Drew Bartkiewicz

How I think about making low-information decisionsI’ve made a lot of Investment decisions with incomplete information. That’s venture. That’s poker. That’s what I am obsessed about on TheFirstBet.co. Brian Bell and I got into the real question behind those decisions: How do you get better at choosing when you still don’t know enough? What actually reduces risk? And how much of this is just pattern recognition with better data? One thing stood out to me: The answer is not “trust your gut” or “let AI decide.”It’s both. Brian has built an investing process around a weighted scorecard, historical data, and AI-assisted analysis — but he still overrides it when his judgment says something’s off. That matters.Because the biggest shift in the last few years is not that investing got easier. It’s that you can now know more, faster. You can: compare founders against thousands of past companies catch inconsistencies in a data room identify fragility before it shows up in traction rank opportunities before you ever get on a call But the human part still matters. Founder quality. Timing. Vision. Whether something is a feature or a platform. Whether the company can actually compound. That’s the hard part. And maybe that’s the point: AI can sharpen the signal. It can’t replace judgment. Still figuring this out. Hear the rest of the conversation: https://lnkd.in/g8DHkvBA

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One of our latest companies DN Capital - directionally this is where agentic AI can help augment humans in the workplace rather than replace humans. Congratulations to our partner Guy Ward Thomas and the rest of the DN Capital AI investment team on this newest portfolio company. Nenad Marovac Thomas Rubens Ian Marsh Gülsah Wilke Raoul Oscar F. Jack Pierrepont Maddie Coughlin Celine Xiao

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Glad to contribute to this piece from the National Security Institute (NSI) Aviation became extraordinarily safe not because it anticipated every failure, but because it built institutions that investigate accidents and near misses, publish authoritative findings, and turn failures into collective knowledge. AI needs similar machinery: an independent, technically sophisticated, NTSB-like institution empowered to investigate significant incidents and near misses. We do not need consensus on every AI risk theory before building the capacity to learn from failure. Aviation did not eliminate accidents and then create a safety culture; it created a safety culture by refusing to waste an accident. #AI #NationalSecurity

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Two articles I've been thinking about together this week: Amir Kabir at Overlook VC on "the defining tension of 2026: extraordinary concentration at the infrastructure layer, extraordinary democratization at the application layer" Take a read: https://lnkd.in/gyaFg-nB And Isaac Arnold's framework for what actually makes an application layer company durable: workflow entanglement, domain specific knowledge, and data that compounds from usage rather than just intelligence. Take a read for yourself: https://lnkd.in/gSDXA-vH Amir identifies where the opportunity is, Isaac identifies why most companies building there won't capture it durably and what separates the ones that will.

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**Navigating the Fusion Frontier: General Fusion’s Path to Public Markets** The recent announcement of General Fusion's $1 billion reverse merger highlights a pivotal moment for companies in the fusion power sector. With over $300 million in funding through this deal, it sparks conversation about the resilience and strategic pivots necessary for startups facing challenges in fundraising. At ElevenX Capital, we recognize the volatility in emerging technologies like fusion power. This highlights the need for a measured investment approach that considers both technological potential and market readiness. How do you assess risk versus reward in high-stakes sectors like fusion? #investing #innovation #venturecapital #entrepreneurship

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