Alex Yarosh Get Free Snapshot

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@tjrobertson52

2025-12-03

What Company Data Should You Share With AI? Connecting Google Drive to ChatGPT sounds great until the model starts pulling random call transcript chatter into your strategy...

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If you're using a large language model for work, Gemini, ChatGPT, Claude, it's important that you give it the necessary context. All the model makers understand this, which is why all of them have made it easier to connect things like a Google Drive.

But I keep seeing people making the same mistake. At least once a week I hear of someone very excited that they've connected Google Drive to ChatGPT or Gemini or Claude and they've given it access to all their call transcripts and documents and now they can ask questions and produce strategy and brainstorm with all that context in mind. And this is great.

It really is. You'll get much more useful high quality output from the model once it has that context.

But as someone who's been doing this for about two years, I see people making the same mistakes. The problem is when you give the model that much unstructured content, we're talking about hundreds of documents in some cases, you're leaving it up to the model to decide what context is relevant for a given prompt. Now some models are better at this than others.

Gemini 3 is the best at handling messy context. ChatGPT is the worst. But even Gemini is gonna make mistakes.

It's gonna pull in context that's irrelevant and it's gonna miss important relevant context.

The biggest issue seem to come when people include Rock Hall transcripts. Sure, these call transcripts are gonna contain a lot of useful information. They're also going to include random conversations about what everyone did over the weekend.

Some of the information will eventually be outdated and there might be internal conversations that you don't want in public facing content. So while having access to all this context might be better than no context, there's a much better way to do it.

I recommend setting up a project in Claude or Gemini and then just take the time to decide what context you actually want the model to have. Now, based on what you're asking the model to do, you'll want it to have a different set of context. So the second half of the strategy is to clearly label all the documents you give it and then provide clear instructions on when to use each document.

It does take a little time to set this up and maintain the project, but you can have the project help you with that part as well. Some documents can just be added as is. For example, the transcripts of each of these videos is added to one master document.

And in the project instructions, we tell Claude or Gemini to pull from these transcripts whenever it needs an opinion from me. But for messier documents like a call transcript, you can just give the transcript to the project, ask it to carefully review the call transcript and consider any existing documents in the project that need to be updated or amended.

We maintain Projects like this for each of our clients, it's hard to exaggerate what a difference it makes.

Source Intelligence

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Large AI workspaces need curated context because unstructured document archives leave relevance selection to the model.

2 related signals · AI context systems / Call transcript handling

  • Build project knowledge bases with selected documents, clear labels, and instructions for when each source should be used.
  • Review call transcripts into structured project updates before adding them to an AI workspace, and keep messy originals separate.

Questions this source answers

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What is this source mainly about?

Large AI workspaces need curated context because unstructured document archives leave relevance selection to the model.

What should an operator take from it?

Build project knowledge bases with selected documents, clear labels, and instructions for when each source should be used.

Which topics does it connect to?

This source is connected to AI context systems, Call transcript handling.

What public evidence supports the record?

If you're using a large language model for work, Gemini, ChatGPT, Claude, it's important that you give it the necessary context. All the model makers understand this, which is why all of them have made it easier to connect things like a Google Drive. But I keep seeing people making the same mistake...