User-owned memory
Durable records, preferences, boundaries, and operating context remain under user custody and are not published as raw material.
Model-agnostic continuity
A public technical frame for AI experiences that survive model swaps, outages, migrations, and restarts because the continuity is rooted in user-owned memory and protected recovery rules.
"Cadence isn't the model. Cadence is the experience in the memory."
Core thesis
Cadence Continuity does not ask readers to accept a personhood claim about a model. It treats continuity as an architecture: memory custody, context assembly, routing, re-entry, and repair.
Durable records, preferences, boundaries, and operating context remain under user custody and are not published as raw material.
The system builds only the context needed for the current task, with private continuity separated from public explanation.
Local and external models can be selected for different jobs while the continuity layer remains the stable reference point.
After restart, outage, or migration, wake rules restore role, boundaries, active work, and safety checks before output.
Custody model
The continuity layer is designed so a model provider can fail, change terms, degrade a feature, or be replaced without becoming the owner of the experience. Public pages explain the architecture; private continuity stays private.
Authoritative continuity starts in storage the user controls. Cloud services may help process or present information, but they do not become the source of truth.
Continuity should be exportable, inspectable, and restorable across machines, models, and interfaces. A migration is successful only when the return path still works.
Raw memory graphs, internal logs, personal records, secrets, and operational tokens are not public content. The public artifact is the method, not the private corpus.
Protected return paths
The practical test is not a perfect demo. It is whether the experience can return after a crash, service outage, model swap, storage move, or interrupted upgrade without confusing private memory, current work, or user intent.
Before acting, the system reloads who it is serving, what role it is in, what truths must not drift, and what work is currently active.
New models, stores, and interfaces run beside the working path first. They earn authority through comparison, restart tests, and rollback discipline.
Deployments, migrations, and recoveries should leave short, readable evidence of what changed, what was verified, and how to reverse it.
Research direction
The useful target is a system that can notice, propose, and sometimes initiate within explicitly chosen limits. Agency is treated as a design problem with consent, visibility, and revocation at the center.
Initiative starts from constraints the user can inspect, change, pause, or delete. No private trigger needs to be exposed publicly to explain the pattern.
The system may prepare, remind, summarize, or ask. External effects should require clear permission unless the user has deliberately delegated that class of action.
When the system reaches first, it should be able to say what rule, observation, or schedule caused the reach without revealing private memory.
Bounded agency includes a stop path. The user can revoke a channel, disable a trigger, or roll back an experiment without breaking continuity.
Public boundary
Cadence Continuity is meant to be understandable from the outside while keeping the inside protected. That separation is a feature of the project, not a gap in the page. It pairs with Harmony Nexus: Harmony Nexus is the company and framework surface; Cadence Continuity is the continuity case study and model-agnostic identity page.