100× Your Campaign Launches Using Claude Code

Julia Nimchinski:
Welcome to the show, Jordan! Thanks.

Jordan Crawford:
Thanks so much for having me.

Julia Nimchinski:
Sessions, last but not least, and the most promising session of the day, 100 acts. You’re efficient. Let’s go! How do you do that?

Jordan Crawford:
Yeah, so… let’s have a conversation about this, because I think that my answer 6 months ago might have been much different. And… And my answer doesn’t change every two days, you know, you see all these tools, and you’re like, oh, there’s the latest Manis OpenClaw, should I be running all my business through OpenClaw? It’s like, no, you shouldn’t do that, that’s, like, totally insane. But… Cloud Code specifically is a… a very large step change in the amount of… synthesis of good information and the ability to act on that and to create campaigns. And so, I would say that, Never before have we been able to use these AI tools to be able to blend together such really great raw intelligence data, like the calls, information about Closed One, information from the internet, and then to turn that into campaigns. And that’s kind of the promise of what Cloud Codes does, and it’s what I do with my clients.

Julia Nimchinski:
Boom. Before we get started, what could go wrong? And what goes wrong most frequently.

Jordan Crawford:
Well, I always quote the Patriot here, which is a really great movie if you haven’t seen it, and one of the things that Mel Gibson’s character advises there is to aim small and to miss small. And so, when I’m building these sort of context engines inside of repos, which is just a fancy word for a folder. I am, I’m not connecting with any of my customers’ systems, except to pull in information. So I’ll, like, pull in Gong transcripts, or I’ll have them export stuff from Salesforce. And so, the worst thing that could go wrong in the type… and I’m building campaigns, usually. So the worst thing that can go wrong is, is really the list could be bad. Like, the, you know, maybe you didn’t enrich the emails in the right way, or maybe you didn’t validate the LinkedIn profiles. And so the campaign could, if it’s not spot-checked right, the context could get away from you. But it’s not like it’s going to, like, overwrite your CRM, or… because I don’t give it that permission. I always tell people. That what you say matters. And so, the more powerful the tools are, if you’re just like, delete all my files, it’ll do that thing. And so, you just have to, don’t… you know, don’t… you’re gonna… if you fuck around, you’re gonna find out. And so, don’t do that. So I would say, like, don’t integrate with… don’t… only allow read capabilities from these tools, don’t, allow write capabilities. And then, Play in a space where, when you turn the dial up to 100, you’re not gonna run into walls. And that you control… once it’s done, you control the output. And so, I generally won’t say, just go push this to the systems and send the messages. That’s no, like, I have a human QA that looks at all the context that, That we built up to say, is the output good? And oftentimes, the output is not good, like, you have to make, iterations and changes.

Julia Nimchinski:
I have so many questions, like, how many people are working on a given campaign? I mean, potentially that ROI? You mentioned human QA, so I’m just… Starting to one.

Jordan Crawford:
can you ask the question in a different way? Like, what do you mean?

Julia Nimchinski:
Yeah, like, I mean, a person that would, like, say you would set up the campaign, then there’s a human QA, additionally, from what I’m gathering, overseeing the campaign, or.

Jordan Crawford:
I mean, really, it’s… At the end of the day, the… Sort of key pieces of information are, is this the right person we should be going after?

Julia Nimchinski:
on…

Jordan Crawford:
is this person the person we think it is? So, like, this is their LinkedIn URL, and this is their information, and also, is this message actually relevant to them? based on the source information. And so, like, one of the things… I talk about this, like, it’s turtles all the way down. So one of the things I built with Cloud Code is, like, a QA website. So it’s like, when you’re done with a campaign, you’re like, hey, let me review this. And it’s all designed for you to, like, look at the copy, type in information, and go next, type in information next, and then feed that back to the large language model to go fix it. So, the speed at which you can iterate on improving the quality has… Just increased, but it also means that the amount of errors also has increased by a lot. And so, if you can speed up both of those things, where you can get to an 80% validate and fix and fix and fix as fast as possible, you still can ship a campaign much faster than if you’re going around in, you know, sort of the old school tools, and you’re clicking filters, and you’re… you know, and generally the message that comes out of those things is really terrible. And so that’s kind of the promise of Cloud Code, is that it’s It’s not about personalization, it’s not about adding information about Jordan and what Jordan does. It’s about prioritization, which is, you can have Claude Code go find a bunch of different information from the public web. Like, a good example of this is I have a customer that sells in a healthcare I work with a lot of companies in healthcare, and there’s a bunch of additional grants that apply specifically if you meet some Byzantine amount of criteria. Well, the AI can go find, you know, NPIs, national provider IDs, they exist for every practitioner in the country, at the practitioner level and at the company level, and you can go figure out which of those Meet the 87 criteria to get $2 million in federal funding. And if you can do that, well, the message becomes obvious. Jordan, the… this latest grant from the federal government is X or Y or Z dollars. It says that you have to have these four criteria. You do! Did you know about it? Right? And that’s something that has nothing to do with personalization, it’s not about trying to understand, who the person is, like, no, it’s about prioritization based on taking public data that you didn’t know existed, and consolidating it. And Cloud Code is really, really good at that, if you give it the goal. And what that goal needs to look like is, these are my customers, here’s what I do, what is the most valuable thing I can provide to them, based on their situation and what I sell.

