How work becomes lasting project understanding.

A conversation can contain a decision without making it available to the next session. As work continues, separate accounts of the project can disagree or fall behind.

RAG retrieves information. Coyra maintains understanding.

Raw retrieval remains useful for discovery. Finding relevant source material and maintaining canonical semantic project state solve different problems: one helps discover evidence; the other keeps an explicit account of what is true now.

The Semantic State Cycle connects retrieval, AI work, reconciliation, and reuse. Each round begins with project understanding and ends by bringing that understanding up to date.

Consider a change to a project requirement. Your AI needs the current decision and the constraints around it, then must record how the finished work changes what the project knows.

Your AI starts from the Semantic Map: the structure of the project. It identifies the relevant areas and retrieves the minimum sufficient context for the work ahead.

For the requirement change, that means understanding the affected area and its governing constraints before acting. The map provides orientation; the selected context provides the detail.

Your AI interprets the goal, makes the semantic judgements, and executes the intended change. Completion freezes the account of what was done, ready for reconciliation.

Coyra runs no generative model. Your AI provides intelligence; Coyra provides persistence, structure, integrity, retrieval, and continuity.

Your AI integrates the resulting knowledge into canonical project state. For the changed requirement, it updates the affected understanding to reflect the result, rather than leaving the next agent to infer it from a completion note.

Completion and merge are separate. Merging commits the completed result into Project Context permanently; corrections then happen through new work.

Coyra does not ask the AI to keep the project up to date — it makes an out-of-date project unusable.

A node is an area of project understanding. A node with unreconciled work against it cannot be read by your AI. The only path to reading it runs through updating it, so the next read cannot silently reuse that unfinished understanding.

The updated requirement now belongs to the project, alongside the history of how it changed. The next task, session, or authorised agent starts from that shared state and repeats the cycle.

This is the continuity Coyra provides: work changes the project, and the resulting understanding stays available beyond the conversation that produced it.