An ambitious research exploration into modeling an AI companion as an operating system kernel with 43 cognitive subsystems.
LEO represents an ambitious, conceptually deep exploration into treating AI companion software as a full operating system. It defined 43 granular cognitive subsystems, an atomic rollback boot sequence, and a multi-tier memory architecture. However, an exhaustive audit revealed an acute implementation reality gap: 281 direct-database violations bypassed the CMMU gatekeeper, test suites relied excessively on stubs, and interface over-engineering accumulated substantial technical debt.
Can an intelligent companion be structured as an operating system—with a Kernel, CMMU (Cognitive Memory Management Unit), Interconnect, and Scheduler—without collapsing under architectural drift and integration debt?
Specified an elaborate 43-subsystem OS architecture with multi-database persistence.
Fast development bypassed memory gatekeepers, introducing 281 direct-database calls.
Discovered test suite passing 297 tests while masking 11 broken real-world integrations via mocks.
Preserved research insights and cataloged the divergence as foundational lessons for subsequent systems.