When selecting an AI ecosystem for business use, reliability and feature completeness are critical factors; OpenAI's ChatGPT with Codex offers superior stability (no frequent outages), built-in image generation, unified automation capabilities, and better cost efficiency compared to Claude, which suffers from compute limitations and fragmented interfaces.
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I Switched From Claude to ChatGPT (the difference is insane)Ajouté :
I am about to admit something that is going to upset a lot of people watching this. For the last two years, I have been using Claude heavily. I recommended it on this channel. My entire company built workflows around it. And honestly, Claude became the operating system underneath how our team worked every single day. But then a few weeks ago, I sent this message to my entire company.
We're moving to OpenAI. And this was not a casual switch. I don't move a 250 person company onto a different AI ecosystem for fun. But I had to do it when the math stopped making sense because right now OpenAI has caught up with Claude from GPT 5.5 to Codeex.
OpenAI now does basically everything we were using Claude for projects, skills, vibe coding, automations, everything.
And honestly, in many cases, it's working better, faster, and cheaper for us at scale. Now, why does this matter to you? Because whichever AI ecosystem you choose right now is going to become deeply integrated into how you work over the next few years. It's going to learn your projects, your writing style, your workflows, your team, your business. So choosing the wrong ecosystem today can become a very expensive mistake later.
And once I show you what changed, how we migrated everything, and why we made this decision, I genuinely don't think you'll be able to go back.
For context, I run multiple AI companies with a team of over 250 people and users across 100 plus countries. So when something breaks inside one of these AI ecosystems, I feel it before anybody else does. My team feels it, my students feel it. So in this video, I'm going to break down exactly why we switched from Claude to OpenAI. We'll cover GPT projects, codecs, agents, vibe coding, automations, deep research, fact-checking, image generation, and the features most people don't even know exist. And if you stick around till the very end, I'm going to show you how to make the switch from Claude to Open AI without losing your memory, your context, and your projects. All of it will come with you. But here's a quick note before we begin. I run a free WhatsApp community where I drop every AI tool, prompt, and workflow I'm using right now. Most of what gets shared there ends up on this channel weeks later. The people inside are already building with stuff most of YouTube hasn't heard of yet. Join today or watch the next video and realize why you should have joined today. Links in the description. Now, let's get into the video. So, let me start with the thing that broke me. Look at this. This is the Claude status page. Anyone can pull this up. It tracks all of Claude services for the last 90 days. And if you see these red lines right here, that's a partial outage. The orange ones are also issues and the green ones are the good days.
The days where Claude is actually up and running. But look at how much red there is. Red, orange, red. It just keeps going. I was sitting there all day trying to use Claude. And every time I'd open it up, there'd be another outage, bug, or delay. And if I scroll down to the past incident section, you can see it laid out by date. The major reason that keeps showing up is literally that Claude was out of compute. Claude has been trying to fix this. They have partnered with XAI to use their supercomputers and solve this issue, but it's not solved yet. And the AI world moves fast. So, I had to make my switch.
And honestly, I haven't seen Chad GPT go dumb or not work up to the mark. It's just been consistent every day. Now, look, the UI between Chat GPT and Claude isn't that different at first glance, but once you actually open the Chat GPT on the web, you realize it's not just a chat box. It's a full control center.
You've got library, you've got apps, deep research, codecs, projects, and agents. Let's compare every single one of those to claude. Let me start with library. So library is basically where every single image you've ever generated lives. You click on it and you can see your entire history of every visual you've made. Not only does Claude not have anything like this, Claude doesn't even generate images yet. Then there's apps. Chat GPT lets you connect Slack, Canva, Figma, Notion, Air Table, and many such tools. And once you've connected them, you can chat with them like they're part of Chat GPT itself.
