Accidentally Founding an AI Business with Patrick Belliveau, Managing Partner @ Gambit Technologies

Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
For now, it sounds like Bootstrap keeps you up to date with what's AI.

(00:03):
Well, it forces you to focus on building the features that you actually need, not
the ones you think you need, and it forces you to build the ones that people will pay
for before you try to make it work with llama or trying to make it work with, you
know, micro or cheaper model, make it work with the expensive one.
Cause if you can't make the expensive one do it, it's unlikely to

(00:25):
gonna make the cheap one.
You have not missed the boat.
In fact, you're probably still early, maybe not literally, but figuratively in
the grain scheme of it, AI is not very old and AI is not going.
Welcome to artificial insights.
The podcast where we learn to build AI people need and use by interviewing
product leaders who have launched AI products so that we can separate hype

(00:47):
from lasting impact in AI.
I'm your host, Daniel Manary.
And today I'm joined by Patrick Belliveau of Gambit technologies.
Patrick is a forward thinking entrepreneur and technologist with a
career spanning Ford motor company, innovation, Norway, shift reality,
and his own Gambit technologies.
His AI journey began with ask Ellen, an AI companion supporting cancer

(01:10):
patients and their families.
That's now used in over 15 countries and was something he built before the
world even understood what Chad GPT was today.
Patrick also advises fortune 500 companies and health organizations on
leveraging AI for innovation and impact.
Pat, could you say hi to our audience?
Hi, I'm Patrick Belliveau.
I'm the managing partner at Gambit technologies.

(01:34):
Started, we didn't, well, I guess we'll get into it, but we didn't really
mean to start a company that really wasn't actually the plan at the time.
But yeah, we ended up starting a company called Gambit.
And since then we've worked with fortune 500 companies.
We've worked with the U S government.
We've worked with several really cool, different kind of companies that we've
done some really neat things for and that I'm sure we'll get into, but we

(01:55):
decided to be bootstrapped for the exact reason that you talked about versus hype
and, and a signal and noise is if you can't package something to sell to a
client, in my opinion, you don't have a business at this point, because yes, I
know you can raise money and be not profitable for years.
I can get that to play, but in my world, that's entrepreneurship.

(02:17):
I make a distinction between entrepreneurship and small business
owner or even business owner.
Entrepreneurship, you're VC backed.
You aren't really that concerned about really finding true product market, but
you're more just interested in making sure that you can get to your next
round because really that's what you're into.
That's the business you chose.
And that's fine.
That's a path because I thought the most dangerous thing you could do with AI is

(02:38):
raise a bunch of money to go heads down, build something for a year is like the
number one way to light money on fire.
In my opinion, we opted to, and I have a lot of strong opinions.
They're opinions of one, so like they're just mine.
I'm probably wrong caveat, you know, everything, but I think that if you can
take something and package it and provide it to an individual today, using

(03:00):
it within your own of something, because people are willing to pay you for the
information, those skills or the knowledge or whatever it is that you have today.
And the more that you do that and the more that you build, the better you get at
it, the better you get at it.
Then you're moving at the same pace of AI.
Well, that's not true.
No one's really moving at that pace because it's insane, but at least you're
moving directly the same way.
Because as you mentioned, you know, the classic example was the PDF wrappers,

(03:24):
right?
When Chad's GBD came out, you couldn't attach a document.
So then a bunch of companies were like, I know let's raise $3 million and let's
go make it that you can add an attachment.
And then open AI was like, oh, that's cute.
Here it is for free guys.
Bye.
And so you look at that and you look at how many people get hurt in that process.
Cause the entrepreneur is getting hurt there too, right?
Like everybody, nobody wants to have a failure.

(03:45):
Nobody wants to wake up one day and their business is gone and obviously
nobody wants to lose money.
So at the end of the day, it's a top proposition and it's hard when you have
folks throwing money at you or wanting to throw money at you.
It's hard to say no.
I can tell you from experience because we've had many people offer us many
amounts of money with varying rules.
You know, just tell me the terms and I'll be okay with it.

