Latest / Founders and Funding / Ep 22 - Niall Moran - Fractional CTO & Startup Advisor

Transcript

Ep 22 - Niall Moran - Fractional CTO & Startup Advisor · Founders and Funding

• 0:01
  Hi, welcome to the Founders and Funding podcast.
• 0:03
  I'm your host, Philip Smith. On the podcast, I'll be
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  interviewing founders, investors, startup advisors on
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  how to fund the journey of your startup and some tips and advice
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  they have for you along the way. This podcast is sponsored by
• 0:17
  Perfect Technologies and Laden. Enjoy the episode.
• 0:23
  Hi, Niall, welcome to the Founders and Funding podcast.
• 0:25
  Hi. Phil, thanks for having me.
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  Well, look, thank you for taking the time for coming on.
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  I know you're very busy. And now to kick us off, could
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  you tell me a bit about yourself as your background?
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  Sure. So I'm in the IT industry quite
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  a while, 20 plus years. I describe myself as a builder
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  at heart. So I spent most of my career
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  building software applications, building solutions for
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  customers, always kind of customer facing across multiple
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  industries, every industry that's out there from public
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  sector to pharma. So yeah, I described myself as a
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  builder builder at heart. I spent a lot of time building
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  applications. I've also spent a lot of time on
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  the go to market side and strategy side with Google and
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  and Microsoft. So I, I feel I have that kind of
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  mix of, you know, technical builder architecture, but also
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  on the kind of strategy and go to market side.
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  So that's that's me, yeah. Hmm, Well, it's a great
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  combination. You know, most people are the
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  kind of leaning very heavily into the tech side or the go to
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  market side. But I think it really is
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  valuable to learn even at a height level as much as you can
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  about how the other side operates and communicate them.
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  And so well done, I suppose working as great companies,
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  having a great career gives you the opportunity to do that and
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  talk to me a bit more about what you're working on now with the
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  Sidekick CTO. Sure.
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  You know, I, last November I left Google, I finished with
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  Google and I decided I was at a, at a, at the point of my career
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  where I wanted to try and do something myself, go out, go out
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  on my own. And again, leaning back into
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  that, you know, builder mentality, the, the kind of tech
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  stuff I've done over the years mixed with the kind of strategy
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  piece. I said, you know, this would be
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  kind of a, you know, an interesting time to, to get back
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  into my startup stuff. I was a CTO of a startup in the
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  past. I was working for an, an agent
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  investment group and I really loved startup.
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  So I think the, the hustle, you know, the, the builder mentality
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  to get it done at all costs really kind of aligned with
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  where I like to work or where I get energy.
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  And I'd never really done it out on my own as a consultant, as a
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  freelance consultant. So I decided to not give that a
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  go, you know, and that's where Sidekick CTO came from, right?
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  So I spend my time either advising startups at a very high
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  level or getting really deep into the technology for for
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  some, I joined tech operators there recently so that, you
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  know, get back into the Angel investment piece of advisory
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  piece and it's going great. I'm busy.
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  I'm probably a little bit too busy, right?
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  It is a good problem to have. I think that the scene has
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  changed significantly in terms of the AI piece.
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  And I know, you know, I'd love to talk about that as well, but
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  you know, so it's a really exciting time.
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  And I think, you know, Dublin, Ireland has always been a kind
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  of a hotbed of activity for the perspective of startups.
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  And, and you know, I'm delighted to get back into it.
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  And I, and I've kind of built some, some of my own projects as
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  well, Pulse IQ dot fit as a kind of fitness AI, kind of AI
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  coaching fitness platform and that I've built myself.
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  So, you know, really excited to get back, get back into it.
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  Fantastic. Well, it's, it's great.
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  We'll see. It's good to be, you know, I
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  suppose, you know, really unique, but great.
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  You are in position where you're on that the technical builder
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  side and you can advise tariffs, but also develop new setups, but
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  also get into the investment, uh, part of it as well.
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  And see, I know you mentioned there.
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  So you were the CTO and startup advisor for the Lucy Fund?
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  That's right. Yeah.
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  Going back, going back quite a while.
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  So, you know, so that was a great one because it was it was
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  a mix of building products and scaling products.
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  And at that time, by the way, we didn't have AI doing everything
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  for us, right? We had to, we had to do the hard
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  work ourselves. We didn't even have, you know,
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  cloud hosting really AWS were was just kind of getting going.
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  And so that was a great time as well because cloud was the big
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  thing and and then, you know, as well as building the actual
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  platform, we were we were kind of investing in other companies,
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  yeah, through our kind of technical delivery model.
