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.

A 'dam' represents pent-up demand where users are frustrated and merely 'coping' with the status quo. Introducing a 10x better solution, often via new tech, doesn't create demand; it bursts the dam, releasing a flood of customers who see it as a magical fix for a problem they already have.

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.

A slightly better UI or a faster experience is not enough to unseat an entrenched competitor. The new product's value must be so overwhelmingly superior that it makes the significant cost and effort of switching an obvious, undeniable decision for the customer from the very first demo.

Users will switch from an incumbent if a competitor makes the experience feel effortless. The key is to shift the user's feeling from maneuvering a complex 'tractor' to seamlessly riding a 'bicycle,' creating a level of delight that overcomes the high costs of switching.

To appeal to the "layperson" rather than tech early adopters, Comet's designers made the core browser experience familiar, like Google Chrome. This reduces cognitive load, allowing users to focus their limited learning bandwidth on the novel AI features, even if it disappoints power users expecting a radical redesign.

While OpenAI has strong brand recognition with ChatGPT, it's strategically vulnerable. Giants like Google and Microsoft can embed superior or equivalent AI into existing products with massive user bases and established monetization channels. OpenAI lacks these, making its long-term dominance questionable as technical differentiation erodes.

To win mainstream adoption, privacy-centric AI products cannot rely on privacy alone. They must first achieve feature parity with market leaders like ChatGPT. Users are unwilling to sacrifice significant convenience and productivity for privacy, making it a required, but not differentiating, feature.

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.