Project continuity
What is project continuity?
AI made it normal for a project to pass through many hands: yours, a teammate’s, an agent’s. What did not become normal is keeping the project whole between them.
Project continuity is the ability to resume a project with its current state, history and rationale intact, regardless of which human, AI, tool or session picks it up next.
Sessions end. Projects don’t.
Work with AI happens in sessions. Each conversation starts from zero, does real work, then closes. The project is different: it lasts across dozens of those sessions, across model upgrades, tool switches and handovers between people.
When the session is the only container, everything the session learned dies with it. The decisions lose their reasons. The unfinished work goes invisible. The next session, human or AI, rebuilds a partial version of the project from scratch.
Continuity is what carries the project across the gap.
What a project needs to continue.
A project context should include the decisions and their rationale, the work still open, the documents that carry durable knowledge, and the history of how the project changed over time.
Decisions
The intentional past. What was chosen, why, and which alternatives were ruled out. A decision without its rationale is a rule waiting to be broken by accident.
Open work
The present. Tasks and unresolved threads that stay visible until someone actually closes them, so the project always knows what needs attention now.
Documents
The durable knowledge. Not every note, but the documents the project depends on, kept with their versions and their origin.
Sessions
The movement. What connects one state of the project to the next: what changed, who moved it, where the work stopped.
Decisions preserve the why. Open work preserves the present. Documents preserve the knowledge. Sessions preserve the movement.
What project continuity is not.
Not AI memory
AI memory helps an agent remember facts. Project continuity helps a project preserve its state, history and rationale so that someone or something else can pick it back up later.
Not project management
Plans, deadlines and boards organize the future. Continuity keeps what already happened, why it happened, and what is still unresolved. Both are useful. They answer different questions.
Not documentation discipline
A perfect wiki asks everyone to write it and keep it current. Continuity is captured where the work happens, so the record survives even when the discipline slips.
Palimpse does not replace any of these separately. It links what lets the project be resumed without reconstruction: the state, the history and the rationale, in one place.
AI memory vs project continuity, compared What AI project memory misses
How continuity works in practice.
Continuity only works if it costs almost nothing. In Palimpse it takes two gestures around the work you were going to do anyway.
Start briefed
Ask your AI to pick up the project.
catch_upreturns what changed since the last visit, with open tasks on top and the project’s durable memory alongside. No re-explaining, no archaeology through old chats.Work as usual
In Claude, ChatGPT, Cursor or any compatible MCP client. Palimpse connects once over MCP with OAuth and stays underneath the work. How the MCP connection works.
End with a record
log_sessionkeeps the summary, the decisions with their rejected alternatives, the documents touched, and the tasks opened or closed. The next session starts from that new state.
The history becomes a by-product of the work.
Give your project its continuity.
Palimpse is free for solo work and connects to the AI tools you already use. Start a project today, and let every next session pick it up exactly where it stands.