Video Title: If I Wanted to Start a Career in AI in 2026, I'd Do This (Without Coding)
Author: Liam Ottley
Duration: 49 minutes
Description: The video discusses the pathways to starting a career in AI in 2026, focusing on both coding and no-code routes. It features insights from David Ebbelaar, founder of Datalumina.
Pathways to AI Careers
Monetization in AI
Core Skills for AI Engineers
Future of AI Agencies
Developer Path
No-Code Path
“You don't have to code in order to be successful in AI; it's something you can explore.” - David Ebbelaar
Freelancing:
Agencies:
Educational Consulting:
Fundamentals of Language Models:
System Design:
Application Development:
Monitoring and Evaluation:
Deployment Strategies:
“The definition of success has broadened a lot... there are so many ways to monetize AI.” - David Ebbelaar
Market Trends:
Rise of No-Code Solutions:
The video by Liam Ottley and David Ebbelaar provides a comprehensive overview of the evolving landscape of AI careers in 2026. It emphasizes the importance of adaptability, continuous learning, and the exploration of both coding and no-code pathways. With the rapid advancements in AI tools and the increasing demand for skilled professionals, individuals interested in pursuing a career in AI have unprecedented opportunities to succeed, regardless of their technical background.
This analysis highlights the potential for anyone to break into the AI field by utilizing available resources, community support, and innovative tools.
Do you think you need to go to university? It >> could very well be that it's hard for you to find a job. Everything that happened over the past one or two years, there will be very few. >> Do you need to learn to code to succeed in AI? >> I would say these days, everyone is trying to get into AI. But the question is how do I need to learn how to code? What routes are there in? What ways can I actually monetize it? And what does success actually look like? So, I wanted to have this discussion with my good friend Dave Eblahar who runs Data Luminina, a training program for people getting into Genai as a developer. and also a founder of his own agency. So we have a lot in common there and this discussion is really a debate for both camps of do you need to learn how to code? Do you take the developer route or can you come through and learn no code and build a successful business and create the life of your dreams that way. So hope you enjoy this conversation with Dave. >> Dave mate what's up? What have you been doing? >> What up Liam? Great to be here man. So primarily what we're focusing on right now in data luminina is we're really building out the educational programs that we have for all of the developers that we want to help in the AI space and essentially help people all the way from never having written for example a single line of of code all the way to the AI engineering that we do and then also selling that as a service to clients for example as a freelancer and then of course with the agency working on the client projects trying to scale that up uh And that's constantly moving, right? Still trying to figure out how to best go about that. The types of clients that we want to work with and the types of like niching down we want to do with the agency. I think that's also something you can probably relate to. Yeah. No, we can we can get into agency niching a bit later, but I want I want to start off with what probably people have clicked on here to uh to have a listen about, which is this, do you need to learn to code to succeed in AI, which has been a pretty hot topic. I mean, I got I got flamed a lot at the start of my kind of my career on on YouTube here for I think even like before we were mates like you made I made the I started talking about obviously the no code stuff and what we were seeing with like client delivery. I think you made a video and you like said there's there's some guys on the internet talking about this no code stuff but I think like we've all kind of converged on the same conclusion that it doesn't really matter how the you build the stuff like like with the agent builder coming out and things like that it's very clear now uh what the what the final resolution there was. But as someone who's literally training people into into G AI development, you're probably the best person to talk to in this. But what's your perspective on do you need to learn to code to succeed in AI? Um we probably should get clear on what what success means first. So for for say your students, what do you what do you class as as success? >> So when it comes to the students I work with, success in AI primarily means look >> I want to learn how to code to probably like land a job uh or start as a freelancer, do my own thing. But most of them want to get a job in the field and that is as a programmer as an AI engineer as a developer. So that's what most of my students would define as success. But if we come back to look if you want to take part in AI, if you want to ride this wave essentially, do you need to know how to code? I would say definitely not. Even though like that's heavily that's my background, that's what I specialize in. That's what I love. There are so many ways that you can be successful within the space, right? I know plenty of people who make a living like just going to businesses and helping just helping the the the employees there get started with AI understand what what that looks like. So for for the people like watching it really comes down to look at what kind of level um do you want to work with AI? Do you just want to use the tools that are already available? Do you want to learn how to use these models? Then that's a level you can play the game at. or do are you like more interested in this and maybe a little bit more technical and you feel like look I I really also want to learn how to code and then that could be uh something for you to focus on and that's also how you can be successful. So yeah long long answer short you don't have to code in order to be successful in AI it's something you can explore. I think one of the the good things that we're seeing at the moment is the market really taking shape and over the past I'd say 12 12 months it's become very clear that there's a there's a development portion there's of course like the no code development there's there's make.com there's uh any of the I mean agent builder coming out now as well it's very clear that there's a there's definitely a path into it that way and then there's the more like I want to be an actual geni engineer and I mean these are the people that we need at at companies and agencies like ours there's also the consulting route that's popping up there's also the outright education like you're talking about some people that you you already know, you can go into companies and train them on how to use JGBT. I I still think that's a massive opportunity. I've had people who are who are good mates of mine getting into doing workshops. I think if you're looking to come in like the original route into AI was was through the the low code or or to actual development and now there's like I think you kind of flip it on its head and go in through the workshop route, go start with education and then move down to offering consulting after that and then eventually get into development at the end of it. So you used to be able to only go through the development portion, but I think now you could come down from the top and start off as