Building on an AI model is like the early App Store. Sam Altman warns that thin wrappers risk being absorbed as features (like a flashlight app). To survive, startups must use AI as an enabler for a complex, defensible business (like Uber) before the platform makes them obsolete.
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The founder predicts that hyper-specific vertical AI solutions are too easy to replicate. While they may find initial traction, they lack a durable moat. The stronger, long-term business is building horizontal tools that empower users to solve their own complex problems.
Widespread anxiety from founders before OpenAI's Developer Day highlights a key challenge for AI startups. The fear is not a new competitor, but that the underlying platform (OpenAI) will launch a feature that completely absorbs their product's functionality, making their business obsolete overnight.
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.
OpenAI CEO Sam Altman now publicly hedges that winning requires the best models, product, *and* infrastructure. This marks a significant industry-wide shift away from the earlier belief that a sufficiently advanced model would make product differentiation irrelevant. The focus is now on the complete, cohesive user experience.
Counter to fears that foundation models will obsolete all apps, AI startups can build defensible businesses by embedding AI into unique workflows, owning the customer relationship, and creating network effects. This mirrors how top App Store apps succeeded despite Apple's platform dominance.
The founder of Stormy AI focuses on building a company that benefits from, rather than competes with, improving foundation models. He avoids over-optimizing for current model limitations, ensuring his business becomes stronger, not obsolete, with every new release like GPT-5. This strategy is key to building a durable AI company.
Perplexity's CEO argues that building foundational models is not necessary for success. By focusing on the end-to-end consumer experience and leveraging increasingly commoditized models, startups can build a highly valuable business without needing billions in funding for model training.
Most current AI tools are skeuomorphic—they just perform old tasks more efficiently. The real transformation will come from "AI-native" applications that create entirely new business models, just as Uber was an "iPhone-native" concept unimaginable before its time. The biggest winners will use AI to become the industry, not just sell to it.
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).
The existential threat from large language models is greatest for apps that are essentially single-feature utilities (e.g., a keyword recommender). Complex SaaS products that solve a multifaceted "job to be done," like a CRM or error monitoring tool, are far less likely to be fully replaced.
