Claude Mythos Is Coming: How to Prepare Before Everyone Else

[00:00:00]Rumor on the street says that Anthropic is just days away from releasing the most powerful AI model in the entire world, Claude Mythos. And my question to you is this. If Claude Mythos showed up in Claude, would you be prepared to use it to advance your business or career?

[00:00:16]If not, the time to prepare is right now. When this model releases, I want to be able to use it right away to help my business. In this video, I'm going to discuss the things that you need to understand about Mythos before it launches and then how to prepare to use it in Claude desktop app and Claude Code for both general agent work and AI coding work. My name is Riley Brown.

[00:00:39]Let's dive in. All right, guys. We have a lot to cover today. We're discussing how to prepare for this new type of AI model that blows all of the other AI models that came before it out of the water. But again, there's going to be a lot of trade-offs. This model is very heavyweight and it's going to be very expensive. So the first thing I want to discuss what is claude mythos and so claude mythos is an AI model released by anthropic and over the last few years you've heard of models released by the names of haiku claude sonnet and claude opus and claude mythos will actually be a new class of model that is currently behind closed doors. So, Anthropic has basically deemed these models not safe for the public. Some speculate that this is not actually true and that they're using this as an excuse because they just don't have enough compute to serve the model to the public, but we'll see when it releases. Right now, the only people who have access are large companies that have deals with Anthropic and then certain parts of the government. But soon, it'll be opened up to everyone. And I think it's useful to actually go through the timeline of the different Claude models because it's been a really fun to watch. And so if we go back to 2023, the first model they released was Claude V1. I don't think I I'd hardly heard of them at this point.

[00:01:59]And I think I first heard about them with Claude 2, but it wasn't that good.

[00:02:03]No one really switched over. However, 2024 was the year that everything changed. Claude released three models.

[00:02:10]Claude 3 Opus, Claude 3 Haiku, and Claude 3 Sonnet. These were the first Haiku, Sonnet, and Opus models. And so this was kind of in the first few months of 2024. And this didn't create the massive boom like the next model, which was Claude 3.5 sonnet. And so Claude 3.5 sonnet was the model that changed everything in the world of AI coding forever. In fact, this model was responsible for vibe coding. I still remember using it. When I first started using this model in the Claude app, I was copying and pasting code from Claude into Replet and it was the first time that I'd ever felt vibe coding and it was truly a spectacular model. It was added into tools like cursor which absolutely blew up and everyone was using cursor in like from this 24 2024 to 2025 era. And then a model came out in early 2025 which was Claude 3.7in. So this model was the first uh model that started thinking. It was you know at at the end of 2024 early 2025 that's when models started thinking. That's when DeepSeek released uh R1 and then um GPT released I think it was 03 which were these first like models that really thought for a long time before it um gave a response and that's when AI models started getting really good at tool calls and it was kind of a step up from 3.5. the models really started thinking for longer, which was a really interesting concept at the time. And then we got Sonnet 4 and Opus 4, which were pretty good. I remember this was a decent step up, but it wasn't an insane step up. At Opus 4.1, which was released towards the end, I think it was August of 2025. This is when I started realizing it was oneshotting like really hard mobile apps. You could create a mobile app with a front end and a backend. It wasn't perfect. It didn't it wasn't automatic by any means, but you could create a mobile app with a front end and a back end, maybe a simple notes app or even like a Flappy Bird game with a leaderboard that was multiplayer. You could actually oneshot these apps, you know, like 30 or 40% of the time. And so, Opus 4.1 was when I started noticing AI getting really, really good at coding. And Opus 4.5 was the first model that kind of blew everyone's mind. This is when Andre Karpathy at the end of last year started talking about how AI is moving way faster than he he thought.

[00:04:39]He famously said, "I've never felt this far behind as a programmer." And the whole world woke up, especially on Twitter. Everyone started building really cool things. And Opus 4.5, I will add, is like people started using it for general use cases. people started realizing that you could use Opus 4.5 for like marketing use cases and uh more general use case. Uh this is the model that was in OpenClaw when it was released and Opus 4.5 was the best model in OpenClaw. Opus 4.5 was absolutely insane. Then we got 4.6, 4.7, and 4.8.

