Most people are no longer upgrading their Android phones every two years. It’s now the norm for consumers to replace their devices every three or four years. It also doesn’t hurt that carriers have embraced 36-month or even 48-month contracts.
As such, I totally understand if you’re buying a phone with the intention of keeping it for three or more years. But before you put your money down or sign that contract, I’ve got some tips to keep in mind if you want to buy a phone that will last for years and years.
What’s the best tip if you’re buying a phone to keep for a long time?
238 votes
1. Look for a long update policy
Robert Triggs / Android Authority
My first tip when buying a smartphone for the long haul is to ensure it has a long update policy. This means that the phone will receive software upgrades for many years to come, bringing new features and keeping the device secure.
Google, Samsung, and HONOR’s top-end phones all offer seven years of OS and security upgrades, making these the best performers in this regard. Meanwhile, high-end phones from the likes of Xiaomi and OnePlus often come with four major OS upgrades and six years of security patches. On the other end of the spectrum, cheap Motorola phones usually only get two OS updates and three years of security patches.
In other words, if you plan to keep a cheap Motorola phone for five years, it will stop receiving updates just after the midway point. This means your device won’t be protected against newfound vulnerabilities. The lack of Android OS upgrades after two years also means you won’t receive many new features down the line.
2. Get a phone with great long-term battery health
Joe Maring / Android Authority
All smartphone batteries degrade over time, effectively losing 20% of their capacity after a set number of charging cycles. It’s why your new phone lasts for ages compared to the same phone two or three years later. However, phone batteries don’t degrade at the same rate.
Some phones have batteries rated for 800 charging cycles (i.e., roughly two years) before they’ve essentially lost 20% capacity. Google and Apple’s phones are rated for 1,000 charging cycles. Samsung is the top dog, though, as its flagship phones are rated for 2,000 cycles (more than four years) before effectively losing 20%. That means if you’ve got a Samsung phone and a Pixel device with the same battery capacity, the Pixel will see a more severe drop in battery life after a few years.
Needless to say, you should check how many charging cycles your next phone is rated for if you don’t want its battery life to fall off a cliff after a couple of years. Manufacturers sometimes post this info on their product pages, but they can also be cagey about it. I’d also recommend you visit the EU’s EPREL database to find these details.
3. Or get a phone with a big battery
Mishaal Rahman / Android Authority
There’s more to a smartphone’s long-term battery life than charging cycles, though. The actual battery capacity also plays a major role if you want to keep a phone for ages. After all, who cares if the phone’s battery ages very slowly when it’s a small battery capacity anyway?
I’d recommend buying a phone with a large battery (5,000mAh or higher), as this softens the blow of degradation. A phone with an average-sized battery will effectively turn into a device with a small battery owing to that ~20% capacity loss over time. However, a phone with a large battery will turn into one with an average-sized battery.
Of course, you ideally want a phone with both a huge battery and slow degradation. But a huge battery can help offset typical degradation. Furthermore, a phone with a large battery doesn’t need to be charged as often as one with a small battery, so it won’t accrue charging cycles as quickly. However, even a phone with a big battery will see a noticeable decline in endurance after five or six years.
4. Get the phone with more storage (or a microSD card)
Hadlee Simons / Android Authority
You’ll accrue a ton of files as you use your phone over the years. This includes photos, videos, documents, downloaded podcasts, offline music playlists, and WhatsApp-related data. I therefore recommend buying a phone with plenty of storage if you plan to keep it for the long run. This way, you’re unlikely to run out of storage after a year or two. It also means you don’t have to constantly clean up files to claw back space.
I’d suggest buying a phone with at least 256GB of storage in 2026, as 128GB can fill up pretty quickly with captured media, downloaded music, and more. The good news is that the latest flagship phones from Apple, Samsung, and most Chinese brands offer 256GB of base storage. However, Google’s Pixel phones and many mid-range devices still start at just 128GB. This isn’t bad if you don’t use the camera much, or if you frequently offload photos and videos to cloud storage, but it’s better to be safe than sorry.
Another option is to find a phone with a built-in microSD card slot, allowing you to expand your storage with a memory card. Unfortunately, this feature is largely limited to budget Android phones and Sony’s high-end Xperia devices.
5. Make sure the phone has good performance
Ryan Haines / Android Authority
Many smartphones slow down over time, so it’s worth considering a phone that has good performance. Because much like battery degradation, a phone with mediocre performance on day one might be a stuttering mess four or five years later. But a phone with good performance out of the box should still be relatively smooth, or at least satisfactory, down the line. The big difference is that you can always replace your battery, but you can’t replace your phone’s processor.
Don’t skimp on performance if you want your next phone to last for years and years.
Furthermore, manufacturers and Google constantly bring new features to their phones with each major update. Some of these features require a relatively powerful phone, leaving you in the lurch if your device has no horsepower. You should also consider device performance if you’re a mobile gamer, as a phone with disappointing performance in 2026 is less likely to support the most demanding games a few years from now. My rule of thumb is to buy phones with Snapdragon 8 series chips, recent Snapdragon 7 series processors, Dimensity 8000 or 9000 chips, Samsung’s Exynos 2×00 series, or Google’s Tensor line.
Some Chinese brands like OPPO, vivo, and OnePlus also make interesting claims about long-term performance. For example, OnePlus asserts that the Nord CE 6 Lite will maintain its smoothness for five years, while vivo made the same claim for its V50. I imagine that if these phones have middling performance on day one, this promise just means they’ll have the same middling performance five years from now. I’d still prioritize a good chip and a decent amount of RAM (8GB or more) over these claims, though. But it’s something else to keep in mind if you want to keep your phone for three or more years.
6. Keep durability in mind
Joe Maring / Android Authority
Another important consideration is the phone’s durability. After all, you don’t want your new device to break after its first drop. There are several durability-related factors worth knowing.
Perhaps the most important consideration is the type of protective glass on the phone’s display. Gorilla Glass is the most popular protective glass solution on the market, but there are many versions. Some cheap phones use old Gorilla Glass versions (i.e., Gorilla Glass 3), but you should really look for the Gorilla Glass Victus series and Gorilla Glass 7i if you want more robust protection. Some of the most durable phones on the market use ceramic-based protective glass, such as Gorilla Glass Ceramic, HONOR NanoCrystal Shield, and Gorilla Armor, for improved scratch resistance. Does the phone you’re eyeing have a glass back? Then you should also make sure that the rear cover is protected by Gorilla Glass.
You should also check your phone’s IP rating, which is expressed as two digits (e.g., IP53, IP68). The first digit refers to dust resistance, while the second refers to freshwater resistance. That means a phone with an IP53 rating can resist dust and splashes but can’t be dunked in water. Meanwhile, a phone with an IP67 rating or higher is sealed against dust and can be immersed in water. Some phones don’t have prominent IP ratings at all, but might have “water-repellent” designs. Translation: You can probably use the phone in the rain, but that’s it.
7. Also consider repairability and spare parts
Rita El Khoury / Android Authority
Another key tip when buying a phone for long-term usage is to make sure that repairs won’t be a problem. Phones officially sold in your country will often have official or authorized repair centers, but it’s a good idea to double-check this.
If you don’t mind DIY repairs, you should find out how easy it is to repair your future smartphone. The iFixit platform often posts written articles and videos detailing a phone’s repairability, complete with a score out of 10. The JerryRigEverything and PBKReviews YouTube channels also deliver great teardown videos. Otherwise, Fairphone is the undisputed king of repairable phones, while HMD has also released a few repairable phones in the last couple of years.
Even if you don’t plan to fix your own phone, you should still find out how easy it is to get spare parts for your prospective phone. Some brands sell spare parts via their website or repair centers, while others might partner with iFixit. The likes of Google and Samsung both sell spare parts in the US, with Google also confirming it’ll offer them for seven years, matching their phone update policy. That’s good news and means you won’t be left in the lurch if you need a new screen or battery five years from now. This also means you can buy spare parts and then take both the parts and your broken phone to an alternative repair store if you’d like.
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Anytime you’re talking about the hottest game on Steam, there’s an evergreen unspoken caveat: ‘after Counter-Strike, of course.’ CS2 is unquestionably Steam’s killer app—it has well over a million concurrent players as I write this according to SteamDB, and it’s showing no signs of slowing down. But don’t count out the game it once absorbed and then spat out: its predecessor, Global Offensive.
According to SteamDB, it hit an all-time (post re-release) concurrent player peak just three days ago. That’s a bit more than 68,000 simultaneous terrorists and counter-terrorists. While that’s small potatoes compared to the original game at its peak or CS2 right now—SteamDB appears to only go back to earlier this year when CS:GO un-merged from CS2—it marks a sudden upward trend, a pretty impressive showing for a game you can’t just search up on Steam normally. It’s drawing similar numbers to Deadlock, another (much newer) Valve game you also can’t simply browse for and download.
As the 28th most played game on Steam right now, it’s bigger on the platform than Baldur’s Gate 3, Rainbow Six Siege, Battlefield 6, and all sorts of other blockbusters. It’s no Meccha Chameleon, but not shabby for a game that’s 14 years old, and interesting to note that it’s growing beyond the initial hype it attracted back when the standalone version was first restored earlier this year.
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It seems like further evidence of what PC Gamer’s Andy Chalk observed in his story back then: that this town is, in fact, big enough for two Counter-Strikes. It’s honestly big enough for much more than that: the original Counter-Strike and Source both have healthy playerbases of their own all these years later, and that’s to say nothing of similar games that aren’t even on Steam like Valorant. The landscape for tactical FPS is as diverse as I can remember, and that remains true if you only play games with “Counter-Strike” in the title.
