How to Sell Claude Workflows (Without Starting an Agency)

0:00 So, everybody's telling you the same way to make money with AI in 2026, which is to start an AI agency, find clients, and then sell them AI automations. But the opportunity to build a profitable AI

0:09 agency is shifting. The real opportunity for most people right now is to become the AI person. And right now, this is the closest thing to a job that can't be replaced. I actually used to be an AI

0:17 person at one of the biggest banks in the world just a few years ago. Now, that position has seen a huge increase in demand over the last couple of years, and it will keep growing. So, in this

0:25 video, I'll break down what the AI person actually is, why every business is going to be desperate for one, and the exact road map for you to become one. So, let's begin. All right. So,

0:33 what actually is the AI person? Right now, there's two types of people using AI at work. The first type opens up chatbt or co-pilot, asks a couple questions, gets an answer, and that's

0:42 pretty much where it ends. While the second type knows how to take AI and actually build something with it. Whether that's an agent that runs the support inbox or a workflow that writes

0:50 their weekly report or a system that cleans up the data before anyone touches it. The AI person is the second type of person. You're the go-to inside a business for anything AI, the one who

0:58 finds the problems worth automating and then builds the fix. And you can do this one of two ways. You can do it as your own thing, going business to business and selling it as a service or in-house

1:06 where you become the AI person inside of a company. And that seed is worth going after because it's the fastest growing, best paid ground in the entire job market right now. And I mean that with

1:15 actual numbers. PWC tracks over a billion job ads every single year. And in their 2026 report, workers with AI skills are getting paid a 62% premium over people doing the exact same job

1:25 without those AI skills. And a couple of years ago, that premium was only 25%, but it more than doubled. And it's still going up. The roles at the very top, pay a lot more than that. The forward

1:35 deployed engineer, which is basically the AI person who's heavily focused on building, went from around 640 job postings to over 5,000 in a single year. And Palanteer pays them about 210 grand

1:45 at the median. and OpenAI and Enthropic are also hiring the same role right now. And Chief AI officer, a title that barely existed 3 years ago, is paying a median of 1.6 million at the companies

1:55 that are actually disclosing this kind of stuff. Those postings were up 478% in one year. The number of job titles that even mention AI have tripled since 2022 and almost 2/3 of them are outside of

2:05 tech. So, healthcare, marketing, logistics, management. So, being the AI person isn't just some niche tech job. It's turning into a requirement in every company and every department. And the

2:13 earlier that you can become the AI person, the faster you can move up. So that's the value to you. But the reason that every business is about to need this person comes down to one single

2:20 gap. Almost every company already knows that AI matters. You know, they've got the budget and they're under real pressure to use it so that they don't fall behind their [music] competitors.

2:28 But the problem is almost none of them have pulled it off successfully. I'm sure you guys have all heard that MIT study. They ran a study on enterprise AI products in 2025 and they found that 95%

2:37 of company AI pilots delivered no measurable return at all. And then McKenzie found basically the same thing. 88% of companies say that they're using AI somewhere, but only 7% of companies

2:45 have actually scaled it across the business. So, what we're seeing is the budget's there, the pressure is there, the results are not there. Every one of these companies needs someone who can

2:53 walk in and turn the AI spend into an actual result. And right now, that seat is pretty empty. And real quick, before we jump into the actual road map, I want to let you know that I have a full guide

3:00 on how to price AI workflows in my free school community, which you can access for completely free using the link in the description. I also published a video alongside that guide where I go

3:08 over all these different scenarios and methods, which I will tag right up here if you want to check that out. Now, whether you want to sell your services to businesses or you want to be the

3:15 in-house AI person, understanding what I talk about in that video is really important because it's all about proving the value that these systems will create and justifying the expense, which is how

3:23 if you're the in-house AI person, you're able to go ask for, you know, bigger budgets and more resources for your projects that you want to take on. So, anyways, let's get back to the video.

3:30 Here is the actual road map to becoming the in-house AI person. And I broke it into three phases. So phase one is just to position yourself. You start as a builder and that just means you're the

3:39 one actually making things with AI, not the person just talking about AI in the meetings. Then you're going to go ahead and pick your niche. So don't try to be the AI person for the whole company on

3:46 day one. Just start with one team with a few workflows. Choose the team you're already on and make that your [music] patch of ground. Then you start to market right inside a company. That just

3:54 means you make your work visible. So you help co-workers with their most annoying task. You ask your boss what eats up the most time in the department. And now you're not guessing what to build.

