Sebastian Metti

This week, I’m looking forward to joining OpenAI's Founder Forum on Healthcare to speak on a panel exploring how AI can sit side-by-side with clinicians, health systems, and patients. As Hemant Taneja, CEO of General Catalyst and one of our investors, reflected after Davos, “the undercurrent is all about trust and relationships.” That’s especially true in healthcare, where AI only works if stakeholders come together with shared standards around data, governance, and accountability. I’ll be sharing what we’ve learned building agentic AI in highly regulated environments across the U.S. and Canada, and why the future isn’t about centralizing data, but letting intelligence go to where data already lives. Grateful to OpenAI for bringing together operators focused on getting this right. If you’ll be there, I’d love to connect.

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Microsoft's new AI diagnoses diseases 4x better than your doctor. But, when will hospitals and regulators catch up? On today's episode of Venture Daily, I spoke with Jaimal Soni (Insight Health) about the tipping point where AI doesn’t just assist in medicine, but actually replaces parts of it. We also cover Mark Zuckerberg's Superintelligence Labs team (with members from OpenAI, Anthropic, and Google's DeepMind) and Oracle's record-breaking $30B cloud deal. Check out the full episode below! YouTube: https://lnkd.in/gwdmnE66 Spotify: https://lnkd.in/gEUxZxaY

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Big milestone for the portfolio 🚀 Proud to have backed VUGENE as they announce a new partnership with Inotiv (NASDAQ: NOTV) to bring AI-powered bioinformatics and multi-omics into mainstream drug discovery workflows. AI + data-rich biology + real-world pharma workflows = faster, smarter drug R&D. 🧬🤖

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Zooming out on AI in biopharma — with Vijay Pande Vijay Pande left Andreessen Horowitz this summer after 11 years as a life sciences investor. Now, he’s building a new firm focused on AI. He joins Post-Hoc Live to take the 10,000-foot view of AI in biotech and Silicon Valley: what do investors get right and wrong about biotech? What are the business models for AI in biopharma? Which moonshot project will stick? We’ll continue the conversation next week at Endpoints AI Day. Sign up for the virtual program here: https://lnkd.in/gvvCQrkn

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The numbers are in. And they should change how you think about capital allocation. US hyperscalers have committed to spending between $660 billion and $690 billion on #AI #infrastructure in 2026 alone — nearly doubling 2025 levels. Amazon at ~$200B. Alphabet Inc. at $175-185B. Meta at $115-135B. Microsoft tracking $120B+. Oracle at $50B. But here's what most commentators are missing: the story isn't about Big Tech's capex budgets. It's about who finances the physical layer when demand outstrips supply. Microsoft has disclosed an $80 billion backlog of Azure orders it cannot fulfil due to power constraints. Every hyperscaler reports being supply-constrained, not demand-constrained. That means the bottleneck isn't algorithms — it's atoms. Power. Land. Cooling. Connectivity. And that's where the capital architecture gets interesting. Abu Dhabi's MGX — backed by Mubadala and chaired by Sheikh Tahnoun bin Zayed — is quietly becoming one of the most consequential infrastructure investors on the planet. $7 billion committed to #Stargate. A $40 billion acquisition of Aligned Data Centers with BlackRock. Europe's largest AI campus breaking ground near Paris in 2026 at 1.4 gigawatts. And now in talks for hundreds of millions into Anthropic's $20 billion round. This isn't passive LP capital. This is #sovereign infrastructure principal capital — deployed with generational time horizons that traditional #PE simply cannot match. The question every investor and entrepreneur in my network should be asking: when the hyperscalers are capacity-constrained, who builds the next gigawatt? The answer is increasingly sovereign wealth vehicles and patient capital structures that didn't exist five years ago. The AI race is no longer won in the lab. It's won on the grid. https://lnkd.in/d_ChJnYw https://lnkd.in/dZwQJsSs #AIInfrastructure #SovereignWealth #CapitalAllocation #DataCenters #MGX #Stargate #EmergingMarkets #InvestmentStrategy #CleanTech #EnergyTransition #PrivateCapital #FrontierMarkets #AI #InfrastructureInvestment #GulfCapital