Let me actually show you. I'm in apps right now. Let's grab Canva. It's already connected, so I can just go start a chat. I'm going to type make me a launch pitch deck for the latest release of the iPhone 18. I'm going to select the Pro model because I want the Thinking version. And watch this. First, it's reasoning through it, saying it's going to treat the iPhone 18 details as hypothetical concepts rather than confirmed specs because the specs aren't out yet. That's the model knowing context. Then this little generate design button shows up next to the Canva logo. I click it and Canva builds the slides right there inside ChatGpt. Five pages of them. I can open it in Canva if I want to edit it or I can just cycle through the slides right here in the chat. Now, Claude can connect to Canva too, but it can't generate its own images like chat GPT. It can only take pre-generated photos from the internet.
Okay, so apps are great, but what about when you actually need to dig into something serious? That's where deep research comes in. Most AI research tools scrape the top Google results and call it a day. But deep research lets you point it at specific websites. If you're researching a competitor and want to reference three specific blogs, you just feed it those three blogs. And the answer comes back with exact citations from those exact pages. Let's feed it this YouTube video and prompt it to get a full report with sources. And look at this. It pulls everything together and gives me a structured report with the original sources cited. Claude also has a decent deep research feature. However, it doesn't have this option to add reference links. But that's not all.
Research is only as good as the truth sitting at the bottom of it. So, let me show you the test that actually sealed this whole switch for me. So, I found this open-source fact check skill on GitHub. And what it does is it plugs into your AI and forces it to verify claims against the live web before it answers you. So, I installed the exact same skill on both Claude and on ChatGpt. But this time, let's use ChatgPT super app codeex. You can simply type Codex desktop on Google and install it on your laptop. This is what the interface looks like. If I want to install a skill on Codeex, all you have to do is paste the GitHub link in the chat box and type save this as a skill called fact check skill. Similarly, on Claude, you follow the same process. In my Claude, the fact check skill is pre-installed. So now, let's give both of them the exact same prompt. The prompt was use the fact check skill and check if it's true or not and give me the source or the original source for this. And then I pasted in this viral story that was floating around the internet on a guy who asked Codex to make him $5 autonomously. And Codex actually went out and made him $16.88 on its own. Now let's watch what happens. Claude comes back and says the claim is unverified. Then it gives me this big list of red flags. Says it couldn't locate a verifiable primary source that there are inconsistencies.
and it gives me zero links, nothing to click on or follow up on. Now, let's see the result on Codeex. Look, it comes back with way more context. It verifies the claim and gives me the exact link to the tweet posted by a guy named Chris on X. So, I click the link and it opens the original post. I used the same skill, the same prompt, but got two completely different outcomes. And this is when I knew this wasn't just a model difference anymore. This was a thinking difference.
Codeex actually goes the extra step to find the truth. For me, that ended the conversation because if you're using AI to research, to write, to build, to ship anything that has your name on it, you need a tool that can find the truth.
Okay, so let me show you a few more things that are baked into chat GPT that Claude either doesn't have or doesn't do as well. First is custom GPTs. So, if I click on GPTs in the sidebar, this opens up the explore GPTs page. And these are honestly one of the most underrated things in the entire chat GPT ecosystem.
Custom GPTs are built for specific tasks such as research and analysis, programming, image generation, writing, there's a GPT for almost anything you can think of. So if you're writing prompts for Invido, there's a GPT for that. If you're working in Canva, there's a Canva GPT specifically optimized for it. You don't have to build your prompt from scratch every time. someone's already built a specialist GPT for your exact use case.
Then you've got something called projects which is basically a dedicated workspace. So chat GPT can stay focused on one goal or workflow. So if I click on projects in the sidebar and create a new project, any chat I have inside this project, any file I upload, any skill I add, it all lives in one organized space. So if I'm working on YouTube content, all of it stays together. 3 months later, I can come back to this project and pick up exactly where I left off. Then you've got agents, which are basically little AI workers that can run tasks for you. Things like researching the web, organizing data, replying to emails, booking meetings, generating reports, or even running multi-step workflows automatically. When you click on agents in the sidebar, you can see a list of pre-built agents, or you can hit build a new agent and create your own.
