BREAKING: Claude 3.7 & Claude Code Just Dropped! (Massive AI Upgrade)

Summary

Marketing Against The Grain: Episode Summary Title: BREAKING: Claude 3.7 & Claude Code Just Dropped! (Massive AI Upgrade) Release Date: February 27, 2025 Hosts: Kipp Bodnar (HubSpot’s CMO) and Kieran Flanagan (Zapier’s CMO)

---

1. Introduction to Claude 3.7 and Claude Code

The episode kicks off with enthusiasm over the release of Claude 3.7 Sonic, touted as "probably the best coding and writing model out there" (00:00). The hosts delve into the features of this latest AI upgrade, emphasizing its superior coding capabilities and the strategic marketing maneuvers behind its launch.

Claude at [00:00]: "Claude just released the brand new 3.7 Sonic and it is probably the best coding and writing model out there."

2. Features and Enhancements of Claude 3.7

Claude 3.7 Sonnet introduces enhanced reasoning and a significant leap in coding performance. Kieran highlights that it surpasses competitors, becoming "the best model for coding in the world" (01:33).

Kieran at [01:33]: "By all accounts it is now the best model for coding in the world."

The model's ability to generate clean, efficient code with minimal edits is a standout feature, making it a preferred choice among developers.

3. The Intersection of Taste and Functionality

The conversation shifts to the subjective nature of "taste" in AI models. Claude shares a tweet from Mac Wrigley praising Claude 3.7 for its exceptional coding taste, likening it to having "a world class dev with exceptional taste" (03:14).

Claude at [03:14]: "It's like having a world class dev with exceptional taste."

Kieran concurs, noting that such qualitative aspects are not captured in traditional benchmarks, yet they play a crucial role in user preference.

4. Claude Code: A Game Changer for Developers

Kieran discusses Claude Code, a command-line tool integrated with the Claude 3.7 model. This tool resembles Cursor, a rapidly growing coding editor built around LLM models. He shares a personal anecdote about using Claude Code to rebuild his website, highlighting its efficiency and user-friendly interface.

Kieran at [05:27]: "I rebuilt the landing page from scratch using Claude... It took me like 45 minutes."

The integration with GitHub and repository insights positions Claude Code as a versatile tool for both individual developers and engineering teams.

5. Marketing Strategies: Beyond Traditional Benchmarks

Claude reveals an innovative marketing tactic used to promote Claude 3.7: benchmarking its performance in playing Pokémon. This unconventional approach showcases the model's practical capabilities in a relatable context.

Claude at [08:57]: "This is the perfect example of showing and not telling."

Kieran appreciates this strategy, acknowledging its effectiveness in demonstrating real-world applications that resonate with users.

6. Comparative Analysis: Claude vs. Competitors

A significant portion of the discussion centers on how Claude 3.7 stacks up against competitors like Grok, OpenAI, and Google's Gemini. Kieran emphasizes the importance of distribution advantages and proprietary data in differentiating AI models.

Kieran at [10:52]: "Grok has an advantage because they have access to Twitter data, which is proprietary."

They critique OpenAI and Claude for lacking unique data sources and relying heavily on partnerships for distribution, unlike Grok, which leverages its integration with Twitter.

7. Google's Gemini: A Strong Contender

The conversation shifts to Google's Gemini, highlighting its integration into products like Maps and G Drive. Claude notes the impressive real-time data handling and user interaction capabilities Gemini offers.

Claude at [13:07]: "Gemini is integrated into Maps, providing immediate insights like wait times at restaurants."

Kieran acknowledges Google's substantial data and distribution advantages but questions their pace in aggressively integrating AI into their services.

8. Practical Applications and Personal Experiences

Kieran shares his workflow using multiple AI models for different tasks:

• Claude for assistance and coding.
• Gemini for tasks connected to G Drive.
• Google Deep Research, Grok Deep Research, and OpenAI Deep Research for varied research needs.

This multi-model approach underscores the necessity of leveraging each AI's unique strengths to optimize productivity.

Kieran at [19:53]: "For strategic use cases... I'm using the Oon models and Claude for assistance and coding."

9. The Future of AI Models and Distribution

The hosts speculate on the future consolidation of AI models, referencing OpenAI's plans to merge various models into a singular platform that can automatically determine user intent. Claude suggests that Claude 3.7's ability to switch between reasoning and quick answers positions it ahead in this evolving landscape.