nontechnical and if you're talking about like success, if it's monetary success, there's so many different ways to do it now. So there's definitely still a massive need for the for the AI engineers and that's only going to increase. Like we're we're always hiring as I'm sure sure you are for good talent, but the the definition of of success is is really broadened a lot. Obviously you teach the the genai development actual actual codebased. Um, do you think it's necessary for those kinds of people to also pick up the the lower code stuff and be kind of cuz we have this as well when we're hiring for our developers at Morningside. We will also say, hey, it's like it's a it's a nice to have if you're also familiar with that whole no code stack because it's just like in a lot of cases it's much more expedient to to build on that or we might have a client project that is already using that or we want to build something ourselves. So there's like two sides to it and obviously the the ideal developer would have both. So what do you think? Okay guys, very quickly two things from me. If you're a business owner who's interested in what generative AI can do for your business, you can get in touch with me and my team at Mornings.AI in one of the links in the description below and we can start your entire AI transformation process going all the way from the education and training of your staff to the identification of the best AI use cases for your company all the way through to development and beyond. We have worked with some of the world's biggest sports teams and also publicly traded companies. So rest assured, you are in good hands. If you're an aspiring entrepreneur and want to start your own AI business and you haven't already joined my free school community, it's down there in one of the links in the description below. has my full free course on how to start your own AI agency as a complete beginner. And you're surrounded by over a quarter million people who are also striving towards the same thing. There's no better place on the planet right now to be surrounded by like-minded people. And you get free weekly Q&A with me where you can ask questions directly to me about how to start and scale your business. I'll see you in there. I totally agree with you there. We in our agency had to learn the hard way. So, um, a lot of engineers of course super technical, right? They want to solve most of their problems through like the the technical knowledge and the tools that they have, right? So, similar to when you have a hammer, everything looks like a nail, right? But then stepping in and like zooming out a little bit and be like, look, this is actually a problem. Like you don't need to custom build for this. Like you don't need to spend like two, three weeks, maybe even a month to set this up and then have the whole like production pipeline. This can literally just be an NAND automation and we can set it up in a day. Even if you are super technical, even if you're an engineer and that is what you do, knowing also how to use these low code no code tools and knowing how they work and also being able to u uh clearly educate a client and say look you're asking for this but it would actually be better for you if we do it that like this long term. This is also something I'm uh teaching in my programs right now just so um that also the clients that also work with our students have a better overall experience so you don't end up wasting like tens of thousands of dollars maybe on a proof of concept that in the end doesn't work that maybe could have been validated with a quick NAN build. >> Yeah 100%. Um and with with your students that you're working with why don't you if you could just give a rough rundown if someone else was wanting to take that path and get into the point of like basically AI freelancing. um why don't you give your your route through that you're pushing them pushing them through and then I can kind of give uh and and some examples as well of of sort of the other route if you're completely nontechnical now and you're wanting to learn AI I can I can kind of give what I've seen works on on mine. >> Yeah, sure. So I can quickly walk you through kind of like my path. Um and then what I do right now is I I teach the exact same path that I went through but then just in a way I could just >> not in 10 years or whatever. >> Just not in 10 years. So I started I started studying AI actually in 2013 already. So this is literally over 10 years ago. So did the bachelor, did the master uh yeah technical training and then out of uni I started um I started working as a data scientist and I already immediately got into freelancing just just came came out of nowhere on my path like in the beginning like the first one to be honest was quite lucky and then from there you just like built built the skill built the muscle and you essentially know how to find the next project and the next project and that's essentially how you roll into it. That's how I got there. First it was in data science and then when chat GPT was released I immediately saw look I need to go all in on AI this on genai I should say I need to go all in on geni. So that's what I did with it with the business. And at that time um before this chat GPT boom and when I was just starting out with YouTube, what I primarily was doing, I was mostly going from long-term contract to long-term contract. Because one of the things that you should understand about freelancing in the tech industry. So this is if you have technical skills, if you are a programmer, it's not so much that you jump from like a 3K project to a 5K project and you're juggling three to five clients per month. Like you can do this, but as a freelance in the tech industry, like 80% of them, they just have one or two clients at the same time and just cruise three months, six months. I even had contracts that were just a year long and they're not full-time. And then on top of that, I would stack other uh projects as well. And there are actually people here who are paid to find people like you and place them inside companies where you can just cruise for 24 hours per week or 32 hours per week. And then that is a way into freelancing for you. So that's kind of like a stepping stone that I did in the beginning. And then um as uh Chet GBT was getting bigger and bigger at that time, I was already I was I already had my YouTube channel. Creating content is of course another great way to like get yourself on the radar. I don't have to tell you this. And with that, you also find that over time, if you do it right, you'll get inbound leads. So, this is now where you have these longer term contracts which are paid really well. Like if you're an engineer, like hourly rates, €100 or 100 USD, 120, 150, and if you have like 24 22 or 20 32 hours per week, you can make great money. So that's all great. Then when you stack a personal brand on top of that and you also start to get inbound leads and you with those you focus more on the on the quick projects that you maybe do via a uh for a fixed price, right? That is essentially the the secret sauce in the mix that we teach inside our program. So that hybrid approach where on the one hand you have the security as an engineer or developer and you stack smaller more higher paid projects on top of that and that's how we find that students have really high success rate. It's really fun. the work is dynamic. Uh, but you never have have to have that feast or famine