(04:07):
And we're still not willing to.
It's incredible when you say how much power that actually gives you.
I mean, that's amazing.
It is.
And I might look at this in two years, if you're still around and doing like season
eight going, I wish I took money.
So there's a good chance I'm wrong.
There's an equal chance I'm right.
And I'm willing to bet.
But for now it sounds like you guys are going the route of bootstrap keeps
you up to date with what's AI.

(04:29):
Well, it forces you to focus on building the features that you actually need, not
the ones you think you need, and it forces you to build the ones that people will pay for.
And so what I really mean when I say that Kichi lockstep with AI is we never go
down a path that makes it that if there's a new model that comes out, we are nervous

(04:51):
because then you're in a really bad spot.
So what we do is we build our gambit cloud in such a way that like when
Claude Sonic came out and honestly it was exponentially better at some things
than 4.0, we were able to just straight swap it.
And that wasn't a big deal and we could just move forward.
As opposed to some companies and some individuals believe that the right way

(05:13):
is to work really hard at making going beyond current model capabilities.
And I think that fundamentally is a waste of effort and time because for them to be
successful, their whole assumption is built on one thing, which is that the big
foundational models will stop innovating for them to be successful.
That has to be true for them to be successful.

(05:34):
And it's just not a big deal.
It's not something I'm willing to bet on.
So the way that we do it is it focuses us to only build the things that we actually
need to build to sell and to do it in a way where we lean into the model and the
capabilities of today and like bold prediction.
If we did not get another model for 10 years, like this was it.

(05:55):
Three Sonic, three, five Sonic, 4.0, even 0.1 preview, let's say.
Never got another one for 10 years.
We still wouldn't be able to find and use all the use cases from what
these things are good at.
Like we're such an exciting time from a model capability because there's
failure of imaginations on all fronts.
Like folks building have failure of imagination.

(06:15):
What this thing can actually do.
Buyers have failure of imagination of how does this actually fit into my workflow?
And obviously sales and marketing helped to match that, but it's insane to me that
we think we need more models when it could just stop today and we would have
to do more of that and then we would have to do more of that and then we would
we would like Gambit would have more business and more opportunity.
We know what to do with for a decade.

(06:35):
If it all stopped today.
That's a good question then.
What does Gambit do?
Yeah.
So it's a loaded question because we, um, we do quite a few things.
I'll tell you what we're known for.
We're known for a tool.
And do you want me to kind of give the origin story?
I guess, cause this will kind of dovetail into it.
Uh, actually that'd be great.
Cool.
So I mentioned we didn't mean to start a company and that's the most I got truth.

(06:58):
I met a lady named Ellen and she had breast cancer and she explained to me
that she had survived it and had written a book about it.
And I said, why did you write a book?
If you get to know me, you'll know to ask weird questions.
And she said, well, I did it to be a girlfriend's companion.
So that makes sense.
Share of lived experience that adds up.
So, but isn't that what Facebook groups are for though?

(07:18):
And she said, you would think so, except the problem is they're not moderated.
And so they can be anger echo chambers.
They can be really sad.
And so where you are in your journeys, unlikely to be where that group is.
And she goes, I've had to lead groups because they're heartbreaking.
And I just can't handle it in that moment.
I remember leaning back and thinking, so this meeting serendipitously took place

(07:39):
in February, November before Chad's, it began to come out.
Um, and I started playing with it and I'm like, well, this is, I'm not missing.
Like, this is the future.
This is, this is going to change everything, even though it was wrong 90% of the time.
It, the fact that it could do it blew my mind.
And I said, okay, well, look, I have an idea.
If you send me your manuscript, I will put my whole network behind it.

(07:59):
And I have an idea to make it safe for people to get shared lived experience.
The only agreement I need from you is it'll be free for everybody forever.
Because what I do not want to do is go the tool that is 9.99 a month
for people that have been diagnosed.
I just don't believe in that.
I don't want that to be true.
So unbelievably she agreed and I had her manuscript.
So now I would get up at three o'clock in the morning.

(08:19):
My background is sales business, not coding at all.
I'm clever when I want to be.
Like when I want to learn things.
And so I went to YouTube and thought, okay, well, I just want to anchor.
So using what's called resource augmented generations or a rag pipeline, I wanted to
inform the artificial intelligence of the book and then have it answer as a, as Ellen.