Keep up to date with the most important stories and the best deals, as picked by the PC Gamer team.
Today’s post highlight the top homeware design companies and services for new product design and 3D modeling. Designing homeware products takes more than just creativity. It also needs patience, time, and careful planning because the product should not only look good but also work properly in everyday life. From furniture and kitchen products to decor and storage items, every detail matters when creating something people will use inside their homes.
We feature different designs according to your product needs and go through with you along with the process as they turn your ideas into real sellable products that can be used in any kind of home. CAD Crowd plays a significant role as they link you with different freelance designers across the world who get the work done, specializing in any homeware designs, developing your products, and even 3D modeling design services, which makes all the process easy and smooth.
1. Cad Crowd
A platform that best helps businesses with skilled freelance designers and engineers from different parts of the world. They specialized in homeware product design, including furniture, kitchen products, decor pieces, and other household items. What makes the platform useful is the flexibility it offers when hiring talent. They also offer hands-on guidance which users can track the process and really has a quality check to portfolios in every freelance designer as they provide serious projects and clear instructions in every design. Somehow they work with a balance of creativity and authenticity that makes them stand out in all other platforms.
Arcadroat Outsourcing mainly works on interiors, homeware, designs, architecture, homeware projects. They provide clean technical drawings such as cover visualizations, and any production-ready files that truly makes the production of the manufacturing smooth and a fast delivery workflow in which they have been collaboratively working with teams that have clear standards and supports flexibility in any brands they have been working, even from small decor pieces to large product collections.
ArcCGI creates professional 3D images for interior and homeware projects. The studio brings products to life not just beautifully, but also ensures its functionality. They pay close attention to textures, materials, lighting, and consistency in every design. From furniture rendering projects to decorative items, their visuals help brands present products clearly, and speed up approvals. Their teams are very dependable as they approve designs faster and lessen the possible revisions as they want to speed up the presentation process for its launching to be successful.
ARKANCE helps companies improve their workflows through digital tools, design systems, and product management solutions, for they aim to reduce errors as the product process moves towards its production. Its approach supports homeware and consumer goods, especially when they want their products to be developed, and for long-term value for clients across the globe who want to partner with a team that uses well-known tools and organized systems.
Arttech Studio mainly focuses on helping homeware brands to turn their ideas into detailed and carefully done drawings and 3D designs. They provide design support for both architectural and product-based projects, helping clients create professional presentation and production-ready concepts, ensuring that they meet deadlines on time. They also work well with professionally creative and are ready for a market launch, as they are both good in providing service with startups.
Astoria Design Group designs and creates products from concept to production. They help clients with ideas, prototypes, drawings, and factory coordination with ease which are very easy to use because they focus on clear instructions and are practical to users. Their 3D design team works closely with the brands who helped in refining look, materials, and function, which enables them to launch these products faster and have no to minimal errors. Clients appreciate how they refine materials, improve usability, and help brands launch products with production issues.
Away Digital creates realistic 3D visuals and presentations for homeware and furniture brands. Their team focuses on helping businesses bring product ideas to life through high-quality renderings and interactive visuals. These presentations are useful for online stores, catalogs, product approvals, and marketing campaigns. Away Digital ensures to help brands to meet their budget as they go through with the process with easier teams, helping them to approve designs quickly. The results are consistent and reliable worldwide for their team consists of professionally dependable experts.
BLUENT Engineering provides drafting, CAD design, 3D modeling services for architecture and homeware products. Their team supports clients with organized workflows and dependable project designs, which ensures that products run smoothly. What clients value about the company is that they are able to handle big projects and communicate clearly, improving coordination, and professionally meeting production needs. Their structured approach helps everything to be done easily as they follow a structured workflow to provide skilled project management in delivering consistent and reliable projects across the globe.
CAD or CAM services technically offer services that will help product designers and manufacturers to turn their visions as a market-ready product. Through design drawings and 3D designs, they create these files ready for manufacturing with exact measurements, ensuring that what they produce are reliable drawings and instructions. Clients appreciate their ability to handle complex projects while maintaining clear communication throughout the design process. With a team that works with different manufacturing methods and follows a specific approach that leads to consistent manufacturing transitions across various teams and different regions worldwide. Their approach helps brands create reliable production-ready designs efficiently.
CAD Design Company supports engineering, architecture, and homeware teams through 3D modeling and visualization services. They are known for organized workflows, dependable delivery, and strong communication with clients. It appreciates them in a way that they work collaboratively as they ensure time and updates that keeps you on track into the process so that there will be less to minimum mistakes as they go through with meeting their needs. They are also very reliable and flexible, helping teams to receive high-quality results that exceed their expectations. They operate worldwide and handle projects of any size, aiming to provide step-by-step processes in producing 3D visuals for production.
CAD Drafter offers a top-notch quality in providing clear design drawings and 3D models to architecture, construction, and homeware teams. They adapt to different project requirements and CAD standards while maintaining accuracy and consistency as they provide clear communication and precise designs, ensuring to reduce mistakes, ensuring projects to be on track, making everyone coordinated throughout the process. It is a great choice since they are guaranteed to be a reliable partner for any homeware brands, not just locally, but also worldwide.
CAD Drafting Services helps clients create detailed files and technical instructions for homeware production. It makes the work done smoothly exactly for engineering, architecture, and any homeware projects. CAD drafting services flexibly works with a lot of CAD platforms in which they follow certain standards in order to have no to minimal errors as they go through their approval process and make things go smooth and ready to launch as fast as they could. From interior to fixtures and cabinetry or furniture modeling services, they all benefit from structured workflows, clear documentation, and an organized process as their organized process helps products move faster from concept to launch.
CAD home design is an ideal help for those brands that want to turn their ideas into livable designs through different services—such as drafting, modeling, and 3D visualization, that ensures coordination, smoothness, and precision. Their team works closely with builders, designers, and product developers to create accurate project outputs. They focus clarity and precise project based outcome as well making sure they track every process so that they find no major errors later on. So if you are a home product brand that wants to have efficient and reliable professional support and aims to have an easy and seamless project process, CAD Home Design INC is something that could help you with it
CAD-IT provides CAD drafting, simulation, and product data management solutions for furniture and homeware brands that ensures an easy flow and collaboration between design and product teams in order to produce product-ready designs. CAD-IT works collaboratively with furniture designers, consumer products, and homeware brands, ensuring that every drawing they produce meets the realistic standards of production.
They focus on quality control, accuracy, and smooth collaboration throughout the entire development process. They also integrate existing designs and manufacturing platforms in order to ensure a full-scale production in creating every concept to market-ready ones. So what makes them defendable is that they provide a complete solution, which doesn’t just focus on creativity but also high precision. So if you want a smooth transition from idea to full product to production projects, then CAD-IT could totally help you to combine creativity with precision and make them a dependable partner for product development.
CAD logic helps improve modeling speed in-house skill levels and consistency of teams that want a practical guidance in creating software implementation, customization, and ongoing support as they serve furniture designs, product developers, and homeware brands, even manufacturing teams that are looking for a workflow efficiency. Why they matter is that they manage evolving products effectively, and their team doesn’t just focus on skill development. Their team focuses on improving productivity while maintaining reliable long-term design processes. Clients appreciate their practical guidance and professional communication.
CAD MicroSolutions supports homeware brands with CAD tools, design solutions, and technical guidance that helps products move smoothly towards manufacturing. By this, it highly requires strong CAD skills and clear standards in order to have a design that is consistent and production-ready. The company empowers product teams to not just handle simple projects but also to deal with complex assemblies as well as coordinating with suppliers confidently to make sure that they provide high standards across different projects. Through the help of CAD MicroSolutions, clients value their ability to improve productivity while maintaining accuracy and readiness.
CAD Outsourcing Consultancy Services mainly helps homeware and furniture teams to manage multiple projects efficiently. They offer 3D modeling, technical documentation, CAD drafting, and any design assistance from across different platforms. Their flexible services allow clients to outsource technical tasks while focusing on product innovation and branding. They also have a clear communication with the top-notch dependable results that focus on precise and accurate projects that are made with their specific needs. That’s what makes them reliable across markets worldwide and makes them a great choice for trusted partners in any homeware brands.
Chief Architect provides software solutions for interior and residential design projects. Their tools help designers create realistic layout, furniture placements, and 3D visualizations before products move into production. Through Chief Architect, they would be able to have clear and detailed layouts in which they could realistically see how this furniture will fit in a specific space and can explore with different materials before proceeding to a long-term commitment of the process production. This software is very perfect, especially for custom home products that need outputs that require both technical accuracy and visual presentations.
Creating homeware design projects is very difficult, especially when needing to deep dive into its furniture layouts and designing it to be the exact type of what we envisioned it to be. They support clients in creating accurate models, improving design quality, and streamlining workflows. Through the help of CAD software and training and consulting, these designers could tailor their product needs and engineer it to how they exactly want it to be. This company helped teams in improving their model to become accurate and precise and efficient quality all throughout the production. They matter most since they support long-term growth and a smoother processing of the product development, which helps a lot of companies to have production-ready products that they could present in the market worldwide.
Design Launchers provides design, modeling, prototyping services that help clients turn homeware concepts into manufacturing products which ensures accord ordination all in one process. Through their help, designers and manufacturers are able to have fast project timelines ensuring little to no mistakes without excessive costs. As they also ensure that the products are not just beautifully made but also sellable and manufacturable. So it is really a best choice for any homeware brands and their ability to combine creativeness with practical solutions.
