Sam Altman believes incumbents who just add AI features to existing products (like search or messaging) will lose to new, AI-native products. He argues true value comes not from summarizing messages, but from creating proactive agents that fundamentally change user workflows from the ground up.
Don't view AI as just a feature set. Instead, treat "intelligence" as a fundamental new building block for software, on par with established primitives like databases or APIs. When conceptualizing any new product, assume this intelligence layer is a non-negotiable part of the technology stack to solve user problems effectively.
Don't just sprinkle AI features onto your existing product ('AI at the edge'). Transformative companies rethink workflows and shrink their old codebase, making the LLM a core part of the solution. This is about re-architecting the solution from the ground up, not just enhancing it.
Incumbent companies are slowed by the need to retrofit AI into existing processes and tribal knowledge. AI-native startups, however, can build their entire operational model around agent-based, prompt-driven workflows from day one, creating a structural advantage that is difficult for larger companies to copy.
Sam Altman's deal-making prowess isn't just skill; it's fueled by leverage from leading OpenAI, the breakout AI company. Partners feel compelled to collaborate, fearing shareholder backlash for missing the 'next Google', which gives Altman a significant advantage.
Competing in the AI era requires a fundamental cultural shift towards experimentation and scientific rigor. According to Intercom's CEO, older companies can't just decide to build an AI feature; they need a complete operational reset to match the speed and learning cycles of AI-native disruptors.
Incumbents face the innovator's dilemma; they can't afford to scrap existing infrastructure for AI. Startups can build "AI-native" from a clean sheet, creating a fundamental advantage that legacy players can't replicate by just bolting on features.
Sam Altman argues that the key to winning is not a single feature but the ability to repeatedly innovate first. Competitors who copy often replicate design mistakes and are always a step behind, making cloning a poor long-term strategy for them.
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.
YC Partner Harsh Taggar notes a strategic shift where new AI companies are not just selling software to incumbents (e.g., an AI tool for insurance). Instead, they are building "AI-native full stack" businesses that operate as the incumbent themselves (e.g., an AI-powered insurance brokerage).
OpenAI's CEO believes a significant gap exists between what current AI models can do and how people actually use them. He calls this "overhang," suggesting most users still query powerful models with simple tasks, leaving immense economic value untapped because human workflows adapt slowly.