Sung Lee

We’re thrilled to back Anil Varanasi and the Meter team as they take on one of the most overlooked bottlenecks in modern business: enterprise networking. For too long, IT teams have been burdened by fragmented systems, unpredictable costs, and outdated infrastructure. Meter’s vertically integrated, Network-as-a-Service model changes that—bringing simplicity, predictability, and intelligence to a space that desperately needs it. This isn’t just about better networks; it’s about laying the groundwork for autonomous, AI-optimized infrastructure. Proud to support this exceptional team alongside General Catalyst, Microsoft, Sequoia Capital, J.P. Morgan, and Tishman Speyer . Read more about why we invested here: https://lnkd.in/erhYMDxz.

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Cohu’s stronger than expected Q3 results driven by recurring revenue growth might look like a small headline, but it actually reflects a deeper shift in how the semiconductor industry is evolving. For years, equipment firms lived with sharp cycles of boom and bust. Now companies like Cohu are finding a way to smooth those cycles through software, services, and predictive maintenance that generate steady income even when capex slows. From an investor’s view, this is what structural maturity looks like. The real value is no longer in one time tool sales, but in building long term relationships that monetize uptime, calibration, and optimization. It is the same approach that turned industrial automation companies into reliable cash flow engines. For a sector long addicted to volatility, this move toward recurring revenue feels both strategic and stabilizing. Still, there is a question worth asking. As more semiconductor equipment players turn to subscription and analytics based models, will it make the industry more resilient or more concentrated. Recurring revenue often rewards scale and data access. Smaller firms may struggle to replicate that level of integration, meaning stability for some could become dependency for others. Cohu’s results point to what the future of semiconductor equipment might look like, part hardware, part service, part data. It is a quiet transformation that could make this industry less cyclical, more predictable, and far more attractive for long term capital. Are we seeing true resilience take shape, or just another layer of control built through recurring revenue. #Semiconductors #CapitalEquipment #RecurringRevenue #AdvancedManufacturing #StrategicInvesting #TechnologyLeadership #InnovationDebate

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Santa Barbara Venture Partners has raised a $25M second fund to invest into software and AI, as covered in The Wall Street Journal Pro, Axios Pro Rata, and here in Pacific Coast Business Times. Fund II builds on the success of six successful exits (full and partial) in five years, Fund I’s top quartile performance, and a major competitive advantage in offering extensive customer acquisition and marketing expertise to SBVP portfolio companies. Fund II extends the firm’s unique strategy of generating continuous returns for investors in an asset class otherwise plagued by illiquidity challenges. Five years in, all fourteen SBVP portfolio companies are performing well. SBVP generally invests in companies with $2M to $50M in recurring revenue which are growing 75-200%+ that have outstanding client retention metrics. The firm typically participates in Series A through C rounds, or SBVP buys stock directly from existing founders or other shareholders. Many of SBVP’s 150+ fund investors (from across two funds and fourteen SPVs) are top marketing and sales executives from leading tech firms. They provide the portfolio with expertise in over 25 different marketing and customer acquisition channels and methods to accelerate revenue growth. Limited Partners include leaders from Adobe, Google, Procore Technologies, AppFolio, Snowflake, Salesforce, Zoom, RingCentral, CBS, Pinterest, and various other top firms. LPs work with portfolio companies on demand generation, sales, and marketing, and accelerate product marketing, revops, audio/TV marketing, content, social media, SEM, media buying, account-based marketing, customer success, sales enablement, branding, strategic alliances, trade show marketing, and other areas. https://lnkd.in/gkwaxivz