Flatworld Solutions delivers scalable support to homeware brands, manufacturers, and design teams that need to manage their homeware products’ production precisely and efficiently. So through the help of this company, and providing outsourced CAD 3D modeling services for furniture, decor, and fixtures, they’d be able to organize workflows and clear project tracking systems.. Flatworld Solutions also follows a certain workflow in which helps teams to see the tracking of projects in order to have no errors in the long run. They are very expert in technicality, which moves ideas smoothly from concept to production ready. So they are very the best choice for brands that want to seek reliable outsourced product development, for they are a practical choice and an efficient partner that will really guide you up until the end of the process.
Idea Reality provides a consistent and reliable way in showcasing products to different homeware brands and marketing teams as they offer services such as animation, interactive visualization, and 3D rendering that surely brings their product ideas into a functional, market-ready one. Idea reality matters most because the visuals support product reviews, marketing campaigns, and client presentations while helping reduce misunderstandings during development. Through them, homeware teams get quality and precise professionally made visuals which engages the product’s intention confidently to the market. They provide consistency across all stages of project development worldwide, which also make them a dependable choice for these homeware brands.
IDSS Global provides CAD modeling, simulation, and product lifecycle management services for homeware and furniture brands. They mainly design and coordinate between teams and suppliers so that they can ensure that everything is accurately detailed and manufacturable. This company follows a structured approach so that later on, there are no mistakes to happen, and they work closely with furniture and consumer product brands.
What clients love about this is that they benefit from the team’s technical expertise and structured workflow that helps speed up approvals and reduce production errors. If you are a homeware brand that is looking for an efficient, high-quality, and with scalability, IDSS Global will greatly help for they operate smoothly in a competitive market environment. They are very dependable since they don’t just make a clear and reliable process of development from the beginning to finish, but also ensure that every detail is keenly worked on.
It is very known that if we design a furniture or an interior product or any homeware things, it really requires powerful software that could help us get through until the end of the production. Through IMSI design and through the help of their CAD and BIM tools, on organized coordination between suppliers, manufacturers, and product developers. The software helps designers to polish presentations and quickly turn concepts into the process of production without any unnecessary complexity. A lot of users like the platform because it feels practical, professional, and cost-efficient at the same time. It also helps clients create polished presentations more quickly.
India CAD Works offers services such as 3D modeling, CAD drafting, and design outsourcing that greatly helps homeware teams to create precise drawings of their furniture and production files efficiently. Clients appreciate their clear communication, competitive pricing, and organized project management since they offer high-quality projects and they adhere to specific design standards that are truly beneficial throughout the production process. India CAD Works also ensures that homeware teams meet deadlines and manage the complexity of every project since they reduce internal workload and establish workflows as they deliver quality designs not just locally but in the entire world. Many brands also value how flexible they are with different project requirements.
JCAD Incorporation provides CAD drafting, technical documentation, and modeling services for product development and construction-related projects. They provide modeling, CAD drafting, and technical documentation services for any product development teams, construction, and engineering. What clients often choose is that they maintain reliable communication and clear deliverables throughout the process. They give emphasis on practical execution since they don’t want to have unnecessary errors or complications in the long run. And this is what makes them a dependable technical support for a lot of homeware brands since they guarantee stress-free, efficient, and a product base that is professionally competitive along global markets.
Logical CAD Solutions helps create precise furniture drawings, production-ready files, and layouts that are ready to present in the market through the use of 3D modeling, CAD drafting, and design support that are best reliable for any product teams and homeware brands. A lot of brands appreciate how transparent and detail-oriented they are during development.
They work across interiors, product development, architecture, ensuring that they get to meet the needs of these multiple platforms without compromising the standards of the industry. Instead of overcomplicating things, they focus on organized workflows and realistic solutions that help projects move faster. Provides reliable outsourced support, which makes many houseware brands to accurately rely on them since they provide efficient, quality, and consistent results and can be confidently present in the global product development.
MC Line Studios helps homeware clients transform ideas into technical drawings and visual presentations. Their services include drafting, visualization, and 3D modeling for furniture and interior design products, or any furniture, creating precise drawings and presentations that are easy to understand with the people. What clients value about them is that they provide consistent quality and communicate well and deliver deliverables right on time. As they also emphasize teamwork to provide practical solutions in order to not meet or lessen the errors and revisions in the long run. They guide every client in developing projects from the very start of conceptualizing it to delivering a quality and clear dependable design. Their collaborative approach also helps reduce revisions and improve project coordination.
This studio greatly helps in turning interior concepts into precise, production-ready drawings and assemblies through the use of 3D modeling, product concept design services, and CAD drafting for homeware brands. Their organized files and technical drawings help manufacturers handle production more smoothly. What clients value about this studio is their flexibility and willingness to different project sizes and design requirements. Their team works collaboratively with manufacturers, designers, and product developers. And this is what makes them a reliable partner for most homeware brands since they aim to reach a quality that isn’t compromising with the time and a seamless and smooth development production that operates anywhere in the world.
Onshape is a cloud-based CAD platform designed for collaborative product development. They serve designers, distributed product development teams, and homeware brands, ensuring that they provide them with real-time collaboration and work smoothly in order to reduce errors in the long run and ensuring to avoid file conflicts while going through with the process of working with multiple locations or partners. Many homeware brands use the platform because it makes communication and design updates much faster. So Onshape is technically perfect for brands who work with more than one partner. They keep designs precise and communicate it clearly, which helps teams to move fast in creating their project while not compromising its quality and accountability worldwide.
OptiMAR Precon helps clients in helping homeware brands that find it difficult to create designs, especially when it needs complex elements. They offer CAD drafting, architectural planning services, and project design coordination services to make sure that every drawing that is presented aligns best to the product’s needs so that it will be accurate and everything will come out as organized as it could be. The company works collaboratively with manufacturers, designers, and builders, ensuring that everyone is aligned with the standards in order to not have massive mistakes in the long run, to not have pricey, costly surprises later on. Through Optimar Precon, a lot of homeware teams can be able to present their projects more confidently, helping the projects stay efficient and easier to manage.
Pacific CAD is best for homework teams that need accurate and reliable design support for they provide a trusted, and dependable solution. One reason many companies with them is their ability to stay organized even when handling detailed projects, CAD drafting, and manufacturing documentations for other products that include furniture. They work closely on multiple kinds of projects, from commercial to residential spaces and product lines, since they are very flexible and try to adapt to different sizes as they deliver it on time without compromising its quality.
They are also known for responding quickly and keeping production files accurate from start to finish and sticking to standards that they follow throughout the process. They are very keen details as well, tracking every technical task to ensure to only have minimal to no errors along the way. Pacific CAD makes sure that homeware brands stay productive even without having a lot of staff to do the work. Through this, they are becoming a dependable partner for a lot of homeware teams that aim to have a smooth production and receive results that are consistent since day one.
Rapid3D helps homeware brands to create accurate digital models, fixtures, and physical models for furniture and other products. Their services include 3D modeling, scanning, and prototype design services, for furniture and homeware products. What clients value about them is that they provide practical solutions to every problem and that they also handle design iterations. What makes them useful is how they help brands test ideas early and identify possible design problems before manufacturing it full scale. Rapid3D is totally an ideal choice for homeware brands that aims to have a product development that is fast and helps in improving product confidence across the market worldwide.
Saratek provides a full range of CAD services and engineering that includes drafting, simulation, for clients creating manufacturable homeware products. Instead of only focusing on design appearance , they also pay attention to technical performance and production requirements. It’s what clients value about them, they are very expert in technicality, providing them an organized workflow and ensuring that the designs they produce are totally ready for production.
Through their approach that focuses on combining creative design with manufacturing realities, Saratech is able to avoid the risk of having massive errors in the long run so that they could not have costly delays. And this is what makes them a dependable choice for any brands that seeks practical and solution-based companies in which their ideas can be brought to life with high quality and professionally ready for manufacturing worldwide.
Shalin Designs works closely with furniture and homeware brands that want to create custom or products that are in small batches. They offer a variety of services such as CAD modeling, product rendering and design, and ensuring an organized production of these digital drawings. They work well because they don’t just create visually appealing products, but they balance it with functionality and usability where they don’t limit their way in collaborating with clients in details that are needed during the process of creating the project design. Through their clear documentation, smooth process of prototyping, and easy coordination with different supplier brands. Shalin Designs become a trusted partner for personalized and hands-on their approach feels during collaboration and they could confidently present worldwide.
Shopr3D is a design platform built for creating simple but fast product design. Homework designers make product concepts reliably and test ideas precisely as they create designs with the use of hands-on tools. They centralize in reducing complexity of products, supporting its collaboration with the clients as they meet the product needs collaboratively throughout the process. It allows users to sketch, edit, and improve ideas quickly without slowing down the creative process, and accurate homework designs that could be best for presenting in the market pool worldwide.
Turning ideas into a manufacturable product that is not just aesthetically good but also practical can be difficult at times, especially when you don’t know where to start. Good thing, Sumer Innovations is a great partner, especially for homeware and consumer product brands that want to have a product design that is functional and quality-based. They offer CAD modeling, material selection, cost efficiency, and product functionality. Why they work best is because they focus not just on material knowledge and cost awareness factors, but also putting a strong emphasis on the practicality of the design without compromising its quality.
They also work collaboratively with the clients to make sure that the products are made efficiently all throughout the process. Through focusing as well in reducing the developmental risk of the product and making sure that the production is smooth so that it ensures a functional project output, Sumer Innovations becomes a trusted partner for brands that seeks a design execution that is reliable and really made with a thoughtful approach since they provide a full product development process worldwide.
