even a simple “What’s working? What’s not?” retro can be an amazing starting point in identifying where you need to focus next. Share early, share often.Don’t wait until your designs are polished to get input. Messy sketches and rough prototypes invite collaboration. When others feel like they’ve helped shape the work, they’re more invested in its success. Practice active listening.When someone critiques your work, don’t immediately defend. Pause. Ask follow-up questions. Reframe the feedback. Collaboration isn’t about consensus; it’s about finding a shared direction that can honour multiple truths. Co-own the outcome.Let go of your ego. The best UX work isn’t “your” work. It’s the result of many voices, skill sets, and conversations converging toward a solution that helps users. It’s not “I”, it’s “we” that will solve this problem together. Conclusion: UX Is A Team Sport Great design doesn’t emerge from a vacuum. It comes from open dialogue, cross-functional understanding, and a shared commitment to solving real problems for real people. If there’s one thing I wish every early-career designer knew, it’s this: Collaboration is not a side skill. It’s the engine behind every meaningful design outcome. And for seasoned professionals, it’s the superpower that turns good teams into great ones. So next time you’re tempted to go heads-down and just “crank out a design,” pause to reflect. Ask who else should be in the room. And invite them in, not just to review your work, but to help create it. Because in the end, the best UX isn’t just what you make. It’s what you make together. Further Reading On SmashingMag “Presenting UX Research And Design To Stakeholders: The Power Of Persuasion,” Victor Yocco “Transforming The Relationship Between Designers And Developers,” Chris Day “Effective Communication For Everyday Meetings,” Andrii Zhdan “Preventing Bad UX Through Integrated Design Workflows,” Ceara Crawshaw