We've built a couple of these and they're genuinely powerful. Moving on, inside the settings, you've got something called personalization where you can actually set your character style and tone. You can pick characteristics like warm or enthusiastic. You can turn emojis on or off. You can set fast answers. All of this just makes Chat GPT feel like it's actually yours. There's even a voice option. So, I can go into general settings, change the accent, the language, or even the voice. Let me play one. Hey, I'm ready to hit the ground running.
>> That's the breeze voice. It sounds like an actual person. And then there's temporary chat. So, if I want to have a conversation that doesn't get saved to my history or memory, I just flip on temporary chat. Whatever I do in there disappears. Now, let me show you what Claude looks like next to all of this.
Just to be fair, look, I want to be fair here. Claude does have some good things going for it. You can add files. You've got skills, connectors, research, all their models in a drop down. You've got voice mode. There's even an incognito mode, which is nice. It even has something called artifacts. It's a feature where Claude can generate little standalone apps, documents, designs, anything visual, and you can save them and reuse them. I've actually built a few of these myself. But here's where it falls apart. Claude has rate limits. If I had to explain it to you using an example, you can exhaust all your credits on Claude in just 10 to 20 prompts a day. On ChatGpt, you would take many more prompts a day to hit the cap. Secondly, Claude doesn't have its own image generation model. So if you want to make an image, you have to send it out to some other tool. Chat GPT has image generation built right in. And the quality is one of the best out there right now. Third, Claude has also broken its app into three parts. There's the chat interface, the co-work, and the claude code interface. Co-work is basically claude code for nontechnical people. So if you don't know how to code, you can use co-work to run projects, schedule task, and build live artifacts. Then claude code is for the coders and is similar to Codex by chat GPT. But here's where the real problem lies. Claude Code burns through tokens fast. My $200 Claude plan used to die in 4 to 5 days. With Codeex, I run the same or heavier workload and the credits last me a whole month. This has saved my engineering team tens of thousands of rupees every week. Now we've come to my favorite segment. These last two points are easily my favorites. And after this, I'll show you exactly how to switch from Claude to GPT. So stick around. Let's talk about Codeex. I like to think of it as Chat GPT super app. Codeex used to be the developer app inside ChatgPT. But it's not really that anymore because OpenAI basically realized something important. People don't want five different AI apps for five different tasks. They want one place where everything just works. So instead of fragmenting the experience like Claude did with chat, co-work, and claude code, OpenAI started merging everything together into Codeex. And now Codeex powers almost everything. It runs image generation. It runs code. It runs deep research. It analyzes files. And it even handles automations. It does all of that inside one clean interface that barely feels technical at all. You can download the desktop app or if you're a developer using VS Code, Cursor or Windsurf, you can run it directly as an IDE extension.
Let me show you how well it works. So, I'm inside the Codeex desktop app right now. I type create a poster for Mother's Day. Now, watch what happens. Codeex automatically routes the task to the right workflow, picks the right image model, and generates the result on its own. And suddenly, there's a full floral happy Mother's Day poster sitting there.
The image quality right now is honestly insane. It's easily one of the best image models available today. Just like this, you can literally do everything inside Codex. Now, there are two ways Codex is superior to other platforms.
First is Vibe Coding. when it comes to building full stack products with both front end and back end. Codeex was consistently better and more reliable for our team. Now, if you're just building basic websites, Claude Code and Cowwork are still great and the difference honestly becomes pretty small. But the second advantage is much bigger. Codeex is extremely good at building actual apps on your Mac or Windows machine, not just websites running in a browser. You can create internal tools, personal apps, automations, and desktop software without writing code yourself. That's why I call it a super app because instead of splitting AI into 10 separate tools, it consolidates everything Chat GPT can do into one app that just works.
