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Boris Cherny predicts AI will weaken traditional business moats. Switching costs decrease as AI can port systems, and process power is less defensible as AI can replicate complex workflows. However, foundational moats like network effects and scale economies will remain strong or grow in importance.
Permira's analysis suggests AI can replicate software features, eroding the value of high switching costs and recurring revenue. The new moat is whether a company owns critical data or is deeply embedded in workflows.
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.
Moats like migration pain, proprietary data, and UI lock-in are weakening. AI agents are flexible with interfaces and can easily replicate code and migrate data, forcing companies to find new, more distinct sources of value beyond simply 'owning' the customer.
The term "unsloppable" describes companies whose competitive advantage isn't their codebase, which AI can replicate. Instead, their strength comes from durable moats like hardware, strong network effects (Uber), exclusive IP (Disney), or physical infrastructure, which are difficult for AI-powered startups to clone.
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."
Software's main competitive advantage isn't code, but its deep integration into customer data and workflows, creating high switching costs. AI threatens this moat by automating those integrated tasks, reducing customer stickiness and pricing power.
As AI accelerates technological progress and shortens relevance cycles, traditional tech moats become less defensible. However, network effects—especially in complex, fragmented marketplaces—remain a powerful and durable advantage. An AI agent cannot be simply prompted to "create a network effect."
AI coding agents will make migrating between complex enterprise systems like SAP and Oracle dramatically easier and cheaper. This erodes the moat of high switching costs, forcing incumbents to compete on product value rather than customer lock-in, where they once held customers as "hostages."
As AI makes it possible to replicate any SaaS application's features within days, the defensibility of a product no longer lies in its engineering complexity. The real, enduring moat is the network effect, which AI cannot trivially reproduce.