Doug Pepper

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.

We just crossed $500M ARR and welcomed new investors to @ElevenLabs: BlackRock, Wellington, Nvidia, Santander, Jamie Foxx, Eva Longoria and more. Natural, human-like communication will be critical to broad AI adoption - and these new investors help us accelerate that work.

Big news: Hightouch has raised $150M at a $2.75B valuation, led by @GoldmanSachs and @BainCapVC. We’re dreaming big for this next chapter of Hightouch. Learn more about our not-so-secret plan to reinvent marketing with agentic AI: hightouch.com/blog/hightouch…

Uncommon founders build uncommon companies. We're honored to partner with the ones defining the AI era. Thank you to @matiii and @MaxJunestrand for sharing your perspectives and @nmasc_ and @Bloomberg @technology for helping tell our story. Read more: bloomberg.com/news/articles/… Disclaimer: bit.ly/4tSG5Ev

Hightouch reaches $100M ARR fueled by marketing tools powered by AI techcrunch.com/2026/04/15/hig…

Congratulations to @may_habib on being named to @Inc.'s Female Founders list — for the third consecutive year. When we first partnered with @Get_Writer in 2023, the AI market was still oriented around consumer chat. ICONIQ Partner @sruthiramaswami put it plainly: “In 2023, the market landscape was really consumer-oriented, chat-based platforms. ChatGPT, Claude, Copilot for Microsoft—no one was thinking about transforming how content generation and analysis were happening at the enterprise level.”