Call transcript handling

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...

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...