Tejjy offers CAD, BIM modeling services, and design support services for residential, commercial, and homeware-related projects. They work with a lot of different software platforms, ensuring that they follow the standards of every industry, ensuring collaboration between designers and consultants, and also some manufacturers. What clients appreciate about them is that they provide predictable timelines and clear documentation which promises a smooth and structured workflow throughout the process. So, Tejjy is the best choice for any homeware brands that want reliable support in every multiple teams and technical requirements, either it be residential or commercial projects. Their services help keep projects aligned with schedules and industry standards
The AEC Associates creates homeware teams to make precise and clear drawings that are easy to turn into a real-world project. They focus heavily on accuracy and project coordination, which helps clients reduce mistakes during manufacturing. Through following the standards of the industry and using workflows that best aligns with every project needs, the AECS Associates makes approval times since files are prepared clearly and professionally. So for any homeware brands that want to make the production easier and professionally smooth, whether for commercial or residential spaces, then AECS Shades is the great choice for you.
TRC provides homeware brands with design, engineering, and consulting services that helps them to have their products move smoothly towards the production level. Especially when they aim for detailed and careful planning matters, the firm works best with product-focused teams, manufacturers, making sure that every design that they do meets the standards of technicality and regulatory needs to ensure that there will be no problem that they will face a long head. What clients love about TRC’s approach is that they are efficient, precise, and they handle complex projects smoothly without compromising its quality at the end. TRC helps a lot of teams move through development, aligning their designs with manufacturing realities, while also ensuring a smooth and reliable delivery timelines across global markets.
A lot of homeware brands are looking for reliable and predictable outcomes as they go through in producing their product designs. Good thing, Unicore offers engineers to improve consistency, accuracy, and production readiness across different projects. The company creates these precise and clear CAD drawings to homeware brands while ensuring its consistent quality and production readiness as it emphasizes standard processes and compliance, making sure that everything runs smoothly and effectively. With the help of Unicore, homeware teams are able to have fewer to minimal last rework along the way and receive products that are high volumes and absolutely consistently made with high-quality creativity that could be confidently produced as replicable products across global markets.
Whitewood Millwork specializes in custom cabinetry, furniture, and wood-based homeware products. Along with their creativeness, they are known for combining detailed craftsmanship with practical construction methods that make products durable and functional. Why Whitewood Millwork works best in this expertise is that they understand every material that they use, and they limit productions as long as they try to specialize in one project each time, as they install requirements, ensuring that all of the designs are not just attractive, but also buildable and functional. Whitewood Millwork is an ideal for any homeware team that aims for durability and expecting a premium result in either commercial or residential projects. Through following a certain standard approach and producing high-quality custom wood products, their experience with premium woodwork also helps create products that feel refined and professionally finished.
X-Procad creatively helps homeware brands to become production-ready. It all started from an idea that leads to a product development that seeks to meet exact guidelines and needs of the certain brand. To make this all come to life, the company provides concept 3D modeling, CAD drafting, and a lot of technical designs in order to support the furniture and product development of these homeware brands. What clients love about X-Pro because they communicate updates clearly and adapt well to design changes during development.
Through delivering product-ready files and following standards, specifications rightly, the company is able to provide and deliver organized and support faster fabrication of every project that leads to no confusion and minimal revisions of every project that they produce. They are a reliable choice for any brands, especially those who work with tight schedules or frequent design updates since they maintain the momentum and help these brands reduce confusion, speed up approvals, and keep projects moving efficiently.
Creating homeware products is not as simple as making something look beautiful. A successful product also needs to be functional, comfortable to use, durable, and suitable for everyday living. While having all the ideas in mind about creating different homeware products, it’s really difficult to turn those concepts to life all by yourself. That’s why in this article, we have provided you with the companies. That gives you the perfect designers that will help you turn your ideas into a real-life use. They make your sketches into complete market-ready products using a lot of technical tools and a lot of expertise.
How Cad Crowd can help
CAD Crowd makes it easy for any homeware brand teams to find freelance 3D designers that are highly skilled and expert in specializing in this project-based output. That process usually includes planning, testing, and manufacturing preparation. You can depend on it since it produces well-crafted products and turns every idea into a smart and professionally ready for the market. Contact us for a free quote.
MacKenzie Brown is the founder and CEO of Cad Crowd. With over 18 years of experience in launching and scaling platforms specializing in CAD services, product design, manufacturing, hardware, and software development, MacKenzie is a recognized authority in the engineering industry. Under his leadership, Cad Crowd serves esteemed clients like NASA, JPL, the U.S. Navy, and Fortune 500 companies, empowering innovators with access to high-quality design and engineering talent.
At the bidding of BioWare’s bosses, David Gaider created the world of Thedas, the setting of Dragon Age. And lo, it was beautiful, for a time. But he left the company after an abortive spell on Anthem, and today he’s working on a new RPG.
“You play a crew of rogues in an airship that go around performing heists,” he says. “And this leads you into a plot that becomes, maybe, your more typical RPG.”
Gaider is best known for his dark riffs on sword and sorcery—beginning with the half a million words he wrote for Baldur’s Gate 2, before taking on the all-timer Neverwinter Nights campaign Hordes of the Underdark. Then there was the decade he spent steering Dragon Age. But this time, he’s shooting for something a little more lighthearted.
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“I wanted to do something that was not full-on comedy, but something that could make me smile,” he says. “It seems like at this point in the world, we could use something like that. I know I could. So that’s what we’ve been working on, and it’s been getting a great reception.”
The trouble is, the games industry is currently on fire. “It’s been almost three years it’s been going through this weird contraction,” Gaider says. “The most obvious effect of that is all the layoffs, but that’s just really a symptom of all the studios clenching at once. On the funding side, nobody wants to actually commit to a project unless they think it’s a sure thing, and that boils down to existing IPs, sequels, that sort of thing. New projects, almost nothing’s getting funded.”
And so, the praise that Gaider’s heist RPG has been getting from publishers hasn’t yet resulted in the cash needed to complete it. “Our first prototype was a much simpler version,” he says. “We had our vertical slice, roughly of the quality level that we would release at, and a bit more of the game at a simpler version to show the publisher what we were thinking. And then they’re like, ‘Well, we want to see this further along’. So we had to take that and expand on it quite a bit more.”
(Image credit: EA)
A lot of publishers today are looking primarily to fund games that are already 80% completed—minimising their risk as they help projects across the finish line. “With one publisher, we said to them, ‘Are you really waiting for us to finish the project before you commit to it?’ And they embarrassedly were like, ‘Well, in so many words, I guess, yeah.’ There’s a lot of smaller studios like ours that are really struggling at this point.”
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There’s a lot of smaller studios like ours that are really struggling at this point.
David Gaider
Gaider co-founded Summerfall Studios in Australia almost a decade ago, and spearheaded the development of Stray Gods—which played like a classic Telltale story, only with musical numbers that adapted according to your choices. Though not a full-fledged RPG, it left me with the same queasy sense I’d felt playing Dragon Age: Origins—that perhaps my love of its characters had led me to make indefensible decisions.
Ironically enough, Gaider believes that Baldur’s Gate 3 torpedoed any chance Stray Gods had of commercial success. “I don’t think Larian were expecting Baldur’s Gate 3 to be a big hit,” he says. “They were hoping, maybe, but they were nervous. In fact, they moved their release date because they were really nervous about, of all things, Starfield.”
(Image credit: Summerfall Studios)
Larian pulled the launch date of Baldur’s Gate 3 forward—a move almost unheard of in game development—and plonked it right on top of Stray Gods. “I was kind of raw about that,” Gaider says. “Would Stray Gods have been a hit if that hadn’t happened? I don’t know, but it certainly meant that we had a real hard time getting noticed.”
Afterwards, Summerfall made DLC, and built a narrative-focused deckbuilder named Malys, starring an exorcist on a motorbike. “We really didn’t expect Malys to make any money, actually. It was a little side project we did to keep all hands at the studio busy while we were working on this project,” Gaider says. “If Malys had sold better, maybe we could have had a bit of a longer runway to get this prototype finished up. But you know, we’re doing what we can.” Finding further funding for the heist RPG is “make it or break it for the studio,” Gaider says. “So, lots of stress.”
Meanwhile, at BioWare, the series Gaider helped birth has continued in his absence. Dragon Age: The Veilguard came out in 2024, though Gaider didn’t play it. “I know too much about what went on behind the scenes,” he says. “The ordeal that the team that remained went through to make it. And I know that they were handicapped from the get go. Electronic Arts really did a number on them in terms of setting them up to fail, honestly.”
(Image credit: BioWare)
In PC Gamer’s largely positive review of Dragon Age: The Veilguard, the major complaint was that there wasn’t enough friction in its world; too few of the conflicting ideologies which, in previous entries, had caused head-on clashes in beliefs between would-be allies.
They need the ability to be unhappy with your decisions, and possibly even turn on you.
David Gaider
“In terms of having characters with agency, I think that’s vital,” Gaider says. “They need the ability to be unhappy with your decisions, and possibly even turn on you. If you don’t follow it to its natural conclusion, it’s like playing a D&D game where you know that the DM will never kill your character.”
Without that potential for real loss, Gaider reckons, a game loses its tension and capacity to convince. “Is that what the writing team on Veilguard intended? I don’t know that’s necessarily the case. I think that’s what they were kind of forced into, would be my guess, without knowing details.”
