Personal essay argues the 'post-frontier-model' era favors small, specialized AI
This is a personal blog essay about what comes after the race for the biggest, most powerful AI models (). It argues that the era of one giant model dominating is fading, and what matters next is smaller, specialized models tuned for specific tasks and deployed cheaply.
The author claims that success will depend less on who builds the largest model and more on who integrates AI most effectively into real products and workflows. It also argues that falling (the cost of actually running a trained model) mean individual developers and small teams can now build things that used to require a large company's resources.
Key points
- Argues the post-frontier-model era shifts value toward small, specialized AI models
- Claims into real products/workflows matters more than raw model size
- Predicts falling let s build what once needed big-company resources
- Personal opinion essay — no concrete data or product announcements included