Does syncing my own devices give coworkers editing access?

No. Device synchronization and collaboration between separate people are different requirements. Check the workflow for your graph version and test with a teammate using their own account.

Should our team share one Logseq login?

Use a supported workflow with separate accounts. A shared login makes it harder to control individual access and does not turn a personal synchronization feature into multiuser collaboration.

Can we collaborate without moving the whole research collection?

Yes. A reviewed summary or selected published page may be enough when colleagues only need to read. Name its maintainer and explain how readers can suggest corrections.

Will fenbs read our Logseq notes automatically?

No. Manually transfer the selected project facts and references you want to keep in fenbs. Connected assistants read the project context saved there, rather than automatically importing your notebook.

Logseq Collaboration: Share Notes and Keep Team Work Clear

Logseq collaboration depends on the graph version and whether teammates need to edit or only read. Use this setup and testing checklist to share useful notes while keeping team decisions clear.

July 27, 2026Updated October 21, 20265 min read

Logseq collaboration can mean editing a database graph together, publishing pages for others to read, or handing off selected notes. Choose the method after checking your graph version: database-graph collaboration and older file-graph Sync have different capabilities.

A graph is your collection of connected notes. Sharing that collection helps teammates see your thinking, but someone still needs to identify the approved conclusion and next action. fenbs can hold those team decisions, tasks and AI context while Logseq remains the place you develop the notes.

How should you start sharing a Logseq graph?

Choose one small project and make a separate test graph. Back up the original notes before changing their storage or sharing setup.
Identify whether you use a file graph or a database graph. Ask every participant to check their version before following the same instructions.
Decide whether colleagues need to edit together, read selected pages, or receive an occasional summary. Pick one sharing method for that job.
Agree on who maintains the shared material and where final decisions belong. Keep personal journal entries outside the trial.
Test with another person using their own account. Check edits or published content, attachments, access removal and recovery before adding important notes.

Write the intended outcome in one sentence: "Two researchers can edit the project notes, and the designer can read the approved summary." This makes the trial measurable. The shared team brain collection covers the broader problem of keeping team knowledge usable across people and assistants.

Which graph version supports live teamwork?

Start with the official version changes guide (opens in a new tab). It distinguishes database graphs from file graphs, which are maintained as Logseq OG. Instructions for one are not a reliable setup guide for the other.

The Logseq project README (opens in a new tab) describes database-graph Sync as RTC, meaning real-time collaboration. It also gives the current testing status and access route. Check that guidance before adopting it, and follow its recommendation to try a noncritical project with backups.

For a database graph, the documented starting steps are to set up an encryption password in Settings, choose Create db graph from the graph menu, and select Use Logseq Sync. Follow the database Sync instructions (opens in a new tab) for current access requirements. Confirm that your teammate can join with their own account before moving team material.

For older file-graph Sync, the official Sync setup guide (opens in a new tab) explicitly warns that it is not designed for multiple people using one graph together. That guide also warns against combining Logseq Sync with another service syncing the same folder. Sharing a folder or an account does not establish a supported multiuser editing workflow.

Do teammates need editing access or a reference copy?

Many requests to "collaborate in Logseq" only require a colleague to read a conclusion. Give that person the smallest useful record. Sending an entire research collection when they need a design rationale creates extra reading and may expose unrelated material.

Choose the sharing workflow by the outcome you need
Need	Possible route	What to verify
Edit notes together	Database-graph collaboration through the supported Sync workflow.	Access for each participant, current release guidance and a recovery test.
Read selected notes	Publish a selected page or provide a reviewed reference copy.	Exactly what readers can see and how you update or withdraw it.
Contribute occasional feedback	One person maintains the graph and collects feedback separately.	Who incorporates corrections and which copy is current.

The database documentation describes Logseq Publish (opens in a new tab) pages as read-only, with optional password protection and a separate republishing step for changes. Publishing therefore serves a different purpose from joint editing. Test the reader view rather than judging privacy from your own logged-in view.

If one person maintains the notes, label the shared summary with its owner and last review date. Ask readers to send corrections to that person so conflicting copies do not become competing instructions. For broader software choices, use the guide to apps for teams.

What rules keep shared notes understandable?

Agree on a short structure before adding more people. Each project summary should explain its purpose, point to supporting material and distinguish questions from agreed answers. A newcomer should understand the current situation without opening every linked note.

Label observations, proposals and approved decisions distinctly in ordinary language.
Attach a source location to a factual claim and a responsible person to an action.
Record why an answer changed instead of quietly replacing the old conclusion.
Keep private notes separate from the material everyone is allowed to use.

For example, a studio might gather three approaches to a client intake form. The project summary should say which approach the client approved and what still needs checking. The other approaches can remain useful research without looking like equally current instructions.

Adapt a few team norms examples to your situation rather than building a long handbook. When an agreement controls ongoing work, record it in fenbs Decisions and rules so connected assistants can read it with the project context.

How do notes become shared work for AI assistants?

Select the information that changes the next action: the goal, approved choices, open questions and remaining checks. Verify that summary against the notes before sharing it with an assistant. A useful summary preserves uncertainty; it does not turn an interesting suggestion into a team commitment.

Keeping that summary outside private conversations is the practical concern behind AI memory for teams. For the wider division of work between people and assistants, see AI collaboration for team work. Here the immediate job is making the outcome of your Logseq research usable by the next participant.

How fenbs helps

Give shared notes a clear next action

Manually add the checked conclusion from your Logseq notes to a fenbs project. Record the decision a person made, add tasks for the remaining work, and ask connected assistants to read that context before starting. Keep the research in Logseq and maintain the current work record together.

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What should you test before using real project notes?

Run the test with harmless sample content and write down the result. For joint editing, have two people change different notes and then the same note. Reconnect after one person works offline and confirm that both can find the expected result.

For publishing, inspect the shared link from a separate browser session. Check attachments, linked material and any password requirement. Revise the original, update the published copy through the documented workflow, and confirm the reader sees the revision.

Finally, recover the sample notes from a backup and test removing access. Record which devices and accounts you tested. A successful demo on the owner's laptop does not establish that the whole team can use the setup.

How to do this with fenbs

Create a free account. One person can start free, with no credit card; use a team kanban board when colleagues need shared access.
Add the project and a short AI context note containing the checked conclusion and selected references from Logseq. Transfer these manually.
Record the person's approved choices in Decisions and rules. Add tasks for the next actions and keep unresolved questions explicit.
Connect a supported assistant using the integration guides. Ask it to read the project context before working.
Before stopping, ask the assistant to save task progress and Where we left off, including what was checked and what the next session should do.

fenbs is not the right fit for editing a linked-note graph together; evaluate Logseq's collaboration workflow for that job. fenbs does not import or synchronize your Logseq graph. Use it when the team needs a common record of decisions and progress that its supported AI assistants can read.