(Image credit: BioWare, Electronic Arts)
Back in Baldur’s Gate 2, companions could betray the player, or become so appalled at their actions that they drew their swords and fought their former comrades to the death. And even later, in Dragon Age: Origins, a disagreement with a party member might mean losing their support right before the final battle—scuppering your well-honed battle strategies and spell synergies in the process.
But over time, BioWare shifted towards the path of least upset to the player. Companions became less like human beings, corralled into uneasy cooperation, and more like foils you could simply send to camp or a waiting spaceship—ready to be dusted off and reactivated at the hero’s convenience.
“That sort of sentiment was getting stronger and stronger even as Dragon Age went along,” Gaider says. “This idea that, ‘Oh, we can’t let the player accidentally screw themselves.’ I think that was part and parcel with, ‘We need to have as broad a player base as possible, so we can’t make it too difficult. We can’t let the player get themselves into a position where now they can’t finish the game.'”
(Image credit: BioWare)
Gaider thinks that kind of thinking was backwards. “This idea that we can’t permanently take someone out of a group, that followers have to be agreeable for purely gameplay reasons, runs contrary against the thing that made BioWare games most popular,” he says.
So why not just lean into what you do best, rather than trying to lean away from it in order to make other things more broadly acceptable?
David Gaider
“The earlier games, all the reviews that came out, they always talked about the amazing characters. So why not just lean into what you do best, rather than trying to lean away from it in order to make other things more broadly acceptable? If you’re not making a game for the audience that loves those games, you’re trying to make this game acceptable to some action gamer who, what, doesn’t like difficulty? Who is that?”
If Gaider gets to finish his heist RPG, it’s fair to assume it’ll hew close to the long-held philosophy hinted at here. A commitment to imbuing characters with inner lives which, at times, override the immediate desires of players.
(Image credit: BioWare, EA)
“We tried ‘all the romances are available to everyone’ in Dragon Age 2, and I didn’t like what effect that had on the characters,” he says. “I get it, players want what they want. But from a project level you have to answer the question: why are these characters here? Are they there just to provide enjoyment for the player? And if the answer is yes, perfectly valid answer. But if the answer is, ‘No, our goal with this writing is to create believable characters that have agency of their own, and that’s part of their appeal’? Then you should follow through with them having identities of their own. They should have the ability to turn down the player. This is not about wish fulfillment.”
Of course, if a publisher doesn’t bite, Gaider might not get to make his heist RPG at all. “I’m kind of philosophical about it,” he says. “Not everything lasts forever. Seven or eight years is a nice long run, and it’s been fantastic. As to what I would do afterwards, if that was the end of Summerfall, I don’t know. Is it even possible to find a job in the industry these days? Would I be competing with people of my own seniority, and begging for a job?”
One upside, in that scenario, would be setting aside the responsibility of running a studio and letting someone else handle the pitches. “Oh, what I wouldn’t give to work on Owlcat’s The Expanse game,” Gaider says. “The Expanse is right in there with my core interests. I’ve watched the show a few times, I’ve read the books. That’d be great. If I could find something that lit a fire under me, that’d be the ideal.”
(Image credit: Owlcat Games)
And Dragon Age? News recently circulated that Richard Garriott might get his hands on the copyright for Ultima, so it’s not impossible to imagine that Gaider might one day have an opportunity to play in Thedas again.
“If you’d asked me that in the past, I would have said absolutely not. That I’d done my time,” he says. “But I do like a challenge. So if, out of some weird alignment of the stars, somebody handed the Dragon Age franchise back to me and said, ‘Breathe the life back into this baby’? That’d be a tough one, but I think that’d be an interesting thing to do.
“To go back to the basics of what made Dragon Age appeal to so many people in the first place. And go somewhere dark and dangerous, and do things that will make people upset. I think that’s what I would want to do with it.”
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Google is relaunching its smart speaker ecosystem for the “Gemini era,” as it has stated so many times with recent products. While I’m not fully convinced this new speaker is a truly revolutionary Gemini-powered speaker when compared to existing Google and Nest speakers, the overall quality of the Google Home Speaker is a great value for $99.
Whether you’re looking for a new music-playing speaker that understands basic commands or want an extra speaker to enhance your smart home, this is a solid choice with some annoying software issues that will hopefully be cleared up in the near future.
Google Home Speaker price, availability, and specs
(Image credit: Nicholas Sutrich / Android Central)
The 2026 Google Home Speaker is the first smart speaker from Google that’s designed “from the ground up for Gemini.” It’s the first Google speaker to include a proper NPU for AI processing, an upgrade over ML processors in the past few Nest releases. It retails for $99 and comes in two colors globally — Hazel and Porcelain — while U.S. customers can also choose from Berry or Jade varieties. My review unit is Jade.
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Google includes 6 months of Google Home Premium for free (a $60 value) when you purchase a Google Home Speaker before September 30, 2026.
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Google Home Speaker (2026) specs
Catrgory
Google Home Speaker
Speaker
Omni-directional 58mm full-range driver
Microphone
3 far-field mics, hardware mute switch
Dimensions
86.6mm/3.4in high x 107mm/4.2in diameter
Weight
396g
Power adapter
30W USB-C PC/PPS charger
RAM
1GB LPDDR4
Storage
4GB EMMC
Processor
Quad-core A55 2.0 GHz with NPU
Connectivity
Wi-Fi 6, Bluetooth 5.4, Thread 1.3 border router (2.4GHz), Matter
Colors
Globally: Hazel, Porcelain
U.S. exclusive: Jade, Berry
Mostly the right priorities
(Image credit: Nicholas Sutrich / Android Central)
For the past few years, Google has used the Nest brand name for its smart speakers, but I’ve rarely called them that. Whether it’s the Nest Mini or one of the Nest Hub smart displays, my household always refers to them audibly as the Google speaker or the Google display.
Because of that, I think it makes a lot more sense to keep using the Google name as the proper brand, and I know I’m not the only person who calls their smart speaker “Google” something or other. Thankfully, Google rectified the name without ruining the excellent design and the sort of feng shui character of the Nest line of smart speakers.
(Image credit: Nicholas Sutrich / Android Central)
The 2026 speaker is still clad in homey fabric that looks graceful and unobtrusive on a shelf. It’s the ideal size between the tiny Nest Mini and the gargantuan Google Home Max speaker, with appropriately sized audio components. It’s even got a cute little glowing light underneath that makes it feel more like you’re talking to a smart little robot than mumbling into a speaker.
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But I don’t understand why Google speakers seem to almost always have some weird issue with the power cables. Earlier models used barrel plugs and proprietary chargers, creating unnecessary e-waste. This model uses a standard 30W Google USB-C charger, but the cable is hardwired into the speaker, meaning you’ll either have to splice it when it eventually breaks or toss the speaker and buy a new one. Dumb.
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(Image credit: Nicholas Sutrich / Android Central)
(Image credit: Nicholas Sutrich / Android Central)
(Image credit: Nicholas Sutrich / Android Central)
(Image credit: Nicholas Sutrich / Android Central)
Since it’s slightly smaller than the Nest Audio speaker (yes, there have been a lot of options over the years), the audio quality won’t be quite as good, but the Google Home Speaker’s advantage is that its speaker is omnidirectional. Depending on how you want to mount it, this could make a big difference.
You can also use the Google Home Speaker in conjunction with a Google TV Streamer to create a surround sound setup, which is a great feature I’m glad Google finally adopted from Amazon Echo and Fire TV devices.
I’m not exactly an audiophile and don’t care much about top-notch sound, so I found these speakers ideal, as they’re a notable upgrade over the Nest Minis I have around the house. Nest Audio fans should stick with those unless they have issues with using Gemini.
(Image credit: Nicholas Sutrich / Android Central)
And while “built for Gemini” should be the actual upgrade for the Google Home Speaker over any other Nest or Google speaker, my experience with it has been extremely inconsistent. If I ask it to turn the lights on or off, check my cameras, or even what the weather will be like next week, responses generally take about 1 second to process. This is much faster than the other Google speakers in my house, for the most part.
But some commands are bizarrely slow. Setting a timer, for example, often takes 20-25 seconds of processing time before I receive an “OK, setting a timer” response. Asking it to add bananas to my grocery list also takes 5-10 seconds. This bizarre behavior persists through reboots, so I don’t know what to make of it. Clearly, the speaker isn’t doing as much local processing for simple commands like this as I had hoped. Google is aware of the issues (as I’m not the only one experiencing them), and I will update this review if they are resolved.
This is particularly annoying because all of the other features I’ve used over the past week have been great. Gemini allows you to chain multiple commands together or even express complex commands, while Assistant can only do one at a time. For example, you can ask it to “turn off all lights except for the bedroom light,” a command I issue nightly as I tuck in for reading time.
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(Image credit: Android Central)
(Image credit: Android Central)
This isn’t particularly unique to this new speaker since Gemini has been rolled out to even the oldest 2016 Google Home speaker (which is still in operation in my house), but this speaker is certainly going to be supported for years to come, while those older speakers will eventually receive an end-of-life update.
At some point, Google had locked down several features behind the annoying Voice Match feature. I don’t want to use Voice Match, but I (and others in my house) do want to check my calendar, and Google finally allows users to do that on its smart speakers.
This speaker also seems to actually understand commands, including simple ones like “stop” when a timer is going off, while I swear half my other speakers ignore my commands half the time. Maybe time will also turn this one into a pretty paperweight, but it’s pretty great for the time being.
Should you buy it?
(Image credit: Nicholas Sutrich / Android Central)
The 2026 Google Home Speaker is a generally good little product that delivers great audio quality in a compelling design, with a virtual assistant that seems to actually understand you. Processing time is strangely lengthy for some simple commands (like setting a timer), but this is almost certainly a bug rather than a product defect.
