Yesterday, OpenAI opened access to the GPT-4.1 API. It’s a refined version of their flagship model—faster and architecturally closer to the concept of ‘agents.’ In parallel, the company officially announced it is winding down GPT-4.5, its most resource-intensive model, due to its excessive complexity and support challenges. With GPT-4.5, it seems they hit an architectural dead end.
We are at a point where models appear and disappear rapidly. They are becoming what they should be: tools, not landmark events. We have a growing catalog of specialized AIs: some calculate, others write code, plan tasks, or generate video. But the average user should not be expected to know and choose between every AI in existence. That paradigm defies the logic of good user experience.
The AI market is shifting toward a place where the holistic experience matters more than the individual model. This signals a move away from manually ‘switching networks’ and toward systems that think, propose, and adapt on behalf of the user. The interface in demand is not a dashboard asking, “What model should I turn on?” but one that understands the user’s goal and figures out how to achieve it.
This brings us back to the foundational challenge: designing the thinking system for AI. The rapid cycle of model releases and deprecations is a market-wide signal. The brief existence of an expensive and complex model like GPT-4.5 proves that simply scaling up is not the answer. The real work lies in building the cognitive architecture that makes these powerful tools truly useful.