Eric Chin

Some very welcome news for VC and PE firms, as well as other entities investing in startup and emerging growth companies. The California Department of Financial Protection and Innovation (DFPI) has announced the suspension of the implementation and enforcement of the data collection and reporting regime imposed by the Fair Investment Practices by Venture Capital Companies Law (FIPVCC). This decision comes pending the completion of a rule-making process initiated by the DFPI in response to feedback from stakeholders affected by the regime. As a result, the DFPI will not require covered entities to submit further registrations or file reports by the April 1, 2026 deadline. For more information, visit the DFPI website: https://lnkd.in/eqjJbSFz

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I've been building tech companies since before Google existed. Proud to be part of the Haverford College entrepreneurial community — a place that quietly produces world-changers. Dr. Bill Harris developed breakthrough coatings that made artificial hips last, changing orthopedic medicine forever. Alex Karp co-founded Palantir Technologies and helped define the AI era. Sang H. Cho, building hello82,a K-pop-native media and commerce platform for the Western market. And Katrina Spade is reinventing what we do with our bodies after death — giving them back to the earth. And I've had the privilege of building through every major tech cycle since the web's earliest days. Haverford doesn't make much noise about it. But the tradition runs deep. And Haverford students are carrying on this proud legacy on campus through Haverford Accelerator. Join Fahim Mosharrof and me this Thursday — link below.

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A few highlights from this week's Going Direct episode with Jamie Gull on US re-industrialization and his newly minted pre-seed VC fund Wave Function Ventures. He’s highly technical, invests in deep tech founders at the earliest stages, and is all-in on the, “techno-industrial” movement. Full episode at bottom of post. 1. The push for globalisation made a lot of sense from a dollar and cents standpoint, but was clearly shortsighted. History tells us it’s not a wise move and now we’re a bit stuck. 2. Biggest challenge to US re-industrialization - regulation/red tape from the both government + general public. Its a really big deal and primary blocker. 3. 2nd biggest challenge to US re-industrialization - not enough top-notch teams to fill all the good hard tech ideas. Without the right talent, you’ll just burn through cash and die fast. 4. Jamie is about to close his first fund at Wave. He’s investing across aerospace, defense, energy, robotics at earliest stages. His biggest value-add as a solo-GP is his technical background. 5. Jamie knew he’d be an engineer since he was a kid. His grandpa was a pilot, mom was a pilot, and he got his pilot license in high school.  Jamie cut his teeth at SpaceX for 5+ years where he learned the value of scrappy engineering. 6. Jamie’s take on energy: Everything valuable that we do requires energy. The US is very far behind China and the #1 thing where he's spending time on right now.  7. Jamie’s take on humanoids: household robots don’t make sense. He sees the real opportunity for humanoids in doing dangerous, high-value work in shipyards and factories. 8.  In deep tech storytelling is life or death. You might have the right team and technology, but if you can’t tell the story, you won’t survive the first three years. 9. Jamie Gull’s advice to non-technical founders building a deep-tech company: good luck… Link to full episode at Going Direct: https://lnkd.in/e5iDNPhK

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Today is the due date of California’s Fair Investment Practices' first annual demographic report, and my team at Fabric VC is proud to report on our 100% diverse-led portfolio. 🎉 We look forward to seeing other funds like ours changing the paradigm in VC, and will be calling out those whose numbers look far different than ours to start making intentional choices to create a more diverse VC system. #FIPVCC