If Google can reduce processing time for some commands, this will be my go-to speaker recommendation for the future. Gemini has been excellent for smart home commands in my experience, and far more understanding of every other type of command than Assistant has been for the past half-decade, and that’s really all I want out of a smart speaker, anyway.
Artificial intelligence is rewriting the world, and simultaneously inventing a whole new language to describe how it’s doing it. Sit in on any product meeting, pitch, or panel these days, and you’ll hear people toss around LLMs, RAG, RLHF, and a dozen other terms that can make even very smart people in the tech world feel a little insecure. This glossary is our attempt to fix that: pain-English definitions of the AI terms you’re most likely to actually run into, whether you’re building with this stuff, investing in it, or just trying to keep up by reading TechCrunch or listening to related podcasts. We update it regularly as the field evolves, so consider it a living document, much like the AI systems it describes.
Artificial general intelligence, or AGI, is a nebulous term. But it generally refers to AI that’s more capable than the average human at many, if not most, tasks. OpenAI CEO Sam Altman once described AGI as the “equivalent of a median human that you could hire as a co-worker.” Meanwhile, OpenAI’s charter defines AGI as “highly autonomous systems that outperform humans at most economically valuable work.” Google DeepMind’s understanding differs slightly from these two definitions; the lab views AGI as “AI that’s at least as capable as humans at most cognitive tasks.” Confused? Not to worry — so are experts at the forefront of AI research.
An AI agent refers to a tool that uses AI technologies to perform a series of tasks on your behalf — beyond what a more basic AI chatbot could do — such as filing expenses, booking tickets or a table at a restaurant, or even writing and maintaining code. However, as we’ve explained before, there are lots of moving pieces in this emergent space, so “AI agent” might mean different things to different people. Infrastructure is also still being built out to deliver on its envisaged capabilities. But the basic concept implies an autonomous system that may draw on multiple AI systems to carry out multistep tasks.
Think of API endpoints as “buttons” on the back of a piece of software that other programs can press to make it do things. Developers use these interfaces to build integrations — for example, allowing one application to pull data from another, or enabling an AI agent to control third-party services directly without a human manually operating each interface. Most smart home devices and connected platforms have these hidden buttons available, even if ordinary users never see or interact with them. As AI agents grow more capable, they are increasingly able to find and use these endpoints on their own, opening up powerful — and sometimes unexpected — possibilities for automation.
Given a simple question, a human brain can answer without even thinking too much about it — things like “which animal is taller, a giraffe or a cat?” But in many cases, you often need a pen and paper to come up with the right answer because there are intermediary steps. For instance, if a farmer has chickens and cows, and together they have 40 heads and 120 legs, you might need to write down a simple equation to come up with the answer (20 chickens and 20 cows).
In an AI context, chain-of-thought reasoning for large language models means breaking down a problem into smaller, intermediate steps to improve the quality of the end result. It usually takes longer to get an answer, but the answer is more likely to be correct, especially in a logic or coding context. Reasoning models are developed from traditional large language models and optimized for chain-of-thought thinking thanks to reinforcement learning.
This is a more specific concept that an “AI agent,” which means a program that can take actions on its own, step by step, to complete a goal. A coding agent is a specialized version applied to software development. Rather than simply suggesting code for a human to review and paste in, a coding agent can write, test, and debug code autonomously, handling the kind of iterative, trial-and-error work that typically consumes a developer’s day. These agents can operate across entire codebases, spotting bugs, running tests, and pushing fixes with minimal human oversight. Think of it like hiring a very fast intern who never sleeps and never loses focus — though, as with any intern, a human still needs to review the work.
Although somewhat of a multivalent term, compute generally refers to the vital computational power that allows AI models to operate. This type of processing fuels the AI industry, giving it the ability to train and deploy its powerful models. The term is often a shorthand for the kinds of hardware that provides the computational power — things like GPUs, CPUs, TPUs, and other forms of infrastructure that form the bedrock of the modern AI industry.
A subset of self-improving machine learning in which AI algorithms are designed with a multi-layered, artificial neural network (ANN) structure. This allows them to make more complex correlations compared to simpler machine learning-based systems, such as linear models or decision trees. The structure of deep learning algorithms draws inspiration from the interconnected pathways of neurons in the human brain.
Deep learning AI models are able to identify important characteristics in data themselves, rather than requiring human engineers to define these features. The structure also supports algorithms that can learn from errors and, through a process of repetition and adjustment, improve their own outputs. However, deep learning systems require a lot of data points to yield good results (millions or more). They also typically take longer to train compared to simpler machine learning algorithms — so development costs tend to be higher.
Diffusion is the tech at the heart of many art-, music-, and text-generating AI models. Inspired by physics, diffusion systems slowly “destroy” the structure of data — for example, photos, songs, and so on — by adding noise until there’s nothing left. In physics, diffusion is spontaneous and irreversible — sugar diffused in coffee can’t be restored to cube form. But diffusion systems in AI aim to learn a sort of “reverse diffusion” process to restore the destroyed data, gaining the ability to recover the data from noise.
Distillation is a technique used to extract knowledge from a large AI model with a ‘teacher-student’ model. Developers send requests to a teacher model and record the outputs. Answers are sometimes compared with a dataset to see how accurate they are. These outputs are then used to train the student model, which is trained to approximate the teacher’s behavior.
Distillation can be used to create a smaller, more efficient model based on a larger model with a minimal distillation loss. This is likely how OpenAI developed GPT-4 Turbo, a faster version of GPT-4.
While all AI companies use distillation internally, it may have also been used by some AI companies to catch up with frontier models. Distillation from a competitor usually violates the terms of service of AI API and chat assistants.
This refers to the further training of an AI model to optimize performance for a more specific task or area than was previously a focal point of its training — typically by feeding in new, specialized (i.e., task-oriented) data.
Many AI startups are taking large language models as a starting point to build a commercial product but are vying to amp up utility for a target sector or task by supplementing earlier training cycles with fine-tuning based on their own domain-specific knowledge and expertise.
A GAN, or Generative Adversarial Network, is a type of machine learning framework that underpins some important developments in generative AI when it comes to producing realistic data — including (but not only) deepfake tools. GANs involve the use of a pair of neural networks, one of which draws on its training data to generate an output that is passed to the other model to evaluate.
The two models are essentially programmed to try to outdo each other. The generator is trying to get its output past the discriminator, while the discriminator is working to spot artificially generated data. This structured contest can optimize AI outputs to be more realistic without the need for additional human intervention. Though GANs work best for narrower applications (such as producing realistic photos or videos), rather than general purpose AI.
Hallucination is the AI industry’s preferred term for AI models making stuff up — literally generating information that is incorrect. Obviously, it’s a huge problem for AI quality.
Hallucinations produce GenAI outputs that can be misleading and could even lead to real-life risks — with potentially dangerous consequences (think of a health query that returns harmful medical advice).
The problem of AIs fabricating information is thought to arise as a consequence of gaps in training data. Hallucinations are contributing to a push toward increasingly specialized and/or vertical AI models — i.e. domain-specific AIs that require narrower expertise — as a way to reduce the likelihood of knowledge gaps and shrink disinformation risks.
Inference is the process of running an AI model. It’s setting a model loose to make predictions or draw conclusions from previously seen data. To be clear, inference can’t happen without training; a model must learn patterns in a set of data before it can effectively extrapolate from this training data.
Many types of hardware can perform inference, ranging from smartphone processors to beefy GPUs to custom-designed AI accelerators. But not all of them can run models equally well. Very large models would take ages to make predictions on, say, a laptop versus a cloud server with high-end AI chips.
Large language models, or LLMs, are the AI models used by popular AI assistants, such as ChatGPT, Claude, Google’s Gemini, Meta’s AI Llama, Microsoft Copilot, or Mistral’s Le Chat. When you chat with an AI assistant, you interact with a large language model that processes your request directly or with the help of different available tools, such as web browsing or code interpreters.
LLMs are deep neural networks made of billions of numerical parameters (or weights, see below) that learn the relationships between words and phrases and create a representation of language, a sort of multidimensional map of words.
These models are created from encoding the patterns they find in billions of books, articles, and transcripts. When you prompt an LLM, the model generates the most likely pattern that fits the prompt.
Memory cache refers to an important process that boosts inference (which is the process by which AI works to generate a response to a user’s query). In essence, caching is an optimization technique, designed to make inference more efficient. AI is obviously driven by high-octane mathematical calculations and every time those calculations are made, they use up more power. Caching is designed to cut down on the number of calculations a model might have to run by saving particular calculations for future user queries and operations. There are different kinds of memory caching, although one of the more well-known is KV (or key value) caching. KV caching works in transformer-based models, and increases efficiency, driving faster results by reducing the amount of time (and algorithmic labor) it takes to generate answers to user questions.
Model Context Protocol, or MCP, is an open standard that lets AI models connect to outside tools and data — your files, databases, or apps like Slack and Google Drive — without a developer building a custom connector for every single pairing. Think of it as a USB-C port for AI. Anthropic introduced MCP in 2024 and later handed it over to the Linux Foundation, and it’s since been adopted by OpenAI, Google, and Microsoft, making it one of the fastest-spreading standards in recent AI history.
