The limits of intelligence are partly the limits of the architecture through which it must think.
Current models encounter semantic, knowledge, and structural bottlenecks. More computation can extend a trajectory, but it does not guarantee that the system can identify the point where its reasoning diverged, choose a better cognitive strategy, or incorporate a newly discovered abstraction.
Architecture of Intelligence makes cognition inspectable and revisable by design.
We study inference-time mechanisms, reflective decoding, memory, process supervision, rollback, and learned cognitive control. The aim is an architecture that can expose its reasoning boundary, intervene before a failure becomes an answer, and reorganize how it approaches the next problem.
Architecture is therefore not only a question of scale. It is the design of the operations through which a system understands, examines, learns, and acts.