The Karpathy CLAUDE.md File That 43,000 Developers Installed in 1 Week

• Channel: Jay E | RoboNuggets
• Video: Watch on YouTube
• Tags: robonuggets karpathy claude md

Overview

Full breakdown of Karpathy’s viral CLAUDE.md file — the configuration file that fixes the biggest problems every Claude Code user faces, listing top AI agent mistakes and how to avoid them.

Key Takeaways

• What if one file can fix the biggest problems that every cloud code user deals with? well, andrew carpathie listed down the top mistakes that every ai agent makes, and the single-cloud.md file just codified the fixes for those mistakes,
• Does it. and if you’re new here, my name’s jay, i spend over a decade working with brands you’re probably know, have been in ai’s main masters in data science, and now i run our ai solutions practice in one
• Analysis of how to work with agents better. it’s actually a pretty detailed one, and you can see here at the bottom that it already garnered 7, almost 8 million views at this point. now a lot of people took
• This developer forest, so credit where it’s due. and if you go to this skill, what it is is basically a single cloud.md file to improve cloud code’s behavior, which is derived from the observations from that tweet. and i
• Provides here are boiled down to 4 key principles, which i’ll talk about in a bit. and i think regardless whether you want to use this cloud.md file or not, learning about the principles will level up how you use
• To provide your cloud code with this github link. but if you’re already using cloud code, most likely you already have a cloud.md file, in which case it would be better for you to provide a more detailed prompt like
• Detailed installation prompt. i will link it down below if you need it. but as i mentioned, the core of this cloud.md file are these four principles that i think are worth learning no matter what ai agent you use.
• Mistake that these agents make is that the models make wrong assumptions on your behalf and just run along with them without checking. they also don’t manage their confusion, they don’t see clarifications, and they don’t surface inconsistencies. and so
• How you should work with agents better, it is basically this. it is almost always better to have your agent ask you questions in order to clarify intent before it starts building and coding things for you. and so just
• Is just give each of these agents a copy of this rubric application to illustrate the difference between the approaches of these agents with one of the agents not having this core paddy principle built in in the other agent
• To the rubric app. if we send it to both with this one to recap has that carpaddy skill and cloud.md already installed. and so now that both of those sessions are done, you can see this one with the
• This local host 10,01, this also confirmed to be that the toggle is in the top right bar next to search. and you can see that it is actually here. and it was able to implement that because it actually