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I’ve been part of recent GenAI discussions in the GCC. Product choice isn’t where decisions slow down. What I keep hearing are harder questions about data, compute, and long-term control. That’s when it starts making sense. In Saudi Arabia, Qatar, and the UAE, GenAI is increasingly treated less like software and more like infrastructure. Once AI starts shaping public services, healthcare, regulation, or economic planning, outsourcing the core capability feels risky. You can buy tools easily. Owning the capability is harder, but it’s safer. That’s why I see the focus shifting to 3 things commercial GenAI products can’t really solve on their own: Data - Arabic data that reflects local language, culture, and business reality is a strategic asset. Compute - If critical workloads run on infrastructure you don’t control, continuity becomes fragile. Control - If you don’t own the full stack, you don’t decide how AI is trained, deployed, or governed. Seen through a normal tech or VC lens, some of these AI infrastructure investments being made here look hard to justify. They only start to make sense when you see GenAI the same way you see power, ports, or telecom. The takeaway for me is simple. If GenAI is becoming core to how decisions are made, it can’t sit only in IT or innovation teams. Someone has to own it end-to-end, with clear accountability and long-term funding logic. To leaders and investors, my question is - If AI becomes critical to your system, who owns it, and are they accountable for how it performs over time? #SaudiArabia #GenAI #Vision2030 #VentureCapital #GCC

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NYU Langone Health’s informatics leaders recently predicted fully autonomous clinical AI within 5 years with no physician sign-off. Algorithms titrating blood pressure meds, retinopathy screening running end-to-end without a clinician in sight. Their reasoning is hard to argue with as we're facing a shortage of 85,000+ physicians by 2036 and the current care model doesn't have an answer for that, and it seems clear that AI will be playing more of role in providing care going forward. But the next question is more difficult to answer: Are we automating the right things, for the right reasons?   Utah is already stress-testing this with Doctronic by automating routine prescription renewals for chronic condition patients. I wrote about this a month ago - renewals are repetitive, pulling clinicians away from patients who need actual judgment and create gaps in care when they fall through the cracks. If that pilot scales, it frees up real capacity. What makes it work is that prescription renewals are largely protocol-driven. The decision tree is narrow, the inputs are structured, and removing friction there doesn't mean removing judgment from care. Clay Christensen would have called these protocol-driven care pathways 'precision medicine,' having advanced originally from the primordial soup of 'intuitive medicine,' to the mid-stage 'empirical medicine,' to finally precision status. We're seeing the same logic play out across our portfolio companies. Janie automates the administrative workflows that quietly drain clinical capacity, things like billing, prior auth, and care coordination, giving practices back time that should never have been spent on paperwork. FlyteHealth takes a similar approach on the clinical side, combining a multidisciplinary care team with technology to manage obesity, hypertension, and diabetes at scale. The care team stays central and the automation handles everything that doesn't require them. That's the model I find most compelling. Where I get more cautious is with patients who have multiple conditions, polypharmacy risk, or subtle behavioral changes that don’t show up in structured data. A system that's right 95% of the time still needs airtight guardrails for the other 5%, and building those guardrails well requires people who understand what failure looks like. Here's the thing: AI IS NOT GENERALLY INTELLIGENT, AND WE CAN RELY ON IT TO FAIL AT 'LAST MILE' JUDGMENT WORK THAT REQUIRES GENERAL INTELLIGENCE. The goal here shouldn't be to remove humans from care. It should be to stop wasting clinical talent on work that doesn't require it. As routine tasks get automated, clinicians should have more room for nuanced conversation, the shared decision, the patient who needs persuasion as much as a prescription. Utah and NYU deserve real credit for running these experiments in the open.

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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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🎙️ Featured Podcast: What Gives Early-Stage Investors an Edge? I joined the Resilient Alpha Podcast, hosted by IVYFON, to talk about our strategy at GD Partners — and how we identify transformational companies in healthcare and frontier innovation. 💡 In this short clip, I discuss GD Partners’ unique investment lens and how we approach early-stage opportunities in healthcare and frontier innovation. 📺 If you're interested in the full conversation, the full episode is available in the comments section. Thanks to Marty S. and IVYFON for the invitation, and to Elizabeth Cho-Fertikh for leading such a thoughtful conversation — always grateful to contribute to discussions that move the industry forward. #venturecapital #healthcareinnovation #earlystageinvesting #GDPartners #ResilientAlpha #IVYFON #founders #startups

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We address a few key debates on Bili post FY25 results and ahead of the upcoming 1Q26 print (likely in mid May). Bili's share price has been largely resilient YTD vs. HSTech index, and we expect the name to outperform on continued fast ads growth, games accelerating from mid year and margin expansion potential with AI investments largely manageable. Despite the stock trading at 20X fwd PE (one of more expensive names vs. China Internet's 15X), we see Bili as a resilient name in our China Games/Entertainment coverage, largely immune from AI disruption and Bytedance competition, while at the same time delivering 30% EPS cagr 2025-28E. Reiterate Buy.