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Over the weekend I was thinking about how GPT-5 and other recent model upgrades will push industrial automation forward, and translate into physical-world actions. Our focus at nvp capital is on founders building in vertical AI, and while much of that is LLM based today, in the future (especially for industrial use cases) we see a world where that becomes driven by Vision–Language–Action models (VLAs). GPT-5 takes a real step forward in multimodal reasoning — not just reading text, but interpreting images in context. Drop in a photo of a landmark and it often nails the location (and yes, it will tell you it’s better than GPT-4!). 📸 Multimodal context is a bridge to actions, where productivity gains can really scale. Today, OpenAI and other foundation model players focus on digital actions, while physical actions -- the domain of VLAs -- are mostly pursued by companies with physical assets and data, like Gemini or Grok. For founders building in industrial and robotic automation 🤖, interest in VLAs is growing — even if they’re still too early for broad commercial use. GPT-5’s integrated handling of text, images, and other inputs could make it an ideal VLA “brain,” capable of interpreting scenes, following nuanced instructions, and planning precise, multi-step actions that lead to highly adaptable agents moving seamlessly from perception to action. An open question is whether OpenAI will step into that physical domain — or leave VLAs to those already playing in the hardware-heavy world ⚙️. Either way, if you’re building vertical software using VLAs, we’d love to talk to you!

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“Isn’t defense just another deep-tech vertical?” I get this question a lot since taking on defense venture investing alongside my work in Greentech, Biosolutions, Quantum, and AI. The short answer: no. Defense runs on different clocks. And different stakes. The customer is often singular. Timelines are long. Trust and institutional alignment matter as much as technology. What’s changed is the urgency. Geopolitics is no longer abstract. Capability gaps are real. Timelines are compressing - while the innovation system remains slow. Progress doesn’t happen in isolation. It depends on close collaboration with industry, real manufacturing capability, and trusted ties into national defense - here in Denmark and across allied countries. Much of the most important work happens quietly. Confidentiality is part of the model. Still learning. But convinced: Defense investing requires a different operating model - one shaped by longer timelines, concentrated customers, industrial scale, and sovereign responsibility. And getting that right has never mattered more. Simon Øelund Johan Bitsch Nielsen Magnus Bielefeldt Jon Arskog

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We recently invested in Mutable Tactics through our early‑stage fund. The company is building software that enables a single operator to coordinate entire fleets of autonomous vehicles that operate as a team, even when communications are degraded or denied. In our latest Portfolio Spotlight podcast, Leah Martin speaks with Colin MacLeod, Co-Founder and CEO of Mutable Tactics, alongside Maureen Haverty, Seraphim Principal. The discussion ranges from advances in autonomy to the practical realities of human–machine teaming in defence and beyond. Well worth a listen for anyone working on autonomy, dual‑use technology, or systems moving from prototype into service. Full episode linked below. #SeraphimSpace #DualUse #DefenceTech

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It is great to be working with RaviKiran Gopalan and Aditya Akella as they build Canyon Code, the workflow intelligence layer for heterogenous AI datacenters. Proud to see these fellow Indian Institute of Technology, Madras alums taking a research-led approach to tackle a large problem within enterprise AI today: abstracting the complexity of heterogenous datacenters to deliver agentic workflow level transparency. NewBuild Venture Capital co-led this pre-seed round alongside Cota Capital and Blackhorn Ventures.

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"Build the event you wish existed" That's what we at Monadical did last week at #NYTW. We wanted an AI Engineers discussion for Engineers. There's always a lot of events out there for VCs to network, or for startups to learn about G2M, but very little on lessons learned from actual engineers in the field. So that's the event we hosted. Big thank yous to our awesome panel, Roy Pereira, Ben Cohen and Corey J. Gallon. Here's the key takeaways and the AI tools we're using. 🚀 All three panelists independently called AI Agents the most transformative LLM application they’ve used. They specifically called out Claude 3.5 Sonnet for its accuracy and reliability. 🪨 We dug into how LLMs are “jagged”, not general. They can be shockingly good at some tasks and completely fail at others. Everyone agreed: good evaluations are critical (and hard.) 🧪 Corey noted how public benchmarks and reality are two different things. Most public evals are saturated or gamed. ♊ Ben emphasized that AI projects are actually two projects: building the tool and building the evaluation process. 🧱 We explored how falling dev costs may impact startup defensibility and labor demand. Roy shared that founders are already shifting strategies in response. ⚒️ In a world of daily AI launches, the panel discussed how they decide what’s worth attention, and what’s just noise. They called out tools like Goose, Aider, Claude Code, and Monadical’s own Cubbi, which helps run agentic workflows safely in dev environments. (links in the comments). CTA: What would you want to hear in an AI Applied Engineering talk you attended?

