Foundation Capital @FoundationCap

Introducing Kombai 2.0 - the first AI design engineer. We keep hearing that AGI is almost here. Still, we’re stuck with coding agents that don’t have taste and design tools that don’t understand our codebase. Both are artifacts of a world where design and engineering were two different jobs, with a handoff in between. That world is changing fast. Today, designers ship code, engineers want to escape handoffs, and everyone wants to build tasteful UX. Kombai is built for this new world. Design and engineering, finally on the same side.

.@Solana is cementing its next phase of blockchain distribution by investing in verticalization and challenging traditional mobile players. With a decentralized app store and hardware designed to run on the Solana network, it’s positioned to reach users in ways that no other crypto network has before. FC partner @alemartcard interviewed @toly, co-founder and CEO of @Solana, at Accelerate 2026 a couple of weeks ago. Watch our full interview here to learn more about his journey as a founder, what went into building Solana, and what's next for the platform: youtube.com/watch?v=UW8qaI…

Congratulations to our General Partner @vassallo on being named to this year’s @Forbes Midas List! This recognition reflects the extraordinary founders Steve has had the privilege to back and build alongside. We’re proud to celebrate him, and even prouder to stand beside the founders who make Foundation Capital possible. forbes.com/profile/steve-…

Proud to be on this year’s Forbes Midas List 100. But the list isn't really measuring what people think it's measuring. - It measures @andrewdfeldman , building wafer-scale silicon when the industry said it couldn't be done. - It measures @toly, betting on a new way to build blockchains. - It measures Pierre-Damien Vaujour and Alex Greenberg, going all-in on satellite buses before they had clarity on the future. - It measures Lynn Jurich and Edward Fenster, rebuilding Sunrun overnight when the 2008 GFC broke the model. These are the people who move the world from what is to what ought to be. And I feel lucky to play a supporting role. I love what I do and I love who I get to do it with too.

For the past few years, the story about AI and design has been a story about loss - of creativity, control, and craft. Our new research with @designerfund suggests the opposite is happening. We just published AI in Design 2026, our second annual report together, and the headline finding is that designers are doing more, owning more, and shipping more than they did a year ago. A few data points stood out. 91% of designers now use AI weekly, up from 53% a year ago. The designer-engineer is no longer an oxymoron: half the designers we surveyed have pushed frontend or backend code, and 20% now call themselves "design engineers." And as the lines between design, engineering, and product blur, designers are increasingly the ones holding the vision and the quality bar across the entire build. The full report draws on a survey of 900+ designers across 60+ countries and offers a look inside how design teams at our portfolio companies @Framer and @Stripe, as well as teams at @AnthropicAI, @Linear, @NotionHQ, @Shopify, and @SierraPlatform, are working with AI. We distilled the findings that stood out to us most on our Ideas page: foundationcapital.com/ideas/how-ai-i…

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“What you are responsible for as a designer is shifting and changing. But that does not mean that we need fewer designers. We need more designers, and they need to do things differently than they did. If we evolve, we should be a very key part of building software for the next 10, 15 years.” — @benblumenrose We’re in @FastCompany! Check out this feature on the AI in Design report we did with @designerfund, which details how AI is changing design in tech, for the second year in a row: fastcompany.com/91543989/ai-in…

X says design is dead. The data says otherwise. In partnership with @designerfund, we surveyed 900 designers in tech and interviewed design leaders at companies like @AnthropicAI, @stripe, @linear, and more. Here's what we found. Designers are doing more, owning more, and shipping more than they were a year ago. Half of all designers - ICs, founders, and design leaders - have shipped AI-generated code to production. The question is no longer should designers code. It is when and how. Designers who have leaned into AI are 2x more likely to feel creative, confident, and capable. The bar is higher and those who are experimenting are the ones clearing it. The AI toolkit more than doubled in a year. Designers used 3 AI tools in 2025. They are using 7 now and some are even building their own. Inside the report you’ll find: - The top 7 AI tools designers are using in 2026 - The 2 new skills design leaders are screening for this year - How to build a culture that makes designers 2x as creative and capable Huge thanks to @benblumenrose, @robynxpark and the Designer Fund team for driving this. Read the full report below.

The 2026 State of AI in Design is out today! stateofaidesign.com In partnership with @designerfund , we surveyed 900 designers in tech and interviewed design leaders at companies like @AnthropicAI, @Stripe, @Linear, and more. Here’s what we found: ➡️ Code is getting democratized. More than 50% of surveyed designers have shipped AI-generated code to production. ➡️ The human is still in the loop. 80% of designers say human judgment remains essential for creative direction and quality decisions. ➡️ Product-building roles are blurring. 65% of designers now manage more PM and engineering tasks along with design. Check out the report to learn more about: 🔧 The most popular AI tools in the designer’s stack 🏗️ How the best AI-native companies structure their design teams ✨ The company culture trait that appears alongside the most creative and capable designers

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AI in Design 2026 is out today. Our second annual report explores how design tools, craft, and teams are evolving in the age of AI. Built from 900+ survey responses across 60 countries, 25+ in-depth interviews, and case studies coming soon. See it here: stateofaidesign.com

Our 2026 Design in AI Report is now live! This report is the culmination of thousands of people hours and many late nights to create what we believe is the most comprehensive, well-researched report capturing and synthesizing the state of Design + AI today. While we used AI in many areas, a report like this still required deep thinking, grit, and humans coming together to do what they do best. The final report spans nearly 20k words covering the survey results of over 900 people paired with dozens of qualitative interviews. Over the coming months we will also release 7 beautiful case studies showing how top design teams are working on the ground featuring designers at @AnthropicAI, @framer, @linear, @NotionHQ, @Shopify, @SierraPlatform, and @stripe. This work is a true labor of love to help guide a design community we hold so dear. Link in the comments and please let us know what you think. Your feedback helps us shape how we will evolve this work over the coming years...