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3 weeks in the Bay Area!! Inspiring conversations with multiple amazing founders, operators, investors, and old friends. As the saying goes, “The future is already here—it’s just unevenly distributed.” As an early-stage VC (and an eternal optimist), here are a few musings that stood out (including obvious ones also!) :) 1. HALO assets (Hard Asset, Low Obsolescence) are having a moment in this AI wave. 2. Compute constraints are real — capacity looks tight through 2027/28. 3. Storage/memory remains undersupplied (next 2 years atleast)… but important reminder that every boom in memory/storage has eventually led to overbuild and a bust cycle  4. Physical AI & robotics are here to stay and seeing massive tailwinds — movement from bits to atoms (physical). 5. Consumer is out of favor (for now) — lack of conviction around $10B outcomes which is tablestakes outcome for valley funds. 6. The Valley funds radical, not incremental — humanoids, hardtech, frontier bets, moonshot application ideas are the norm. 7. Cybersecurity feels like it’s in a “Mythos phase” — signal vs noise still unclear. 8. Enterprise AI demand is vertical — but need to monitor real ARR vs experimental ARR /spends driven by top down board diktats for AI adoption. Upward direction of travel for enterprise is for real though. Also change management in large enterprises for AI transformational projects will not be trivial. Indian IT svcs could reinvent and play in this realm 9. Pure Software faces long-term decay questions — not overnight disruption, but underwriting terminal value and long term free cash flows is getting harder as models keep getting better. 10. SMBs could be massive beneficiaries of intelligence becoming democratized and ubiquitous. "One and done" rounds could be an option for smaller funds to consider and back 11. N=1 personalization could drive the next wave of stickiness in AI products. 12. Serendipity compounds in dense ecosystems — the Bay still has that magic given talent and idea density. 13. India has a shot at leading the Global South in frugal AI innovation—but will need to compete head-on with China. 14. Expect real scientific breakthroughs (drug discovery etc) in the next 12–24 months — frontier models are compressing research cycles dramatically. 15. Jevons paradox may counter the deflationary narrative. era of abundance potentially approaching! 16. Investment alpha = moving from non-consensus → next consensus. 17. Expect enterprise headcount reallocation — from back office to front office (more FDEs, more consultative sales). Net takeaway: I remain optimistic. Humans adapt. We always have. Expect volatility, false starts, and hype cycles. Important to separate signal from noise. Personal reminder: Stay curious. Keep learning. Work hard. Expand the surface area for luck—and let serendipity do its thing :) Photo: Back at the Goldman Sachs building—where I spent time during 2006–2008. Next stop: New York. Can’t wait 😊 #AI #startupinvesting #deeptech

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One of the most fun things I get to do at General Catalyst is work with Karthik Vellanki, who is reimagining the way that CPG works, from pet supplements (yes, you read that right) to hygiene products. Impressive real world analog to the Anthropic vending machine story (links in comment): What happens when you let AI run a brand? cc: Yuri Sagalov Neeraj Arora

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The Operator’s Edge – Part IX From Entry to Exit: Why Operator’s MOIC Is the New Standard for Realization By George Konstantopoulos | PE Operatinghttps://lnkd.in/gaXnizQj

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This is an exciting, landmark initiative. Financing and venture-scaling expertise are recognized as constraints for the growth of deep-tech enterprises from India. To address this gap, the Indian Deep Tech Investment Alliance (IDTA), convened by Celesta Capital and other prominent investors, brings U.S. and Indian venture capital firms together to commit their expertise and over $1 billion of capital to start-ups in critical and emerging technologies. The IDTA welcomes similarly committed venture firms and corporations to join in this initiative. Please read the details in the below post.

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On behalf of Titanium Innovation Investments, my Partner Abhinav Jain and me are proud to announce our latest investment in ProcessMiner Inc. With the growing demand for ROI-centric, AI-driven solutions in the Physical industries, we strongly believe that ProcessMiner is well positioned to capitalize on this opportunity. The company’s focus on serving critical infrastructure / continuous manufacturing end-markets such as Paper & Pulp, Food & Beverage, Wastewater Treatment etc. aligns well with our Industrial Technology Fund’s investment mandates. We are very excited to be leading ProcessMiner’s first ever funding round and partnering / working together with Karim Pourak, Kamran Paynabar, Tom Morris and the rest of the remarkable team at ProcessMiner. https://lnkd.in/gw2zhFvV

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Intel received $20 billion in government subsidies and customer prepayments this year but still posted a net loss, revealing that capital intensity alone cannot solve foundry economics. The mechanism is structural: foundries require both massive upfront investment and sustained utilization to generate returns. Government funding covers the capital expenditure but cannot guarantee the customer demand needed to fill those fabs. Without consistent throughput, each additional dollar of capacity investment actually worsens unit economics because fixed costs get spread across fewer chips produced. This creates a paradox where Intel's $100 billion fab buildout could become either a competitive moat or a structural burden, depending entirely on whether the company can secure long-term customer commitments. The subsidies buy Intel time and capacity, but they don't solve the fundamental challenge of competing against TSMC for external customers while simultaneously serving internal chip design needs. The critical question isn't whether Intel can build advanced fabs—the funding ensures they can. The question is whether their foundry business model can generate sufficient utilization rates to justify the economics of operating those fabs at scale, especially when competing against an incumbent with established customer relationships and proven execution. Link in comments 👇