Transcript

What if one file can fix the biggest problems that every cloud code user deals with? Well, Andrew Carpathie listed down the top mistakes that every AI agent makes, and the single-cloud.md file just codified the fixes for those mistakes, and almost 43,000 people installed it just in the past week. In this video, I’ll break down what this magical cloud.md does, how it improves your AI agent setup so that YouTube can use cloud as good as how Carpathie does it. And if you’re new here, my name’s Jay, I spend over a decade working with brands you’re probably know, have been in AI’s main masters in data science, and now I run our AI solutions practice in one of the largest AI communities globally. Let’s get started. So some time ago, Andrew Carpathie, who previously headed Tesla AI and also part of the founding team of Open AI, made this now viral tweet where he provided a good analysis of how to work with agents better. It’s actually a pretty detailed one, and you can see here at the bottom that it already garnered 7, almost 8 million views at this point. Now a lot of people took note of this tweet once again, because over the past week, what happened was this repo called Andrew Carpathie skills just shot up in popularity over at GitHub now at over 43,000 stars, and it was made and published by this developer forest, so credit where it’s due. And if you go to this skill, what it is is basically a single cloud.md file to improve cloud code’s behavior, which is derived from the observations from that tweet. And I think the reason why it became so popular and viral over the past week is simply because of how simple it is, it’s one cloud.md file that you just drop into your cloud code, and also the solution that it provides here are boiled down to 4 key principles, which I’ll talk about in a bit. And I think regardless whether you want to use this cloud.md file or not, learning about the principles will level up how you use your AI agents in order to make sure that you get the output that you want, whenever you work with cloud. But if you were looking to install this and try this out yourself, what you can simply do is to provide your cloud code with this GitHub link. But if you’re already using cloud code, most likely you already have a cloud.md file, in which case it would be better for you to provide a more detailed prompt like this, where you explain to your agent that you’re giving it a set of guidelines, call it carpaddy skills, and more importantly to suggest to you how you can best integrate it to your specific setup. So it is more detailed installation prompt. I will link it down below if you need it. But as I mentioned, the core of this cloud.md file are these four principles that I think are worth learning no matter what AI agent you use. So the first principle that it instills to your agent is that it allows cloud code to think before coding. And just refer back to what Andre wrote here. You can see he mentioned that the most common category of mistake that these agents make is that the models make wrong assumptions on your behalf and just run along with them without checking. They also don’t manage their confusion, they don’t see clarifications, and they don’t surface inconsistencies. And so the core idea for this principle is this. Without this rule, cloud assumes what you want with it, cloud asks first. And so if you were to boil down one key principle that you should follow in order to upgrade how you should work with agents better, it is basically this. It is almost always better to have your agent ask you questions in order to clarify intent before it starts building and coding things for you. And so just to illustrate this, what I have here are two cloud code sessions. This one doesn’t have the core paddy cloud.md. And this one is where I will though that cloud.md we just talked about. And what I’m going to do is just give each of these agents a copy of this rubric application to illustrate the difference between the approaches of these agents with one of the agents not having this core paddy principle built in in the other agent following the principle that we just talked about. So now just to show the difference between these two. If I send the same task to both of them, we’re simply requesting let’s say to add a toggle for light mode to the rubric app. If we send it to both with this one to recap has that carpaddy skill and cloud.md already installed. And so now that both of those sessions are done, you can see this one with the core paddy cloud.md confirmed to me that there is a light mode toggle. But if I look at the application it’s working on, it doesn’t actually have it. And if you compare that with this session, which was working on this local host 10,01, this also confirmed to be that the toggle is in the top right bar next to search. And you can see that it is actually here. And it was able to implement that because it actually taught true the problem. And even was able to decide what are the right colors across all of the other icons in here, which if you compare that to this one, which was coming from the agent without that cloud.md file, it thought that it was able to do the task but not really. And if you want to sort of peek under the hood on why the carpaddy cloud.md is more proficient with what it just did. If you ask both the outline the steps that they just took, you can see the vanilla cloud code. It did do some detailed steps like finding the right files, reading the CSS variables, and trying to add a light team CSS. But if you just compare that with the outline of the steps of the carpaddy cloud code, you can see this is much more detailed versus what the vanilla cloud code did. And so the result of that is that we just won’t prompt. It was able to one shot this light team for us without any issues. Now real quick, we just released the agentic AI master class for our members at Robo Nuggets, which takes you from zero to master you when working with agents. There’s a link to the community in the pinned comment below. We’ve got founders in their whole land that they’re first client in weeks, live build sessions where we create this stuff together and the actual templates behind what I showed in this video. The community is also the reason these lessons get made. So see that below if that’s for you. The second principle that it implements is to put simplicity first. In just going back to what Andre wrote here, he mentioned that these AI agents by default will implement an inefficient bloated and brittle construction, which is sometimes over a thousand lines of code. It’s up to you to challenge that and only then will they be able to realize that they can actually cut it down to 100 lines or less. And so without this principle, your AI agent tends to overbuild, but with it, cloud is writing the minimum. And the reason by the way why this is so important is because you have to remember that these AI agents, they are mostly trained on production code basis and so they default to production patterns, which is mostly large scale in nature. And so when you ask for a simple feature and it tends to overthink, it tends to overbuild, but what this cloud that MD file does is that it allows your agent to put simplicity first. So now for our second test, what I’ll be doing is ask