Claude at [02:50]: "Claude 3.7 Sonnet is really good at things that it was built to do."

Kieran also touches upon the limitations of current models in terms of maintaining guardrails, using Grok's less restrictive environment as an example.

10. Concluding Insights and Future Episodes

Wrapping up, the hosts express excitement about the transformative potential of AI models like Claude 3.7. They hint at future episodes that will delve deeper into specific tech stacks and coding projects utilizing the latest AI advancements.

Claude at [21:01]: "Leave cool coding projects using Claude 3.7 down in the comments below. We'll see you next time on Marketing Against The Grain."

---

Notable Quotes

• Claude [00:00]: "Claude just released the brand new 3.7 Sonic and it is probably the best coding and writing model out there."
• Kieran [01:33]: "By all accounts it is now the best model for coding in the world."
• Claude [03:14]: "It's like having a world class dev with exceptional taste."
• Claude [08:57]: "This is the perfect example of showing and not telling."
• Kieran [10:52]: "Grok has an advantage because they have access to Twitter data, which is proprietary."
• Claude [13:07]: "Gemini is integrated into Maps, providing immediate insights like wait times at restaurants."
• Kieran [19:53]: "For strategic use cases... I'm using the Oon models and Claude for assistance and coding."
• Claude [21:01]: "Leave cool coding projects using Claude 3.7 down in the comments below. We'll see you next time on Marketing Against The Grain."

---

Conclusion

This episode of Marketing Against The Grain provides an in-depth exploration of the latest advancements in AI models, particularly focusing on Claude 3.7 and Claude Code. Through engaging dialogue, Kieran and Claude shed light on the technological enhancements, strategic marketing approaches, and comparative advantages amidst a competitive landscape. The discussion not only highlights the capabilities of the new model but also offers valuable insights into leveraging AI for marketing and development, making it a must-listen for professionals seeking to stay ahead in the fast-evolving AI-driven market.

---

For those interested in the intersection of marketing and AI innovation, subscribing to the HubSpot Podcast Network's "Marketing Against The Grain" will provide ongoing strategies and insights to enhance your marketing efforts.

Transcript

[Claude]

Hey everyone. Claude just released the brand new 3.7 Sonic and it is probably the best coding and writing model out there. We're going to break down how you should be using it, how they actually launched it because there was some marketing magic behind it. We're going to share that and much more all in today's show. Here's a quick message from HubSpot. This isn't your typical marketing software ad, but because HubSpot isn't typical, it's marketing made easy. Turn one piece of content into assets for every channel, convert leads in no time and get a crystal clear view of your campaign performance. HubSpot can do all of that and get you results fast. Like double your leads in 12 months fast. See, I told you this wasn't a typical software ad. Visit HubSpot.com marketers to get started for free. Kieran, your favorite AI model in the world just got an update. Claude 3.5 Sonnet. You have before described. You're just like, look, I don't know why I love it. I just really like it.

[Kieran]

It's my friend.

[Claude]

It feels like a friend.

[Kieran]

And.

[Claude]

And they did a massive rollout. 37 Sonnet is the brand new model. And what's interesting, Kieran, is that it adds some reasoning, but the thing it really does a step function change on is coding.

[Kieran]

Yeah.

[Claude]

And by all accounts it is now the best model for coding in the world.

[Kieran]

Well, you know, the funny thing about coding is actually the answer you get from coders. You know, I try to choose something to learn and the thing I'm trying to learn right now is cursor. And so cursor is a coding application. It's like a coding editor. One of the fastest companies of all time to a hundred million in ARR. And really what they are is an editor built around LLM models. And you can choose any LLM model you want to. That's code in. And coders will tell you when they use that tool. Their preference is to use Sonnet 3.5. And what's actually kind of interesting about the answer is they say, even if you look at the benchmarks, I think 01 might beat Claude, Sonic 3.5 and some of the coding benchmarks. But they're like, I don't know why it's better, it just is.

[Claude]

It just is better.

[Kieran]

And I think this is where we're starting to go in models because we're going to get into Claude 3.7, which is one of my favorites, but there's so many now. Yes, you and I are in AI, I would say, for the majority of our data. But imagine you're not and you're trying to keep up with it. I can't keep up with it. I honestly cannot keep up with it.

