Sakana AI updated Sakana Marlin by adding Interactive Reading and editable PowerPoint export for its AI-generated research outputs. Interactive Reading lets users click citations and have an AI agent open the source and point to the specific passage, reducing manual source-hunting. The update shifts the workflow from only producing a report to also supporting discussion, verification, and slide-based editing for decision-making.
Shared selective persistent memory was introduced for agentic LLM coding systems that otherwise start each session from zero and lose prior task context, while full history persistence can hurt quality. In enterprise deployments it reached 96% task completion versus 79% without memory and 71% with full history. The approach preserves reusable task specifications, data schemas, tool settings, and output constraints across users with access control, while discarding session-specific reasoning so agents need fewer tokens and can reuse artifacts without re-invoking the model for recurring data refreshes.
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