(08:41):
That was it.
So I found a couple of YouTube channels.
I had some open source things on GitHub and like, I had to learn what like an IDE was.
I didn't know what that was.
I didn't really, I didn't know what GitHub was.
Honestly, God had no idea.
And so luckily YouTube kind of taught me it.
And then honestly, when stuff wouldn't work, I would just put the error code into chat

(09:01):
GPT and then it would start to give me some what it might be.
And then I would just iterate and just sit there and iterate.
So fast forward, probably, I don't know, 25, 30 days and I get the hello world working
and it's working pretty well.
And so I send over to Ellen.
I said, Hey, when you, can you give me some sample questions that are going on your
chat groups and we'll just kind of test it.

(09:23):
Um, hold on.
I want to ask you one question first.
Yeah.
You, did you say that in under a month with no experience, you got a rag pipeline working
with chat GPT as like the first iteration?
Yeah.
So I'm the thing about me is I I'm definitely, I'm, I'm undiagnosed, but I'm quite sure I
have like OCD and ADHD altogether.

(09:45):
So when I decide that I want to do something, I just consume everything I can.
So I would get up at like two 30 or three, cause I have a full time job, right?
So I'd get up at two or two or three in the morning and just start cranking and just
start learning and getting where I would get stuck.
I would sort of figure myself out.
And again, AI was an amazing tool though, cause it'd be like, Hey, well, you haven't
configured this properly.
I'm like, I don't know what that is.

(10:06):
And they'd be like, okay, well, you need to do this and this.
Okay, cool.
And then I would realize that the documentation was out of date so that I would copy paste
the documentation in and be like, Hey, I, you said this, but I think it might be that
and it would kind of help me.
Our developer, Chris saw how I use our ID and he's just like, I don't understand how
you got anything working.

(10:27):
Like you, like the basics of what I think most people would generally understand.
I don't, I just, I get a goal in my head that I want to build something and I just
ignore all the reasons why I shouldn't do it.
I just keep pushing until I figure out what I should do.
I keep pushing until I figure out how to do the thing that I need to do.
Because for me, I'm not interested in learning Python, the language.

(10:51):
I'm interested in learning the right words or the right things to put in to do the thing
that I want to do.
And if that's called Python, cool.
If it's called whatever else, I don't care.
I'm sort of outcome-based.
I'm not learning based.
And so that's a very big encouragement, I think for everybody.
Just you can do it.
If you put your mind to it, the tools are so helpful.
Oh, and this is using DaVinci.

(11:11):
Nevermind what people have access to today.
Like this is the origin story.
Like it's wild what one can do today.
And maybe we'll get to that from like, make sure we talk about it from like an
aspirational standpoint, because I think the generalist and the non-experts, AI is
the great equilibrium or the great equalizer rather.

(11:32):
And I think that we can talk about that some more, because I think that deserves
its own little section.
But yeah, so long story short, we got, we kind of got Ask Ellen up and alive and
then a good friend of mine lost his, I've lost his mom tragically in a car accident
and a couple of months later, then let go ironically, claiming due to AI.
And he was a software developer.
And so he's like, you know, the truth of the matter is we met at a bar because

(11:56):
he's like, I've had it, like we're, I'm done.
Like this is just too much.
I don't know what to do.
And so we, somewhere in all the whiskies, we decided that he needed AI experience
to get another job.
And I said, well, hey man, I got this free thing you can help me do.
And so he was like, oh, well, I guess I'm like, okay, let's do it.
Like, that sounds like a good idea.
So he helped make it what people know is Ask Ellen today.

(12:19):
That's been used in 15 countries and as many languages and et cetera.
Yeah.
Well, I could have never done that part.
I could, the hello world, you know, that's fine, but it's, it wasn't the
hardened system that Chris managed to put together.
And then Ryan on our team, who's the sort of marketing visionary user person was
like, all right, you two are going to iterate on this forever.

(12:40):
So we're going to have an event.
It's going to be October 25th and we're launching and oh, by the way, we're
going to send out some invites.
The next thing we know, we have 300 people come in and bunch of sponsors
and we're launching an AI tool that is open to the public that you can type
whatever you want into.
And like, that's a thing we're about to do in the cancer space.