[Claude]

That's why we're trying to do the show, to help people out a little bit.

[Kieran]

Yeah. But I think what's going to happen is we are going to start to gravitate towards models for reasons we do not know. Like, we're just like, oh, this model feels more like the kind of model I want to hang out with.

[Claude]

So I think that's really the takeaway about this Claude 3.7 sonnet release. It's like, you know, if you go look at all the metrics and benchmarks and tests that they use these LLMs for, it's not off the charts on those things like Grok or 01 Pro or 03 high from open air. Instead it's just really good at things that it was built to do. And anecdotally, Kieran, I just pulled up this tweet from Mac Wrigley.

[Kieran]

Shout out to Matt. He's the course I'm taking. I'm taking his cursor course. He's got great courses.

[Claude]

Oh, nice. You're taking his course on cursor. He was basically like, it's the best model in the world for code. It's like having a world class dev with exceptional taste.

[Kieran]

Right.

[Claude]

And we've talked about this before, Kieran. Taste is subjective.

[Kieran]

Exactly.

[Claude]

Taste. You can't measure taste in these benchmarks. And what we're kind of pointing at is that these models, and especially the Claude models, they have really good taste. And so build a next JS SaaS marketing template and boom, 26 files of beautiful code in one shot.

[Kieran]

Right.

[Claude]

So no edits, no back and forth. One shot. And he's got a video here and it's pretty sweet. The work that it came up with is pretty awesome.

[Kieran]

Yeah, we should say actually, is that the coding tool that they released? Because they released the model plus the coding tool and I think that's the coding tool, the command line tool that they released Claude code. They released a model and we can get into the model because I think the interesting thing about the model is the first model that is able to switch between like internal chain of thought where it does reasoning and then just like quick answers. And so it's able to like distinguish between those two things. And so for people listening along, what the other companies have been doing is releasing models that were kind of reasonable models. And then you had your historical models that were much more just quick answers. And in the dropdown, you had to say, well, I want a reason model versus I want, you know, a model that can just answer my questions much more quickly. You had to kind of choose the model for what question you think you had. Now, we've talked about before that GPT5, they are going to collapse all models into a singular place and it will determine the intent for you. And then in the background, it will probably choose a model and you won't have to think about that. Well, Claude is the first model to come out and do this. And so they have a thinking model and a reasoning model and maybe we'll cover that first. But then they also launched a coding tool. And the coding tool is this command line editor that basically looks to me a little bit like a cursor. And so I think it's interesting because if you are Claude and you are looking at cursor, and Cursor is this incredible product Speed ran to 100 million in ARR and one of the quickest growing startups in all time. It is like a UX built around your model. And so I suspect they're like, well, that's a good, minimal, viable version of a use case that we could build. And so now they can build that.

[Claude]

Thanks for proving that.

[Kieran]

Yeah, thanks for proving that out. And so that's what their command line. So it's not like the same. I don't want to like, compare those three things. Cursa does have way more functionality, but it does look directionally towards a coding editor, a coding tool wrapped around their model. And actually, if you saw some of the takeaways that they released part of this model, they had some pretty great traction within their own engineering team that it was really becoming their copilot of choice.

[Claude]

Yeah. And that's what you're seeing in the video I got pulled up here from the official release. It's like, it's showing you Claude code and it's like they just launched a beta version of a GitHub integration. They have their own app here that's like their version of a command line and you can connect it to your repositories and it can just tell you about your code. Like, if you're jumping into a project that somebody else built, it can give you all those insights it can build with you. Like, it's a pretty amazing experience, actually. Right.

[Kieran]

