Any content in every context. ADEPT first receives each unique element of content - be it typed characters or a link to some content (like a document, video or audio files) - independent of any identifying context. Only then, does it associate particular contextual uses with that element of content. Thereafter, ADEPT recycles each element of content within a defined method of contextualization to unify any knowledge in one instance.
This is the most speculative and critical of all claims about ADEPT - that there exists in ADEPT, a method of ordering patterns that mirrors the actual order of the universe. The goal is not to replicate the universe, but to model anything upon the same rules and patterns to which everything naturally conforms.
Time exists as a concept represented within ADEPT's Limited Iterative Ontological Notation rather than as a deterministic factor in the notation itself. This is a significant departure from the most influential and widespread ontological approaches in use today which make temporal considerations fundamental to their systematic ordering.
Counter-intuitively, limitation is the key to ADEPT's powerful expressiveness. In ADEPT, complexity is the product of simple constraints and iteration. This expression even extends to a theory of the mind that encompasses a means of modeling patterns for sensation, actual behavior, consciousness, and subconsciousness.
Built entirely upon abstraction, ADEPT approaches the modeling of anything using a single notation that remains constant regardless of where it is applied. The remarkable thing about ADEPT is just how flexible and analytically capable it is in any domain, even without customization.
ADEPT's limited and uniform design allows for automated indexing of any information. An ADEPT instance is quick to access, search, and analyze a unified knowledge store without needing a query language.