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I actually think most apps are going away--not just because *text* is easier, but ai driven chat in general will probably consume most app experiences.

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Believe it or not, even this astounding measure of AI offering 4x improved accuracy at 20% of the cost versus human physician’s diagnostics vastly undersells the current AI advantage. This paper only includes the cost of the diagnostic effort. What it does not include, is any consideration of the costs of mistaken diagnoses, both in money and in lives. Incorrect diagnoses lead to massively increased cost in treatment, ongoing disease, and worsening conditions. The faster these capabilities are rolled out across public health, the better.

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I’m excited to announce that we at Manas AI have entered into a strategic agreement with Schrödinger intended to shorten our drug discovery timelines. Our partnership will allow Manas to leverage Schrödinger’s industry-leading computational platform to aid building Manas’ physics-based “world model” — an AI platform for discovering new protein-binding molecules that can target disease. This agreement includes deep access to Schrödinger’s computational molecular discovery platform combined with expert support aimed at optimizing the impact of the platform; designed to ensure Manas AI’s algorithms are fully harmonized with Schrödinger’s predictive power. Together with Schrödinger, we’re committed to ushering in a new era of drug discovery by combining frontier AI with best-in-class physics.

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"The 'impossible' is just a milestone we haven't reached yet." In my years leading teams in precision medicine and drug discovery, I’ve heard the word “impossible” more times than I can count. "It’s impossible to target that mutation." "It’s impossible to make this treatment affordable." "It’s impossible to change the healthcare system." But here is what I’ve learned: The "impossible" is usually just a lack of data, a lack of collaboration, or a lack of imagination. When we look at a patient fighting for their life, "impossible" isn't an answer; it's a starting line. We don't just build technology for the sake of innovation; we build it to turn "terminal" into "treatable" and "someday" into "today." Whether you are a scientist in a lab, an executive in a boardroom, or a caregiver at a bedside, your work is the bridge to that next milestone. Let’s stop measuring success by the hurdles we face, and start measuring it by the lives we change when we decide to jump over them anyway. The future of healthcare isn't a destination. It’s a journey we are navigating together, one breakthrough at a time. 🚀 #InnovationMindset #HealthcareLeadership #FutureOfMedicine #HealthcareInnovation #PrecisionMedicine Dr. Prasun Mishra #FutureOfHealth #HumanityFirst American Association for Precision Medicine (AAPM) #AAPMHealth #AAPMHealth WISE World Investors & Entrepreneurs Society #news

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**Exploring AI's Role in Healthcare: Claude vs. ChatGPT Health** The recent launch of Anthropic’s Claude for Healthcare, coming swiftly after OpenAI's ChatGPT Health announcement, highlights the increasing synergy between AI and the healthcare sector. As we observe these innovations, it's crucial for investors to consider how AI can transform healthcare delivery, improve patient outcomes, and optimize costs. At ElevenX Capital, we believe that understanding these advancements will shape the future of investment strategies. How do you see AI shaping the current and future healthcare landscape? #investing #innovation #venturecapital #entrepreneurship

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Embracing AI in life sciences is crucial for maintaining competitiveness in today's landscape. AI plays a pivotal role in revolutionizing drug discovery, facilitating rapid and precise predictions of molecular interactions. Companies utilizing AI algorithms can slash research time by up to 30%, expediting market entry. This shift not only boosts innovation but also improves patient outcomes via tailored therapies. The next phase involves assessing how your organization can seamlessly integrate AI tools into its research workflows. How do you intend to incorporate AI into your upcoming projects? #AILifeSciencesInnovation #DrugDiscovery #Biopharma #Leadership #DataCulture #FAIRdata

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**Harnessing AI and Genetics for Early Detection in Healthcare** AI-driven insights combined with genetic analysis are revolutionizing early detection of conditions like aortic stenosis. This interdisciplinary approach not only improves patient outcomes but also highlights opportunities for innovation in the healthcare sector. At ElevenX Capital, we see significant potential for startups at the intersection of technology and healthcare. How might your investment strategy adapt to incorporate these advancements in genomic medicine and AI? #investing #innovation #venturecapital #entrepreneurship #genetics #ai

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**Harnessing AI for Vaccine Development** The intersection of genetics and AI presents unprecedented opportunities in identifying effective vaccines by predicting viral evolution. By analyzing vast genetic data, AI can forecast mutations, enabling proactive vaccine design. At ElevenX Capital, we recognize the transformative potential of these advancements in healthcare investment strategies. How can Limited Partners leverage this synergy to enhance their portfolio? #investing #innovation #venturecapital #entrepreneurship #genetics #ai

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