life cycles that you can have, right, as an agency owner or as a freelancer. >> Are you saying that everyone should do the the content thing? Cuz that's something that I've I've struggled with with um helping my students. >> You should try content and see if it's for you. See if you like it. But it's not for everyone. It's just not for everyone. But you you don't know that until you give it a try. So this is and this is then also like kind of like tricky to do, right? is you need to get in a couple of reps because in the beginning everyone's going to suck, right? In the beginning, no one is good at this and you need to get better at this. You also need to have just some kind of like it factor, right? Some people just have that and then you see the channels pop up. That is just something where you just got to you just got to be really honest with yourself and you got to put in the work. You got to try and like make a couple of videos. See if you like it. See if you get some traction and also like critically look at at the videos and actually like look it is this adding really any value? Am I really helping people? What are what do the comments look like? And if you get some early traction there and you really like it, that could be a good signal that you should continue with that. If you like absolutely dread it and you tried like three, five videos and you're like, I hate this. I don't see any results. It might be that content is not for you. And it might be more so that for example as an engineer, as a technical person, you are way better off maybe for example going on a platform like Upwork and being more behind the scenes and just bang out proposals there and make sure you create a killer profile there and build up the reputation there so you never have to worry about any sales or marketing and clients just come to you. So that's another way that you can create inbound leads. there are more uh alternatives that you can get into >> the pathway into it. We've got obviously there's there's like a Python base and stuff and I assume there's like do you put your guys through a mandatory set of like fixed projects like hey you're going to run into a rag system you're going to run into like a a chat 2 database system like what's is there obviously a Python base probably if they're learning that initially and then going through to uh knocking off a few of those initial builds like what would you say if you had to have like the main three to five uh use cases that if you were to learn to code uh you would need to to know as a GI developer. Great question. So when um when it comes to essentially building Genai applications that can actually make it to production, I would say there are six key components that you really need to understand beyond just the basic Python skills, right? So first is really about the uh really the the fundamentals that you need to understand about the the language models that you're working with. So this is everything that has to do with like tokenization, prompt engineering, how do these models work. This is the entry point. So you start to get a fundamental understanding of look we have this medium that is a language model and we as engineers we can program around this. This is also where you get into all of the SDKs for all of the big models right so open AI entropic understand how how they work understand what function calling is understand what structured output is uh how to use tools in there so really these fundamentals then the second thing that you really need to understand is um system design. So this is now knowing that you have this this medium that is a a large language model and how to look at the business process and I always recommend like really creating diagrams and going to the whiteboard >> and then designing the architecture and designing the system. This is also sometimes referred to as a cognitive architecture. So can you draw out on the whiteboard what the business process is where you just need like simple programming logic and where you maybe need large language models because all really AI engineering and GI engineering really is about is about essentially taking a problem and finding a small enough component where you want to pluck in the language model. You don't want to solve big problems with large language models because that can get really messy. The third thing that you need to uh essentially that we also walk people through is getting to the core of okay look I can uh take this model I can build stuff with it but how do I piece it together in something that we would call a production ready application right so this is your endpoints your databases how do you stack that together using ideally using docker that's what we recommend and you package it in such a way where now it becomes an application then you're already uh really far ahead in terms of what you can And then if you want to get even further, what you also need is you need a solid solid understanding of rack and all the like concepts around that. So retrieval augmented generation. So factor databases, factor pipelines, how you can take uh document processing pipelines and then also advanced algorithms that you can use to uh improve your your retrieval ranking. >> Yeah, reranking etc. So all of these concepts around rack I would say that's also a core skill where if you want to get into any job uh whether it's freelancing or full-time like you need to know rag because otherwise the interview will be kind of awkward. Essentially the next step after that is this is probably the most important one everything that has to do with monitoring evaluations and guardrails because these applications are messy. The thing the one of the challenges with Gen AI and with AI engineering is as soon as you launch something whether it's a proof of concept and MVP it's never going to be 100%. It's going to be 60 70 80% and this is tricky because for some use cases 80% might not be enough and it might take you for example like 1 2 3 weeks to get to 80% and it might take you 6 months to get to 85% and it still might not be enough. So you need to have a really good set of tools and skills to understand monitoring. So we for example use lang fuse uh for that internally. You need to understand about guard rails, how to set up evaluations. And then step number six that you also need is uh a solid understanding of deployment. So your deployment strategies, you take all of all of the things that you did before that and now you can actually put that onto a server or deploy it somewhere and now it can actually start to generate value. So that's the road map. we uh we take people through um and also all of the things that I had to learn over the over the last years which we now use to help yeah build and deploy all of the projects for our clients. Well, I'd be interested to to know your thoughts on I mean, you talked there about the the difficulty and the success rates that that you encounter in pretty much any any tune AI project and and we know this very well at Morningside as well, how much that last like 5 10% can be sometimes and on some use cases it's it's okay and like you can have a little bit of particular if there's like a human in the middle or or a staff member using it, but as soon as that's going out to the prospects um and the outer world, then then you're in in trouble. But with this new agent builder and what OpenAI has released there, obviously multi- aent and I mean that just makes me like