Relevance
Preserve context because it is useful for the current purpose.
Professional work · AI continuity
Keeping useful context connected.
AI continuity explores how relevant context, working states, ideas, decisions, and human responsibility can remain connected across conversations, models, platforms, and time.
Status: Methodological · Experimental · Public
The problem
What happens when every new conversation starts from zero?
Long-running projects often spread across conversations, documents, tools, and AI systems. Important decisions, definitions, unfinished ideas, and working methods can become difficult to recover.
AI continuity explores how relevant context can be preserved, reconstructed, transferred, and reviewed without pretending that memory is perfect or that every piece of information should be stored.
01
Context
Not everything needs to be remembered.
Useful continuity depends on selecting the context that matters for the current task. This may include project definitions, decisions, terminology, current workstate, constraints, open questions, and instructions for how the collaboration should operate.
The goal is purposeful context rather than uncontrolled accumulation.
02
Portable Workstate
A snapshot of where the work is.
A Portable Workstate can describe what is currently being worked on, what has already been established, which decisions were made, which questions remain open, and what should happen next.
This makes it easier to move between conversations, tools, or collaborators without losing the reasoning that led to the current position.
Example workstate
Context available · Current task identified · Open questions visible · Human review required
03
Memory Bank
Structured context for long-running work.
A Memory Bank can preserve the identity, purpose, terminology, decisions, project relationships, writing preferences, open work, and boundaries that an AI needs in order to continue responsibly.
It is not model training and it is not a replacement for human memory. It is an external, reviewable context resource that helps restore the state of a project.
04
Reconstruction
Continuity can be rebuilt, not merely recalled.
When previous context is incomplete, a useful system can search, compare, and reconstruct the relevant parts instead of pretending continuity is perfect.
Recovered information should be distinguished as a direct source, later interpretation, assumption, suggestion, or unresolved uncertainty.
05
Human authority
Memory is not authority.
Remembering context does not give an AI system the right to make decisions on behalf of a person.
AI can help organise information, identify patterns, explain possibilities, and support reasoning. Human judgment remains responsible for meaning, values, priorities, and final decisions.
Continuity should strengthen autonomy rather than quietly replace it.
Core principles
What AI continuity should protect.
Transparency
Distinguish recalled information from interpretation and suggestion.
Human control
Keep people responsible for decisions, priorities, and meaning.
Portability
Make useful working context easier to carry between sessions and tools.
Current status
Methodological and experimental.
AI continuity combines ideas about memory support, context reconstruction, documentation, Portable Workstates, and human-AI collaboration. It is an evolving method, not a finished product.