[00:05:16]Personally, I think it's somewhat slowed down in terms of how good it is. So 4.6 was really good. Um, it was a step up from 4.5, but I do believe that 4.7 and 4.8 have been small improvements compared to like 4.5 and 4.1. We have reached this point where it's slowed down a little bit. But guys, this is a whole new ball game. This is a whole new type of model coming soon, right? You look at this. All of these models right here are either Opus, right? They're either Haiku Sonnet or Opus. We're getting a new model. We're getting a new model within the next few weeks. And this model is right here. So this model is going to be called Claude Mythos. And this model is bigger. It is stronger, more powerful. It works for longer than any model that came before it. However, the pricing, which we'll get to a little bit later, matches with that. This model is going to be insanely expensive. Okay, Riley. So what? We have this new class of model, clog mythos. Well, why is this important for business? Because if you've been following Claude mythos, you know that it's extremely good at coding.

[00:06:23]It's going to be the best coding model in the world likely. According to Anthropic, it's also going to be worldclass at locating security vulnerabilities within large repositories. In fact, they actually found 271 security vulnerabilities in Firefox 150. And so this model is just known for finding secure security vulnerabilities and really really good at coding. However, if you've been following the whole AI coding movement since about this time right here, you know that as AI models, as they get better at AI coding, they also get better at generalpurpose tasks. And this is why Claude has released two sections within their desktop app, which is Claude code for AI coding and Claude co-work for generalpurpose tasks. And we're going to get to this in just a second. And so this model is going to be very, very good at research. It's incredible at research. And that's one of the ways it finds security vulnerabilities. It's not just natural at it. It's really good at traversing the internet and finding different ideas, connecting different ideas, and reasoning more globally. And that's what's going to make it a really general a good general purpose agent as well.

[00:07:40]And it'll be able to perform these tasks for days and even weeks at a time. I'm sure Mythos 1 or Mythos 2 will be able to do uh like a task for over a month and be effective. And so these models, not only they can go off for longer and longer, they get better at using tools.

[00:07:58]And the reason this matters for a business is it's better at using company data and integrations and controlling the different apps that you and your company use all the time. And so this would be my focus to you if you're not going to use this for like AI coding purposes. Uh if you want to use this for general purpose, I highly recommend focusing on using AI with tools like email, Slack, all of the data and metrics from your company. linear, GitHub, all of the social media platforms that you can give tracking to this model will be able to do research longer, find connections so that you can be more successful in business. And that is how I'm thinking about Claude Mythos.

[00:08:36]How do I give it access to all of my data as a company? And I have two companies, right? I have chorus.com, which is a general purpose agent uh platform, and then I have my own like creator business. And I try to I'm I want to get to the point where I'm creating seven high quality videos like this every single week, like every single day, maybe five. And I will need AI to help me with these presentations to help me prepare. And so that's how I'm thinking about it. And so what you need to realize is that all the tools you use are being rebuilt to be used by agents. If you watch my previous video, you saw that I was using Convex. and Convex. I was using Convex inside codeex and I was using it as the database provider and I was creating these little things called mini apps inside codeex.

[00:09:21]Convex was a database provider prior to this AI movement like before all of this went down but this tool convex which is again it's a lot like superbase or firebase or something like that. Uh all of these tools are being rebuilt to be used by agents. every single huge tool that you use or every single tool in general will be rebuilt from the ground up to be used by agents. So realize that this is where the value is connecting the tools you already use to AI agents and these AI agents that you're connecting them to are getting a lot smarter. And basically every time we get new models, every iteration of these cla models, they get better and better at controlling tools, right? And these next generation AI models like Mythos and whatever comes after we'll be able to use these tools for better and for longer and soon fully autonomously. And we can already see glimpses with the GPT 5.5 with their goal feature where it can just go off for days. And you can do the same goal feature within Claude, but like Mythos is rumored to be able to just go off for like days at a time. And so if I were to summarize this section, Claude Mythos will be smarter. It will work for longer. It'll use your own tools that you already use better for coding or for general use cases and it will be a complete step up from models that came before it and as we'll get to a little bit later for a lot more money.

[00:10:44]But that brings me to the next question.

[00:10:46]Where should I or where should you use Mythos? So in order to use Claude Mythos, I would definitely use it within their claw desktop app or if you're technical, of course, you can use it in the terminal, right? You can open up the terminal and you can just use it here.

