Even with comparable model quality, user experience details create significant product stickiness for LLMs. Google's Gemini feels much slower than ChatGPT, and ChatGPT's mobile app includes satisfying haptic feedback. This superior, faster-feeling UX is a key differentiator that causes users to churn back from competitors.

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.

OpenAI found that significant upgrades to model intelligence, particularly for complex reasoning, did not improve user engagement. Users overwhelmingly prefer faster, simpler answers over more accurate but time-consuming responses, a disconnect that benefited competitors like Google.

Historically criticized for poor productization, Google is showing a turnaround. Gemini features like 'Dynamic View,' which creates interactive presentations from prompts, demonstrate a newfound ability to translate powerful AI into novel, user-centric products, challenging OpenAI's lead in product-led growth.

Despite access to state-of-the-art models, most ChatGPT users defaulted to older versions. The cognitive load of using a "model picker" and uncertainty about speed/quality trade-offs were bigger barriers than price. Automating this choice is key to driving mass adoption of advanced AI reasoning.

Large AI labs like OpenAI are not always the primary innovators in product experience. Instead, a "supply chain of product ideas" exists where startups first popularize new interfaces, like templated creation. The labs then observe what works and integrate these proven concepts into their own platforms.

Despite Google Gemini's impressive benchmarks, its mobile app is reportedly struggling with basic connectivity issues. This cedes the critical ground of user habit to ChatGPT's reliable mobile experience. In the AI race, a seamless, stable user interface can be a more powerful retention tool than raw model performance.

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.

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.