Unlike competitors feeling pressure to build proprietary AI foundation models, Apple can simply partner with providers like Google. This reveals Apple's true moat isn't the model itself but its massive hardware distribution network, giving it leverage to integrate best-in-class AI without the high cost of in-house development.

Despite analysts viewing live sports as a prime use case for the Apple Vision Pro, Apple's F1 partnership announcement omits plans for immersive 3D or spatial content. This failure to connect a major content acquisition with its new flagship hardware represents a significant missed opportunity to drive hardware adoption.

While no-code can help validate an idea, it inevitably leads to a growth-killing stall. Founders will hit a platform limitation that forces them to stand still for 3-6 months to rewrite the entire codebase from scratch. This sacrifices critical early-stage feature velocity and market responsiveness.

Luckey argues analysts misunderstand the Vision Pro's strategy. At $3,500, it's not a mass-market product. Its goal is to make VR highly desirable and aspirational. By solving the "want" problem first, Apple primes the market for future, lower-cost versions, avoiding the trap of making a cheap product nobody wants.

Apple's failure to provide immersive, 3D spatial video for its new F1 partnership is a major missed opportunity for the Vision Pro. Live sports are a primary driver for VR/AR adoption. Offering only a standard 2D broadcast in a virtual environment fails to create a differentiated experience that would justify the hardware's cost for hardcore fans and drive platform adoption.

By mandating its own WebKit engine and banning more capable alternatives on iOS, Apple prevents web applications from competing effectively with native apps, pushing developers toward its lucrative App Store ecosystem.

OpenAI's platform strategy, which centralizes app distribution through ChatGPT, mirrors Apple's iOS model. This creates a 'walled garden' that could follow Cory Doctorow's 'inshittification' pattern: initially benefiting users, then locking them in, and finally exploiting them once they cannot easily leave the ecosystem.

Despite the hype, AI's impact on daily life remains minimal because most consumer apps haven't changed. The true societal shift will occur when new, AI-native applications are built from the ground up, much like the iPhone enabled a new class of apps, rather than just bolting AI features onto old frameworks.

A conflict is brewing on consumer devices where OS-level AI (e.g., Apple Intelligence) directly competes with application-level AI (e.g., Gemini in Gmail). This forces users into a confusing choice for the same task, like rewriting text. The friction between these layers will necessitate a new paradigm for how AI features are integrated and presented to the end-user.