[00:11:03]You'll be able to use it in the terminal within cla code. I honestly love using this, but I am starting to use the desktop app a little bit more. I am starting a little bit to like co-work. I just really like the documents that it creates. And so, yeah, I've spent the last few days using co-work because I'm already trying to figure out how I'm going to integrate Mythos into my like video prep. I think it's plenty worth it for me. Instead of like hiring someone full-time, which could end up costing me over $100,000 per year, I'm definitely going to be using Mythos and maybe I'll spend 10 to 20K a year on doing research for these videos. In my opinion, uh Claude Co-work is a lot better at codecs at just like spatial understanding within these documents. It can just create way better documents that you can export to PDFs. It just has better design understanding in general. And their HTML documents, which I have one right here. These are just really good.

[00:12:01]I really like the charts that they create. They create really good visuals.

[00:12:05]And I've just find I really really enjoy using Claude Co-work for these types of tasks. And then if you want to actually do full coding tasks where you create an app with like a front end and a backend and one that requires a browser, maybe you want to use React, you can use Cloud Code. The one thing I'll say about claude code if you're using it if you're coming from codeex I will say their inapp browser it's not quite as good yet but again this is where you do general agent tasks and this is where you're going to do codingbased tasks once mythos is released you can do it now of course and you should prepare for this but when mythos release I recommend using it within co-work or within cloud code and so if you want to do something like a landing page web app or create a mobile app you're going to use cloud code if you want to create something like a document a presentation a spreadsheet or like I showed you a single HTML file. You can use Claude Co-work. Both of these can be connected to your own internal tools. Whether you are in Claude code or if you are in co-work tab and you can hit browse plugins and just like all of the other tools like cursor or codeex, you can very easily integrate all of your tools. It has all of them and all of these platforms have all of the integrations which is really cool. And connecting this to claude code that uses mythos is going to be incredibly powerful. So plugins, connectors, and skills. And one thing I want to mention and I think this is really, really, really important actually is a lot of these general agent tasks are incredibly subjective whereas a lot of the coding tasks are more objective, right? Does the app work?

[00:13:43]Right? That is very easy to verify. Yes, that works. Or no, it doesn't work. But the reason why some people like say that it's not as good at general purpose work, you know, something like creating for example like a content script or even something like a YouTube thumbnail or, you know, an ad, creating all these things, these are highly subjective and so these are actually harder to train.

[00:14:07]When they're training these models, it's harder to verify whether something's good because that's again that's how basically how these models learn how to do it. They basically use reinforcement learning and they either give you a thumbs up or a thumbs down and they train the model to be more like the thumbs up. But if something's really subjective, it's it's really hard to do that because some people thinks it's good, some people think it's bad, and it's just this game of picking taste.

[00:14:30]And that's why these models end up kind of behaving different in the general purpose tasks because the people who train them are just different. They're doing the thumbs up and the thumbs down differently. But there are certain things that are very objective, you know, like writing a good Python code in the back end is just like very straightforward. And so these models are going to be very similar in that regard.

[00:14:48]And so the key to getting the most out of Claude Opus or in the future Claude Mythos is coming up with really highquality examples for your company and then turning those into skills. So, if you think about it, when Mythos comes out, you are going to have a goal and you're going to try and use Mythos to reach this goal. Whether your goal is research or having it literally do all of your emails, which I'm actually working on right now, I've actually automated a lot of my at least on one side of my business, all my emails. a highle business strategy, whether you're using it for ads or content scripts for UGC or even building a full mobile app for your in-person store, you absolutely need to make sure that Mythos understands what good looks like. And you might be thinking, Riley, you you're crazy.

[00:15:39]You're going to use Mythos, the model this expensive to create content scripts for UGC. The answer is yes. First of all, because Mythos is going to be really really good at noticing patterns between a lot of data. And with for this example, which is content scripts, there is an API that you can use. It's called foreplay. I don't know why. It's kind of a weird name. It's not like that. Uh this is like an API that pulls ads from anyone. So you could tell Mythos, right?

[00:16:07]You could tell Mythos, "Hey, Mythos, please go uh find all of my competitors ads from the last week, pull them, and get the transcripts for all of them."