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  So that was really exciting. So I, I got a really broadview
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  of what's a good idea, what's a bad idea, how to, you know, on
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  the execution side, then what? What's a good idea and what's a
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  bad idea from an execution perspective.
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  So yeah, I really enjoy that work and glad to, as I say, glad
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  to be glad to be doing it again. I'm busy.
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  Yeah, absolutely. And I suppose to put it back to
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  the present a bit, what What does an average day look like
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  right now? Right now I'm, you know, knee
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  deep building a platform with a company called better futures,
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  really exciting product sets. Of course it's AI, but it's AI
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  in a very specific space where you know, in, in the engineering
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  world and mechanical engineering world where it's very document
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  centric, very regulatory environments as well.
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  So it's, it's, it's hard to kind of, you know, replace the
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  engineering knowledge that's there.
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  So in fact, it's impossible and we shouldn't be doing that,
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  right? Because the, the, the, the kind
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  of level of detail we're talking about.
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  So it's, it's, it's really about assisting engineers, taking them
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  away from paperwork and getting them doing more of the
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  innovative work that's required from engineers across all sorts
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  of products. So better futures as a company,
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  better futures at AI, uh, knee deep building that platform and
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  getting it out there. We've got customers on boarding
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  right now. It's it's so it's a very
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  exciting time and I'm loving it. Fantastic.
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  I'll be sure to check that out. And I suppose to talk then a bit
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  more about AI. How?
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  How has AI changed the way you work?
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  So it's this isn't, there's two ways we're going to answer that
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  question, right? One, is it kind of a
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  chronological view? Because if you had asked me that
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  question three months ago, it'll probably give me a different
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  answer. Yeah, that's because it hasn't
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  changed how we're working. It's it's, you know, it's going
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  to sound like a bit of a marketing tagline, but it's
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  completely transformed how we're working.
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  You know, I see right now there, there are a lot of metrics we
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  use to kind of gauge developer success, but I think percentage
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  of lines of code written with written manually is a big one.
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  And you know, how much of your code has been written by AI.
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  Is, is, is really important to me right now, just from the
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  perspective of similar to the example I just gave of the
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  Mechanical Engineers, right? I, I want engineers focused on
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  innovation and that means solving problems in new ways.
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  And I don't necessarily want them writing code, you know, and
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  they're two distinct things. I think the world is focused
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  very much on AI writing code, which means we don't need
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  engineers anymore. And that's just not true.
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  We need engineers because they're the creativity around
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  the applications and around the products that we build.
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  AI has very much transformed how we do that and how we
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  accelerate. So what we can do now with a few
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  people, you know, when I was doing the work we talked about,
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  you know, 12 years ago, it was a team of 40 people.
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  Right now it's a team of three or four people.
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  And that is a real difference. And that means we can do more
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  with that forty person team, right?
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  It means we can, we can scale quicker, we can we can
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  accelerate into new markets quicker.
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  So it's, it's definitely transformed what we do and
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  primarily in the area of, you know, AI coding and also, you
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  know, documentation. I mentioned the documentation
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  use case there earlier on. Like a lot of the work that an
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  engineer would be, you know, doing a software engineer would
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  be doing is kind of documenting what they're doing, making sure
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  everything is well documented. And, and anybody who's been
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  around for a while knows that documentation is only as good as
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  how up to date it is, right? If it's even a few days out of
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  date, it's useless because it could send people in the wrong
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  direction. So using AI to, you know, keep
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  our documentation up to date is a really great use case for it
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  as well. And it all just points towards
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  allowing developers or engineers to focus on engineering rather
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  than writing code. Yeah.
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  Yeah, I really like that. It's like there's pros and cons.
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  I absolutely. And it's you know, like if if
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  you if people are listeners or many of them are will be are
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  familiar with loverball. Those are the types of platforms
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  you can get AI to write code, but you know, you need the you
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  certainly need the the engineers, the developers there
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  to really problem solve and make it a product and something that
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  people actually want to use. So there's always going to be a
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  huge need for that and get that. I think getting that combination
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  that makes right as you described there is, is what's
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  important. And talk to me a bit about
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  defensibility. Uh, now I know we, we've had
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  past conversations about that, you know, you know, and why is
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  that important? Well, defensibility is always
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  important for a start up so that you know, they could when when
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  they launched their company. It's not, it's not easily
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  reproduced. That's the key thing.
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  And but I think what's interesting about defensibility
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  right now is, and a lot of the rules around this are the same.
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  They've always been the same. You know, an idea is not enough.
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  It's all about the execution. For example, a lot of great
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  ideas out there, but you know, it's not a, you know, we've got
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  to get them executed. So but, but defensibility used,
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  it used to be enough maybe to build an application, you know,
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  and spend time building it, a complex application, you know,
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  software solution of some sort and get it out to market.
