The landscape that made OpenAI, Anthropic, and Google AI powerhouses is cracking. Startups now treat foundation models as interchangeable commodities, swapping between GPT, Claude, and Gemini mid-development without users noticing. This shift threatens to turn today's AI leaders into low-margin suppliers in what one founder calls "selling coffee beans to Starbucks."
The question that's haunting AI boardrooms from San Francisco to Seattle isn't about artificial general intelligence anymore - it's simpler and more existential: Do foundation models actually matter?
The answer emerging from startup conversations across Silicon Valley suggests a fundamental shift that could upend the entire AI power structure. Companies that once competed fiercely to access the latest OpenAI or Anthropic models now casually swap between them like switching cloud providers.
"For startups, it no longer matters whether their product sits on top of GPT-5, Claude or Gemini," explains TechCrunch's Russell Brandom, who's been tracking this seismic shift. "They expect to be able to switch models mid-release without end users noticing the difference."
This commoditization became crystal clear at last week's Boxworks conference, where the entire focus centered on user-facing software built on top of AI models rather than the models themselves. The message was unmistakable: the real innovation happens at the application layer, not in the foundation.
The technical reality driving this shift cuts to the core of AI economics. Pre-training - that initial process of teaching AI models using massive datasets - has hit what researchers call "diminishing returns." The scaling benefits that made companies like OpenAI untouchable are slowing down, while post-training and reinforcement learning have become the new frontiers of progress.
"If you want to make a better AI coding tool, you're better off working on fine-tuning and interface design rather than spending another few billion dollars worth in server time on pre-training," notes the analysis. Anthropic's Claude Code success proves foundation model companies can excel in these areas too, but it's no longer an exclusive advantage.
The implications are staggering for an industry built on the assumption that foundation model companies would own the future. Throughout the AI boom, being bullish on artificial intelligence meant betting on , , and becoming "generationally important companies." Silicon Valley's platform thinking suggested these companies would capture the lion's share of AI's economic value.