[00:16:17]And it could just do this, right? And so you could in theory pull the transcripts from like 40 of your competitors. Maybe you pull like 300 ad 300 ad transcripts, right? You can feed that to Mythos, right? And you can even filter them for their longest running ads. So you could get the 100 highest quality ads from your 10 competitors, right? And so these are just highquality examples. And so part of your job with Mythos is you don't need to manually go get highquality examples. Maybe you just need to give Mythos access to go find highquality examples and give it enough context so that it can find the right ones. If it knows, if Mythos knows a lot about my company, it can go use this API called foreplay and scrape the right competitors. We can just tell Mythos to go find them, create one exactly like that. And you know what? I love creating content. I love creating highquality content. I don't want to spend my time scripting ads manually. What if we just send Mythos off? It'll come back with really high quality scripts because Mythos is going to be better than Opus at finding the patterns. Yes, it's going to be five times as expensive, but more than likely it'll be worth it than me spending my time. I'd much rather spend my time doing higher leverage tasks than doing ads. Yes, we could hire people, but mythos might just be cheaper and faster. And this may be as simple as going to Claude Co-work and saying, "Hey, what APIs can I give you?" Um or you could say APIs/plugins uh can I give you so that you can get access to really high quality examples of top performing blank. In the previous case, it was ads. But as you'll see in the next video that I make, I'm going to be making a social media agent. And I'm going to give my agent access to scraping any Instagram video or any Tik Tok video or any YouTube video. And it can scrape an entire account and find highquality examples and then it will be able to create content scripts for our company. And so what you should be focusing on is like how can you give your agent Mythos access to highquality examples and then that's how you measure how well mythos is doing at any given task. And so when you're testing Mythos, whether it's a coding task or it's a general purpose task for me, I'm going to use it a lot for doing research for videos just like this, right? I'm going to gather a ton of examples of scripts that I've created or research papers that I've created. I'm going to compare the output of Mythos to those examples that gives you a benchmark. How close is it to a specific example? If you just kind of randomly prompt Mythos, if you randomly prompt any new AI model and you don't have something to compare it to, it's really hard to gauge whether or not it's actually a good model for you or your company. So, the first test that I will be doing with Mythos is I'm just going to give it full access to my email. When I give it full access to my email, the first thing I'm going to tell it to do is to analyze all of my emails, figure out what my goals are, figure out everything about me, and then it's going to use all of that context. And then every day, it's basically going to filter out all of the unimportant emails, which is really cool. And every single day, I'm going to have it go through the 50 emails that I need to respond to, and it's just going to create a draft for the first week. I'll have it create a draft with the eventual goal of just having it autonomously run my emails, right? As if I could trust it to be an executive assistant. And I'm going to see like are these emails actually emails that I would send. And for the first week, I'm just going to measure how many of these emails are ready are ready to be sent with no edits. Right? Is it getting the email correct? That's how I verify it. If I allow Mythos to draft 50 emails for me based on all my context, how many of them did I send with no edits, right?

[00:20:12]Maybe it's 31 with Mythos and maybe it's only 16 for Opus. Maybe I only sent 16 of the emails with Opus and with Sonnet and maybe it's only nine. And you should measure these things and this allows you to make the decision. Is Mythos worth the cost? Which brings us to the fun question of how much does Mythos cost?

[00:20:35]The answer to this question is Mythos is very very expensive. And I actually tweeted this today because Claude Mythos is going to be five times as expensive as Opus. And back when I was spending a lot more time with vibecode.dev, which was a mobile app builder, we realized that with Opus 4.6, six. It could it was oneshotting really complex apps, but it was still costing like sometimes $40 per prompt because it'd have to generate all the code and it would have to test the app, then fix the code. It would have to build a backend and a front end and then it would need to deploy it fully to the app store. And all of this would cost like $40, $30 sometimes depending on how difficult the app was to create. And so if you just think about this, like Mythos, I guarantee you, will be able to just oneshot 98% of mobile apps. It'll cost around $120 to $400 when using the Mythos API. For one single prompt, it could cost up to around $500 if it's a complex app. to dig in a little bit deeper on price. It is five times as expensive as Opus and it's like 4 something times more expensive than GPT 5.5 and I think it's a fun benchmark uh with DeepSeek V4 Pro.

[00:21:57]So Deepsee is a little bit worse.

