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“No man steps into the same river twice. It is not the same river, and it is not the same man,” @SycamoreLabs founder @SriViswan shares. “It also applies to Sycamore. No Sycamore software runs twice in the same enterprise, for it is not the same software.” Enterprise software is outdated. Sycamore is building AI-powered systems to make companies autonomous using a dynamic agentic AI operating system that constantly improves itself. “Every time our agent runs in an enterprise, it updates itself and gets better.” From The Investment Memo, with @ravirajjain.

Some of the best founders take unconventional career journeys. @SriViswan is no exception. His diverse and extensive career experience led him to build @SycamoreLabs, an operating system for enterprise AI agents. We recently co-led his $65M seed raise alongside @coatuemgmt and

"In the morning we decide what needs to be built. Every person has up to five or seven agents working with them. By evening we set it all up so that when we're sleeping, the agents do the work." @SriViswan (Founder and CEO of Sycamore Labs), on what building software at "machine speed" looks like: "Our productivity is measured by how we can unlock agents. Every day we come in and say: what can we do today so we can unleash the agents to do better, faster, cheaper?" "We're a 24/7 company. Not for humans, but for agents." From The Investment Memo with @ravirajjain

“No man steps into the same river twice. It is not the same river, and it is not the same man,” @SycamoreLabs founder @SriViswan shares. “It also applies to Sycamore. No Sycamore software runs twice in the same enterprise, for it is not the same software.” Enterprise software is outdated. Sycamore is building AI-powered systems to make companies autonomous using a dynamic agentic AI operating system that constantly improves itself. “Every time our agent runs in an enterprise, it updates itself and gets better.” From The Investment Memo, with @ravirajjain.

Some of the best founders take unconventional career journeys. @SriViswan is no exception. His diverse and extensive career experience led him to build @SycamoreLabs, an operating system for enterprise AI agents. We recently co-led his $65M seed raise alongside @coatuemgmt and had the pleasure of talking with him on our latest episode of The Investment Memo. Sri and Lightspeed Partner @ravirajjain discussed the current market gap for enterprise AI software and how Sycamore differentiates. Check out the video below to hear more. 0:00 Introduction to The Investment Memo 3:44 Reflections on Enterprise Software Challenges 5:50 The Current Enterprise Software Landscape 8:07 Enterprise Requirements: Security, Trust, and Compliance 12:15 Sycamore’s Agent Operating System and How Software Improves Itself 14:07 The Market Opportunity for Sycamore Labs 17:02 Building at Machine Speed: Sycamore's Development Process 20:52 From Two-Week Sprints to Daily Cycles 25:52 Why Lightspeed as an Investment Partner 27:29 $65M Raise and Future Milestones 28:47 Closing Remarks

Great companies are built from great products. Unforgettable companies are forged from long-standing relationships. Excited to share that we are leading the Seed round for @SycamoreLabs, founded by @SriViswan, alongside @coatuemgmt. After 15 years of history, we are excited to back Sri at this pivotal time. Enterprise software is overdue for a change, and Sycamore is building an AI-powered system to transform traditional SaaS tools. If the last era of enterprise optimized for systems, this one optimizes for intelligence. We are looking forward to this new chapter.

What if AI could design the chips that power the next generation of AI? That’s the vision behind @RicursiveAI, an AI-driven semiconductor design platform that uses reinforcement learning to compress the chip development process from years to weeks. We led their $300M Series A in January, and Co-Founders @annadgoldie and @Azaliamirh went in-depth about Ricursive and the future of AI-driven chip design in this episode of The Investment Memo with Lightspeed partner @guruchahal. 0:00 Welcome, Anna Goldie and Azalia Mirhoseini! 3:10 How the Idea for AI Chip Design Started 4:58 How They Expanded From Software to Chip Design 5:27 Turning the Idea Into a Google Moonshot 7:20 When Google Leadership Realized the Potential 10:35 Why Physical Design Is the Hardest Part of Chip Design 13:51 The 3-Phase Vision for the Future of Chip Design 17:51 Market Opportunity & Industry Disruption 20:24 The “Designless” Future of Hardware 22:04 Speed, Innovation & AI-Driven Exploration 21:00 The Role of Engineers in an AI-Driven Future 24:22 The Founders’ Unique Partnership Story 25:44 How They Hire World-Class Talent 27:05 Choosing the Right Investors 30:42 Advice for AI Researchers & Founders 33:16 What’s Most Important in the Next 12 months?

.@Doctronic Co-Founder Dr. Adam Oskowitz on why AI-native care is coming faster than most expect: “70–80% of medicine is algorithmic or guideline-based.” “There is a fundamental math problem with medicine. We will never have enough supply of doctors to meet the demands of patients.” “A lot of this can be done with AI. The question is how fast we get there.” From The Investment Memo

“What happens when the doctor and the AI disagree?” Dr. Adam Oskowitz of @Doctronic: “If you took two doctors and had them see a patient, they oftentimes disagree.” “What you really want to evaluate is whether either is doing something unsafe or not following clinical guidelines.” “That’s how we approach it.” “We’ve found that AIs tend to follow the guidelines better than humans.” - The Investment Memo

“Most people don’t know how to reach out and touch the healthcare system when they have a problem” - @doctronic Co-Founder Dr. Adam Oskowitz Adam and Co-Founder @mattpavelle joined Lightspeed Partners @f_fatemi21 and Brenton Fargnoli, M.D. on The Investment Memo this week to

Bucky Moore on what makes an AI application company actually defensible — and why the Palantir FDE playbook becomes increasingly important. "There are some industries where they're very large, far enough afield from where the model providers are today, and the context engineering to actually get the customer data into the model is just so messy." "Being really good at that is not only defensible, it allows you to generate a feedback loop where you hear a lot of their secrets. And those secrets allow you to make your product better at the expense of anyone else in the space. Because if you're serving the customer, they're only serving you those secrets." "Palantir is a good example of this in the pre-AI era, and I think we're going to see many companies ascend in that same way." @buckymoore on @tbpn

Bucky Moore on why inference is the most underrated market in AI: "Inference, if you look at it as a market, will be much bigger than cloud computing was pre-ChatGPT." "There will be an inference platform for real-time video models. There will be an inference platform for open-source and custom language models. There will be an inference platform built specifically for long-running agents." "We're just going to see that industry, which today looks like one industry, break up into many because of how big it is and how much room there is for specialization." @buckymoore on @tbpn

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