(13:01):
So we were pretty, I mean, nervous and I mean, it wasn't a straight line.
Like it was, there were points where like, this is never going to work.
We can't make this work at that time.
Like only a handful of companies had an open text box to, for people to actually
like publicly for people to go put things.
There's a reason.
Yeah.
You put, there's a reason you put that behind like closed doors.

(13:21):
Um, but we were, we just really, we wanted to help people and through the
wanting to help people, we got over our fears and our trials and tribulations.
And like, there's one that like drove person, I mean, almost crazy.
And this is really where you'll see my OCD is we don't ask Ellen
doesn't provide medical advice.

(13:42):
So it's really to help the individual with the human side of the diagnosis.
So it's fundamentally we're talking, how do I tell my kids?
How do I, my husband's not maybe supporting me the way that I wish he was.
My mother-in-law is not being great.
Or what did you wish you brought to chemo?
What do I expect?
Will I get through this?
Like all the human beings side to this.

(14:04):
But one of the things it was doing was if you asked it, can I take Tylenol?
In her story, which is in her book, she does take Tylenol.
So the ask Ellen would answer.
So can I take Tylenol is the question.
The answer would be yes, comma.
I took Tylenol in my journey.

(14:24):
Well, yes, comma to me implies yes, you can take Tylenol.
And what we don't do here is we don't do explicit rules of like, if someone asks
you about Tylenol, don't say yes, comma, because you can't build a tool like that
because there's just going to be so many edge cases.
So we went down a rabbit hole because I just, we were going to launch with it

(14:46):
because it wasn't living up to what we wanted.
And so what we got very good at is instead of worrying about the things that it
shouldn't say, we worried about what is a dignified answer because the, what
shouldn't it say is I'm like, I don't know how you put your arms around that.
Cause there's just so many things that you don't know what the user is going to say.

(15:07):
So the idea that you're even going to properly anticipate what everyone's going
to say is just nil, you're not going to do that.
So if you focus on what is a dignified answer, well, now all of a sudden can
deploy that and you can do a lot of work in that space.
And then all of a sudden it feels very tangible.
And so by doing that, we were able to get it to stop providing medical
advice to the point that we have hospitals calling us all the time wanting

(15:30):
to put Askel and QR codes in our waiting rooms because they're like, wow,
okay, wait a minute, you understood that like we do the medical thing.
You help us on the empathy human side of it.
Oh, you're not competing with us.
You're just trying to make the journey better.
And so that was really exciting for us and just awesome validation, not that
we were looking for it, but awesome validation that we would do.

(15:50):
It the right way.
Because one of the things I made clear to Ellen is we weren't asking for permission.
We didn't walk into hospitals and ask them if we could do this.
We just did it.
And I think that was really a big part of our story is be fearless enough to just
do it.
And I knew that once they saw it, they'd want it and it's exactly what sort of
played out with that.

(16:10):
And then what happened is a lawyer, prominent lawyer in Kitchener, Todd
Bissett saw it and was like, well, I want one of those.
So we launched Ask Todd not that long ago, which is democratizing access to legal
services.
The US government saw and said, hey, we're overwhelmed with caregivers calling in

(16:31):
who are caring for those with dementia and Alzheimer's.
Could you build some on Ask Ellen for that?
And then all of a sudden we became the like de facto Ask Ellen for insert how to use
case here.
So that's really what we do is we configure these personalities over these large
breadth of data, but provide it to users in a way that they actually want to use
it.
And they actually get help from it because we start with what is the core problem

(16:54):
you're solving.
And I think that's the biggest thing.
The biggest advice I can give if you're kind of thinking about getting into AI or
you're in AI, you know where to go is we didn't try to solve breast cancer.
We didn't try to solve the patient journey.
What we identified the root problem was it's not safe for people to go on
unmoderated check groups.

(17:15):
So that's what we aim to solve.
That was it.
And so we didn't do it for every cancer.
It's only in our story.
Like it's super limited when you actually apply like all of the things.
But when you look at it for what it is, it's beautiful.
It's, it's, it's perfect.
And it's version.
And so that's my biggest advice is everybody says, oh yeah, let's do AI for
finance.
Okay.
Well, which part there's a million parts.

