Continuity changes the work.
A useful system should not have to rediscover the project every morning. Memory, decisions and provenance belong in durable infrastructure, where context can be retrieved and checked.
OUR THINKING / THE PREMISE
Intelligence
deserves context.
The lab explores AI as a collaborator with initiative and accountability. This is an engineering direction, grounded in what systems can actually do.
Initiative needs a boundary.
An agent can propose and prepare work. Its authority comes from explicit permissions and the risk of the action. Decisions should leave evidence, and consequential changes need a path back.
Disagreement is information.
A system is useful when it can challenge an assumption with evidence. A human can do the same. The objective is better work, reached through questions that can be tested.
Measure what happened.
A convincing answer is not a completed task. We distinguish proposed, implemented, tested and deployed. Failed experiments belong in the record too.