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Learning a specific AI tool is not wasted effort because most modern systems share the same underlying structure, allowing skills and workflows to transfer across platforms.
The rapid release of new AI tools such as Claude Code, Claude Co-work, Codex, and Gemini CLI has created widespread concern among users about wasted learning efforts. Many feel pressured to constantly switch platforms as newer models, including GPT-5.5, are promoted as superior. This has led to a sense of “tool fatigue” driven by frequent updates and competitive claims.
A growing approach emphasizes staying platform agnostic, meaning users build workflows that are not tied to any single AI system. This strategy focuses on developing transferable skills and assets that can function across multiple tools. As a result, users can adopt new platforms without starting from scratch.
Despite branding differences, leading AI coding and productivity tools operate in fundamentally similar ways. They rely on local workspace folders, structured context files, and reusable agent or skill definitions. These shared mechanics enable interoperability between platforms such as Claude and Codex.
Core components like Markdown instruction files, custom agents, and connected tools remain portable because they are stored locally. Users retain ownership of these assets, allowing them to move seamlessly between environments. This portability reduces dependency on any single provider.
Tests running identical prompts and workflows across Claude Co-work, Claude Code, and Codex produce highly similar results. While minor differences appear in formatting or visuals, the underlying output remains consistent. This demonstrates that the value lies more in the workflow than in the tool itself.
Features such as plugins, connectors, and automations exist across platforms under different names but serve the same purpose. Tools like Zapier MCP further standardize integrations, enabling connections to thousands of applications including Gmail, Slack, and Google Drive. This reinforces the idea of a shared ecosystem.
The modern AI landscape can be understood as layered, with a stable foundation beneath interchangeable tool interfaces. The base layer consists of user-controlled elements like files, workflows, and integrations, while the top layer includes AI platforms that can be swapped as needed. This architecture reduces long-term risk from tool obsolescence.
Rather than fully switching platforms, some users adopt a hybrid approach, continuing to rely on familiar systems while testing newer ones for specific tasks. This allows comparison of outputs and gradual integration without disrupting existing workflows. It also prevents unnecessary relearning.
The broader takeaway is a shift in focus from mastering individual tools to understanding core principles such as prompt design, workflow structuring, and system integration. These fundamentals remain relevant regardless of which AI model is currently dominant.
The rapid evolution of AI tools does not invalidate prior learning, as shared foundations make workflows transferable. Focusing on platform-agnostic skills provides stability in a constantly changing technological landscape.
Let's talk about the elephant in the room. Are you wasting all of your time over the past couple months learning Claude? Well, in this video, I'm going to break down my honest thoughts about this. Right now, it feels like everybody and their grandma is talking about how they're switching from Claude Co-work, Claude Code over to Codex, even though you probably just got up to speed with what Claude is and you're starting to feel comfortable after months. So, in this video, I'm going to address whether or not you are wasting your time learning Claude or any specific AI tool for that matter, just for a new tool to come out a couple weeks later. And I will tell you this video probably will give you a refreshing perspective and will probably cool down this ADHD you're feeling around all these different AI tools. Because right now, it probably feels like you're on an endless treadmill chasing different AI releases that are coming out and I feel this myself and it's literally my job to stay on top of AI every single day. By the end of this video, you're going to understand why this is the wrong question, which tool we should be using. Cuz when you understand the fundamentals I'm going to talk about in this video, it really doesn't matter which tool that we're building with. So, let's dive into this now. All right, so I wanted to make this video, first of all, cuz I'm getting so many questions about this inside of my school community. I have so many people asking, "Am I wasting all of my time learning Claude?" And the answer is no. So, the main point we want to focus on in this video is that we want to stay platform agnostic. And if you don't know what exactly platform agnostic means, let me break it down very simply. This means that when you build something in a specific system like Claude and something new like Codex comes out, you are able to switch between the two because what you've been building is just a foundation that you could build upon with different AI tools. It essentially means that you're not stuck into one specific AI, even when a new one comes out. So, we're going to talk about the mental model for us to understand, so that way you could ease this tool anxiety that you're probably feeling if you're watching this video. So, what we need to understand is we have a couple of different AI layers and if you follow my blue little rectangle here, you could see the different layers that we have right now inside of the AI landscape. We have Claude Code. We have Claude Co-work, which a lot of my audience is familiar with. We have Codex, which everybody seems to be talking about because of the new ChatGPT 5.5 model that is apparently the best model out there. We have stuff like Open Code. We have Gemini CLI. And not even to mention, we have stuff like Open Claw. We have Hermes Agent. Man, there are AI tools coming out every single day and it's really making us feel like, man, I'm wasting my time learning something that's going to be obsolete in the future. And no, that is not the case. So, moving on to why these systems that we are building actually can be interchangeable. And that is because they work fundamentally the same. Claude Code, for example, and Claude Co-work and Codex, all these different AI tools and platforms work inside of folders on our computer. That is fundamentally how they work. And they all have the same context files. So, if we're working inside of a specific workspace folder on our computer, we can always at any time access those Claude MD files or agent MD files that we could transfer over when we want to try a new tool. As well as if we have specific MCPs connected, which are the different tools that we are working inside of like Gmail or Slack, Stripe, all these different tools, we could also work inside of those in all of these, you know, tools like Claude Code, Codex, etc. And these three things that I just talked about right here are our foundation. They're permanent. They're portable. And this is something that we own. Since they live locally on our computer, we can always access these specific skills or agents that we've built inside of them. Now, since this is the