THE LIVING ARCHIVE

From punched cards to autonomous collaborators: the ideas, people, languages and systems that taught machines to follow—and increasingly interpret—human intent.

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Tag: long-running-agents

Designing for Agentic Persistence: How Long-Running AI Should Maintain Motivation Across Interruptions

Long-running agents need persistent goals, checkpoints, compaction, structured notes, failure recovery, and interruption-aware motivation so the user can pause without losing continuity or being pressured back into the loop.

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Checkpoints and Save States for Long-Running AI Tasks

Checkpoints and save states let long-running agents pause, resume, recover, and hand off work without losing goals, decisions, approvals, or evidence of what already happened.

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