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🦄 $150M to improve tutoring and education globally. Preply just announced a new round, putting the company on a clear trajectory to become an iconic global marketplace. In a world obsessed with fast wins and volatile growth, some companies quietly beat their goals year after year — for more than 6 years in this case (as long as we’ve at Acurio Ventures been partners). A few learnings from this journey, relevant for founders and investors: Pick a growing market with an unsolved problem. 2 out of 8 billion people globally are learning a second language. Despite many options, outcomes are still poor. Our original thesis was simple: if you build the reference platform, everyone who wants to learn will eventually come to you. Category leadership matters. When we backed Kirill Bigai and Dmytro Voloshyn back in 2019 (together with Rob Kniaz), there were dozens of similar startups. Small details showed Preply had already built a superior tutor base and a scalable growth engine. Build a product customers love. Speaking a language and teaching it are very different things. Preply transformed the learning experience by combining a motivated base of +100,000 tutors with tools that actually drive outcomes. Never stop experimenting. Few companies maintain a strong experimentation culture as they scale. Preply’s DNA reminded me of Booking.com — enabling them to execute 10x better than most marketplaces. Great companies turn every change into an opportunity. From riding the post-COVID shift to online learning, to betting early and heavily on AI as Dmytro Voloshyn has excelled at. What once sounded like sci-fi is now reality. Great companies become talent magnets A company maturity can't be addressed only by looking at the revenue, profit or product. I like to see how much better they become at attracting talent and retaining it. Proud that Acurio Ventures made this possible and the WestCap team saw things as bullish as we do and are now supporting the next phase of Preply’s journey. Huge congratulations to the entire Preply team!!

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Addepar continues to demonstrate that the real advantage ahead lies in platforms that unify data, insight, and action. Eric’s session at Sway Minds highlighted why it became one of Sway Ventures’ early investments, and why so many of our LPs use it as their system of record.

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San Diego-based Manifold (AI Detection and Response platform) has raised $8 million in seed funding; lead backer Costanoa Ventures, along with several institutional investors including Cherry Ventures, Rain Capital, Modern Technical Fund, and angel investors.

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At our recent LP Advisory Council meeting, LPs asked about headlines claiming AI is undermining SaaS. Our view is that the two are mutually reinforcing, not mutually exclusive. We are bullish on AI, and we believe certain SaaS leaders (with systems of record/action, first-party data and data rights, network effects, ambitious AI roadmaps, etc.) are well-positioned to capitalize on the agentic AI opportunity. There are multiple reasons for this. To start, consider what’s happening today with SaaS. The median company in the SEG SaaS Index grew 13% in Q2 while doubling its EBITDA margin year over year, with a top quartile growth rate above 20%. SaaS accounts for only 25% of overall software revenue in 2025, according to Gartner, so secular growth from on-premise to SaaS migrations should continue for years. Notably, this growth largely comes before many SaaS firms monetize a new wave of agents. Meanwhile, small AI startups with little revenue are burning cash and trying to sell. At the other end of the spectrum, Klarna’s much-hyped move to replace Salesforce with AI proved overstated; the CEO later said he was “tremendously embarrassed” by the fallout. SaaS pessimists might ask themselves: Has any large enterprise successfully replaced SaaS systems of record with an LLM? Rather than the AI-SaaS story being one of complete disruption, I believe it’s moving in waves, not unlike how businesses have historically incorporated new technologies:  ● Wave 1 (2023): “Get me some AI so we’re not left out” (a reprise of 1996’s “build a web page and we’ll figure it out later”). ● Wave 2 (2024-mid 2025): “Show me the budget and ROI. Also, why do we need an expensive AI model over a cheap one?” ● Wave 3 (late 2025): "I need enterprise-grade AI that integrates seamlessly, delivers measurable results and won’t disrupt core ops with experimental tools." We can’t say for sure what will happen next, but we do know how software brings value to the enterprise. SaaS is more than software code; it’s digital business intelligence using code to express that intelligence. That takes massive data sets and business experience brought to bear on enterprise functions, at scale and over time. It’s about executing tasks efficiently today, then innovating new tasks over time. For these reasons, we see a supercharged future of AI-enabled enterprise software that enhances productivity and innovation in dramatic ways. That future is less about ever-larger foundation models or narrow AI startups that complicate the stack. Instead, we see integrated software systems that orchestrate digital services to accelerate complex tasks, with agents as the 2026 step-function. AI is a massive force multiplier in that equation, but not a radical disruptor. At Thoma Bravo, we welcome the AI-SaaS conversation. We’re healthily paranoid as part of our mindset. But evidence, history, and business logic suggest that the AI revolution is set to accelerate SaaS value and growth, not undermine it.

