To survive against subsidized tools from model providers like OpenAI and Anthropic, AI applications must avoid a price war. Instead, the winning strategy is to focus on superior product experience and serve as a neutral orchestration layer that allows users to choose the best underlying model.

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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.

The inconsistency and 'laziness' of base LLMs is a major hurdle. The best application-layer companies differentiate themselves not by just wrapping a model, but by building a complex harness that ensures the right amount of intelligence is reliably applied to a specific user task, creating a defensible product.

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.

Top-tier coding models from Google, OpenAI, and Anthropic are functionally equivalent and similarly priced. This commoditization means the real competition is not on model performance, but on building a sticky product ecosystem (like Claude Code) that creates user lock-in through a familiar workflow and environment.

The novelty of new AI model capabilities is wearing off for consumers. The next competitive frontier is not about marginal gains in model performance but about creating superior products. The consensus is that current models are "good enough" for most applications, making product differentiation key.

In a crowded market where startups offer free or heavily subsidized AI tokens to gain users, Vercel intentionally prices its tokens at cost. They reject undercutting the market, betting instead that a superior, higher-quality product will win customers willing to pay for value.

Like Kayak for flights, being a model aggregator provides superior value to users who want access to the best tool for a specific job. Big tech companies are restricted to their own models, creating an opportunity for startups to win by offering a 'single pane of glass' across all available models.

As foundational AI models become commoditized, the key differentiator is shifting from marginal improvements in model capability to superior user experience and productization. Companies that focus on polish, ease of use, and thoughtful integration will win, making product managers the new heroes of the AI race.

In a space like AI where everyone uses the same models and tech moats are rare, competing on technology is futile. The winning strategy is to ignore the competition, focus intensely on a narrow ideal customer, and build an amazing product vision tailored specifically to their needs.

The AI value chain flows from hardware (NVIDIA) to apps, with LLM providers currently capturing most of the margin. The long-term viability of app-layer businesses depends on a competitive model layer. This competition drives down API costs, preventing model providers from having excessive pricing power and allowing apps to build sustainable businesses.

DevTools Must Differentiate on Product, Not Price, to Compete with Model Providers | RiffOn