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🚀 Big congratulations to BQP on raising USD 5mn to scale their quantum-powered simulation engine for aerospace, automotive and other mission-critical sectors. The round saw participation from many renowned global investors, reinforcing confidence in their breakthrough approach. As an o2 Angels Network portfolio company, BQP exemplifies the kind of #deeptech we back — building foundational IP, solving non-trivial computational problems, and developing defensible technology moats. Their quantum simulation platform delivers capabilities classical systems can’t; enabling faster design cycles, higher accuracy, and safer, more efficient outcomes in complex engineering environments. This is not just innovation — it’s infrastructure for the future of aerospace, defense, and energy. 💡 At o2 Angels Network, we back founders solving high-impact, high-risk industrial challenges with technology that protects lives and transforms operations. Our portfolio includes Fabheads Automation, Green Tiger Mobility Pvt. Ltd., Eeki, CultYvate, Skye Air Mobility, NAVARS EDUTECH, Janitri, Velectron Labs Private Limited, Abhiyantrik Solutions, Nexstem, REGRIP "RE-ENGINEERED TYRES", SpaceFields, Unibose Technology Private Limited, BQP, Vgenomics, and many others pushing the boundaries of innovation. Onward and upward! 🌍🔬 #QuantumComputing #DeepTech #Simulation #Aerospace #IndustrialInnovation #IPDriven #TechnicalMoat #VentureCapital #O2Angels #NextGenTech

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📊 AmTech Daily: Deals Defining America's Future — Feb 25, 2026 Each morning, Commonweal Ventures compiles the day's top #AmTech deals and news at the intersection of government and technology. Here's today's. Comment "Subscribe" to get the full briefing, news included, in your inbox. Education  🔹 Subject (Beverly Hills, CA), which offers an AI-powered digital curriculum platform for middle and high school students, raised $28 million in funding led by Vistara Growth, joined by NextEquity Partners, Green Street Impact Partners, Outcomes Collective Growth Capital, and other existing investors. Health  🔹 Handl Health (Los Angeles, CA), which provides an analytics platform to help health plans and benefits consultants design employer health benefits that lower costs and improve care quality, raised $14.2 million in Series A funding led by Arthur Ventures, joined by Syndra Capital Partners, a strategic investor, Mucker Capital, Riverfront Ventures, Digital Health Venture Partners, and Boutique Venture Partners. Aerospace  🔹 Sophia Space (Pasadena, CA), building orbital data centers composed of ultra-thin, solar-powered computer panels called TILES that sit on or next to satellites, raised $10 million in seed funding led by Alpha Funds, KDDI Corporation Green Partners Fund, and Unlock Venture Partners. Finance  🔹 Comeryx Insurance (Denver, CO), which runs an AI-driven online insurance platform that automatically prices and issues specialty liability coverage for small trade contractors that traditional carriers won't easily underwrite, raised $7.5 million in seed funding led by Altai Ventures, joined by American Family Ventures, Intact Ventures, Boulder Ventures, Arch Capital Group, and Echelon. AI Chips  🔹 Cerebras (Sunnyvale, CA), which designs wafer-scale AI chips and computer systems that let large organizations train and run advanced AI models faster and more efficiently, has confidentially filed to go public in the U.S. after previously raising more than $2.5 billion in private funding across eight rounds. Energy  🔹 Terrasmart's eBOS division (Grand Rapids, MI), which makes prefabricated electrical wiring and combiner-box systems that connect utility-scale solar panels to inverters and the grid, was acquired by GameChange Energy Technologies for $70 million to extend its end-to-end solar infrastructure offering. What is #AmTech? It's our term for the companies tackling America's biggest challenges in sectors like energy, defense, healthcare, and infrastructure. In these markets, the path to building category-winning companies runs through government, and the founders who understand that are building the most consequential technology businesses of our generation.

