Foundation Capital

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Foundation Capital

Foundation Capital

@FoundationCap

For 30 years, we've backed extraordinary founders from day zero.

Palo Alto, CA Beigetreten Ağustos 2009
56 Folgt16K Follower
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Designer Fund
Designer Fund@designerfund·
Based in Austin or heading there for SXSW? We're hosting a happy hour on Saturday, March 14 alongside @framer and @foundationcap. Designers, product leaders, founders - we'd love to see you there. Space is limited. Apply to attend: luma.com/mrx7m3q5
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Steve Vassallo
Steve Vassallo@vassallo·
10 years ago, I backed @andrewdfeldman before there was a company. Now, he is defining the future of AI. I first met Andrew in 2009 when he was building SeaMicro. Even back then, he stood out. He was a force of nature. Extremely intense. Deeply technical. A builder in the purest sense. You could feel the sparks flying off him. After Andrew joined AMD, we stayed in touch. Over the next year or so, we met 6-7 times. Sometimes in our office. Sometimes at a coffee shop in Portola Valley. Sometimes at our local tennis and swim club. We were talking, riffing on ideas and exploring what might be interesting or broken. Conversation after conversation, we kept coming back to one thing: deep learning workloads were growing exponentially and traditional compute architectures and data center models were buckling under that pressure. By the time Andrew and his all-star co-founders Sean Lie, Gary Lauterbach, Jean-Philippe Fricker and Michael James were ready to go all-in, we already had a deep belief in them. In fact, I asked Andrew if we could be his first term sheet. Shortly after our investment, @ericvishria from Benchmark, our co-lead in Cerebras’ first round joked with me “you did 2 years of work on Cerebras, I did 4 days.” A testament to Eric’s conviction in the opportunity. Fast forward 10 years and it has been an unbelievable journey. I’m both incredibly proud to have been the first partner in Cerebras and to call Andrew my friend. Watching the team overcome adversity after adversity to shape the most impactful technology of our lifetime has been a defining part of my last decade. And I still can’t wait for everything that is still to come. Keep at it my friend.
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Steve Vassallo
Steve Vassallo@vassallo·
@cerebras is now a generational AI company. But between 2018 and 2019, one tiny component nearly killed the company. Back then we were deep into building the first wafer-scale system. Everything depended on a single part most people will never notice. The interposer. It sits between the main board and the dinner-plate-sized silicon wafer. It has to carry enormous power and data loads while having to survive massive thermal cycling. Cold to hot. Off to fully lit. Over and over again. We had just built the largest chip in the world. There was no existing supply chain for it so we had to single source this part. That alone is terrifying. One vendor, no backup. If it failed, the system failed. If the system failed, the company could have failed. For almost three years, this thing was the boogeyman in every board meeting. Would it maintain electrical continuity? Would it warp under load? Would it survive burn-in? Would it work at scale? For long stretches, the honest answer was “we don’t know.” We were burning millions of dollars per month. Time was not our friend. A redesign could have pushed us far enough back that the market might have moved on. At one point, we pulled in a group that I first worked with at IDEO and that used to be called "Failure Analysis". That is not who you call when things are going well! We went back to first principles. Physics. Materials science. Coefficients of thermal expansion. Power dissipation per square millimeter. Analyzing what happens when you push this much power through a system at these temperatures. Again and again. Slowly, painfully, we got there. Finally the interposer worked. Every company pushing the frontier runs into problems like this. There are rarely quick, clever fixes. You just have to do real failure analysis, over and over, until the answer starts to reveal itself. The Cerebras team is itself built from the strongest, toughest material I’ve seen. They earned every inch of the other side of that problem.
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ashu garg
ashu garg@ashugarg·
After @JayaGup10 and I published our context graphs p.o.v., the question we heard most was how do you actually build one? @akoratana wrote one of the most insightful answers I've seen. His core insight: you don't prescribe the schema upfront. You let agents discover it through use. When an agent investigates an incident or completes a task, it traverses your company's systems. That trajectory is a decision trace. Accumulate enough of them, and a map of how your organization actually operates emerges. "The schema isn't the starting point. It's the output.” This is also why startups have an edge. Agents can live in the execution path in a way traditional software can't - they’re present at decision time and can capture traces as a byproduct of work. Incumbents would have to retrofit this into workflows they don't control. It's been a month since we published the original piece. I wrote up what we've learned: what resonated, where we got pushback, and the questions we’re still working through: foundationcapital.com/context-graphs…
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YO
YO@yield·
Introducing $YO, the governance token powering the yield engine for crypto. Discover how $YO holders can shape the future of onchain yield 🧵⤵️
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The Information
The Information@theinformation·
Today on TITV: -Netflix ad revenue & where Warner Bros. Deal goes from here | @RichLightShed, Co-founder of LightShed Partners -Former OpenAI sales exec talks ads, sales tactics | @aliisarosenthal, General Partner at Acrew Capital -Venture capitalists and founders are buzzing about how to turbocharge AI agents | @ashugarg & @JayaGup10, Foundation Capital -Data center inflation is here | @kenbrown12, Finance Editor
The Information@theinformation