sort of shiver as a as an agency owner because I know like a single agent is often difficult enough to get working let alone multiple agents talking to each other. So and baked into that we've got observability, we've got evals and things like that. So what are your thoughts on on this new platform? We're already kind of looking at it for some of our builds that we've got coming up. Um and just try and say, hey, how far can we push this thing? um can we replace them with our custom code with it? Uh what are your thoughts overall on the on the agent builder and how it fits into into the agency landscape and just to develop a toolkit that way? >> Well, it it's one of those things it looks very promising. I haven't really like fully uh like build out an entire project with it, but based on what I've heard is like so it's early, right? And OpenAI has a tendency to release stuff that in the demo looks really good like like the assistance API was also one of those things where we thought oh yeah we don't we can just use the assistance API right we it can take care of rack it can keep track of our our conversations in like the real world like no engineer is is using that so I feel like the the the agent the agent builder is in a similar stage right now where it looks promising but it's still the thing is you are you're building an abstraction a a visual interface over the core logic where at some point you're going to hit a limit. So I think this is still going to be super valuable and for like but similar in a way how NAN is super valuable and make.com is super valuable and all of these tools are super valuable in their own way but at some point you're you're likely going to run into a limitation where yeah now we need to tweak the performance even more and it can get tricky. What I like about agent kit, agent builder in uh uh specifically is that it's like fully like LLM geni first, right? If you look at NAN, make.com, Zapier, they are they were all like low code no code like stacked AI on top of it. So what you see in the design of the system is you see all these common patterns that we need when we're trying to build agent applications. So like guard rails like completely built into it because it's really important and making that really easy and of course like changing all the different models and prompts and all of that. I like how LLM and Genai native it is. Um and I think it's a really good tool but I think ultimately you're going to run into the same issues that you have when you're for example using N8N with more complex builds that at some point you're just going to hit a wall. >> Yeah. I mean when I was looking at it, it obviously looks looks nice and they have made these kind of big big promises before. Um I I think it's interesting from a from a perspective I see them as kind of being the the apple of AI automation at this point. You know, they're trying to make the closed ecosystem where like you know you're not going to be plugging in all these different models. You lose the ability to be model agnostic, but what you get in Exchange is just like ease of use, ease of experience, like a nice customer experience and user experience when you're setting it up. Um, and then all these little like quality of life things that are sort of native to it because it's GI first. So, I'm excited. I'm going to be jumping in more and seeing what I can I can cook up and maybe putting a video out on it. But, I was kind of shocked when it came out to be honest. I didn't I didn't see them going that way. But, it's it's just another example of like when the assistance API came out, they nuked a whole bunch of startups there and they've done it again. Right now, these are all early stages, right? But what you'll find often is that like Chad GBT remains the center of it, right? it usually remains like the nucleus which where it can really easily integrate with with chat GPT who's like everyone is using right so I think having that power and then on top of that like making all of these other tools better and better and better where that that could be really where you get that Apple effect that lock in where you feel like yeah okay I could use that other tool it might be like a couple% better but it's just so easy that I have everything in here why would I even bother >> that's the allure right I think It's I I call it like Apple versus Android where are you going to maybe take a little bit longer to set up and I think once you layer on top something like these these like vibe automation things as I'm I'm calling calling it now where you can like if you go to NAT and they've got for some people you have access to the to the like text interface where you can go text to workflow. I think like the ease of setting stuff up is going to be insane when you have a like an assistant in there on the agent builder where you can like type into it, hey, I'm building this and instead of actually having to move things around manually yourself. um you're able to to prompt in to get it to build it for you. So, uh that that does open a big question which a lot of the agency owners on here would be would be eager to know like this seems like development development is kind of racing to zero and it's like a business is going to start to do this and my my push back on that is like no this is a dev day. It wasn't a business day like it's still developer tools like business are not going to be hopping on there and building their own multi- aent systems. So, it's still uh very much very much in our in our uh court. But with the development becoming a lot easier, there's questions around like is this going to lead to a massive influx of new people in there? And again, I still think like these no code platforms been around and they're probably a lot easier for most of the basic use cases. People have had plenty of time to get into it. Um, but there's sort of the broader question of of what happens to development long term as these things get easier. So, what are your thoughts on on Genai development with the rise of these no-go platforms like viable automation becoming easier and easier and how that's going to affect the uh the agency market? So first let let's start what we already see happening in in the big corporates and the enterprises right and then we can get down to kind of like the agency uh level where what we're already seeing is that kind kind of like the paradigm of really big organizations with huge engineering teams. We already see that shrinking because they're just trying they're just figuring out look if we have like a couple hundred instead of a couple thousand like really good engineers with AI assisted coding tools we can be much more efficient. So there definitely things are changing and yeah we're not really sure where this is. Like on the one hand like every other quarter you get like these crazy new up news updates where it's like oh this company like fired like half of their engineers and then another quarter is like oh they hired them back. So like we're still like trying to figure out but I I there is definitely a trend going on like developer productivity has increased tremendously. I think out of I think out of everything where AI can add value and add productivity right now, it's probably the developers that benefit the most from it in terms of like pure like hours saved on a monthly >> ROI. Yeah. >> Clear ROI because it's just so good there because LLM's and and and AI is like coding is such a nice