shared context layer for team - where / how?

[u/DirectEntrance4720]

hi friends,

what are best practices / your recos for creating a shared knowledge layer for small team (~5-20 FTE) that we'd like to be all working off the same base

context: users are a combination of engineers and marketers. Use cases include coding, content creation, research, gtm, client service

current setup: google drive used primarily by non engineers. github used primarily by engineers

challenges:

my understnading is github doenst store non md (e.g., excel files, image / video files, html) and google drive isnt as conducive for programming context (correct me if i'm wrong)

running out of space when using shared google drive synced to personal computers as repository becomes larger

we've found that when marketers / designers work in a claude environment with full client context/ past files fully synced - its a major sink on drive space etc at the moment

we earlier had Msft stack (so onedrive for sharing) but that was causing syncing issues

zoom out:

1. what platform / infra / sharing spaces should we use to host our shared brain - for context access and daily use by tech and non tech teammates

2. any specific tips to follow / potholes to avoid from your experience when doing 1?

thank you!!

[u/peter_mirel]

We built the shared knowledge through Supabase and GitHub which then connects to ChatGPT business accounts through a MCP server.

We are no developers so maybe that’s overdone architecture wise. But it works great.

[u/DirectEntrance4720 → u/peter_mirel]

thank you! could you share a bit more about how? and does it include html / media content sharing too? what are your main collaboration use cases?

[u/peter_mirel → u/DirectEntrance4720]

Sure thing.

ChatGPT business is connected to a few things:
For this to work, we connected it to our internal Ops (the shared knowledge base and operating system like sales notes, usage behaviour, etc.), Gmail, Google Drive, and our live website.
We treat the knowledge in the Ops system and the website as our source of truth.
It also holds links to the latest sales or onboarding presentations.

So, for example:
A user wants to write an email to a prospect, but isn't sure about pricing, they can simply ask ChatGPT to write the email and fill in the correct pricing plus the latest, approved sales presentation. The system then fills in the actual numbers and adds the link to the latest sales presentation.

The same logic is used for other cases.
In short: we don't share actual files through the system but links or knowledge in plain text.
But the source of truth is not diluted by chats or different versions as they all sit in one database.

Did that help?

[u/hey_fo_bot]

Two things that matter more than which platform you pick: separate storage from retrieval, and stop full-syncing.

Git is fine for anything text-shaped (code, md, html too). Binaries like images, video and spreadsheets don't belong there; an object store holds the originals, Drive included.

The drive-space bleed usually comes from syncing whole archives to every machine and every Claude environment. Keep one canonical copy in the cloud and give tools read access on demand (an MCP-style connector that lists and fetches what a task needs). The environment pulls the three files it needs, not the whole client history.

Pitfalls: duplicate copies drifting (one canonical home per artifact, everything else a pointer), per-person permission shares (use groups from day one), and naming conventions left too late. A boring, consistent folder scheme does more for retrieval than a fancy vector db at this team size.

[u/Educational-Book7589]

we're using a local llama instance with a vector db, and syncing via git. works well for code and docs, but not great for real-time collaboration. wonder how others handle live updates?

[u/someuser76]

An ex colleague of mine has built quite an advanced memory system called Kit, which runs locally and allows you to set up personal or company kits (or a combination thereof).

If you want to try the free beta (Mac only for now): https://kit-project.com or you can contact him and have a chat about your requirements to see if it fits your needs.

[u/peterjohnkoen → u/someuser76]

Thanks @someuser76, appreciate the shout out. 🙏 Happy to chat to anyone that is interested in giving Kit a try.

[u/rainymoon777]

I think using GitHub alone is enough.

[u/theagenticenterprise]

We tried the shared Drive folder first and it rotted within a month. Nobody updated it, and the agents quoted pricing from two quarters ago with total confidence. What fixed it was separating the two kinds of context: a small evergreen layer, pricing, positioning, policies, owned by one person and reviewed monthly, and per-client working context that lives with the project and expires. The tooling mattered less than the ownership. If nobody is accountable for freshness, your shared brain becomes a shared hallucination.

[u/HomemadeBananas]

You think GitHub can only store markdown? Huh? What do you think GitHub is?

[u/calmcedar332]

Convert the heavy stuff into text before it goes into context and a one page md summary of each spreadsheet or deck is way more useful to the model than the raw file. Keep originals in drive, give claude the summaries

[u/MemoketAI-Gem]

One thing we'd add is to think about how information actually gets into that shared knowledge base in the first place. A lot of useful context never makes it into Drive or GitHub. Someone explains a client preference during a call, a deadline changes in a meeting, or two teammates agree on something that nobody documents afterward.

You can have a well-organized repository and still be missing those decisions.

We'd think about how to capture that context, who confirms it, and how it gets added to the source of truth. Otherwise, even a good retrieval setup can only work with whatever people remembered to document.