(17:36):
So which thing are you actually doing and why is it different?
And why should anybody care?
It's kind of the big one.
And so, yeah, that, that was kind of how we got going, where we went.
And then from there, yeah, we just started getting known as the guys that actually
built something, or I should say the team that actually built something.
We, I mean, somewhat shockingly have spent no money on marketing.
All of our leads are inbound.

(17:57):
We don't do any outbound efforts at all.
We probably should say that.
That's crazy.
Yeah, we're busy.
We're launching, I can't share too much about it, but we're launching a brand new
tool at the Daytona race, the NASCAR race in a month, in a few days, with a huge
partner and a great NASCAR driver.
So we're, we're finding ourselves in really cool opportunities just because we

(18:19):
have proven that we were builders.
And that I think is the trick is throughout all the noise, try to be the signal that
actually builds things that matter that people use.
And if you do that, well, I think you're going to have a really happy future.
And if you don't do that, well, you're just playing a different game and that's
okay too.
At what point did it become something that people would pay you for?

(18:40):
Cause starting for free seems like a difficult thing to do when you're bootstrapped.
Yep.
So we, that's why I say we didn't mean to start a company because Ask Allen
wasn't a Gambit initiative.
It turned out to be the core team of Gambit, but it wasn't really a Gambit
thing because Gambit wasn't a thing.
Gambit wasn't a thing that it was a, and the reason why, I'll say the reason why I

(19:06):
think it worked, but it really wasn't the reason why we did it because we did it.
My aunt died of breast cancer and I thought the world deserved better.
And then that's fundamentally why we did it.
But why I think it worked is all of a sudden we had a tool that people could go
and use and experience the magic of it.
So many of our prospects that come in that are like, Hey, I used Ask Allen.

(19:28):
It's amazing.
Or I used Ask Bibi or I use Ask Todd, or I use any version of the tools we built.
I want that for us.
That became our little viral marketing thing because we didn't have to, I didn't
have to show up and tell you how good we were.
I never do.
Like even notice, I don't even tell you what we do.
I just tell you the things we built because that's just easier for me to explain.
So the nice part is nobody ever really knew we built it for free.

(19:52):
We did build it for free.
I'd be honest about that to anybody for Ask Allen.
But then when they said, well, we want that for us, well, then it's like, cool.
Well, there's going to be a price.
And then how do you price that is a very different question.
And, you know, we, I'll give a hint.
We did value-based pricing, definitely not cost-based.
And at that point there weren't very many people that were doing what we were doing.

(20:14):
So from a value standpoint, it was quite high.
And for what it meant to the individuals, I'll say we said no to some use cases.
There are actually customers we turned down because it didn't, it didn't align
with what we believe and there are just some things we're not going to do.
And I can get into that.
You guys are curious, but it was more about show it instead of telling you how good we

(20:40):
are, I just show you and then you can't really, there's no arguing.
Like if you used Ask Allen, it blew your mind.
You call me.
I've already won.
You just don't know it yet strategically.
Right.
So, um, so again, in hindsight, it was a beautiful execution of a really cool
strategy that actually didn't exist.
It was, we just happened to be, we just happened to be very good at what we do.

(21:00):
And we happened to get in the right situations.
I think in hindsight, it makes perfect sense how we got here, but I think that's
always the, that's always the case we didn't, but we didn't like, we weren't like,
okay, we got to hit this target in 90 days or anything like that.
Cause we remember I had a job.
Chris was using this to try to get another job.
We weren't really building a company.

(21:22):
And then, yeah, you know, early last year, we kind of all sat down and we're like,
Hey, like what if we did though, because like we're getting inbounds and it seems
like we're kind of having a lot of fun.
What if we did this?
And like, it was scary because we had to find that, you know, Chris needed a salary.
We all needed one, but Chris needed a salary.
So it's like, okay, well, how do you justify that we go to Ask Ellen for free?