4:02 you're having people on the team actually tell you what would be valuable to them. Then we move on to phase two, which is proving your value. So you start with one task off that list, you

4:10 know, the most expensive, the most repeatable, where if AI gets it a little bit wrong, nobody gets hurt. So these could be weekly reports, meeting notes, sorting the inbox, cleaning up data,

4:18 just the stuff that's boring but really repetitive. And one quick rule before you touch anything, only use the AI tools that your company actually allows. And never put company or customer data

4:26 into something that isn't approved. But here's the most important part. Before you build, you have to name the number that you're aiming to move. This is the whole difference between a builder and a

4:34 consultant because a builder is just going to, you know, build. They're just going to make some things that look cool. But a consultant picks one number and actually moves it. And that number

4:40 almost always falls into one of three buckets, which are time saved, mistakes cut, or money made. So, for example, a Friday report, that number that you're trying to move is maybe 4 hours it eats

4:49 every week, and turning that into something like 20 minutes. But these numbers can also get more specific. And honestly, the more specific the better, like organic form submissions per week

4:56 or average response time or refund percentage. And then once you have the number, you build a fix to move that number and then you record it. You give Claude the real docs behind the task,

5:04 the last few reports, the template, and you work with it until it nails the report every time. And then you record a quick before and after video or case study. So, hey, you know, this used to

5:12 take 4 hours, but watch me do this in 10 minutes because I built this AI system. And then you deliver it for real. And you prove that the number moved, not just saying, hey, you know, this should

5:20 save you some time. You actually measure it. 4 hours down to 20 minutes is 3 and 1/2 hours back every single week. And now you've got proof, not just a promise. And then you basically just run

5:28 that same loop on the next task and the one after that until you've built up a whole stack of wins with real numbers attached. And then you move into phase three, which is to become impossible to

5:36 replace. Because if you have a big stack of wins, but they're, you know, you're not doing anything with them, then it's useless. Because you could build a bunch of systems, they're actually helping the

5:43 business. But if nobody knows, then what's the point? So phase two is about getting the results. Phase three is about making sure those results actually get pinned to your name. Because here's

5:51 what usually happens. Like I said, the business starts saving real money and everybody just assumes someone upstairs will notice and connect it back to you. But usually they won't and it just kind

5:58 of disappears into, oh yeah, we had a great quarter. So what you have to do is connect it. Every win that you bring to the team, you frame it as the business's win, but you make it undeniable that it

6:06 came because of the systems that you built. And when you're able to show them all of this proof, all of these outcomes, that's the math that gets a role created for you. And then you raise

6:14 the altitude because saving people time is useful, but it's not ultimately like what really really grows a business. What really grows a business is attacking constraints. A company only

6:23 grows as fast as its single biggest bottleneck lets it. And at the highest level, every business is one of two things. It's either supply constrained, where they can't produce or deliver

6:30 enough to keep up with demand, or it's demand constrainted, where they could handle way more customers. They just don't have enough coming in. And a quick way to tell which one you're in is just

6:38 to ask what breaks if the company doubled its customers tomorrow. If everything falls over, then you're supply constraint. And if you can handle them just fine and you're just not

6:45 there, then you're demand constraint. And this is truly where you stop being just like, hey, the AI guy, the AI automation guy, and you become the person with the perspective. You walk

6:52 into the room and you say, this is our real bottleneck. this is the exact thing capping our growth and here's the AI system that I'd like to build to attack this constraint. Then you build it, you

7:00 prove that that constraint actually opened up. Same loop as phase two, a much bigger number at a much larger scale. And the second that bottleneck clears, guess what happens? A new one

7:08 takes its place. So then you go attack that one too. And you just keep doing that constraint after constraint. And that's the person that a business physically doesn't want to have to

7:15 replace. You're not shaving a few hours off someone's week anymore. You're the one moving the thing that their entire growth is stuck behind over and over. And at that point, they don't really

7:22 have a choice. the budget gets bigger for your projects. They put more people under you so you can move faster and the resources just start showing up. You're not an employee who's good with AI.

7:30 You're the reason the business is growing. So that's the full road map. Position yourself, prove your value, and become impossible to replace. But there is one catch. You can follow every step

7:36 in this road map, but if you can't actually build the solutions with AI, then none of this works. The good news is you can learn how to build all of it for free in my community. Full courses,

7:44 all the tools, and every resource that I use in my videos. I also put together a resource free guide today that covers everything that I just talked about in this video and it's in my free school

7:52 community as well. And if you get stuck, you've got me and the whole community in there to help you out. So anyways, that's going to do it for this one. And if you got something out of it, please

7:58 give it a like. It helps me out a ton. And as always, I appreciate you guys making it to the end of the video. I'll see you on the next one. Thanks everyone.