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Boris Wertz
Backing mission-driven founders at the earliest stages
Boris Wertz is the founder and general partner of Version One Ventures, a prominent early-stage venture capital firm based in Vancouver, Canada. He is recognized as one of the leading tech investors in North America, focusing on mission-driven founders and innovative startups across various sectors, including Software as a Service (SaaS), marketplaces, cryptocurrency, and climate technology.
Background and Career
Wertz was born in Germany and began his entrepreneurial journey by founding an online marketplace for used and out-of-print books in 1999. This venture was later sold to AbeBooks.com, where he served as COO and managed a team of 60. Following the acquisition of AbeBooks by Amazon, he transitioned into investing, initially as an angel investor before establishing Version One Ventures in 2012. The firm currently manages over $250 million in assets and has invested in more than 100 startups, including notable companies like Coinbase, Dapper Labs, and Uniswap.123
Education
Wertz holds a PhD in Logistics from the WHU – Otto Beisheim School of Management, where he also completed his Master's degree in Business Administration. His academic achievements include being named the Pacific Ernst & Young Entrepreneur of the Year in 2005.134
Investment Philosophy
At Version One Ventures, Wertz emphasizes supporting early-stage companies that tackle significant challenges with innovative solutions. He is known for his strategic approach to investing, aligning fund size with investment strategy and focusing on emerging technologies and sectors.24
Overall, Boris Wertz combines extensive operational experience with a keen eye for potential in the tech landscape, making him a significant figure in the venture capital community.
Highlights
Monthly stablecoin transaction volume now at $1.25 trillion (!) - crypto is rapidly powering non-speculative use cases https://t.co/ahOT6HM4le

3 Years of ChatGPT: Where We Are With AI Today
This November marks 3 yrs since the launch of ChatGPT. Since then, innovation in AI has been relentless - perhaps one of the fastest cycles we’ve ever witnessed in tech. It’s worth pausing to reflect on where we are today and what we’ve learned. 👇
Fast vs. slow takeoff. One of the big debates over the past few years was whether we’d see a fast or slow takeoff toward “super-intelligence” — a state where AI continuously improves itself. Today, it seems clear that super-intelligence is arriving more slowly than the most optimistic predictions suggested.
The limits of LLMs. Early on, many assumed LLMs were the decisive step toward AGI, with progress simply a matter of scaling models and fine-tuning. While LLMs remain an extraordinary advance, the pace of improvement (as measured by benchmark scores) is now more incremental. We may be nearing the ceiling of what this paradigm can achieve.
Good news for startups. Both trends are encouraging for founders and the broader ecosystem. We’re unlikely to see a single model dominate everything. Instead, we’ll have multiple strong horizontal models, with thousands of consumer and enterprise applications layered on top. The structure may end up resembling the Internet: “winner-take-all” dynamics on the consumer side, “winner-take-most” in certain enterprise verticals, but ultimately a fragmented and diverse landscape.
Where value will accrue. Most value will likely concentrate at two ends of the spectrum:
- Close to the metal: chips and infrastructure for training and inference.
- Close to the customer: products with sticky adoption and deep integration into workflows.
The land grab. This is a land-grab moment. Everyone recognizes it, which means competition is fierce. Execution matters more than ever, and the quality of founding teams will be decisive in such an intense environment.
Today’s bottlenecks. Right now, AI is “middle-to-middle,” not yet end-to-end. Prompting and verification remain the two biggest bottlenecks. Startups that solve these pain points will be able to carve out real differentiation.
Technology + business model shifts. The most powerful disruptions happen when technology shifts align with new business models — think ad-supported Internet or SaaS subscriptions replacing perpetual licenses. We’re starting to see this in AI, with models like pay-per-resolution in customer service. Expect more experimentation ahead.
AI isn’t sprinting to AGI — it’s pacing into the mainstream. That means more room for founders to build, compete, and ultimately define what AI becomes.