Julia Nimchinski:
Let’s see it in action.

Jordan Crawford:
Okay, great. So, how do you want to do this? Do you want to… we can do this for, like, any random company? Like, what’s the… like, I feel I always like to add a little chaos to the stuff that I do. So, do you want me to just pick a… and I can share my screen, we can pick a random… that way you know I have nothing up my sleeve?

Julia Nimchinski:
Whatever you feel, it’s gonna represent it the best, yeah.

Jordan Crawford:
Alright, let’s, let’s go do that. So, I’m gonna just get set up here, and… oh, actually… Yeah, I’m gonna get sit up here. So, one of the things I did last night is I downloaded, every single contractor in the… in the… in the world, and I used a tool called the Blitz API to go find LinkedIn URLs, etc. So, the only thing I’m starting with right now is, like, a list of all the contractors, in the country. So you’re gonna sort of see exactly how quickly this thing can go. Alright, I’m in, can you see my screen? Is this working well? Great. So I’m in Claude Code now, so I got it set up, and I just said Claude. Now what I’m going to do is I’m gonna have Claude go find me a, a vertical SAS… actually. Actually, I chatted with, one today. No, maybe I’m just gonna have it find me a random one. Alright, I… this is a list… you’re in a folder here with a list of a bunch of, contractors, and so what I’d like to do is, I’d like to find a vertical SaaS contract… a vertical SaaS company that sells into contractors That has raised at least $10 million in the last year, and where… ideally where they care about things that I can detect on the website. Can you use the EXA MCP server and give me 3 candidates with their websites and describe what they do? So I just used a tool called Whisperflow, to be able to transcribe my voice. And it actually didn’t… Not a problem there? Great. Just gonna copy that. And then Claude’s gonna… I’ve got this bypass permission on, so it’s gonna just rip. It’s gonna go run this. Now, I use this tool called EXA, which is just a really good way to find companies and people. They’ve got a lot of, Oh man, maybe my API key is… So it’s gonna do some web searches. Unfortunately, I can’t paste my API here on camera. because otherwise you guys would have thousands of dollars of my credits. But it’s basically going to go search, and it’s going to go find some vertical SaaS companies. And once we do that, we’re gonna actually go talk about… and I’m just gonna use my voice to talk about some of my frameworks. So there’s nothing up my sleeve here. I’m not… I’m starting with a sort of vanilla version of Cloud Code. And so, it’s basically running regular searches. My MCP is misconfigured here. Generally, you can… the nice thing is you can just paste in your API key or whatever, and Claude can go fix that. And it’s trying to find some folks that we’re gonna begin with. Now, once it does that, what we’re going to do is, we’re gonna have Claude code Go sort of look at actual contractors and tell us. How could you tell that a contractor was a 10 times better fit than another? And so that’s kind of the next step here. Do you have any questions about what’s going to happen as we wait?

Julia Nimchinski:
I have so many questions, like, why, why in the first place, why didn’t you select lot code?

