What carries forward?
How should a system retain context, update a memory and respond to a correction? What would let a person understand and control what carries into their next conversation?
Technology. Human experience.
The conversations in between.
What changes when a conversation lasts for weeks or months? Explore memory, continuity, attachment, shifting expectations and safety across repeated human–AI interactions.
Here, we use “ultra-long-horizon interaction” to frame questions about sustained human–AI conversations. It is a theme for investigation, with no fixed duration threshold implied. Companions are a particular interest, alongside tutors, assistants and other systems people return to over time.
How should a system retain context, update a memory and respond to a correction? What would let a person understand and control what carries into their next conversation?
How might trust, attachment and expectations develop through repeated use? How do we study the experience without assuming the same effects for every person?
How can we assess patterns across sessions, changes in behaviour and the effects of model updates? What would count as evidence of benefit or harm over time?
How should consent, data retention and user control work across a continuing interaction? What happens when a service changes, ends, or loses information a person expected it to remember?
These readings approach different parts of the question. Their methods and timescales differ; a memory benchmark and a study of people’s experiences answer different questions.

Anna’s forthcoming book asks what really happens in very long human–AI conversations. It sits alongside the wider reading here as a contribution to the discussion.
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