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Thrilled to announce that Together Fund is investing in Sentra, alongside a16z speedrun! You track results in Jira. Decisions in Notion. Conversations in Slack. But the reasoning, the debates, trade-offs, and context behind why you chose A over B, disappears into what we call "Dark Matter." A decision made in March looks insane by July because no one remembers the constraints that made it smart. I lived this firsthand at Twitter scaling from 800 to 8,000 employees, and at Google while launching AI Overviews to billions at planet scale. The problem isn't process. Process is compensation for something deeper: organizational amnesia. An organization’s "Systems of Record" doesn’t solve this, they encode it. They store what happened, never why. That's why we are investing in Sentra. Sentra is the always-on collective memory that eliminates organizational amnesia by maintaining accurate context for all members and agents, functioning as an operational nervous system. It connects to every channel where work happens, meetings, Slack, email, code commits, docs, calendars, and treats them not as artifacts to search, but as living signals to synthesize. The fleeting and the permanent, unified into a memory that understands. The founding team is built for this: - Jae Gwan Park (CEO): Product-first founder, memory systems research at UofT and MIT - Ashwin Gopinath (CSO): Former MIT professor, created "Reflexion" (NeurIPS 2023), agents that learn from mistakes, 2x founder - Andrey Starenky (CTO): Early Vapi engineer, ex-IBM, built to process enterprise-scale data firehose Together is an operator-led fund. We invest in problems we've lived. This is one of them. Many congrats Jae, Ashwin and Andrey, we are so excited to partner with you! Read the full thesis: https://lnkd.in/gixj9cE4 Book a demo: https://www.sentra.app/ #OrganizationalMemory #AI #Sentra #TogetherFund #a16z #ContextGraphs

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🚨 BREAKING: 8090 Industries & Fidelis New Energy launch American Intelligence & Power Corporation, a Premier Energy & AI Infrastructure Platform, with Strategic Support from Sanjeev Mordani of LuminArx Capital. Read more below: https://lnkd.in/g3SDtNVS 💡 AI leadership is not a software problem. ⚡ It is an energy and infrastructure problem.  🇺🇸 The next chapter of American power will be written in electrons delivered, uptime guaranteed, and gigawatts built. For the last several years, a small, relentless group of infrastructure developers, engineers, operators, and builders responsible for some of North America’s largest energy infrastructure assets like the Alberta Power Line, Ørsted North America, Howard Energy Partners, WhiteWater have been working quietly on something most people said was IMPOSSIBLE: A purpose-built, sovereign, utility-grade AI power and compute platform. Today, that work has a name:  American Intelligence & Power Corporation 🚦 And it has a flagship site Monarch: America's First Legislatively Authorized Integrated AI Utility & Compute Campus authorized under West Virginia House Bill 2014 (HB2014) as its own islanded utility with special microgrid status This is a AI-scale microgrid and compute campus designed from first principles for intelligence workloads: – 2,380 acres – 8 GW of power generation enabled via land, license, gas supply and water – Extreme load-following capability for AI – Sovereign operational control – A blueprint designed to scale nationally The world is entering an era where compute is industrial, energy is geopolitical, and uptime is national security. Monarch is our opening move. Deep respect to the Fidelis team who spent years building this before it had a headline. Proud for 8090 Industries to be a founding strategic partner in forming AIP with Daniel Shapiro, Bengt Jarlsjo, Gardner Boulmay and team. And grateful to the state and federal leaders like Former Senator Joe Manchin and Governor Jim Morrisey who understood that if America wants to lead in AI, it must first lead in power. Stay tuned. We are just getting started. 🇺🇸⚡ 🦾 cc Kerem Ozmen Wes Mendenhall Grant Brown Brett Buchanan Sanjeev Menon Byron Best Pete Hollis Garuth A. Christie Allardyce Shilpa Patel Michael Jarlsjo, CPA Hannah Jarlsjo Jake Shapiro Sam Shapiro

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From our PearX S25 cohort, meet Pravāh, the AI-native operating system for the electric grid When Mohak Mangal, Dhruv Suri, and Aman Gupta looked at the strain on the U.S. electric grid, they saw a system pushed to its limits. Exploding demand and unpredictable supply have made blackouts increasingly common. This costs the economy more than $150B a year, a number that could 10x in the next five years. Mohak Mangal and team founded Pravāh to help fix it. Their platform helps utilities and grid operators make real-time decisions on load, generation, and congestion, reducing blackout risks, optimizing power procurement, and bringing much-needed stability to the backbone of modern life. We’re proud to support the Pravāh team as they take on one of the toughest and most important infrastructure challenges of our time.

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I’m lucky to work alongside colleagues like Richard Fruehauf, who constantly push my thinking. His latest piece unpacks why U.S. robotics and drone manufacturing faces uphill economics, and how public policy can help turn the tide. One key takeaway: 232 tariffs on robotics imports could help reset the economics that are holding back U.S. investment and production. It’s a sharp perspective on how policy can shape the future of advanced tech here at home. Well worth a read: https://lnkd.in/edMPTQPQ Richard Fruehauf, Robert J. Szczerba, Michael Lutzky, Edward Ovando, Karl Sanchack, Herman Herman, Jeff Legault, Phil English, Richard Fruehauf, Ryan Aument, Michael Guido, Sheila Fitzgerald Sterrett, David McCormick

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