Knowledge retention has gotten surprisingly harder with AI. The work output of a researcher lives across individual sessions, files, and ...
摘要
Elicit 推出 Shared Projects，为团队提供持久保存相关会话、文件、来源、产物和既往工作的空间，使研究知识能随时间累积。不同成员可在各自会话中研究临床证据、竞争格局等不同主题，同时汇入同一共享知识库。该功能面向 Scale 和 Enterprise 机构开放，官方同时发布了产品博客。
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正文 · 原文
Knowledge retention has gotten surprisingly harder with AI. The work output of a researcher lives across individual sessions, files, and personal workflows. Much of it is not available to the rest of the team, leading to unnecessary duplication of effort.
That’s why we built Shared Projects. Shared Projects give teams a persistent home for related sessions, files, sources, artifacts, and prior work, so research knowledge can accumulate over time. For example, two researchers might investigate different topics, such as clinical evidence and the competitive landscape, in distinct sessions while still contributing to the same shared knowledge base.
We want the work teams do with AI to become institutional knowledge that other people can find, understand, and reuse. Instead of every question starting from a blank slate, the work done today can serve as useful context for the work that comes next.
Read the product launch blog here: https://elicit.com/blog/ai-powered-research-is-now-multiplayer
Shared Projects are available for Scale and Enterprise organizations.
来源：Elicit · x.com
引用原文
elicitorg. Knowledge retention has gotten surprisingly harder with AI. The work output of a researcher lives across individual sessions, files, and ...[EB/OL]. (2026-09-03)[访问日期]. https://x.com/elicitorg/status/2095527745388482969.