and defined problem, right? You have a problem, you create a code, you run it. Does it work? No. Okay, you iterate on the error and >> it's all basically text base, right? like a >> it's such a nice environment uh uh to uh to use these language models in and it is now really up to up to us up to the world to figure out okay what's going to be the cursor what's going to be the clawed codes but then for other domains right for the medical domain for for law whatever and that that's a trend that that we're seeing there but then if we boil it down to like the the smaller organizations what I think is going to happen is we will see distribution of all that development talent. Well, where before it was more concentrated um in larger organizations where huge development teams would work together and a lot of companies don't need used to not need a developer. Many industries like you don't need a developer. Right now is like every I feel like every company if you want to stay competitive you should have AI on your radar and you should do stuff with that. Even if you're just like a con construction company, even for like the admin administrative process or something like that, AI can probably help you there. So, what you'll probably see is that you'll have more and more smaller companies that are not going to hire a full-time developer because that doesn't make sense, but they do want in on AI. So, then they're going to look around them and that's where the agencies and the freelancers can come in. So, I that's that's that's a trend that I see. So when we are in this like agency freelance tech bubble right where we see that there are so many people like jumping onto this but if you look outside our bubble there are also so many businesses who are starting to jump on on AI in the nearshort term thinking like next 1 2 3 4 5 years and who knows where AI is then I I still think there is plenty of space for developers at any level whether you use n10.com make or you become a full-blown AI engineer there will be opportunities for you, but you need to be more strategic about it because it could very well be that if you now go to uni, you do computer science, you specialize in AI engineering, it could very well be that it's hard for you to find a job if you go the traditional route and try to uh uh work for the top companies because they're just like rep prioritizing as to what it means to have uh a big engineering teams. Do you think you need to go to university at this point to get into to to succeed in some way? What would you recommend? They do the kind of self-taught scrappy route or they go to university, do the computer science and they add AI on top of that. What do you think is is is the best best route at this point? >> With the knowledge that I have right now and if I look what I learned in uni, there are so there are so much faster ways to to get up up to speed into what's going on. And on top of that, if you go to uni right now, all of the stuff that you'll learn on AI, even even you like computer science, artificial intelligence, that like curriculum will be outdated because they they cannot keep up. Like everything that happened over the past one or two years, there will be very few like uni studies that uh teach what what really can get you a job right now. But that said, having like the credibility, having the university paper, it still is a form of credibility, right? And if you want to get into certain fields or you want to get into certain companies, it might not it might still be required. So, you won't even like really get on the radar if you don't have a degree. That's still the world that we that we live in. But is it a is it a good way to learn AI? Definitely not. just go to YouTube and like watch what the the creators are doing there. Watch the the the latest news and how they are building with these models. So that's how you learn fast and then coming back to do you need it. So it it depends on the route that you want to take and if you're like look I'm also totally okay with maybe like working for like smaller companies starting my own thing then they don't care about your degree and your credentials. They only care if you care about what you >> done. Yeah. >> Yeah. Yeah. The experience talks 100%. And um it just goes to show if you're looking at like the people like with programs and and selling courses around this stuff like even in the online space it's hard to keep up and like even for you you can be you're very very very like on top of things but as soon as you make course material 3 6 months later you got to make new stuff like it even for people who are are literally moving at the at the fastest pace with the stuff. It's still hard to to keep pace. So you can't expect some slow clunky university to be able to do it. The way I see it at least as someone who like I dropped out of uni and I'm glad I did. What do you think is going to get you further in your career? Is it like four years, 5 years and a piece of paper that gets you that credibility or four to five years in the trenches building it and working as a freelancer or building your own agency and stuff like that? So, and I think if you do it right, obviously the four to five years spent in a business like we're I'm only we're only getting into really like year three here and look at look how far both of us have come. So, uh I I know where I I stand on that for sure. >> I share this perspective, right? So, you can follow your old traditional model and it it it might still work out, right? that is still a proven path that you can take, but you don't have to in today's day and age. And if you want to keep up, uni is not the place to go to. And there are plenty of opportunities if you can just if you can build stuff, if you can help people, which now is easier and easier because here here's also the thing. When I was in uni and when I just started working, AI and data science was only really for the big enterprises who had like big budgets, big data sets. We would train custom machine learning models. It would take like months to get to a model that we could put into production all like very long big enterprisey kind of like projects. But right now AI like I've said literally every b business can benefit from that. And knowing that opens up the door for so many opportunities if you just learn how to like work with these tools and actually create useful automation. So don't just like study the material, go and build stuff like and first try to try to solve your own problems, right? That's how how I always like to learn. Like for example, when there's something new, let's try and automate something in my business using some of these new stacks and then you you it starts to click and then once you prove that there there's probably someone else on this planet that is willing to pay you for that uh to help them solve a similar problem. >> You've run through the the the coding route to go and that that you recommend. Uh, as for if you're if you're non-technical and you're watching this and you're wondering about like, oh, what's what's my best way? And if I don't necessarily think I've got the I've got the got the skills or or I don't really see myself going into the full code way. I have seen like dozens if not hundreds of people now, they go into the the low code route, no code route, and they just kind of like bash their head against it until they figure it out. And it's completely possible. Like we have uh I had Henrik