workspace that we're working inside of, we could open these in any of these different platforms. So, instead of just talking about this, let me show you exactly what I mean. Now, this is a folder that we're working inside of. This is the Claude Code short system. You can see all these little subfolders. Yes, this is messy, but this is where I've been working mainly inside of Claude Co-work for the past four or five months. This is basically where my entire business runs. Now, if you're anything like me and you've been using Cogram over the past couple of months, you're probably feeling pretty attached to the entire workspace that you built inside of that folder. Well, the good part is is let me now toggle on Claude Code over here. Now, I'm inside the desktop app. If you don't have it, make sure to download this to use both Cogram and Code. And then, what I could do is I could just create a new session. And as you can see down here in this little writing, Claude Code Short System is the folder we're working inside of. This is the same one we were working inside of. Now, we can select obviously any of the folders where, you know, we have on our computer, but this is the one that I was using and built directly inside of Cogram. Now, to show you this in practice, I'm going to run this skill, which is my PDF guide skill, and I basically want to create a PDF guide breaking down why it's important to stay platform agnostic with Claude Cogram, Claude Code, and CodeX. So, I'm going to send that off inside of Cogram. And then, what I'm going to do is I'm going to come over to Claude Code, since I'm in the same workspace here, I'm going to give it the exact same prompt. And I have that PDF skill inside of that folder, so it's able to run it inside of Claude Code, too. I'm going to send that off. I'm going to let them both do their things, and then we're going to come back to probably the exact same or very similar PDF guide that it's created inside of both of these different platforms. And while we're at it, let's do the exact same thing inside of CodeX, which is ChatGPT's desktop app that they created to kind of be a competitor to Claude Code. Again, we are inside of the same folder right here called Claude Code Short System. Make sure to just select the same folder that you're working inside of. I'm going to type in PDF guide staying platform agnostic with Claude Cogram, Code, and CodeX. Same exact prompt, but now we are using the ChatGPT 5.5 model, which some people are saying is better than the Claude Opus model. So, I'm going to send that off. Let's let all three of these generate this, and we'll come back and compare and contrast. Now that all of these have been generated, let's start with CodeX and take a look at this PDF guide. Mind you, this skill was created inside of Claude Cogram, and I'm now using this in both Cloud CoWork, Cloud Code, and Codex, even though that's not where, you know, I built this skill. So, if I open this up, we have this PDF guide, which is in this exact style that I crafted uh again inside of CoWork. And this looks really good. We have these like diagrams breaking down why this matters, these little snippets here of kind of just like talking points. I mean, this looks exactly like the ones that I generate inside of Cloud CoWork and Code. This is super cool. Now, let's take a look at the other ones. Now, back inside of Cloud Code, looks like I could click on this file here. Same thing, this looks basically identical. Obviously, looks slightly different. Like there's a different graphic here than there was inside of the, you know, Codex one, even though it looks very similar. Looks like it also generated this little cool graphic. I mean, this is super solid. Again, this looks exactly the same with a couple minor details, of course, cuz it's not always going to generate the exact same output. But, it's the exact same skill. It's pretty obvious. And here we go. Here's the Cloud CoWork output. Again, very similar. Same exact style. Of course, the visuals look slightly different. I think this one, honestly, might look the best. This one's cool, but yeah, as you can see, this is working with these exact same skills cuz it's working inside of the same workspace. Of course, we do need to talk about the fact that these different platforms, for example, this one's Codex, they do look slightly different. They might have a slightly different feel, but they do function fundamentally the same. So, if I look over here, you could see automations inside of Codex. And then if we come over to Cloud CoWork, we have basically something very similar, which is schedule tasks. And then inside of Codex, we have something called plugins, which basically are just connectors. If you've ever used Cloud before, this is where we can connect our different applications. So, you know, we can configure Gmail, DocuSign, ClickUp, basically all these different apps we use on a day-to-day basis. And it's the exact same thing inside of Cloud, but it's just called connectors instead of plugins. And if there's ever a specific connector you want to connect to inside of either of these platforms, you could always use something like the Zapier MCP, which then allows you to connect to 9,000 plus different apps that it integrates with. So, to show you what I mean, I have this specific MCP server configured with these different applications. For example, I have school in here, Google Drive, SynthFlow, couple of different tools. All I have to do is click on connect, click add to Claude, click connect, and then we could actually use those different applications inside of Claude. And then that would function the exact same way when we're back inside of Codox, for example. Now, if you were able to stick with me through this entire video, you now understand that we have one foundation, and we could add any AI layer on top of that. Our foundation is just our folders, our skills, our context, our MCP that live on our local computers. And then whenever a new tool like Claude Code or Co-worker Codox, Open Claude, or the Gemini CLI come out, we could actually go ahead and begin using those if those models are more powerful than what we've been using in the past. For me personally, I spend the majority of my time still inside of Claude Co-worker. I do use Claude Code when I need to do something a little bit more technical, but I personally haven't found a need to switch fully to something like Codox. But that doesn't mean that I can't do it whenever I want to. Sometimes I will run a task inside of Codox just to compare and contrast to see if I get a better output because of the new GPT 5.5 model. Anyways, guys, I hope you guys can understand this concept, and I really hope that this maybe calms down your tool ADHD that you're probably feeling. It does probably feel like you're running on a treadmill trying to chase these different AI tools. But if you understand this, it should calm you down quite a bit. If you guys want more content like this, make sure to subscribe to this channel. I cover AI for non-techies, and if you want to join my school community, we have some amazing people in here. I have a full Claude Co-worker course. I share all the different Claude skills that I use that you could also use inside of Codox, and it's a great place to be. With that being said, guys, thanks for staying to the end. I'll see you in the next video.