Jordan Crawford:
Why did I start Cloud Code? Well, Cloud Code is the… only tool that I know of today that can capture your imagination. And so, we generally have a problem of imagination and go to market, which is. We’re stuck in filter thinking, which is, like. It’s employees, I always joke, it’s like, it’s employees, 50 to 500… people. It’s like, so you think when someone adds the 501st employee, everything changes! They wake up, they have that 5… they’re like, everything’s changed around here, cancel all of our contracts, we’re outside of ICP for a bunch of companies. No, it’s ridiculous. It’s just like, people don’t… the world doesn’t work that way. And so, So, instead of thinking from filters down to personas and messages, I’m thinking backwards, which is like, what is the very best message that I could send, and who are the companies that are in the very worst version of the problem that I could serve? Okay, so let’s, like, look at a couple of these. Job site, field cruise. Okay, I like company cam, that’s good. For commercial trade contractors. I kinda like that, too. Commercial, not residential. Mmm, okay. We’re gonna do it for company, Kim. Alright, I’m just gonna talk to Claude. I’m gonna use, Whisper Flow here, Alright, let’s do this for CompanyCam. What I want you to do is, I want you to go research CompanyCam, and give me, sort of, a understanding about who is in their market, who do they serve. And then what I want you to do is, I want you to tell me about two types of customers. A customer that bought from them, like, from case studies, or that you can find online, that seems to be happy, that would… that got a lot of value, and then another customer that, like, got 100x the value. And… and you can… it’s okay if this is theoretical, too, but what I want you to do is just, like, what is the thing that makes that 100x value Like, what type of situation, what pain are they in that they, will get, sort of, 100x the value? And help outline that for me. So, couple things. Right here, you see my context window. So, if you’re ever chatting with, chatGPT weirdly doesn’t do this, but, anytime you chat with a model, if you’re in a window for a very, very long period of time, you kind of know it gets lazy. Because you’re talking about a bunch of things, and, you know, so ChatGPT is like, who are you? What’s going on? So that’s why you start a new chat. And so, that’s essentially what this is showing me. How much space do I have left in the context window? And basically, it gets lazier as it… as the context window gets shorter. And you can see there’s, like, tokens here, so this is, like, a very small number of tokens. Tokens are just a fraction of a word, you could think about that… you could think about it as words. And so this is, like, the total amount of memory this thing has. And so it’s really important when we’re doing as much of our strategic work as possible to do that within, sort of, the 50% of the context window, where it can be most creative without getting confused. And I… you can just ask Claude to add this thing to… this is like a little… So you can ask it to add the information about the context window. So now it’s deploying a bunch of sub-agents to learn about CompanyCam. And what I’m trying to figure out is, like, what makes… remember, I’m not starting with filters, I’m not starting with, like, what is the enrichment… what can the enrichment tool do? I’m starting in the other direction, which is… how… like, who has the worst version of this problem, and how can I tell? And so, I begin… I’m trying to begin with my… with sort of the best part of my imagination, which is, if I had perfect information on the world, how would I know that someone has a 10X problem? And then from there, I can figure out, well, what data do I need to get as close as possible to knowing they have that problem? And those are… if I think about those as two separate things, what is a condition they must be in, and then how exactly do I get the… get that context. That’s, that’s what I’m looking to do. And so Claude is, like, basically, oh, you can see it’s, like, roofing. Also, it’s, like, really important that you see this says Sonnet. Which is… there’s 3 levels of models. There’s Opus model, which is the best model, there’s Sonnet, which is kind of the mid-tier model, and then there’s Haiku, which is the sort of low-tier model. And so, it’s sending this kind of mid-tier model out to go find that information. And the nice thing is that you can see here that none of this is changing my context window. So if ChatGPT was doing this, it would get lazier and lazier and lazier, but this is happening separate. And then all of this work is going to feed back in. You can think about, like, this is the manager. So the manager then will get that information report from, From all of these little research agents. And the nice thing is that I can go longer than with my main task, which is sort of build this go-to-market engine, without the context being lost. That’s, like, sort of really important.

Julia Nimchinski:
What are the indicators, Jordan, to even figure it out, you know, when you’re using ChatGPT? You mentioned that it’s impossible to see the statistic, per se, but, I mean, you just feel that it gets lazier, or…