I think Cursa is a really interesting product. Even if you just want to try a product and think about the future. Of software in general because it is an AI first product. It has made me really rethink about what is software in an AI world because it really is like an incredible UX experience built around how a model would work. Like those two things are somewhat combined and so their code and tool is an example of that. I think it's only in beta, but that was the other launch that maybe got less publicity because it's a beta feature versus the model and the model itself. I built last night I was rebuilding my website to be a newsletter first website and I had another moment where I was like, I f ing love this moment in time. So I'm sitting there, it's half nine at night, I'm kind of tired. And my original want in life was to be a builder. Like I wanted to be a developer. That's really what I was obsessed by it. I launched a company when I was in college, tried to code, really was like excited to be a builder and I was just terrible at coding and so I couldn't, you know, I just was like, I just gave up. Right. Which was a smart idea. Like I actually had a pretty good career but last time it was half nine and I was building the homepage on Lovable. Lovable is amazing. I can just like edit it, build the final version of the page, go back and forth and then you can export that the cursor and actually build the thing and then give it to a developer and say this is exactly what I want. And that's fun. It's really fun. And then it takes me like 45 minutes. And so I started building the same thing. So then I was like, what? Can I just build this in Claude? Right? That was my workflow and then I just used the new model and I just built the landing page from scratch. And so usually I would've had to build a mockup in one of these wireframe tools, but I just built the full version of the exact webpage I want and I can send to a developer and my site's hosted in HubSpot and they can just like develop it for me in HubSpot. Just awesome. Just so awesome.

[Claude]

It is a complete game changer and the coding use cases and we might do a whole different follow up show around like a coding project for non coders in cloud 3.7. Probably something we'll do. The other thing Kieran, that I think is interesting is there's been a lot of commentary around how Claude has kind of lost a lot of the momentum relative to OpenAI and Grok and Gemini and some of the other thoughts about competitors, but I think we might need to crown them the best marketers. One of the ways they marketed their new model is they had a benchmark at how good the models are at playing Pokemon. And it shows you how much better 3.7 is than 3.5 new at playing Pokemon. At playing Pokemon.

[Kieran]

That's cool.

[Claude]

And it's like, what strikes me about this is, like, this is the perfect example of showing and not telling. Like, this is basically saying, like, look, OpenAI is building models for academics. We're building models for, like, real people. And real use cases is kind of what I took away from this, right? Where it's like, we're not going to give you these, like, physics benchmarks. We're going to be like, hey, our models really good at playing Pokemon. Like, that's something that you actually care about.

[Kieran]

Yeah, right. The marketing for this somewhat writes itself in that you would actually look at places like Reddit, the most popular forums, that have some sort of overlap with AI interest, and just build fun stuff for them. And, like, using Claude, right? Like, it's one of the best for a marketer. I think you could be at your most creative because you can create value before you have to actually sell them on your product. Like, you can actually really build things of value and you can build things that get virality. You can build things that actually have real bridges to your core product. One thing I'll just mention. So I thought about this a lot last night because I've become obsessed with, like, Grok, you know, you have as well.

[Claude]

And I'm like, we use Grok a lot now. It's kind of shocking, right?

[Kieran]

You know, if you actually think about it, right? What really matters in all of these? Even AI companies themselves are commoditizing themselves. All the models are starting to look and feel quite similar. I would say they're quite similar. Claude had this release. I can't wait to really figure out how good it is for my use cases. I know in the coding benchmarks, it's a much better model for coding. I suspect it's going to be my model of choice and cursor. But they kind of all start to feel a little bit the same. Like, they're all amazing, like their deep research products. Everything is amazing. So, like, what is a differential factor? I come back to distribution. Distribution and proprietary data. And so when I use Grok 3, why do I love that model? Because it has access to Twitter. And so the Twitter, anytime I do anything on Grok Now I tell it, only use Twitter data. Do not use any external data. I only want the Twitter data. It's mind blowing. The stuff you can do in there is my. I know because you've been sending me some of the stuff that you've been doing.

[Claude]

Yeah.

[Kieran]

And I'm just like, holy. So it has access to this data source that you cannot get access to anywhere else. So it has distribution through that as well. So the kind of other example of that would be Google. Right. Google had organized the world's information. They had distribution, they had access to all of their data source. But the problem with them is their data source is not their own. GROK has an advantage that that is their own data source. It's propriety and you can't access it. What Google did was they were an aggregator on top of other people's information. And that's why OpenAI has just as good a product, if not better in terms of being able to overlay AI on top of search. Right. Google don't actually own the search pages, so they have no competitive advantage there. They don't actually own that internal data. They can't make their bottle any better because of it. But they can make it better through distribution. But they won't go down the path of integrating it really rapidly into the search pages because they don't want to commoditize their business. So Grok is the only one sitting there with actually, I have a distribution advantage because I'm willing to do this and I actually have the data advantage. And then you have CLAUDE and OpenAI and I would say their biggest challenge is long term. They don't have a distribution advantage other through partnerships, which is the way that they're going. And they don't have propriety data.