on the channel recently and he he joined my program uh like a year and a year and a half ago, maybe maybe even more now. Um, and for the first like six to 6 to 12 months, he came in completely green, like absolutely no business or or AI experience. And now after bashing head on.com for I think it was like 6 months before he really started to get the knack of it and started landing clients. But 6 months after that, he started working with voice agents. I connected him with Giannis and now they built a really successful agency and a program as well. And he's one of the one of the leading voices in terms of practitioners actually out there delivering voice AI for businesses. He's there delivering like multi multi-f figure projects for I think they had like a billion dollar uh client. So it's completely possible for you to go that route. And it's just a case of I mean I had Mckll on here recently as well. I'll link that uh in the description, but he was completely non techchnical as well. He's like I'm just going to learn make.com as my base. And I think as a meta skill learning automation via nad or make.com probably push beginners to to make.com just to start. It's a little bit more beginner friendly. But you can just sort of bash your way through it and finding okay personal problems. There's so much information on YouTube now for it. There's I've got a full course on on learning make automation and particularly the AI portion of it. So I'll also link that down below. But all the information is out there. I think people just need to be a bit more patient with themselves. And like you're learning an entirely new kind of automation development skills here from the ground up. It's not going to happen overnight, but it's definitely possible within 3 to 6 months of just working away. If you do some personal projects, do it for your friends and family. start to reach out to people around you. Hey, I've learned this AI automation thing. Uh would there be anything that you're interested in maybe having a chat and see if I can help your business? I'll do it for free. And then from there, you can go to communities like mine and yours and start posting. I've had so many people now who are in there and they're making posts and saying, "Hey, look, I'm available for work. I've done sort of these these few things. I can have a chat with you and let you know if uh there's anything I can help you with offering work for free." And then from there, they start getting paid clients off the back of that. I see even like another layer coming out at the moment in terms of like succeeding in AI where there's these like service delivery platforms that have abstracted it one layer even further where you've got I see you having custom code as the bottom layer and you kind of abstract that into no code and then now instead of like having to learn like six different no code tools and make like have a kind of flexible skill set you can abstract that even further into these like targeted platforms kind of like what Simon has with with Booked in that takes a lot of the complexity away of connecting six tools to just being able to say okay I'm going to build a inbound voice agent or receptionist on this platform and it takes away a lot of the complexity for me. So that's a really really good time for people to be getting in and getting onto onto those platforms and that's just the development portion. If you want to go the AI consultant route, that's a thing. If you want to go AI workshop route, that's another I'm so blessed to have been able to get into this at the time we did and I still think it's ridiculously early. Uh I'm I'm almost close to saying like >> it's pretty hard to not like get some success in this in the space if you just apply yourself, you keep your ears open, you are participating communities. literally I haven't seen a safer bet or a sher bet or like a guaranteed bet in terms of entrepreneurship um that I wish I had when I started. Man, I wish I started on this stuff. >> I was like bashing my head away on on like e-commerce stuff and just eating for so long and losing all my money. Um this is such an incredible time for particularly young people to to start the careers. >> There's one more thing right now which is also was also uh worth something uh looking into right now which is I'm curious to hear your take on it. So you know right now MCPs are like everywhere right? So MCP servers where you have all kinds of tools that are available right now and more and more companies are creating MCP servers for their tool right and you can hook them up to either chatpt or to cloud desktop and one of the things we are exploring right now is instead of like doing builds kind of like from top down. So you come in, you solve a big problem and then you embed that into the business. You kind of like work your you work your way up and you start where people are already using AI because everyone in almost all company like you have some teams already most of the people are already using chat GPT they're already familiar uh with those tools. So then instead of coming in and doing a build for example either like custom or through make.com or nadn to automate a portion you make it available as a tool within an AI chat application that they're already using. And this way you also automatically embed the human in the loop. And now all of a sudden you can let someone like let's say a sales rep you can say hey what are my um what are my appointments for today? Use the MCP server from the calendar. It loads in the context of that day. Okay. Now I see okay I have a I have a call with John at 10. So now all in chat GBT hey let let's actually pull the latest information from the CRM like for John. And now you actually get like a report for the sales rep all in chat GPT. And this is just different way of trying to creating these automation doing it in inside these applications which I think even if you're a beginner and you're not that technical hooking up those MCP servers through tools like chat GBT and cloud desktop anyone can learn that. >> Think of that as like a service like I'll go into your company and I'll set everyone up with the right tools. I'll I'll hook up the MCPS to their uh to their claude and then I'm going to show them how to do it. Is that is that the service? >> For sure. >> Yeah, for sure. I really like that genius >> for you. Like this is a sick surface because you can come in and you can can create all kinds of offers around this, right? I could do 10 tools, tendium CPU servers, this that you can you can you can really package that and >> what essentially the pitch is here is say >> let's say look people inside your company they're all already using CGP right yes they're already using CHP okay that already makes them a certain percentage more productive you like you can find the latest information on I don't know the exact numbers but essentially like the pitch that you have is look in two weeks I can make all of your employees who use CHBT I can make them 5% more productive by integrating custom MCP servers specifically for your business. And >> that's on the low end. That's like absolutely on on the low end of things. Um I mean that's that's just genius cuz you're just like the interface is always a tricky part, you know, like you can build to the back end and stuff and then >> worry about that. You can rely on R&D budget from OpenAI to handle this for you. >> Yeah. No, that's genius. That's genius. Um