Murat Bicer

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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Sanity released its AI Content Operating System - a true game-changer for any enterprise, brand or e-commerce player! Way to go Magnus Kongsli Hillestad and team!

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How Vivek Sodera Built Two Iconic Companies, from LiveRamp to Superhuman Mail. This week, on "Further, Faster" Vivek talks about combining deep founder-market fit, obsessive customer understanding, and ruthless discipline around product-market fit. https://lnkd.in/eiwAdfFY https://lnkd.in/e8iaQHiC

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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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Model ML continues to ship at lightening speed. Huge new set of capabilities as AI continues to rip through finance (and turbo charge the humans who adopt). Great work Chaz Englander Arnie Englander and team

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Jamie Dimon Is A CEO, Not An Oracle: The Big Point The Rabid Capitalist: The Big Point is a brief summary of a detailed note available to paid subscribers. When Jamie Dimon talks, people listen. The question is whether they should. Dimon is qualified as an expert. He runs the largest bank in the United States, sits atop one of the most sophisticated real-time economic datasets in existence, and has navigated JPMorgan through more than two decades of crises. His views carry weight for legitimate reasons. But weight and accuracy are not synonymous, and the distinction must be drawn. This question has fresh urgency. On April 7, 2026, Dimon renewed his warnings about the private credit market in his annual shareholder letter — specifically flagging weakening lending standards, aggressive borrower assumptions, looser covenants, and the proliferation of payment-in-kind (PIK) structures. He has been making variants of this call for over a year. His vision of crisis has not yet arrived. An examination of his track record demonstrates his tendency to identify forthcoming economic events but to misunderstand their timing. Complete content is available for a $15 monthly subscription. Click here to subscribe: https://lnkd.in/e9p3vMkC

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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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I recently sat down with David Prosser at Forbes to discuss how we, at AAF Management Ltd., have strategically positioned ourselves to ride — and invest through — the current AI wave. The conversation came at a meaningful inflection point for us: just days after announcing 𝘛𝘩𝘦 𝘈𝘹𝘪𝘴 𝘍𝘶𝘯𝘥, a $55 million early-stage hybrid vehicle anchored by Mubadala Capital. Over the past decade in venture, I’ve seen the industry evolve through extraordinary macro shifts — the rise and fall of online-native e-commerce brands, the boom and bust of biotech, and the irrational exuberance of the ZIRP-era liquidity that fueled a historic valuation run-up, followed by a painful but necessary reset. Each cycle has followed a familiar pattern: euphoria → over-investment → correction → consolidation → compounding. And every cycle reinforces the same truth: 𝘦𝘯𝘥𝘶𝘳𝘪𝘯𝘨 𝘷𝘢𝘭𝘶𝘦 𝘪𝘴 𝘣𝘶𝘪𝘭𝘵 𝘸𝘩𝘦𝘯 𝘥𝘪𝘴𝘤𝘪𝘱𝘭𝘪𝘯𝘦 𝘮𝘦𝘦𝘵𝘴 𝘤𝘰𝘯𝘷𝘪𝘤𝘵𝘪𝘰𝘯. So, are we in an AI bubble? The honest answer: it depends which asset class you mean. As I said in the interview: “It’s really a story of two different worlds. A handful of very large private companies have been flooded with liquidity and seen huge valuation increases — but that’s not been the experience of small start-ups raising their first $1M to $5M.” Because most investors follow momentum, we’re seeing overzealous valuations in public markets (e.g., NVIDIA) and late-stage private names (e.g., OpenAI, Anthropic, xAI). But in early stage, while Seed valuations have crept up, most AI startups raising $1–5M rounds remain sensible. We see AI as a once-in-a-generation platform shift, not a passing cycle. Through The Axis Fund, we’re intentionally positioned to capture both beta and alpha across this paradigm: Beta — via our 20% fund-of-funds allocation, giving us exposure to the next wave of category-defining AI companies: • Decagon – AI for customer service (backed by Andreessen Horowitz ) • ElevenLabs – AI voice and language models (backed by ICONIQ) • Sanas – AI-powered voice translation (backed by Insight Partners) • Legora – Legal AI for the EU (backed by General Catalyst) Alpha — by cherry-picking the most promising companies across Pre-Seed to Pre-IPO. Our AI thesis is clear: • 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐋𝐚𝐲𝐞𝐫: Agentic workflows driving automation, efficiency, and error reduction. • 𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞: Libraries, tools, and data systems enabling scalable model deployment. • 𝐀𝐩𝐩𝐥𝐢𝐞𝐝 𝐀𝐈 > 𝐚𝐛𝐬𝐭𝐫𝐚𝐜𝐭 𝐀𝐈:  Founders solving real, high-value problems in fintech, healthcare, SaaS, and industrial tech. • 𝐆𝐥𝐨𝐛𝐚𝐥 𝐩𝐞𝐫𝐬𝐩𝐞𝐜𝐭𝐢𝐯𝐞, 𝐥𝐨𝐜𝐚𝐥 𝐞𝐱𝐞𝐜𝐮𝐭𝐢𝐨𝐧: Founders who think globally and execute precisely in their markets. We will stop talking about AI as a category the way we stopped talking about cloud or web protocols, 𝘪𝘵 𝘸𝘪𝘭𝘭 𝘣𝘦𝘤𝘰𝘮𝘦 𝘵𝘩𝘦 𝘥𝘦𝘧𝘢𝘶𝘭𝘵. 👇🏽 Read the full article: https://lnkd.in/ejwREwEe