Jordan Crawford:
Well, so, in Claude, if you’re having a conversation with the desktop version of Claude, it’ll say compacting conversation. And what it does is it summarizes that conversation and basically opens a new window and passes that summarization. So it’s starting again, it says, here’s kind of what we talked about, but it loses the specificity by default. Now, ChatGPT, I actually don’t know what happens if you go if you just keep pasting things. But… You can tell the model starts responding worse. And… and there is a… there’s a… an actual, sort of, it’s not a statistic, but a, a test for this, which is, like, needle in a haystack. So what they do is they dump a bunch of tokens into, you know, Gemini or these models that can take these large context windows and say something like, you know, where was the needle placed? And, like, somewhere in that huge amount of text, there’s a little thing that says, oh, and the thread, along with its companion, was on the dresser. And it’s like, oh, okay, I know a companion to thread is Needle, and now I know it’s on the dresser. So that’s how you can tell how good the recall is. And as your context window expands, it… the recall gets worse and worse and worse. So managing that context window turns out to be very important, and this is the value of Cloud Code specifically is that there are all these sub-agents that are really designed to… so you can see it used 34 different tools, 44,000 tokens. And now it’s sort of passed to the main context window here that’s like, okay, great. Now I have to figure out what Jordan said and how that’s actually relevant to me. And so all I’m doing is getting context. And by the way, if I was working for a company, I would go pull in their Gong calls.

Julia Nimchinski:
And…

Jordan Crawford:
And the nice thing is that at any point, like, this looks scary, I think, to a lot of people. They see this, they’re like, the terminal, oh my god, I’m a go-to-market person, I don’t know how… I’ll never know how to do this. You just talk to it. You just can say, like, I don’t know what I’m doing, I’m totally confused, I’m not a developer, talk to me like I’m not a developer. Like, so you should think about this as just, like, a worse… a poorly designed chat interface. Okay. Great, let’s… some context here. So, $285,000, $68 million of revenue, $2 billion, nice! Mostly U.S, 50 trades. Okay, so this is really key, and the models get a little squirrely the further off you send them, so we’re just gonna do roofing, because I like, I like roofs, I like, you know, just me randomly picking roofing. Because my guess is problems in restoration and exteriors are probably different. Okay, employees, this is, like, classic ICP, $29 a month, cheap. Sales and crew sites, great. Small shops, multi-crew operations. Alright, fantastic. So, great, customer one. These are, like, real… how many active users, when were they founded? 4.7 million photos. For uploading photos, Google Drive, literally full-time position. Someone spent their entire day downloading SD cards. Wow. So now we know the kind of pain, right? We’re getting to, like, real good pain information. There was a full-time role to take pictures. Wow, that’s, like, I didn’t know that was a thing. So they’re paying… they basically are saving 50% on that full-time role, and that’s amazing. So now I’m, I’m, like, getting an understanding… this is pain, right? Pain is, like… Jessica’s, like, climbing on roofs, and Jessica’s only job is to take pictures. Like, that’s a crazy job. There should be, like, a software for that, and, like, this is the value, right? Okay, 100x value. Multi-location doing, insurance claims work. This is really key, right? Because if you’re just, if you’re building roofs for rich people that are just, like, want a fancier roof. You don’t need to take as many pictures, like, I don’t know, is it… I asked you for steel, is it steel? But insurance, like, I want to know, did you really replace that? Was that real hail damage, right? So they have to be able to take insurance. fire water damage, okay? So, imagine roofing companies that do fire water damage. Like, we’re getting a really, really good sense of, of exactly, who this is. A lawsuit for alleged property damage. Okay. Lawsuits are public, that’s something that we can tell. So we kind of have some really good, like, what are the attributes? Fire and storm, storm chasing roofing, amazing. What are the sizes? Multi-state, revenue, growth, 50% of revenue comes from insurance photos scattered across, right? This is the pain. Okay, so we’ve got, like, a good kind of sense of this. Now what we’re gonna do is we’re gonna see if we can find, like, actually good fits here. Alright, now that we have a really good sense of the problem, what I want you to do is, we also have access to the Shovels database here, which has live permit information via an MCP server. So what I’d like you to do is go use your MCP server, and, and you can coordinate this against the contractor list you have in your local repo if you’d like to, but what I’m trying to do is I’m trying to find what are the contractors that have the worst version of this. Right? With actual permit data, with information from their actual website, I don’t know that you can tell the crews, so you probably want to begin with the shovels data, but really what I’d like you to do is narrow this down to find, like, 3 to 5 customers that… or possible leads customers that aren’t customers now, but have, like, likely the worst version of this problem. Now, before you do that, you’re gonna have to come up with a plan with just the tools that you have. To find just these 5 customers. So, think about the best way to accomplish this, and then I just… the output is, I want a story about these 5 customers, and why you think right now they should be, a customer of this company, and why. So, a couple things that I did. So, everything I said was transcribed by this tool called Whisper Flow, and then I switched to plan mode. So, I did Shift-Tab here, and I said, I want… I don’t want you to do… this is a complex enough problem, I want you to tell me how you think you should do it. And it’s like, okay, great. So it’s got some… it’s like looking at all of the data here in its local folder. I just happen to have some contractors. And then what it’s gonna do next is it’s gonna go deploy another agent. I have a… there’s this great tool called Shovels. It is a database for a bunch of permits around the country, 272 million permits, it’s probably higher now, this is the last time I checked. And the idea here is, like, great, I have access to these tools, I’ve got some data, I know the problem here, and now I can say, how can I triangulate this? What is the very best customer? And notice that I didn’t say. 20 employees. No, I said, like, has the worst version of the problem. So basically, and you can see my context window is, like, slowly shrinking here, that… That’s gonna go, like, look in the tools that I have, and determine exactly how to find the best version of who’s in pain.