I I think just generally I'm I'm really still waiting for someone to do it. We have our own education uh like workshops at Morningside that we do. Uh but in terms of building out an entire like I still think if you did a a chatb course for businesses and you broke it sort of general chatbt training and then you broke it down by like uh by department. So like okay if you're in the marketing department here's a few different like here's the specific skills of how you can apply deep research or how you can apply uh the image generation or you can apply sore and things like this and you break it down within each department. I think if you threw on top of that like I'll set up I'll set set up the MCPS for each uh each person's uh chat or cloud instance I think that would that would absolutely cook. So I really think training that that seems to be the lowest hanging fruit in my eyes is just teaching people how to use these tools is already the data on how much more productive uh people are when they're using it. It should be should be an easy sell and also it's probably a lot more lot more scalable than like outright dev. Yeah, the MCP thing smart, bro. >> Yeah, it it's a good one. It's like like it like you don't need to worry about the UI that's covered for you and these MCP servers are getting get better and better and as the models get better. This is also one of one of the things as the AI models get better your solutions also get better. So it's just is like one of the things you just bet on OpenAI and Enropic to like go crush it and then you can build your service around that. We see a lot of opportunity in there and we're just kind of like right now waiting for like the right client, the right use case where they maybe want to custom build and we say look I think we can do this do this just through MCP servers. >> I mean there's the there's a next step after that which is like trying to build the white labelled version of that and doing it through through the API. Um which I still think is a massive opportunity. I I've seen some some startups appear that is kind of like they call like an AI platform for your company and I think this is like a a great idea for someone to to build out. probably a bit on the like sort of heavy side, but when I think about what AI agencies can be upselling to their clients if you have this like hey all of you you already got like 90% shadow AI usage they're all using it they're all sending your data through the through the chat to you without knowing there's a big like risk of leakage there and and and sort of compliance and stuff like that there's that risk how about we set you up a custom platform these things exist already and it's you can have access to all the models you might be able to like query them side by side and then you can start to add on like okay the co-pilots and the agents that you build can start to be put in there as well. And basically you can add like permissions and you can start to analyze how people are using I think just analyzing how say you had that MCP thing set up as well knowing how your your your team are using using chatbt and the things they're using it for that will sort of identify the use cases for the agency to build out. So if you had a platform, it's like, okay, everyone are going to use JPT and Anthropic and Claude and things like this all through this platform and you're able to run analysis off the back of that for the business owner saying, "Hey, look, looks like Sand Sandra and and Jimmy and the marketing department are using it for these specific tasks. We could potentially like mine like the inside out of that and build something." Um, that's kind of that like bottom up allowing them to figure out the the path of least resistance. >> Yeah, it's great. You can also like see who the power users are, right? So you can see like essentially what they're doing like who's using it and who's not. >> Yeah, you could even get put targets on it like we you need to use AI like certain percent like if you want to like sell it is probably like a little bit of a of a build in the beginning but once you have something like that you have that platform you can easily like redeploy it. I know that there are great like starter kits for this already. So like for example, do you know open web? I think it's called open web UI something like that. It it's kind of like this chat GPT clone that you it's open source that use and you can out of the box like this all already like you need to be a developer in order to like really like work with this. But you you see more and more of this where you essentially have a chat clone. You can select all the models and you can white label it and you can just yeah deploy it on premise or completely private for a company that could smash if you have if you have deals like that because if you can sell that there's lot of recurring revenue because you essentially become the vendor. I always think of like you have like rockstar offers for your agency. If you've niched down, you've got like a real specific you sell that you like getting you more appointments is kind of like the the classic one. Can I increase revenue? But the a typical business strategy you have a really like attractive thing like that that you can run ads so you can sort of talk about a lot that gets a lot of people in. But I'm looking more and more what are these upselles that agencies can do. It's like oh yeah you we of course we can build you that that's going to get you a lot more a lot more lot more appointments. Oh, but we could also like hey you probably got shadow AI usage. Why don't we? And is you have like these softwares like the one we've just been talking about where you're basically like a partner or a distributor of you set them up on it. You get like a referral for your kickback from setting them up on it and you can charge them five grand for the setup and stuff like that. I'm really excited as this like agency market continues to kind of flourish and and grow um what the these kinds of solutions that pop up um in the marketplace because it's just going to allow you to expand your revenue so so much and and a lot of the hard work's already been done by the by the SAS platform. Of course, you always find that if you have your foot in the door, like you said, you have a fancy like offer that you can uh like sell on the front end. Whenever you just do a little bit of digging in any company, this just like literally talking to people, it's so easy to find use cases like and it's it mostly comes down to like like process processes that are just like like not optimized. So like every like every company especially if you grow you you have this, right? And AI is so good in that. We also as an agency have like struggled with this at times like what do we want to focus on? And then every time we think okay look this is kind of like a common pattern that we see. I think this is maybe something that we can productize something around and then another client comes in and like look something completely new. It's like oh yeah this is also something you can do and then another client has something completely different. So it's also like I really liked and that's also what I like about the MCP ID right where you can kind of like standardize some kind of an offer is standardize an offer and then you can like get a foot in the door and like look we can like do do this build in like a couple of days we'll give couple of MCP servers