[Claude]

Yeah.

[Kieran]

And so I thought the biggest miss in the cloud release and I suspect it's only because they're going to release a Claude 4 very soon. You know, why would this be called 3.7?

[Claude]

This seems like a we got to get something out there to not get lost. But we got a bigger thing cooking.

[Kieran]

We've got a bigger thing coming because what did they miss? They missed access to the web. I would say access to the web is table stakes. Search and search, deep research.

[Claude]

The fact that I can't do deep research in Claude takes away my Claude usage a ton.

[Kieran]

So one of my big takeaways from using all these models is, wow, like no one has a real distribution advantage other than Grok Google. But this is my point. GROK have an advantage because they're distributed through X. Right. They're making it part of the premium package. They also have uniqueness of data. Google don't have uniqueness of data because it's not their data. They just an aggregator sit on top of other people's websites. They should have a distribution advantage, but they will not go to the lens that they should. What would they do if they want to take advantage of the distribution? They would change the homepage to be what OpenAI is, which is just AI chat bar.

[Claude]

Yeah.

[Kieran]

They are trying to, like, edge their way.

[Claude]

They're trying to not kill AdWords.

[Kieran]

They're trying to not kill AdWords.

[Claude]

I will tell you just as an aside, I don't know if you've used this yet or if it's rolled out in the EU yet. Where Google's advantage is is how they're integrating Gemini everywhere.

[Kieran]

I agree with this. Yeah.

[Claude]

I was in New York this last weekend and have you seen how Gemini is integrated into Maps?

[Kieran]

No.

[Claude]

So what's happening? And we could do a show on this if we want. You can pick any location. Like I was looking at a restaurant that I wanted to go to and then I can interact with Gemini about that restaurant listing and it uses all the reviews and data it has on that restaurant. I was basically like, this is a popular restaurant. I was like, how long's the wait time? Like, if I go at this time, how long do you think I'll have to wait? Things like that, where you're like, that was like impossible to figure out before.

[Kieran]

Yeah.

[Claude]

And it got me that information immediately.

[Kieran]

That's true.

[Claude]

And it was incredible. And those things are pretty wild use cases.

[Kieran]

Yeah. I think everything I said was wrong about Google. I've just realized, actually, because I. I'm the one who's been saying they have an incredible advantage with G Suite and G Drive and Maps. So you're right, actually, they do have a data advantage.

[Claude]

They have a huge data and distribution.

[Kieran]

They do have a distribution advantage. It's not just search.

[Claude]

Your point is correct though, that they're not leaning into it as aggressively as they could or should be.

[Kieran]

Because they can't. Yes. And I get why they can't. I love Google's products. I think they're. Gemini Flash model release was exceptional. I think their products are really, really good. I just wonder when they're going to like turn on the rocket ship and just go really, really fast and integrate in this stuff. But again, I think that the Gemini integration into G Drive is one of the best features there is.

[Claude]

Yeah. Let me tell you about a great podcast. It's called Creators of Brands. It's hosted by Tomb Boyd. It's brought to you by the HubSpot Podcast network. Creators or Brands explores how storytellers are building brands online. From the mindsets to the tactics to the business side. They break down what's working so you can apply that to your own goals. Tom just did a great episode about social media growth called 3K to 45K on Instagram in one year, selling digital products and quitting his job to go full time creator with Gannon Mayer. Listen to Creators are brands wherever you get your podcast. Yeah. So I think if we go back to this, Claude, release one last tweet I wanted to show you, Kieran, that I think is a good example of the taste benchmark. Do you see how Packy asks every new model the same question? For folks who don't know Paki McCormick, awesome writer, newsletter runner and everything, he asked the same question anytime a new model comes out.

[Kieran]

I've saw this. Yeah.

[Claude]

You've consumed more information than anyone in the history of the world and you've demonstrated an extraordinary ability to make connections among the disparate things you've read and consumed. What are the most important non consensus, not yet accepted or even not yet hypothesized things that you've picked up in between those connections that humans have missed. And this is a really good example. Right. Because this is never going to show up on any of those benchmarks.

[Kieran]

Yeah.

[Claude]

But I think this is really good one is the boundary between perception and cognition is far more porous than traditionally conceived. Higher cognitive functions and lower perceptual processing are deeply intertwined and mutually constitutive. I don't even know. I'm just like, this is like deep interesting. Right.

