Chris Dixon – The Future of Tech - [Invest Like the Best, EP.69]

Episode Summary

Executive Summary: Patrick O’Shaughnessy interviews Chris Dixon about how software, networks, and crypto reshape technology, investing, and institutions. Dixon argues that open, malleable systems—especially the internet, blockchain, AI, and new computing platforms—can counter centralization, create new markets, and unlock the next decade of innovation.

Main Topics: Philosophy as a lens on technology (Priority: 6/5): Dixon traces his path from philosophy of mind and logic to technology and investing. Technology’s impact on welfare (Priority: 8/5): He argues tech displaces jobs short term but raises living standards and creates new work over time. Networks and internet architecture (Priority: 9/5): He frames computer science around algorithms and network design, emphasizing software’s flexibility. Centralization vs open platforms (Priority: 10/5): He contrasts the benefits of big tech convenience with the innovation risks of concentrated control. Crypto as a new internet layer (Priority: 10/5): He views Bitcoin and Ethereum as early infrastructure for open value networks and programmable money. AI and new computing platforms (Priority: 9/5): He sees AI, VR/AR, autonomous vehicles, and drones as compounding trends that will reshape computing. Venture investing and founder-market fit (Priority: 7/5): He explains how stage, market timing, and strong people drive early venture outcomes.

Key Arguments: Technology improves welfare overall despite short-term displacement, citing 200 years of better GDP, health, and poverty. Software differs from hardware because it has near-unbounded degrees of freedom and can reinvent itself. Open networks win when developers trust the rules won't change, as the internet did versus AOL. Big platforms provide real utility, but centralization risks stifling future startups and innovation. Crypto is still early infrastructure; today’s limitations are technical, not philosophical. AI progress is real again, with deep learning beating humans on key benchmarks. The next wave includes VR/AR, autonomous cars, drones, and other new computing platforms. At seed stage, people matter more because markets and products evolve; later-stage investing looks more like public-market analysis.

Data Points: Internet age: 25 years old - Dixon says the modern internet is still early in its development. Smartphone users: 3 billion people - He uses this to illustrate the scale of modern mobile computing. Ethereum throughput: 10 transactions a second - He cites this as a major current limitation of decentralized systems. WhatsApp acquisition size: 50 people - He references WhatsApp’s small team at the time of Facebook’s acquisition. WhatsApp acquisition value: 26 billion - He cites the Facebook purchase price as an example of leverage from small teams. ImageNet error rate: 20 to 30% - He describes the historical error rate before deep neural networks improved results. ImageNet performance: below human levels - He says deep neural networks beat human performance on the benchmark. AI research origin: 1940s - He notes AI as a field pioneered in the 1940s. Best app trends window: post-2012 - He says the top iOS apps had largely not changed since around 2012.

Pivotal Quotes: "find out what smart people are working on during the weekends, and you'll know what others will be doing years down the road" — Chris Dixon: His rule of thumb for spotting future tech trends "the rules of the game change later on" — Chris Dixon: He identifies this as the core risk in centralized platforms versus open networks "the idea that there won't be jobs is... just has not been the case in history" — Chris Dixon: He rejects the fixed-lump-of-labor view of technological change

Implications: Listeners should watch which tools attract builders, because today’s hobbyist experiments may become tomorrow’s dominant platforms and investment opportunities.