in-process

This paper introduces 'memory in the loop', where language agents repeatedly access an in-process associative store on every reasoning step. By using a fast (∼100μs) in-process store, the per-step retrieval cost is reduced by three orders of magnitude compared to networked stores, eliminating redundant actions and improving recall across GPT-5-class models.