your employees are already more productive and then they're going to run into limits and they're going to ask questions right hey can it also do this can it also do this and now that could like spiral off to uh bigger builds consulting uh more work >> we find it as well when you work with a company who comes in like they come in hot and they know exactly they seem to know exactly what they want and you're like, "Oh, well, I'm just I I'm here to do what you tell me to a certain degree." Um, that might those those people tend to be a lot more difficult than if you sit them down and like, "Okay, let's let's like get to know your business first. Let's figure out like there's way lower hanging fruit in most cases." And it's so refreshing for us once we started doing consulting and then doing development off the back of that. It's like, "Oh we were like doing the hard stuff all the time cuz we were letting them tell us what to do." And so there's like absolute layups that are that are hidden in most businesses that are that they're not taken advantage of. >> That is so relatable that we we in the beginning had that all the time. And we also had to um in the in the beginning when uh chat GBT and this whole new thing was was new, right? We were also excited as an agent, right? Like sure, yeah, we'll build it. Like that sounds cool. Let's try and build it. And over time, we found that, oh, this is actually pretty hard. And we would have projects that would stay stuck at the proof of concept, right? So, we do like a big build and then it it kind of worked, but it just wasn't good enough to move to the next stage. And it wasn't really because the tech wasn't that good, but it's just like the business case didn't make sense, right? It was actually too big, too hard of a problem. And if you really want to solve it, like you put you need to put like another six figures into it to like get it to a degree and then the business gets >> and then it's still kind of a dice roll as well, you know, like >> you never know. Yeah, you could put even more into this thing like run up the bark up the wrong tree even further and like >> and and as an agency owner, you kind of just like it's not even worth sure, it might be a lot of money, but it's just not worth the stress at that point. So that so that's also that's also a skill uh that you need to develop knowing like which are the use cases uh that are very doable which ones are tricky and how to take the the big ones when when clients just ask hey can you build this out for us to really say look this is a really big problem let's start here because I know we can do that instead of like tackling an entire big problem and automating an entire department or something like that >> and I think what you said before about like the MCP server being a sort of inroad. I think that's a really really smart strategy these days is finding something general. Um I mean or I suppose it's a specific I know every company's going to want to like get more leads or like but in this case like I know all of them are probably wanting to get their employees to be more productive. So if you can find kind of a general small offer that's quite easy for you to deliver but has a has a significant uplift for them and benefit. Hey, I'll come in and I'll set up your team on these MCP servers and uh I'll train them on how to use it. You're going to get a quick lift. that just gets that foot in the door and even if you just like set and forget that and they're going to get the insights on like oh XYZ is using it the most uh these are the kind of insuh use cases that are coming off of it then you've got your foot in the door and from there can come the consulting or the development or further education I really think these these companies do need to be eased into it and that's a really really good way to do it so uh if you're smart and you're getting started you'll try to find um offers like that just to summarize about what we've been through here uh no you don't need to know how to code to succeed in AI And of course like success is is that is it outright monetary? Is it like making a billion dollars? Is it just sort of liquiding your job? There's all these different versions and it's such a diverse range of things that have appeared. The market's really taking shape now. Um Dave has given us a rundown on how if you wanted to go the the developer GI developer route, the things you need to know. I've broken down how if you were a nontechnical person, you can go as well. Um, but overall, if you're watching this, you have the the chance right now to to take action on this stuff and and literally within the space of at 6, 12, 24 months, be living a completely different life or quit your job or whatever it is. Um, and I wholeheartedly believe that. I've seen it hundreds of times now, as I'm sure you have, Dave, as well. So just from from from me and I guess Dave as well like you guys are in the right place and uh every day I'm I'm so happy to see people who have taken this opportunity and run with it cuz um these things this this big and this much of a layup don't come around that often. Well Dave, it's been uh great to have you on mate as always and um hopefully have you back on and we can discuss some more uh of the of the news as it comes out. But yeah, this has been great. So that is all for this episode of the podcast guys. If you want to see something similar that I really think you'd like, you can click up here to watch another one. And remember, if you think you have a story worth telling and some valuable insight you can share with the community, you can fill out my podcast application form in the description below. I'd love to have a chat with you and get some exposure for your business. Aside from that, guys, that's all for the video. Thank you so much for watching and I'll see you in the next
📚 Join the #1 community for AI entrepreneurs and connect with 200,000+ members: https://bit.ly/3WbxgqL 📈 We help entrepreneurs, industry experts & developers build and scale their AI Agency: https://bit.ly/43uRTC3 🤝 Ready to transform your business with AI? Let's talk: https://bit.ly/47eZqGp 🚀 Apply to Join My Team: https://bit.ly/explore-roles 🎙️ Be a guest on my podcast: https://bit.ly/yt-podcast-application My Vlog/BTS Channel: https://bit.ly/LiamOttleyVlogs Connect with Dave Ebbelaar: https://www.youtube.com/@daveebbelaar https://www.linkedin.com/in/daveebbelaar/ Mentioned Videos: https://www.youtube.com/watch?v=5TxSqvPbnWw https://www.youtube.com/watch?v=SeybVD0NMQI https://www.youtube.com/watch?v=3HHMuaGIC30 Everyone’s trying to break into AI — but do you really need to learn Python or can you make it with no-code tools? In this episode, I talk with David Ebbelaar, founder of Datalumina, about the two main routes into AI: → The developer path — mastering Python, RAG, and building production-ready apps → The no-code path — using tools like Make, Relevance AI, and OpenAI’s Agent Builder to launch real automations We cover how to become an AI freelancer, the 6 core skills for modern AI engineers, and how agencies can use ChatGPT + MCP servers to scale services. ⏱️ Timestamps: 00:00 What We're Covering 02:30 Do You Need to Code to Succeed in AI? 04:10 How to Make Money in AI Without Coding 07:50 From Student to AI Freelancer 13:01 The 6 Core Skills for AI Engineers 17:39 OpenAI Agent Builder & Multi-Agent Systems 26:00 The Future of AI Agencies & Freelancing 47:05 Final Takeaways & Advice for 2025