The core architecture for building super-intelligent systems will be standardized within the next few years.
Future innovation will move away from general model growth toward domain-specific post-training and product-led optimization.
The foundational blueprint for super intelligence is nearing completion.
Post-training and domain-specific refinements are the primary vectors for future performance gains.
Significant business value will emerge from deep, vertical integrations rather than broad general intelligence.
The AI landscape is shifting toward specialized players who prioritize product-level optimization within their niche.
This perspective is highly significant as it pushes back on the 'one model to rule them all' narrative. It suggests that once the base technology is commoditized, the competitive moat shifts entirely to proprietary workflows and specialized data tuning.
While most market excitement is focused on the rapid advancement of foundational frontier models, the real long-term advantage will likely belong to duller, less glamorous 'specialist' models that are invisible to the public but deeply embedded in the value chains of multi-billion dollar industries.