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  And straight away you had a lead of months to years on any
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  competition that wanted to get into that market.
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  And you mentioned products like Lovable, you know, so now that
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  changes the game because people can, CE OS can, and I'm not
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  advocating for this, but CE OS can build their own
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  applications. Certainly MVPS with Lovable and
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  Repple and others, OK, it's not just Lovable and get them out to
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  market right, with, you know, fully functioning MVPS.
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  So where's the defensibility then?
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  If if I go and I try and pitch this to somebody and they can
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  reproduce it as quickly as I built it, my defensibility has
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  got to be something else. So I think defensibility for me
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  now is got to be around sticky customers, whether it's a user
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  base community or, you know, enterprise customers.
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  Are they sticky? Do they need to use your
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  product? Because you know, they've been
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  using it and then you've got the data and you know, you're,
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  you're, you know, the, the value in them using your product is
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  the fact that they're using their product, your product,
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  right? That it grows over time and it
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  learns from the customer and that creates a sticky product.
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  And so it doesn't matter that the product could be reproduced
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  relatively quickly, attracting customers, getting them on
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  boarded and making them sticky is still the hard work.
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  And that's the execution piece that's really important.
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  So yeah, ability, forget about it.
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  If you're spending, you know, time figuring out how do I build
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  a better LLM than, you know, I don't know, Google's right then,
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  or how do I build a better model for this particular industry?
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  You know, I'd be careful because, you know, it could be
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  done And let's, let's focus on, let's get something out there.
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  Let's get customers and, you know, let's get them sticky.
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  And honestly, you know, maybe some of the venture capitalists
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  might not agree with me on this, but I think it's more important
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  than revenue or funding right now.
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  You know, get something, get it out there, get people using it,
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  Figure out what works, figure out what doesn't work.
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  Figure out how your product can, you know, adapt to those users
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  so that they become sticky. And now you've got some
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  defensibility that you can go and look for customers to pay
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  you with or go look for collab funding.
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  Yeah, I know I think you're spot on.
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  You know, I do see even off for myself, I see founders kind of
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  be trying to create AI. Suppose a defensibility or a
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  thesis around why their new application is is great and
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  it'll be the one that'll solve this problem.
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  But you know, because the, you know, large because of AI,
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  because things are moving so fast now, people can create
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  products so quickly. And it really is that product
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  market fit and getting customers and make and, and, and making
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  sure that actually are retained and sticky that, that that's
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  really the, the kind of the only defensible, I think, proposition
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  now, because everything else can be, uh, replaced it on so fast.
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  And I suppose a bit broader than looking at some of the, you
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  know, from the founders you've worked with neither there's some
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  kind of common MVP challenges you you've seen them encounter.
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  Yeah, and a lot of the, a lot of the challenges are age-old
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  challenges. So you know, there's a danger
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  and getting caught up in some of them when other things are
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  moving so quickly. And you know, there's a few
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  here, but I'm going to pick the top ones, top of mind ones.
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  The first one is are you building a product or are you
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  building a solution, right? What's the difference?
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  You know, you can spend a lot of cycles with customers building a
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  solution for them, but it's not a product you're building.
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  You know, it's kind of, I always use the analogy of, you know,
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  we're building. If I build you a tailor made kit
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  car just for Philip Smith's, you know, demands you want to the
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  particular color, it was a look a certain way, you're going to
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  love it. It's going to be great.
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  But that doesn't give you product market fit because not
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  everybody wants that car. All of a sudden you got to think
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  about the production line and what you get at the end of the
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  day then isn't that nice shiny product, you know, custom car.
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  It's it's just got it right. Or Volkswagen is going to be for
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  the masses. It's a scale issue.
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  And I see a lot of customer, a lot of startups are actually,
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  you know, they're trying to get customers and are trying to get,
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  you know, which is great, but they end up building the
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  solution for that customer and not actually a product.
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  And the shift away from building something for one customer to a
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  product mindset can be quite seismic.
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  And that's, that's the biggest mistake I see from a, you know,
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  from a CTO perspective is how do we now shift to a, to a product
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  mindset? And that's a whole different
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  world. Think production lines, you
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  know, a, a, a, a kind of a, a, a set of features that we think
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  the masters will like, but maybe one or two customers won't like.
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  And that's fine, right? The other one, I think that the
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  other big one I'm saying right now is the, you know, we talked
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  about it, the AI store, fright, AI generated apps.