Julia Nimchinski:
What’s your logic when you’re asking those questions? I know it’s, you know, hard to codify. Is it happening at the moment and, you know, naturally, or are you following? Yeah.

Jordan Crawford:
everything… goes back to… What is the worst pain a company could be in? And I’m trying to find… I’m trying to find that out. I’m trying to find… How can I tell publicly that someone is in a bad situation? Right? And so, you can kind of see that It described the situation these customers were in, and there’s really a lot of specificity here. And all, like, and how much actual… this is the thing I love about vertical SaaS, they save money, right? Horizontal SaaS is like, buy our B2B SaaS solution so you can get the best tool for your orchestration needs, like. No, it’s like, this is actual money, right? It’s like, oh, they’ve saved $50K a year, right? It’s like, oh, they were facing a $75,000 lawsuit for alleged property damage, right? They want to be able to show up with the records. If you’re facing a $75,000 lawsuit because a customer said, you damaged my roof, it’s like. Here’s the GoPro footage of us arriving at your roof for the first time. There’s a hole in the roof. That was not us. Like, you’re trying to extort us. So… So, basically, the, the, sorry, it got a little confused. No, not Mimi Data Labs, there is a Shovels MCP server, it’s, yeah, you got it wrong. And actually, this is a really good thing. So, it looked at a different… an MCP server is just a way to talk to a database, and this is a healthcare database. So, it’s like, alright, I’m searching, and see, it got a little drunk. It’s like… Nope. And let’s actually see. Yeah, I think this is via Snowflake. I added it, like, semi-recently, but for sure it’s there. And yeah. You can use those census data, web scraping, web search, FEMA risk, like, seems pretty baller. Yeah, go find the most FEMA-risky areas in the entire country, and then, go help me there. So, so you can kind of see, it’s like, oh, great, FEMA risk data, this is so valuable, right? Because we focus on roofing. Now, if we tried to do roofing and plumbing, we had some problems. This is very, very valuable, because now we have an understanding of, like, this is looking for just roofing, and in roofing, the most important thing is that, like, part of that, Part of that value… well, it’s still querying the wrong one… Part of that value is that it is, That you can get that specific. And if we were to pick another vertical, it wouldn’t have found that, hey, look, if it turns out there’s, like, a lot of hail damage, so in San Francisco, California, you’re not going to be doing a lot of insurance work for roofs, because we don’t have rain. I mean, not really. But in Akron, Ohio, and I’m just making things up, maybe not it’s Akron, but, like. Great. Like, Gulf Coast makes a lot of sense, right? Lots of huge… things are bigger in Texas, their raindrops are bigger in Texas, their hail is bigger in Texas. So, if we go after roofers in Texas, we know for sure that they’re gonna have a bigger problem, and especially if we can actually correlate that with weather patterns, I can deterministically tell you, yes, these are the roofers that, based on, their location. have a lot of hail damage reports, because literally, I can look at the weather patterns in the last year. I know we’re getting up of time, so we’re just gonna look at this plan, and talk about it here. But it’s like, great! Who can value 100X? We’ve got a local CSV at 200,000 contractors. I actually had some decision makers, that’s from some other work I’ve did. It’s like, oh, national risk index, so it’s like, county-level hurricane, tornado, hail, flood, wildfire risk. Amazing. We’ve got web scraping and web search. So it’s like, first, look at the highest… this is, like, a different tool, which is… you know, Claude kind of went a little drunk, and it found something useful. That doesn’t usually happen that way, but, great! Poll the top 5 counties, write a Python script, scrape the top candidates’ websites, verify they’re not already customers, cross-reference, write the stories that Like, who they are, what the FEMA risk is, amazing! So I just said, clear context and go. And what Clear Context does, it gives me a new window. So it’s like, I had one window for the plan, and now I have another context window just to go and do this. So that’s kind of what this thing looks like when you’re building.