One week ago, @toly kicked off Accelerate USA in Miami 🇺🇸

.@cerebras just had the biggest tech IPO since 2020. And the reason goes far beyond market momentum. Our ability to run inference on the world’s largest AI models at unmatched speed is at the core of our value. This includes trillion-parameter models and beyond. The smartest models have always been bigger, and the future of AI won’t be defined by who can stack the most GPUs. It will be defined by who can deliver real-time intelligence at scale. Our CFO @BobKomin spoke with @dee_bosa on @CNBC on the day of our IPO on this topic.

Deirdre Bosa @dee_bosa

4 weeks ago

"One of the biggest misconceptions" Cerebras CFO @BobKomin pushes back on the small-models narrative. "We serve all models, and there is no limit to the size of the models that we can serve. Today, we're serving trillion parameter models. We're serving trillion parameter

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In April 2016, I threatened to climb over @andrewdfeldman's fence to give him his first term sheet for @cerebras. It was April Fool’s day, but I wasn’t fooling around. The story started in October 2007, when Andrew and his co-founder Gary Lauterbach had just started SeaMicro. Even then, Andrew was a force of nature. He was extremely intense and miswired in all the right ways. You could feel the sparks flying off him. We didn't invest in SeaMicro, but we stayed in touch. Andrew and the team built SeaMicro then sold it to AMD in 2012. When AMD acquired SeaMicro, I had a hunch Andrew wouldn't last long inside a big company. He has, as I've said many times, immense ambition and a heart full of disobedience. By early 2014, he was looking for an escape hatch. Over the next year and a half, Andrew and I met 6 or 7 times. Sometimes in our office. Sometimes at a coffee shop in Portola Valley. Sometimes at our local tennis and swim club. We kept coming back to one thing: deep learning workloads were growing exponentially, and traditional compute architectures couldn't keep up. GPUs had become the default for neural network training, mainly because researchers had accidentally discovered they were less terrible than CPUs. Andrew, Gary and Sean saw the GPU for what it was: a battlefield promotion of a chip optimized for graphics. Better than a CPU, but not what anyone would design starting from a blank sheet of paper. Their key insight was that memory bandwidth, not raw compute, was the real constraint on what neural networks could achieve. So Andrew, Sean Lie, Gary Lauterbach, Jean-Philippe Fricker and Michael James set out to do something nobody had pulled off in the 75-year history of semiconductors: Build a wafer-scale chip the size of a dinner plate. In April 2016, I asked Andrew if we could be his first term sheet. @ericvishria at Benchmark and I co-led the round along with Pierre Lamond from Eclipse. Then the hard work began. In the 75-year history of computing, no one had made wafer scale work. Which meant no one had ever had to solve the problems that came from trying. How do you power a chip that large? How do you cool one? How do you maintain electrical continuity across tens of thousands of connection points on a single piece of silicon? To get there, Cerebras had to invent in nearly every modern computing discipline at once: semiconductors, systems, data fabric, software, algorithms. Each was a startup in its own right. Their first wafer self-destructed on initial power-up and Andrew and the team were back in the lab the next morning, identifying what didn’t work and coming up with approaches to solving it. Yesterday, Cerebras went public. 19 years after our first meeting, 10 years after that April Fool's term sheet, they’ve built a generational AI company. From a coffee shop in Portola Valley to ringing the bell at the NASDAQ. What a journey. Proud to have been Andrew's first partner in Cerebras. Even prouder to call him my friend.

Get a partner that looks at you the way @vassallo and @FoundationCap looks at @cerebras. Huge congrats on an amazing IPO. All the hard work and relentless pursuit of a bold vision is so inspiring to see. Let’s go!

Steve Vassallo @vassallo

4 weeks ago

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Today, @Cerebras rang the bell at NASDAQ. We wrote their first term sheet in 2016, when our partner @vassallo led Foundation's investment in @andrewdfeldman and his co-founders Sean Lie, Gary Lauterbach, Michael James, and JP Fricker. To get to wafer scale, Cerebras had to invent new approaches to nearly every facet of modern computing at once: semiconductors, systems, data fabric, software, and algorithms. Each was a startup in its own right. Realizing this mission took ten years of relentless engineering. Congratulations to Andrew and the entire Cerebras team! More from Steve on a decade with Cerebras: foundationcapital.com/ideas/reinvent…

We’re excited to share that our portfolio company @IkigaiInc has been acquired by @Celonis! A big congratulations to co-founders Devavrat Shah and Vinayak Ramesh, and the rest of the Ikigai team. When we led Ikigai’s seed in 2021, we saw a team that had built an incredible technology, but that also had a great commercial sense for how to apply it. Ikigai’s Large Graphical Models (LGMs) are purpose-built foundational models that work with structured and tabular data. They help enterprise forecasting teams make predictions for everything from product distribution to supply chain management. Now, paired with Celonis’s deep customer relationships and process intelligence platform, we have all the ingredients to see our context graph thesis come to life—and the companies that control the context layer will define the next generation of enterprise software. Ashu Garg shares more on our blog: foundationcapital.com/ideas/context-…

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