Mixture of Experts is a model architecture that splits a neural network into many smaller specialized sub-networks, or “experts,” and only activates a handful of them for any given task. Rather than routing every request through the entire model — like calling in your whole office for every question — an MoE model has a built-in “router” that picks just the right specialists for the job. This makes it possible to build enormous models that stay relatively fast and cheap to run, since only a fraction of the network is doing work at any one time. Mistral AI’s Mixtral model is a well-known example; OpenAI’s newer GPT models are also widely believed to use some version of this approach, though the company has never officially confirmed it.
A neural network refers to the multi-layered algorithmic structure that underpins deep learning — and, more broadly, the whole boom in generative AI tools following the emergence of large language models.
Although the idea of taking inspiration from the densely interconnected pathways of the human brain as a design structure for data processing algorithms dates all the way back to the 1940s, it was the much more recent rise of graphical processing hardware (GPUs) — via the video game industry — that really unlocked the power of this theory. These chips proved well suited to training algorithms with many more layers than was possible in earlier epochs — enabling neural network-based AI systems to achieve far better performance across many domains, including voice recognition, autonomous navigation, and drug discovery.
Open source refers to software — or, increasingly, AI models — where the underlying code is made publicly available for anyone to use, inspect, or modify. In the AI world, Meta’s Llama family of models is a prominent example; Linux is the famous historical parallel in operating systems. Open source approaches allow researchers, developers, and companies around the world to build on top of one another’s work, accelerating progress and enabling independent safety audits that closed systems cannot easily provide. Closed source means the code is private — you can use the product but not see how it works, as is the case with OpenAI’s GPT models — a distinction that has become one of the defining debates in the AI industry.
Parallelization means doing many things at the same time instead of one after another — like having 10 employees working on different parts of a project at the same time instead of one employee doing everything sequentially. In AI, parallelization is fundamental to both training and inference: modern GPUs are specifically designed to perform thousands of calculations in parallel, which is a big reason why they became the hardware backbone of the industry. As AI systems grow more complex and models grow larger, the ability to parallelize work across many chips and many machines has become one of the most important factors in determining how quickly and cost-effectively models can be built and deployed. Research into better parallelization strategies is now a field of study in its own right.
RAMageddon is the fun new term for a not-so-fun trend that is sweeping the tech industry: an ever-increasing shortage of random access memory, or RAM chips, which power pretty much all the tech products we use in our daily lives. As the AI industry has blossomed, the biggest tech companies and AI labs — all vying to have the most powerful and efficient AI — are buying so much RAM to power their data centers that there’s not much left for the rest of us. And that supply bottleneck means that what’s left is getting more and more expensive.
That includes industries like gaming (where major companies have had to raise prices on consoles because it’s harder to find memory chips for their devices), consumer electronics (where memory shortage could cause the biggest dip in smartphone shipments in more than a decade), and general enterprise computing (because those companies can’t get enough RAM for their own data centers). The surge in prices is only expected to stop after the dreaded shortage ends but, unfortunately, there’s not really much of a sign that’s going to happen anytime soon.
Like AGI, recursive self-improvement is a threshhold for how smart AI can get, and how little it may rely on humans. In the RSI scenario, AI models start improving themselves without human intervention, leading to a huge acceleration in capabilities and autonomy. In some tellings, this would be a cataclysmic moment akin to the singularity, a moment when AI models become immune to outside intervention. But RSI also describes a basic capability — can an AI model design its own successor? — which makes it much easier for engineers to try to build it. A number of recent AI startups have set out to build recursively self-improving models, but most of them dismiss the apocalyptic implications, presenting RSI as simply the next frontier for research.
Reinforcement learning is a way of training AI where a system learns by trying things and receiving rewards for correct answers — like training your beloved pet with treats, except the “pet” in this scenario is a neural network and the “treat” is a mathematical signal indicating success. Unlike supervised learning, where a model is trained on a fixed dataset of labeled examples, reinforcement learning lets a model explore its environment, take actions, and continuously update its behavior based on the feedback it receives. This approach has proven especially powerful for training AI to play games, control robots, and, more recently, sharpen the reasoning ability of large language models. Techniques like reinforcement learning from human feedback, or RLHF, are now central to how leading AI labs fine-tune their models to be more helpful, accurate, and safe.
When it comes to human-machine communication, there are some obvious challenges — people communicate using human language, while AI programs execute tasks through complex algorithmic processes informed by data. Tokens bridge that gap: they are the basic building blocks of human-AI communication, representing discrete segments of data that have been processed or produced by an LLM. They are created through a process called tokenization, which breaks down raw text into bite-sized units a language model can digest, similar to how a compiler translates human language into binary code a computer can understand. In enterprise settings, tokens also determine cost — most AI companies charge for LLM usage on a per-token basis, meaning the more a business uses, the more it pays.
So again, tokens are the small chunks of text — often parts of words rather than whole ones — that AI language models break language into before processing it; they are roughly analogous to “words” for the purposes of understanding AI workloads. Throughput refers to how much can be processed in a given period of time, so token throughput is essentially a measure of how much AI work a system can handle at once. High token throughput is a key goal for AI infrastructure teams, since it determines how many users a model can serve simultaneously and how quickly each of them receives a response. AI researcher Andrej Karpathy has described feeling anxious when his AI subscriptions sit idle — echoing the feeling he had as a grad student when expensive computer hardware wasn’t being fully utilized — a sentiment that captures why maximizing token throughput has become something of an obsession in the field.
Developing machine learning AIs involves a process known as training. In simple terms, this refers to data being fed in in order that the model can learn from patterns and generate useful outputs. Essentially, it’s the process of the system responding to characteristics in the data that enables it to adapt outputs toward a sought-for goal — whether that’s identifying images of cats or producing a haiku on demand.
Training can be expensive because it requires lots of inputs, and the volumes required have been trending upwards — which is why hybrid approaches, such as fine-tuning a rules-based AI with targeted data, can help manage costs without starting entirely from scratch.
A technique where a previously trained AI model is used as the starting point for developing a new model for a different but typically related task — allowing knowledge gained in previous training cycles to be reapplied.
Transfer learning can drive efficiency savings by shortcutting model development. It can also be useful when data for the task that the model is being developed for is somewhat limited. But it’s important to note that the approach has limitations. Models that rely on transfer learning to gain generalized capabilities will likely require training on additional data in order to perform well in their domain of focus
Validation loss is a number that tells you how well an AI model is learning during training — and lower is better. Researchers track it closely as a kind of real-time report card, using it to decide when to stop training, when to adjust hyperparameters, or whether to investigate a potential problem. One of the key concerns it helps flag is overfitting, a condition in which a model memorizes its training data rather than truly learning patterns it can generalize to new situations. Think of it as the difference between a student who genuinely understands the material and one who simply memorized last year’s exam — validation loss helps reveal which one your model is becoming.
Weights are core to AI training, as they determine how much importance (or weight) is given to different features (or input variables) in the data used for training the system — thereby shaping the AI model’s output.
Put another way, weights are numerical parameters that define what’s most salient in a dataset for the given training task. They achieve their function by applying multiplication to inputs. Model training typically begins with weights that are randomly assigned, but as the process unfolds, the weights adjust as the model seeks to arrive at an output that more closely matches the target.
For example, an AI model for predicting housing prices that’s trained on historical real estate data for a target location could include weights for features such as the number of bedrooms and bathrooms, whether a property is detached or semi-detached, whether it has parking, a garage, and so on.
Ultimately, the weights the model attaches to each of these inputs reflect how much they influence the value of a property, based on the given dataset.
This article is updated regularly with new information.
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88% of Businesses Are Using AI Wrong. And Franchises Are Secretly Built to Win
Notion just released one of the most honest AI reports I’ve read in a while. They surveyed 6,118 people across 10 global markets to figure out where companies actually are in their AI journey, not where LinkedIn posts claim they are.
The headline number: 88% of companies are still using AI as a personal chatbot. Drafting emails. Summarizing documents. Brainstorming ideas. Useful, sure. But only 12% have AI actually running workflows in their business. And just 2% have AI operating critical processes end to end.
When I read that, my first thought wasn’t “companies are behind.” It was this: if you run a franchise or multi-location brand, this report is the best news you’ve received all year.
Let me explain why.
The 4 levels of AI maturity, in plain English
Notion structures the report around a four-level model. Here’s my translation after working inside these levels with real businesses:
Level 1: AI as a thought partner (57% of companies). Someone on your team opens ChatGPT, asks it to write a caption or clean up an email. No connection to your business data. This is where most of the world lives
Level 2: AI as an assistant (31%). AI is connected to your systems and context. It knows your brand voice, your documents, your customer data. Tasks get done faster because the AI isn’t starting from zero every time.
Level 3: AI as teammates (10%). This is where it gets interesting. AI agents run recurring workflows on their own, with humans reviewing at checkpoints. Think of a lead follow-up sequence that runs itself, or a reporting workflow that compiles and sends itself every Monday.
Level 4: AI as teammates (2%). AI runs complex, business-critical processes with real autonomy. Very few companies are here, and most don’t need to be there yet.
The important part is the shape of the value curve. It’s not linear. The jump from Level 2 to Level 3 is where the real returns start showing up, because you stop saving minutes per person and start reclaiming entire workflows per team.
A quick story about what these levels look like in real life
A while back we worked with a franchisor whose marketing team was classic Level 1. Everyone had a ChatGPT tab open. Ad copy, captions, email drafts. Individually helpful, collectively invisible. Every location was getting roughly the same generic ads because the AI knew nothing about any of them.
The shift happened when we stopped asking “how can each person use AI” and started with the boring part first: clean location data. We built a small system that pulls together, for every single location, reviews, CRM metrics, POS data, Google Business Profile, the website, and the manual stuff that doesn’t live in any system.