[00:21:59]Actually, it's reasonably worse than these models, but it's getting significantly better. And for a lot of general agent tasks, Deepseek V4 works as good as GPT 5.5 and Opus. And it's a little bit faster, except it is literally 23 times cheaper and 27 times cheaper than GPT 5.5. And if you look at Mythos, DeepSeek V4 Pro is 115 times less expensive than Mythos will be. And so we've never seen an AI model this expensive. It will be very frequent where you will spend $50 on a prompt that's not even coding related. It will be very often you hear about people spending 50 maybe up to $100 on a single prompt, but don't be surprised when you see really high charges for Mythos. So, I want to leave you with some final advice as Mythos comes to be in our world. And the first thing I want to say is just get permission. If you work for a company, really try and get permission to use this model. Really, really push to get access. And one way that you can get access to this or something that might help you get access to this is make sure your boss understands that you're going to verify the return on investment and you're going to measure how well the model does compared to other humans that they could hire and other models that they could use. You need to prove that you are making money using it, right? you are gaining dollars per million tokens spent. That's how you can end up with the unlimited Mythos budget is if you can literally prove to your boss that you are making money. You are printing money using Mythos. And the next thing I'll say is you just need to constantly be experimenting, comparing, and optimizing. And you can use highquality examples. You want to make sure you're giving it context. you're giving it access to the best quality APIs and tools out there so that it has highquality examples. That's going to be a theme over the next year as I really talk about becoming fully agent native.

[00:24:05]It's all about context and highquality examples. And then set limits. You want to avoid the nightmare scenario, which is you wake up one morning, you realize Claude was working for a lot longer than you thought and it just burned through $10,000 worth of tokens, which happens.

[00:24:22]I've heard stories about this. You want to set limits. But also to the other side of this, you also want to set realistic expectations and you're gonna you need to be ready to spend more. And so this is for people who are in companies, right? If you're an individual, maybe you don't have the luxury of just spending a bunch of money on tokens. But at the end of the day, your company should care mostly about return on investment. And you should frame it like that. be like, "Hey, I think if I use Mythos, I can help the company make a lot more money and be more successful." So, you have to frame it like that and be like, "Hey, you just just so you know, this is going to be more expensive, but I truly believe it's going to be worth it in the end." And so, you're you're looking for kind of this like R&D. Be the guy at the company who's treated as R&D research and development. Find ways to use this. And I genuinely believe that any good boss or manager out there will be pretty likely to give you access to mythos. And that's kind of how I see it. Get permission, verify that you get a return on investment compared to humans or other models. You're going to experiment and compare and optimize constantly.

[00:25:29]You're going to try and increase the ROI. Um, you're going to make sure you set limits so you don't do something stupid. And then you're going to make sure you set expectations with your team. We're going to spend a lot more money. It's quite expensive. It's five times more than Opus and Opus and GBD 5.5 are already very expensive AI models. And the way that you're going to minimize cost is you're going to use it within, right? You're going to use it within one of these tools, Claude Desktop and Cloud Co-work. When you use it within the Cloud apps, it's way less expensive than if you use it on an external platform. Then one thing that I will say here is be ready for $500 uh $2,000 and $5,000 plans. I have heard some rumors that these are coming. Right now there is a $20 plan. I believe there's also a $100 plan and a $200 per month plan when you sign up for Claude.

[00:26:23]This is the next iteration. And I made a video in 2024 predicting that we would see a $100 per plan uh and $200 per month plan. This would be very common. I genuinely believe that the next era are the $500, $2,000, $5,000 per month plan.

[00:26:41]More and more companies are viewing this as a replacement of an employee. And so this is, you know, this is $60,000 a year. Anyway, thank you guys so much for watching. This is an incredibly exciting time in the world of AI. We're about to get a whole suite of new models to use in our AI powered super apps like Claude Code, Codeex, Cursor, etc. The models are only going to get better. The open models are going to get better.

[00:27:07]Hopefully, they catch them. Hopefully, they create a model like Mythos for a fraction of the cost. It's going to be really exciting next six months, and I'll be covering it here in great detail. So, make sure to subscribe and like. I'll be moving into my actual studio next week. I'm really excited to rebuild our studio. I moved from SF to New York. Super excited to finally get my studio back. I do not like filming in this Airbnb, but I have to. I owe it to you guys. I'll see you guys later.