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Ankur Crawford's thesis posits that as AI automates software creation, the cost to create code approaches zero, eroding incumbents' moats. The economic value will migrate from software and IT services to the underlying hardware and networking layers that enable this exponential innovation.
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As AI makes software creation cheaper and faster, the investment thesis shifts towards large industrial companies and CapEx-heavy sectors. These tangible assets are less susceptible to digital replication and may see significant margin expansion.
The ability to generate software with AI is like getting newly printed money before inflation hits. For a limited time, those who can leverage AI to build software cheaply have a massive advantage before the market reprices the value of software development downwards for everyone.
As AI and better tools commoditize software creation, traditional technology moats are shrinking. The new defensible advantages are forms of liquidity: aggregated data, marketplace activity, or social interactions. These network effects are harder for competitors to replicate than code or features.
The long-held belief that a complex codebase provides a durable competitive advantage is becoming obsolete due to AI. As software becomes easier to replicate, defensibility shifts away from the technology itself and back toward classic business moats like network effects, brand reputation, and deep industry integration.
As AI makes software development nearly free, traditional engineering moats are disappearing. Businesses must now rely on durable advantages like network effects, economies of scale, brand trust, and defensible IP to survive, becoming "unsloppable."
AI makes software incredibly easy to build and replicate, eroding traditional business moats. Chip Huyen argues the next frontier for durable value is in physical AI and robotics, where hardware development cycles and real-world complexities prevent instant copying.
The 50-year supremacy of asset-light software may be an anomaly. If AI makes software creation nearly free, economic value will shift back to the historical mean: tangible assets like infrastructure, energy, and regulated, liability-bearing businesses that touch the physical world.
As AI makes software creation accessible to everyone, Silicon Valley's historical edge—knowing how to code—disappears. The new defensible moats are assets like proprietary data, trust, or network effects, not the software itself, threatening the region's dominance.
As AI tooling advances, building complex applications becomes trivial, commoditizing software development. Defensibility can no longer come from technical execution. Companies must find moats in business models, distribution, or data, as simply 'building what customers want' is no longer a competitive advantage.
The economic value in AI is rapidly shifting away from foundational models, which are becoming commoditized far faster than anticipated. The real, sustainable business models are emerging at the infrastructure layer (cloud, chips) and the application layer, not in the foundational models themselves.