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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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"We've become so insular in who we talk to and listen to, and I didn't realize how much that was keeping me in tunnel vision and tunnel thinking." Seth Levine, Co-Author of Capital Evolution and Partner at Foundry, talks about seeking out more diversity of thought on Tech Scenes Unplugged. #venturebacked #vcbacked #venturecapital #leadership #ceo #founder #operatingsystem #peakOS #foundermode

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Yesterday, two DCVC-backed companies raised about a half billion dollars. In today's funding environment, that's not that exceptional... Together, the two companies just happen to enable gigawatt-scale AI compute, except in the unprecedentedly small space of only about 40 shipping containers, no exotic cooling required. You have to wonder what the US military might do with a gigawatt-equivalent of compute they could fit in a few C5 flights... or a 100MW-compute platform that fits in a single rocket launch... Even that, in DCVC's world, isn't that exceptional. We like to say we help make the impossible and essential, profitable and available. But what is exceptional, and this is a theme with us folks, is that they are each only two of many of our companies delivering robustly on outcomes considered impossible on VC dollars or in reasonable time, at the point when we backed each company from very early on: - a safe, cost-effective, meltdown-proof, truck-portable 1 megawatt nuclear reactor (Radiant, see https://lnkd.in/gF3JAHwS) for American energy dominance - American-made AI semiconductor chips that match or outperform everything else at 100x the energy efficiency, on off-the-shelf models (Mythic, see https://lnkd.in/gWFdvZFT) We were able to make the calls on these, and how they could work together, along with similar calls on all of their brother and sister impossible companies, because of a very deep bench of unified scientific, engineering, operational, and business building experience considered passé by a lot of other folks. It's how we make the exceptional routine.

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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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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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Thrilled for OVNI Capital to be backing RIFT in a pre-seed round led by AlleyCorp (Luc Ryan-Schreiber). Rift is building the first real-time aerial intelligence network, a new layer of infrastructure for persistent, on-demand visibility where it matters most. This funding will scale production of their autonomous stations, accelerate deployment in high-stakes environments, and expand the team leading the next phase. 🗞️ Explore the full story: - StartupMafia: https://lnkd.in/dARrg25N - BFM Business (FR): https://lnkd.in/eADSUsn7 - Les Échos (FR): https://lnkd.in/eFG3zAy5 👨‍🚀 Join the mission → https://lnkd.in/erm_SrTG

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When I first met Kevin Surace, I immediately understood why his reputation precedes him across Silicon Valley. He’s been building at the frontier of technology for decades and is deeply respected by people across the industry. Kevin was working in AI long before the world caught up to it—pioneering early voice AI technology, building multiple companies, and consistently seeing around corners before the market arrives. He also ‘grew up’ in Silicon Valley with my former co-CEOs, Ben and Marc, from Andreessen Horowitz which made the world feel very small very quickly in the best possible way. 🌎🚀 I was introduced to Kevin by David P Bovenzi at Grand Oaks Capital when I was asked to help bring Token— a company that has spent more than a decade building cryptographic biometric identity assurance technology— into the market in a whole new way… In one conversation I knew I wanted to work with him— and Token, where Kevin is Chairman and CEO. AI has fundamentally changed the identity landscape. Attackers no longer need to “hack in.” They log in—using AI-generated phishing, deepfakes, and automated attacks at global scale and unprecedented speed. AI attacks will continue to be faster and cheaper than anything enterprises and governments have had to defend against before. In Gov and highly regulated industries, identity failure means more than compromised accounts… It’s ransomware attacks on hospitals, critical infrastructure disruption, supply chain shutdowns, financial system compromise, and nation-state intrusion. Identity assurance has become a defining infrastructure challenge of the AI era (Gartner is tracking this emerging category closely). Since joining Token’s mission earlier this year, we’ve relaunched the brand, launched the TokenCore product line, rebuilt the GTM engine, assembled a world-class team, and are bringing a twelve-year innovation into the hands of enterprises, the U.S. government, and allied global organizations who need it most. And I’ve had the privilege of working alongside Kevin every day. In just a few short months I’ve learned an incredible amount from him as a leader, inventor, and operator. As investors we talk about how the biggest breakout companies happen when the technology, the market timing, and the right team all come together at once. That’s what this mission feels like. 🚀 A great read on Kevin’s journey through the early days of AI, finding joy in the process, and lessons on leadership from decades in the trenches: https://lnkd.in/e-iy5iWY Dianne Liu Albert Yanez Khamvong Thammasouk Dan Van Ostrand Paul Wazowicz Christopher DeBaggis Johnny Lam Marcus Yanez Jack Jackson Michael Okland Kortney C. Steve Hunt Ann-Marie Klein FCMA, MBA Ever Wonder The Juno Group Elevate Talent Ventures Torrell F. Elevated Value Partners Monique Shivanandan Robert C.

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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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AI is changing what “scale” actually means. In CTech by Calcalist’s 2026 VC Survey, Haim Bachar and Lee Ben-Gal share how we’re seeing the scaling metric shift - from headcount growth to output per person. This isn’t about doing more with less. It’s about building companies differently from day one - and rethinking how success is measured. See the full article below 👇

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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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