Let's say that you throw a big jar that Claude co-work and it breaks. You'll likely blame the model, but that's not where it broke. If you're new here, I'm Dylan. I run an AI consultancy and I've watched enough clients build these setups to know it's almost always the order, not the model. Anthropic, the company behind Claude, just published the four layers behind any serious setup. So, I'm going to walk you through them in order. And by the end, you'll know exactly which one you skipped and almost everyone skips at least one. So, let's get into it. Now, the setup that I'm going to walk you through is for a different types of situations. Most of you are either in the situation or will soon be in the situation in the coming weeks and months. And it manifests in two ways. Either you have tons and tons of files that are between small and medium in size. So, think five to maybe 50 pages in length for per document. And then maybe you have a couple hundred of those files within a given folder for a given task or topic. This in itself is extremely overwhelming for AI if not set up correctly. The other situation is where you have a few files, maybe 10 to 50 files, and those are maybe above 300 pages. So, there's a few of them, but they're enormous. Both of these situations AI really struggles with. But also at the same time, these are extremely valuable if you can set them up correctly because the AI doesn't decrease in value, it actually increases in value. And before you click away and think, "Oh, well, my setup's not that complex, so I don't need this." Right now, maybe your setup isn't that way, but most of the people I work with, they end up in this situation. Where in the beginning, their setup is very simple. It's just a few few files for a given activity. But over time, as they keep on doing that activity in that folder and weeks and months, etc., those files add up. And as they add up, their setup becomes more complex. And if they didn't set things up correctly in the beginning with the right infrastructure, i.e., the four layers I'm going to walk you through, the AI's intelligence degrades over time and it gets worse. But if done correctly in the beginning, the intelligence increases and it becomes more valuable to you. And that's what we want to focus on and that's what we want to mitigate in the beginning if you're not in the situation already. So, what are these four layers that Anthropic shared? Well, these are the four layers here. I'll walk you through in each in more detail, but as a quick summary, in first we have the instructions, and these aren't just prompts, they act more as guideposts to tell the AI where to look in the important rules. We'll talk more about that later. Then we have memory, and memory is where the AI can self-improve over time, remembering your preferences and facts associated with what you care about. And self-improve is important there, we'll talk more about that as well. Then we have skills, and we've already talked about skills in the past in previous videos, but these are basically systematized processes that we encapsulate into a folder that the AI can call at any given time and do that task perfectly to our standards. And then the fourth layer is connectors. Now, the issue with this is most people jump straight into the fourth layer right away, and that's connecting your AI to other systems. So, think your email, your calendar, etc. But if you add a bunch of connectors to your AI and you've skipped all these first three layers, there's a good chance that the AI is not going to effectively achieve the task the way you wanted it to, especially as the number of files in that folder s- So, let's walk through each one of these layers and how we can prepare for this. Quick pause in your regular programming. This video is brought to you by me, as always. Two things. First off, below is a 30-day AI insight series, completely free. You'll get 30 insights in your inbox of how you can apply AI to your business and your work. The second thing is if you'd like to work with me, below are a series of offerings to see if there's a good fit between the two of us. Now, let's get back to the video. Let's start with the first layer, which is instructions. So, in the blog post drafted by Anthropic, there's a quote in there that resonated with me. And in here it specifically talks about that root file, which is the claw.md file. So, if you're using Codelark, you're always going to have a claw.md in any given folder, cuz that's basically the system instructions, the thing that tells the AI what to do. The mistake people make here is in that file, they tend to have a really long file, so something that's 200-plus lines long. So, it has examples, instructions, all types of stuff. That's the first mistake you're making. The size of that file is critical, and you need to make sure it's extremely small. So, we want to keep it less than I'd say 100 to 50 lines. So, between 50 and 100 lines is the