Once every location had its own data profile, AI-generated ad copy stopped being generic and started being strategic. Now you can build hypotheses per location. A location running at full capacity gets ads pushing premium services, because they don’t need more volume, they need better margins. A location with open capacity gets the opposite: entry-level offers designed to fill the calendar. Same brand, same system, completely different message per unit.
I’ve broken down this whole approach in detail in our multi-location PPC blog, including a video walkthrough, if you want to see how it works step by step.
That’s a Level 1 to Level 3 jump on one workflow. Not the whole business. One workflow. And that’s the pattern I keep seeing: you don’t transform a company, you transform one recurring workflow at a time.
Why franchises are structurally built for Level 3
Here’s the part of the report that made me want to write this post. When you look at who’s actually reaching Level 3 and 4, the profile looks almost exactly like a franchise system. Three data points stand out.
1. You’re the right size
Mid-market companies lead adoption at 17%, while enterprise trails at just 7%. Big companies have more budget, but they also have more committees, more legacy systems, and more people who can say no.
Emerging franchisors and multi-unit operators sit in the sweet spot. You’re big enough to have repeatable processes worth automating, and small enough that a decision made this quarter can be live before the next one.
2. You already have centralized decision-making
This one is huge. Owner and CEO respondents are more than 6 times as likely to be operating at Level 3 or 4 compared to individual contributors. 39% versus 6%. AI transformation is a top-down game.
And franchising is the most top-down business model there is. One decision at the franchisor level deploys across every unit. Your franchisees don’t need to independently figure out AI. They need you to hand them a system that works. That’s not a limitation, that’s leverage. A 200-person company needs 200 people to change behavior. A 40-unit franchise needs one head office to build it once.
3. Your business IS repeatable workflows
Look at where usage actually grows as companies mature. Automating repetitive tasks jumps 18 percentage points. Routing work across tools jumps 15. The mature companies aren’t using AI to write better, they’re using it as the connective tissue between systems.
Now think about what a franchise actually is. It’s a library of standardized, repeatable workflows: local marketing, franchisee onboarding, weekly reporting, compliance checks, customer follow-up. The thing mature organizations struggle to build, standardization, you built years ago. It’s called your operations manual.
Most businesses have to invent their SOPs before they can automate them. You just have to activate what’s already there.
The two traps I see kill franchise AI rollouts
I’d be lying if I said this was easy. The same report shows exactly where things go wrong, and both failure modes hit franchise systems harder than anyone else.
Trap 1: Tool sprawl. “Too many AI tools” is the fastest-growing complaint among advanced organizations, up 14 percentage points at Level 3 and 4. One respondent put it perfectly: too many options exist, but none fits the actual workflow.
Now multiply that across 40 locations. If every franchisee picks their own tools, you don’t have an AI strategy, you have 40 experiments and zero brand consistency. We’ve seen prompt libraries solve part of this for marketing teams, giving every location the same proven inputs instead of everyone freelancing. The principle is the same across the board: one system, one governance layer, one way of doing things.
Trap 2: The readiness gap. Across every maturity level, decision makers say they’re investing in AI faster than employees can keep up. And it gets worse as you advance, climbing from 48% at Level 1 to 68% at Level 4.
This is the trap I see most often. A franchisor buys a tool, announces it in the monthly newsletter, and six months later adoption sits at 15%. The tool wasn’t the problem. There was no training, no rollout plan, no one accountable for making it stick at the unit level. In franchising, a tool that head office loves but franchisees ignore is worse than no tool at all, because now you’ve spent money proving that “AI doesn’t work here.”
The franchisor playbook, based on what Level 3 companies actually do
The report also shows what separates companies that break through. Three things, and they map cleanly to how franchisors already think:
Integrate with existing systems first. The single biggest gap between mature and immature companies is integration, up 18 points. Don’t bolt AI on the side. Build it into the workflows your locations already run.
Build governance before you scale. Mature companies are 16 points more likely to have oversight and governance in place. For a franchise, this is non-negotiable. Brand consistency across units depends on it. Decide what AI can and can’t touch before location number one goes live, not after location number twelve does something off-brand. Governance doesn’t have to mean a 50-page policy document either. It can be as practical as rules inside your prompt library about who approves a prompt before locations can use it. I’ve written about how we structure prompt library approvals if you want a working model to copy.
Measure like a franchisor. Level 3 and 4 companies measure quality metrics, workflow metrics, and financial impact. The immature ones rely on anecdotes about time saved. You already know how to do this. You track AUV, you compare unit economics across locations. Treat AI ROI the same way: per location, comparable, reportable. If you can’t put it on the same dashboard as your unit P&L, it’s not ready to scale.
The window is open right now
Back to that 88% number. Almost nine out of ten businesses, including your competitors, are stuck using AI as a fancy chatbot. The 12% who broke through didn’t get there by buying more tools. They built systems.
Franchising already thinks in systems. You have the SOPs, the centralized decision-making, and the repeatable workflows that mature AI adoption requires. Structurally, you’re ahead. Most franchisors just haven’t activated it yet.
That activation piece, going from scattered individual usage to workflows that actually run, is exactly what we do at Weam. We work with franchisors and multi-location brands as their AI implementation partner, from picking the first workflow to training the teams who’ll run it. And if you’d rather talk it through than take an audit, book a call with us. It’s a conversation, not a pitch.
Clair Obscur: Expedition 33 creative director Guillaume Broche thinks that “games that try to be perfect” often end up “really boring” – and despite his RPG winning countless awards last year, he thinks it includes plenty of “imperfections” that add to its charm.
Speaking in a new episode of Konbini’s Video Game Club on YouTube (below), Broche talks about loads of his favorite games and influences, including the Devil May Cry series.
He thinks that the series’ first game is “a bit of a mess” when you look at Dante’s love interest, Trish (who looks like his own mother), and the “cheesy lines” the protagonist is always saying, but Broche reckons “these games are really endearing” because they’re not perfect.
“You see their flaws, and you think to yourself, ‘Yeah, it’s lame, but I don’t care,'” he says, adding: “Games that try to be perfect, that try to fix all their flaws – they’re usually just really boring. My theory is that it’s just like people. People who try to be perfect are boring because they have no personality. Whereas people who embrace their slightly weird side – in the end – are the interesting ones.”
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But what about Clair Obscur: Expedition 33? It might be a GOTY winner, but when asked about its quirks, Broche has plenty of examples, including its “unbearable” minigames, the fact that “you could get absurdly strong in Act 3,” and that some players could “breeze through the whole thing in one go and won’t see all the content.”
But to that, the devs simply thought: “‘Who cares? It’s just funny. That’s what we love about it.'” And, as Broche says, “the imperfections are part of the charm.”
I definitely think Broche has a point – I spent more time in the Only Up-esque Gestral Games climbing minigame than I’d like to admit, and it was agonizing, but looking back on my 70 hours in the RPG, making my way to the top of that ridiculous tower stands out as one of the highlights of the whole experience.
Personality is important, and Clair Obscur: Expedition 33 has plenty of it.
Today’s Wordle answer should be easy to solve if you’re a foodie.
If you just want to be told today’s word, you can jump to the bottom of this article for today’s Wordle solution revealed. But if you’d rather solve it yourself, keep reading for some clues, tips, and strategies to assist you.
Originally created by engineer Josh Wardle as a gift for his partner, Wordle rapidly spread to become an international phenomenon, with thousands of people around the globe playing every day. Alternate Wordle versions created by fans also sprang up, including battle royale Squabble, music identification game Heardle, and variations like Dordle and Quordle that make you guess multiple words at once.
The best Wordle starting word is the one that speaks to you. But if you prefer to be strategic in your approach, we have a few ideas to help you pick a word that might help you find the solution faster. One tip is to select a word that includes at least two different vowels, plus some common consonants like S, T, R, or N.
Get your last guesses in now, because it’s your final chance to solve today’s Wordle before we reveal the solution.
Drumroll please!
The solution to today’s Wordle is…
PIZZA
Don’t feel down if you didn’t manage to guess it this time. There will be a new Wordle for you to stretch your brain with tomorrow, and we’ll be back again to guide you with more helpful hints. Are you also playing NYT Strands? See hints and answers for today’s Strands.
Reporting by Chance Townsend, Caitlin Welsh, Sam Haysom, Amanda Yeo, Shannon Connellan, Cecily Mauran, Mike Pearl, and Adam Rosenberg contributed to this article.
The latest week-long speedrunning marathon starts on July 5.
Speedrunners are once again descending on Minneapolis to tear through games in aid of a fantastic cause as this year’s edition of Summer Games Done Quick (SGDQ) is about to commence. The week-long, round-the-clock event starts on Sunday. You can watch all of the action live on Twitch. If you miss a particular run, you’ll be able to catch up on the VODs on YouTube.
After a preshow at 12:30PM ET, the action will start at 1PM with a 102% run of one of my favorite games of all time, Donkey Kong Country 2: Diddy’s Kong-Quest. Recent games making their GDQ debut include Don’t Stop, Girlypop!, Super Meat Boy 3D, Pragmata, Resident Evil: Requiem, Unbeatable, Mouse: PI for Hire and Saros.
I’m interested to check out a pinball showcase with Total Nuclear Annihilation as well as the Gordon & Daxter run. This is a modded version of Jak & Daxter in which you play as Gordon Freeman with Half-Life weapons and movement. I always love it when there’s a Super Mario Maker 2 race on the schedule, so I’m looking forward to that too.
As always, SGDQ is raising money for Doctors Without Borders. Last year’s edition raised over $2.4 million for the cause.
