As AI makes it easy to generate 'good enough' software, a functional product is no longer a moat. The new advantage is creating an experience so delightful that users prefer it over a custom-built alternative. This makes design the primary driver of value, setting premium software apart from the infinitely generated.

In the fast-evolving AI space, Vercel's AISDK deliberately remained low-level. CTO Malte Ubl explains that because "we know absolutely nothing" about future AI app patterns, providing a flexible, minimal toolkit was superior to competitors' rigid, high-level frameworks that made incorrect assumptions about user needs.

Simply offering the latest model is no longer a competitive advantage. True value is created in the system built around the model—the system prompts, tools, and overall scaffolding. This 'harness' is what optimizes a model's performance for specific tasks and delivers a superior user experience.

Instead of asking an AI to directly build something, the more effective approach is to instruct it on *how* to solve the problem: gather references, identify best-in-class libraries, and create a framework before implementation. This means working one level of abstraction higher than the code itself.

The obsession with lean methodology has created a market of low-quality, uninspiring software. In this environment, building a polished, considered, and beautiful end-to-end product is no longer a luxury but a true competitive advantage that stands out and inspires users.

Creating feature "modes" (e.g., "uphill mode") instead of exposing core mechanics (e.g., gears) creates a "nightmare bicycle." It prevents users from developing a general framework, limiting their ability to handle novel situations or repair the system.

According to CTO Malte Ubl, Vercel's core principle is rigorous dogfooding. Unlike "ivory tower" framework builders, Vercel ensures its abstractions are practical and robust by first building its own products (like V0) with them, creating a constant, reality-grounded feedback loop.

While professional engineers focus on craft and quality, the average user is satisfied if an AI tool produces a functional result, regardless of its underlying elegance or efficiency. This tendency to accept "good enough" output threatens to devalue the meticulous work of skilled developers.

The era of winning with merely functional software is over. As technology, especially AI, makes baseline functionality easier to build, the key differentiator becomes design excellence and superior craft. Mediocre, 'good enough' products will lose to those that are exceptionally well-designed.