If I Wanted to Start a Career in AI in 2026, I'd Do This (Without Coding)
By Liam Ottley
Summary
## Key takeaways - **Coding not required for AI success**: You don't need to learn to code to succeed in AI; there are many ways to be successful, including using existing tools or focusing on consulting and education. [02:54], [03:47] - **Multiple AI career paths exist**: The AI market offers diverse paths, including developer roles, no-code development using tools like Make.com and Agent Builder, consulting, and education. [04:09], [04:16] - **No-code tools streamline AI development**: No-code platforms like Make.com and Zapier are valuable, but OpenAI's Agent Builder, being GenAI-native, offers a promising approach with built-in guardrails and easier prompt management. [19:38], [20:02] - **University AI curriculum outdated**: University AI curricula are often outdated due to the rapid pace of AI development; self-teaching through online resources and practical building is a faster way to gain relevant skills. [27:50], [28:38] - **MCP servers enhance productivity**: Integrating MCP servers with tools like ChatGPT can boost employee productivity by providing access to custom business data and automating workflows within familiar interfaces. [35:06], [36:06] - **Start with small, impactful AI offers**: For agencies, starting with a small, easily deliverable offer like setting up MCP servers for employee productivity can be an effective inroad to larger consulting or development projects. [46:36], [47:04]
Topics Covered
- AI success doesn't require coding skills.
- New AI pathways bypass traditional development.
- AI tools enhance developer productivity, not replace them.
- AI development is rapidly evolving; university is outdated.
- MCP servers offer a low-friction entry into AI adoption.
Full Transcript
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 Gai development, you're probably
the best person to talk to on 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
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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
>> reanking. 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 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 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
ad 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 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 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. U
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 nitn 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
tennium CPU surface 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 2 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 the back end and stuff and
>> 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 chat
GBT course for businesses and then 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's a good one. is 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
entropic 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 a
custom build and we say look I think we
can do this do is shipped 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 Chad 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
quitting 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
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Thank you so much for watching and I'll
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