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Seed-stage fundraising requires differentiation. Grind Ventures found it at the intersection of three underserved markets Technology transfer from universities creates early-stage opportunities that most VCs miss. Defense and federal marketplace applications provide revenue visibility. Critical infrastructure sectors offer commercial scale. Focused Thesis - Dual-use technologies serving defense and 16 critical infrastructure sectors Technology Transfer - University research teams1-5 years old at $1-3M valuations Revenue Clarity - Federal marketplace provides structured procurement pathways Commercial Scale - Critical infrastructure sectors offer massive addressable markets   Geographic Focus - US-based companies with clear domestic advantages Stage Discipline - Seed investments with defined entry points and milestones The market rewards problem-obsessed founders with healthy margins and cash flow visibility. Dual-use technology delivers both. Which of these thesis elements resonates most with your investment approach? #VC #GrindVentures #ThoughtLeadership

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In venture, small is a strategy - not a constraint. Sequoia’s early playbook is a masterclass in restraint. Across their first 13 US funds (’74–’10) they kept sizes tight, averaged ~10× back to LPs overall, and - per Roelof Botha - Funds XII & XIII each cleared >20×. The point isn’t nostalgia; it’s math. Discipline compounds, bloat doesn’t. A few firms have made this their religion - think Benchmark, USV, Index. Consistent fund size → consistent behavior → a brand you can trust. Meanwhile, the industry’s top-line AUM has swollen to… let’s say “gym-bro levels.” Bigger isn’t better if it breaks alignment. My take ⬇️ - Fund size is a product decision. Keep it intentional and you can stay founder-aligned, move fast, and avoid the asset-gathering treadmill. - Scarcity sharpens selection. When every check has to matter, you chase conviction, not consensus. - Brand follows consistency. Do the same hard thing well, over and over. ⚡️If you’re a founder, ask potential investors: - Will my round actually move the needle for your fund? - What ownership and follow-on strategy keep us aligned over multiple rounds? - How many boards will you sit on at once? We keep our game focused and hands-on at pre-seed/seed. If you’re building something category-defining (and prefer sharp help over a huge logo), my DMs are open. Let’s keep it tight and make it count 🚀

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Seventeen months. That's how long it took Starcloud to go from Y Combinator demo day to a $1.1 billion valuation. $170 million Series A, led by Benchmark and EQT Ventures. The mission: put data centers in low Earth orbit, powered by unlimited solar energy. They already have a satellite running an Nvidia H100 GPU. The next one carries a Blackwell chip. The math behind this is what convinced me. Global AI compute demand is growing faster than we can build power plants to feed it. Every hyperscaler is fighting for the same land, the same grid capacity, the same permits. Starcloud looked at that bottleneck and decided the constraint wasn't technical. It was gravitational. Two years ago, orbital compute was a thought experiment. Today it's a billion-dollar company with real hardware in space. That shift from impossible to inevitable is exactly what deep tech investing is supposed to look like. https://lnkd.in/emvJ6VHf

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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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One of things DCVC looks for in iTechBio companies: early commercial progress, worth billions, from biopharma partners. It’s one of the reasons we invested in Proxima.

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Honored and excited to partner with Drew Baglino and the incredible team at Heron Power as they re-imagine the electric grid for the modern world. Power in America is not zero sum. We deserve access to cheap and abundant electricity and we should win the AI race. And we must build the capacity to manufacture critical technology here at home. When faced with existential challenges, we deploy technology against them. And we win.

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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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My investment framework centers on 7 layers. CASIMIR fits into the first layer which is the Observation Layer. Out of 22 billion IoT devices on earth and ~10k satellites in space in 2026 we may have a 6 billion (and growing) ultra low power devices on earth and space that can one day run on MicroSparc 👍🏼 -> Eternal power chip Harold “Sonny” White + Capital Factory #HardThings #deeptech

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