Julia Nimchinski:
Super cool. Question from Tim here. Incredibly interesting. Has Jordan turned this into specific applications for clients? Has he dealt with security issues to do so?

Jordan Crawford:
This is why I say aim small, miss small. We talk about security issues. I’m not publish… I’m not publishing the web, I’m not pulling from your database, I, like… what security, right? Like, I’m not… everything is happening locally. And I call APIs to sip in information and structure information. All I’m doing is structuring information. When people think about vibe coding, they think, make Salesforce! And it’s like, that’s a ridiculous thing, because there’s such small little applications, like just the thing that I built. There’s no security risk. I shared my screen. You saw everything I was doing. It searched the web. It structured information. It found a tool to use. It used that tool. It’s defining the areas for me. Like, it’s so, so, so quick, but I’m not writing all… you know, that’s why I didn’t paste my API key, like, so… there’s not really a security, concern here, because I’m not pushing it anywhere. The output is a CSV.

Julia Nimchinski:
Karen, can you share more about your clients and how potentially our folks would work with you? Do you work as an agency? Do you advise? Yes.

Jordan Crawford:
Yeah, so, the two values of the things that I do is, like, I’m trying to… build and structure information about the pain in your market, and find the best data to do that. And I’m trying to teach you how to fire me. So unlike most, like, RevOps, consultants that are, like. if you want your HubSpot to be clean, you gotta keep coming here. It’s like, no, no, no, I’m not designed that way. It’s like, I’m gonna get you into Cloud Code, I’m gonna teach you this stuff, you’re going to learn how to do my job so that I can get out. And you can start doing the things that I do. Because this represents a step change in capability, there’s no user experience, I do all of my job only with my voice, except when I have to click the share button on Zoom. But with the exception of that, it’s only my voice. And that’s what I’m trying to teach my clients to do.

Julia Nimchinski:
And in terms of the role, specifically, would it be a founder, a CEO, or a VP of sales, rev ops?

Jordan Crawford:
I mean, I think everyone’s going to be using this tool in the future, and so the people that do the best with it are those that lean into it. So it doesn’t… the role doesn’t really matter, it’s that who has the context and hunger? Those are the two most important things, the context and the hunger. If you don’t want to learn something new, if you’re not interested in taking a step into the future, you’re not gonna like this. You’re gonna get in the terminal, and you’re gonna be… but once you cross the Rubicon, once you can experience it. You’ll find yourself drawn in because the amount of things you can do has just increased exponentially with a tool like this.

Julia Nimchinski:
Super cool. And one last question, what use case is your, I don’t know, most favorite In terms of, like, your work currently with a client.

Jordan Crawford:
Yeah, this is my favorite use case. It’s looking at conference attendees, it’s going to the conference attendee app, it’s being really sneaky, getting all the conference attendee apps, being very sneaky. So if you ever see, like, a network tab inside of one of those, like, conference attendee apps, getting all of the people, finding their LinkedIn URLs, getting phones, getting emails. dumping all of their profiles, their websites into, different agents, and scoring the entire conference for my clients. I’m like, look, there’s 10,000 people that come to this thing, here are the 300 you should call, here’s why you should call them now. Invite them to a dinner, these are your best prospects, everything else is noise. That’s one of my favorite use cases.

Julia Nimchinski:
Super cool. What’s the best next step, after our folks engage with you?

Jordan Crawford:
Oh, are you talking about how to contact me? Or like, yeah. I’m Jordan Crawford, you can find me on LinkedIn, that’s probably the best way. I have a substack, Cannonball GoToMarket, where you can, watch me do some of this stuff, live. It’s a top 50 business substack. And those are, yeah, those are the best places. BlueprintGTM.com is my website.

Julia Nimchinski:
I’m gonna share it after the session. Thanks so much, Jordan.

Jordan Crawford:
Great, thanks for having me. Bye.

Julia Nimchinski:
And that’s a wrap for our AI practice sessions, and join us next time in March for AI Summit. It’s going to be a huge one, and go to Hardscale LoudExchange to register. See you next time.

Jordan Crawford:
Bye, everyone. Bye.