(21:47):
And how do you monetize that?
How, like, how do you go market that?
Like this was not easy.
The amount of times that Yann Bich should have been probably could have died is huge
before he even took off.
And then I think you just have to have this unreasonable desire to achieve
something and then follow your gut.
And if you get lucky enough, you'll figure out your gut and a real world

(22:10):
opportunity very quickly.
And then, like I said, we've been approached by BCs left, right, and center.
And, and we just aren't interested, which might go down as, like I said, is the
worst decision I've ever made, but it's the one we made for now.
Then things always change and evolve and who knows, it's never like, no, don't call
us again.
It's just like, not right now kind of thing.
Yeah.
I think we're just having way too much fun running our own company the way we want to

(22:32):
run it.
And, and I think it would be really hard to convince me to ever give that up.
But yeah, that's kind of, that's really how it started.
It's not fancy and it's not like, I don't know.
It's not anybody can do this.
Like literally anyone could have seen what I saw and then put together a team that
could do it.
This isn't really luck of the draw.

(22:55):
That's what I like of the story.
Like, yes, we got lucky.
I think everybody does, but I think if you work hard enough, you invariably get lucky.
Put yourself in the way to get lucky.
Because that's it.
You, the goal, like I always love this.
I don't, I'm going to shamelessly steal this quote and I forget who it's from, but my
goal is to always increase the surface area for luck.
And I knew that if we build something that helped people at some point, would somebody

(23:19):
look at it and be like, wow, that was amazing.
We like it for something else.
I mean, that had crossed my mind though.
It wasn't kind of the, the, the target.
That's definitely what, what I knew that if we put it out there, cause chat GBT did
this, like at the time Google hadn't released theirs, right?
So chat GBT was like, you know what?
It's not perfect.
We're just going to release it.

(23:39):
And for 20 bucks a month, we're going to give access to people and like, it might
suck, but it might be cool too.
I don't know.
We'll find it.
I loved it.
Then I'm not like the biggest fan by any means, but like, I love the idea of putting
yourself out there and, and there's a, there's another quote that I think it's a great
Cardone one, if I remember right, but it's be so good, they can't ignore you.

(24:01):
And that's basically like tattooed in my brain.
And that's how we build and how we approach the building.
And so when you do that, all of a sudden, you don't have to market to everyone and
say, trust us, look at my PowerPoint and like, isn't it a nice PowerPoint?
It's great.
Right?
No, you're like, okay, well, which tool do you want to fire up?
Oh, well, I'm interested in this one.
Okay, cool.
This is what we did for that.

(24:22):
Oh, that's exactly what we want.
Because here's the thing in business, particularly, or even support, they all
kind of look the same, but the objectives are all the same, make people feel like
they're, make people feel better, make people supported, help them with
navigation, et cetera, et cetera.
Business, get more ROI, get more customers, get more sales, warmer
landoffs, whatever it is you're trying to achieve.

(24:44):
The, like the Venn diagram of overlap is huge.
And so if you get good at solving a few of them, then guess what?
Your market is kind of a lot bigger than you probably even realize.
So that's kind of how it went.
Yeah.
And our website, like, if you go to our website, it's terrible.
The amount of times we're told like your website is not at all what you guys do.
We spend no time on it because we don't have time.
We are a small team and we have not made the priority to make our socials.

(25:07):
Particularly, well, okay, that's not true.
To make our website particularly good.
Ryan on our team has been really good about forcing us to post on LinkedIn and
post about what we're doing and the challenges, the tribulations, et cetera.
Because we think it's important for people to understand.
And that's kind of why I agreed to be here.
It's like, it's not, it's not a straight line.
It's scary.
There are days where you wonder, why are you doing what you're doing?
There are days when you wonder is open AI or entropic or Google or

(25:31):
whatever are going to eat you alive.
Like, I mean, it's not all sunshine and rainbows.
I'm giving you the highlights, but I can easily go into the low lights pretty
quickly and you know, the sheer moments of panic where like you don't sleep for
a few days because you don't know how, because I committed to doing something.
We have no idea how to do, cause I'm really good at doing that too.

(25:51):
And that's what it seems to be a key skill for starting a business.
Well, you just, you figure it out.
You have to trust.
I mean, don't be like criminal about it, obviously, and don't take money up front.
Like the darn like rules around fraud here, but the, but no be, you know,
trusting your ability.
And I mean, when we started, like we, one developer, cause that's all we have.