The Information | TITV | January 21, 2026 x.com/i/broadcasts/1…

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Steve Vassallo
Steve Vassallo@vassallo·
When the thing you wish existed, doesn’t, you build it. That’s exactly what @andrewdfeldman, Sean Lie, and the @Cerebras team set out to do a decade ago. They bet on wafer-scale computing when almost everyone thought it was a dead end. Despite every major semiconductor company trying. No one had ever successfully yielded a wafer-scale chip in the 75-year history of the industry. Cerebras did it in 18 months. What followed was even harder. Packaging, powering, cooling, and writing the software to support wafer-scale systems had never been done before. There were no vendors, no suppliers, and no roadmap. They carved the path. That is true invention. And there’s something incredibly inspiring about doing something that wouldn't exist if you weren't doing it. That’s exactly the ethos of Cerebras. It's been a decade in the making and we’re just getting started.
Andrew Feldman@andrewdfeldman

@OpenAI and @Cerebras have signed a multi-year agreement to deploy 750 megawatts of Cerebras wafer-scale systems to serve OpenAI customers. This has been a decade in the making. Deployment begins in early 2026, and when fully rolled out, it will be the largest high-speed AI inference deployment in the world. OpenAI and Cerebras were both founded in 2015 with radically ambitious goals. OpenAI set out to build the software that would push AI toward general intelligence. Cerebras set out to rethink computing hardware from first principles. Our teams met as far back as 2017. We shared ideas, early work, and a common belief: there would come a point when model scale and hardware architecture would have to converge. That point has arrived. ChatGPT set the direction for the entire industry. It showed the world what AI could be. Now we’re in the next phase - not proving capability, but delivering it at global scale. The history of technology is clear on one thing: speed drives adoption. The PC industry didn’t operate at kilohertz. The internet didn’t change the world on dial-up. AI is no different. As models grow more capable, speed becomes the bottleneck. Slow systems limit what users can do, how often they engage, and whether AI becomes infrastructure or remains a novelty. Cerebras was built for this moment. By keeping computation and memory on a single wafer-scale processor, we eliminate the data-movement penalties that dominate GPU systems. The result is up to 15× faster inference, without sacrificing model size or accuracy. That speed changes product design, user behavior, and ultimately productivity. For consumers, it means AI that feels instantaneous. For the economy, it means agents that can finally drive serious productivity growth. For Cerebras, 2026 will be a defining year. With this collaboration with OpenAI, Cerebras’ wafer-scale technology will reach hundreds of millions - and eventually billions - of users. We’re proud to work alongside OpenAI to bring fast, frontier AI to people around the world. This is what a decade of long-term thinking looks like.

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ashu garg
ashu garg@ashugarg·
New B2BaCEO pod! I jam with @jaminball & @akoratana on why systems of record risk becoming commoditized backends, while the action & equity value moves to interfaces and context graphs that read your decision traces. Come debate with us!
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PlayerZero
PlayerZero@playerzero_ai·
We're excited to announce our partnership with @VirtusaCorp. Virtusa will deploy PlayerZero's AI production engineers across enterprise clients and private equity portfolio companies worldwide, bringing autonomous agents capable of operating production software in support, QA, and modernization. Engineering teams today are stuck in reactive mode, firefighting tickets and incidents while institutional knowledge stays trapped in the heads of a few senior engineers. Our partnership helps change that. PlayerZero brings AI production engineers powered by the Production World Model, a context graph that captures how people, process, and technology work together. Virtusa brings global delivery scale, governance, and deep vertical expertise to help enterprises bootstrap and scale that model. This is about making institutional knowledge durable and scalable. Read more about what we're building together: playerzero.ai/resources/play…
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ashu garg
ashu garg@ashugarg·
It’s just the beginning
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Aparna Dhinakaran
Aparna Dhinakaran@aparnadhinak·
I think @JayaGup10 at @FoundationCap nailed a trend that we're also seeing across thousands of deployed agents: retaining *why* your agents took action is as important as recording what they did. We wrote a blog post about it: arize.com/blog/how-conte… but some quick thoughts in 🧵:
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