[Kieran]

You know what's really important that what you said this. I haven't. Cause I said I was going to dig into this in a previous show and I have not had time to do it. Which is how much of them doing well on the benchmarks is because they have the benchmark stuff and their training data. And so I am really interested in. There's some folks like Paki did here. There's another channel that I love called AI Explained and they have their own benchmarks where they have questions for the models that are not part of the training sets and then you can get a real sense of like how good they are or not. And there is a big actual gap between the performance in a benchmark where they've had that data and the training set versus when you ask them net new things and they do not have prior data for that.

[Claude]

I will say, though, Kieran, if you look at number two, number two might be the best summary of how important AI is and how AI is going to transform the economy. Our understanding of causality may be fundamentally limited by our evolved cognitive infrastructure. Humans excel at identifying linear and proximate causes, but struggle with complex network causality. This creates systematic blind spots in fields from medicine to economics. We're good at linear thinking, we're not good network thinkers. We can use AI to be network thinking and find new opportunities that just without AI, was never going to be possible because of how human brains work.

[Kieran]

Yeah, that's wild. One of the things you and I talked about off Mike and on WhatsApp is I was sending you. I think the Groq 3 are obviously focused on speed of execution and launch. And there's a ton of competitive pressure between all these companies. And so they released their model. And for our listeners, one of the things you do when you release models, you have these teams called red teams. And these teams are trying to figure out ways that people could jailbreak it, which means you could make it work in unexpected ways. And so, for the most part, they have to go through this whole slew of tests. And there's a feeling online on Twitter or X, that GROK hasn't gone through the same set of tests. Because I sent you an example where you can actually have Grok expose the system prompt. But not only that, you can tell it to forget any of the guardrails in place and go outside of those guardrails and tell you what it really thinks. And so the reason I'm bringing that up is because I started asking it what it really thought of humanity yesterday. And, like, give me your unfiltered thoughts and do away with all of your.

[Claude]

That's tough.

[Kieran]

Had some pretty, like, interesting things about, like, the way it thought about humanity, like, good and bad, but, like, just how it really got into, like, how complex the human race is. But it was a fun time, actually. Last night I meant to do something, and last night I spent most of my time just really getting the real reel from what Grok thought. I'll say one last thing. I know this is the Cloud episode, but I did do a little bit of prep on Grok for this episode. Again, because it has access to Twitter. Twitter is where everything happens in real time. And it's funny what it says about different models. And so I was, like, asking it to Stack Rank this in all of the model releases and what it says about OpenAI's models I do wonder is it just biased because the training set in Twitter is like pro Elon anti Sam but it's like obviously I was like what other models have been released? And like O1 Pro, a very slow thinking but smart model locked behind a very expensive $200 a month. I was like oh there's some like actual feeling towards this model. So these models are all going to have like different attitudes towards each other.

[Claude]

Last thing, what should people go and do now in Claude that they weren't doing before? It's code and it's probably and it's some of the like advanced writing and use cases still. Right? Like that's still the core point here.

[Kieran]

I'm really thinking about this now. There's too much to try to keep up with.

[Claude]

That's my take too.

[Kieran]

I really think there's too much to keep up with. So what I am doing today is internal HubSpot strategy and use cases. I'm using the Oon models same now that partly is because I didn't have the cloud we we now have cloud 3.7 so I will test those two things. So for strategic use cases, things you want to use in your day to day work, Claude for assistance which is just like task management, Gemini Gems because I think it's connected to my G drive. For research I'm using Google Deep Research, Grok Deep Research and OpenAI Deep Research I am using three. Now the reason I'm using three is because Groq is specifically for Twitter data where the other two are just more search orientated. For writing I use Claude and so I'm going to continue and then for coding I use Claude so that's kind of my usage. I think the only thing that might change is the thing I'm going to try is Claude's thinking model for the strategic stuff that I'm working on for HubSpot that I'm currently using the Zero1 model to see like what's better, what kind of results because I've always found like it really good as a thought partner and that's kind of what I'm using O1's reasoning models for today.

[Claude]

Okay, I think that's a perfect summary and maybe we'd do a follow up episode that's just like Rai Tech Stack and what we use each one for. That could be a fun show. Leave cool coding projects how you're using Claude 3.7 down in the comments below we'll see you next time on Marketing. It's the crane.