Now, this final use case is my ultimate favorite, and that's automations. Using this, I've made GPT my assistant that does all my boring work for me. Most repetitive work inside companies isn't difficult. It's just constant check-ins, status updates, reminders, and follow-ups. None of it is hard individually, but together these tiny tasks slowly eat hours out of every single workday. That's exactly why automations were introduced. Chat GPT and Codeex now let you schedule prompts to run automatically. It can be daily, weekly, hourly, or every Monday at 9:00 a.m. Basically, however you want. You write the prompt once, set the schedule once, and after that, it just keeps running in the background without you touching it again. Let me show you a real automation we actually use on our team. So, I'm inside the Codex desktop app right now. I click on automations and then new automation. From here, I can either use a template or create one from scratch. So, let me create a new one. I'll call it daily standup. Then, in the prompt box, I type check my Slack every day at 11:05 a.m. and tag the ad channel named YT Team Check-in. Ask what the status is and what we're working on today. After that, I set the schedule to daily at 11:05 a.m. Attach it to my Codeex project and click run now to test it. Now watch what happens. Codex searches the Slack channels, finds the YT team check-in channel and asks me for Slack API permission. I approve it once and the action immediately gets saved into memory so it can keep running in the future automatically. And that's it.
The automation is now live. So let me open Slack and check whether it actually worked. I open the Slack desktop app, go into the YT team check-in channel, and there it is. The message has already been posted. The whole channel has been tagged and it's asking the team what they're working on today. I'm so happy that I never have to do this task manually again. Now imagine stacking 20 automations like this across your company or 50 or even 100. Suddenly AI is freeing my mind up from having to do operational work in my business every single day. So now you've seen the whole picture. Claud's outages, the fact check test, chat GPTs, apps, GPTs, projects, agents, codecs doing image generation and automations and everything in between. And I know exactly what you're sitting there thinking. Okay, yeah, this sounds good, but Cloud already knows me.
It's got my context. It's got my projects. It's got months of memory baked in. Am I really going to throw all of that away and start from zero? No, you're not. Chat GPT has a memory import feature that pulls everything from Claude in about 2 minutes. Here's exactly how you do it. You go into Claude. You ask Claude to dump out everything it knows about you. Your preferences, your context, how you work, your projects, your goals, all of it.
Just a clean export. Claude will spit out a long block of text with everything laid out. Then you copy that whole block, go into chat GPT, paste it into a new chat, and ask it to save this as your memory. That's it. Now, ChatGpt knows everything about you that Claude knew. But look, before I wrap this up, I don't want this video to feel like a hit piece on Claude because it's not. While I think Chat GPT plus Codeex is just more powerful right now compared to Claude and Claude Code, Codeex isn't perfect either. There are real disadvantages I have to call out. The first one is the context window while Claude gives you a million tokens of context. Codeex is sitting at around 50,000. That is a massive difference. So if you're working with huge documents, long code bases, or you need the AI to hold a lot in its head at once, Claude is still ahead. The second one is user experience. Claude's cowork has its own interface. It's just cleaner, simpler to use, and it has features like dispatch that Codeex doesn't have yet. So, if you're a non-technical person who wants the AI to feel friendly and easy, Claude has put real thought into that. I respect it. But for everything else, for the speed, for the stability, for the ecosystem, for the automations, for the image generation, for the fact that my team can actually ship work without the model going down twice a week. ChatGpt and Codeex win. That's just where I am right now and that's why we switched. So here's my challenge to you. Use chat GPT as your main AI for one week. Not as a backup, not as a side experiment, but as your main tool. Run your hardest problems through it. Build an automation. Try deep research with your own list of websites. Open up Codeex and build something. Anything. Just see what happens. Then come back here and drop a comment with the first thing you built or the first thing you automated. I read every single one of them. There's a few things to note before you go. 70% of the people watching this video right now are not subscribed yet, which means YouTube is not going to show you the next AI workflow video we drop. And we drop something new every single week. So, if you want to stay ahead of this stuff instead of always catching up to it, hit that subscribe button right now. And if you want to go deeper into codec specifically, like really understand how to set it up and use it the way my team does, I'll put the video link right here on the screen. Watch that one next. See you.
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