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  I think honestly, there's going to be a graveyard of these
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  things in time to come. You know, there's so much more
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  to building a platform or building a product and than just
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  generating an app, right? You got to think about security,
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  scalability. I literally saw on LinkedIn the
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  other day an article about somebody who used who had
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  launched an app that they had built with a tool like some of
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  the ones we've mentioned, and they managed to delete their
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  entire database with an agent. And this stuff is going to
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  happen, right? It's going to happen and the,
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  the, the, the question is, have you got a disaster recovery
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  plan? Have you got a security plan?
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  Have you got the prevention plan to stop this stuff happening?
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  That's what engineering a product is about, not coding.
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  And that's my fear that a lot of startups are and look rightly so
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  get an MVP out there, get customers using a get feed, but
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  it's an MVP. Turning that into a product is a
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  is a different, a different story.
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  And then then there's a kind of other end of the spectrum where
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  I still see startups going and offshoring an MVP development.
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  And I'm like, you don't need to do that anymore, right?
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  You can do that yourself, OK? Or you can get help from people
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  like me who can build it in days and start getting customers on
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  board. I think that the biggest piece
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  of advice I've given the MVP stuff specifically is, you know,
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  build it quickly, but no, it's an MVP and no, it's a prototype.
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  No, that getting that to scale and turning that into a product
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  with properly production, proper production line behind it is a
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  different story. And you probably need to start
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  thinking about that early as well.
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  And so that you don't end up in that graveyard that I that I
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  mentioned. Yeah, I think there's a good
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  points like I've certainly seen this does the, the new issues
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  being created by as as much as it's solving, uh, you know,
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  problems is creating a lot of a lot of problems as well.
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  Like I see a lot of founders that they're adding because they
• 17:38
  can these add new features, you know, and they end up having
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  1020 features and, you know, without solving the core problem
• 17:45
  just because they can. So they're kind of going into
• 17:47
  future overload and we're getting too excited and they're
• 17:49
  not just kind of pulling it back.
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  We're finding and trying to match the problem with the
• 17:53
  solution and to limited feature set.
• 17:55
  But umm, yeah, it's, it's certainly an exciting and
• 17:58
  interesting space and changing all the time.
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  Uh, before we finish, Niall, what is one key piece of advice
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  you'd have to successfully fund a startup in terms of, you know,
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  trying to help start-ups funding that journey, uh, and how they
• 18:10
  can kind of keep the setup alive to get it to that point where
• 18:13
  they can find that product market fit.
• 18:16
  Yeah. I mean, I will always go back to
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  technical due diligence. You know, we just discussed it,
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  right? It's, it's, it's, you know, make
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  sure what you're building is ready for scale.
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  You know, I talk to, I talk to founders, for example, who
• 18:33
  rightly so are being pushed by their potential investors
• 18:36
  because they don't have a CTO. And I still not all VCs or not
• 18:42
  all investors will insist on that now because of, you know,
• 18:44
  the products we've talked about. But I think it's so important
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  because you need to know what you're creating is, you know,
• 18:51
  not some sort of Frankenstein and there's is actually fit for
• 18:53
  purpose and, and can be delivered.
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  And then I'm firm believer that once you get those architectural
• 19:00
  things right and get that technical due diligence done,
• 19:04
  that AI will help you accelerate your features and will help you
• 19:08
  accelerate your product backlog as long as the framework is in
• 19:11
  place to do that. So I think the advice I'll give
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  you, you know, even from a funding point of view is just
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  make sure that technical due diligence box is ticked and that
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  you're not just going in with AAI driven app that somebody
• 19:27
  else could build for you build and replicate really quickly.
• 19:30
  Even that technical due diligence that shows you're
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  maturely thinking about scale will help you with some sort of
• 19:38
  defensibility, right? Because the Ethan piece is not
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  easily reproduced and you're just building defensibility as
• 19:43
  you go. Yeah, I think that's great
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  advice. I think if you, if you can, if
• 19:47
  you can follow those steps, that instruction, I think you'll be
• 19:50
  able to successfully build and fund and launch a startup and
• 19:53
  find that part of market fit so many funders are striving for
• 19:57
  now. Thanks so much for calling on
• 19:58
  the podcast. It was a really nice
• 19:59
  conversation. You've obviously you had a
• 20:01
  fantastic career and they're still doing amazing work and
• 20:04
  have a lot to share. So thank you for for coming on
• 20:06
  this podcast to share a lot of the insights that you've gained
• 20:09
  from your experience. Thanks for having me, Philip.
• 20:12
  Appreciate that. Thanks, Matt.
• 20:16
  Hi, thanks for listening to this weeks episode of the Founders
• 20:19
  and Funding podcast. If you'd like to be a guest or
• 20:21
  have a guest suggestion, please get in touch.
• 20:24
  Thank you.