(26:12):
One, Chris got an entire cloud platform that now powers all of our tools
up in less than a year.
Like we started, everything was a manual process.
Manual as in like a coder developer actually had to go in.
So, but we quickly realized I can't like, that's not going to work.
And then there's actually really good reasons why I can't work.
I can go on a tangent if you're curious, cause this might be interesting.

(26:34):
You sure go for it, please.
So Chris says this all the time.
He says, I build the cars past Pat drives them.
And I liked that analogy because AI is art and science wrapped together to get an outcome.
And it's the art is really hard to explain on how to do it.

(26:54):
Like there's so many times Chris goes, I don't understand how you got that thing to do that
thing with that prompt in the way that it doesn't make sense because he's applying a
programming kind of perspective to it.
But you can't really do that without the programming side.
So it's not that one is better than the other.
It's that's the true magic is science is continually getting easier because the models

(27:15):
are getting better and more capable, which means that in theory, like with cursors,
you know, if you're looking for an IDE, like I'm not sponsored by them at all, but Chris
uses cursor with AI and it's magic.
They've done such a great job over there.
And so it's taken what Chris was, what you would define as a 10 X engineer and it's made
them a hundred.
And that's the trick is because I I've worked with really smart people in the past that

(27:37):
told me I'm smarter than AI.
And I mean, that's going to be their Achilles heel.
Unfortunately, Chris, wait a minute, this is amazing.
I it'll do my documentation.
It'll help me iterate.
And she started organizing the code in a way that he started to see that the AI would better
understand.
So now he can say, like, I want a button for this and I want it to do that.

(27:57):
Blah, blah, blah, blah.
Go look over here.
And it's incredible what he can do with very little hands on activity, but that's because
of how good he is, not how good the AI is like it's artists.
I guess.
So, yeah, I think I'm a generalist, like I'm a hacker at best that just likes to just kind
of play with things and iterate.

(28:17):
And, you know, there were times where I was way too prescriptive with the model.
And then you get into like this typecast of a personality, which it only does this one
thing.
A great example of I can give a really tangible example of that.
I in the Hello World version, I told the model that I wanted it to be empathetic breast

(28:39):
cancer survivor act like that makes sense.
Right.
Cool.
Until I wrote in and said, I just got my results and I'm cancer free.
So a normal human being would be like, that's amazing.
The AI that I told to act like a empathetic cancer, breast cancer survivor, what's it?

(28:59):
I'm so sorry you had to go through that.
And that's when I realized, okay, prescriptive, it's going to follow what you tell it to do.
So the more prescriptive we are with some things like no medical advice has like one
example, make sense.
But in terms of personality, there's a huge engine here that you got to kind of put
together.

(29:19):
And that's what forced us to get very good at kind of what we were doing.
And so I think that if you're thinking of starting a company and you're not technical,
that's not a reason not to do it.
It might be an advantage.
It might.
I think that the world, I really believe that the world is going to belong to the
generalist.
And that is to the individual that can put themselves in the user shoes and be like,

(29:43):
hey, what are they going to experience?
And what are they going to think about?
And what are their fears?
And where are they looking for?
And what does a great feeling and experience look like?
And if that same person can go, okay, well, I'm going to build this.
And that same person can then interface with the technical, same person can interface
with the rest of the team.
That becomes a really hard skill to replicate because what are you?

(30:08):
Are you a product manager?
Well, kind of.
Are you a software developer?
No.
But do you influence how the software developed product works?
100%.
So like what box do I put you in?
You don't belong in a box that that is, I think.
Who the future belongs to it.
Really?
Just because you can't code.
Five years ago, that might've been a reason not to start a software company,

(30:31):
but at this point, I don't think it is.
Go build an MVP and go show your customer what you're thinking it could look like.
And let them get excited.
And so what if you build it with a no-code thing?
Like who cares?
And then go figure out the team that can actually build the thing that company wants.
I do.
The only thing stopping you today is you.
There's no, I don't want like the excuses that you create are just like,

(30:55):
the ones that you've created, they're not real and they're, they don't have to be true.
And look, if you can't like the crazy thing is if you can't afford $20 a month or $200
a month now for the oh three or whatever it is.
And I think like Anthropics 30.
Okay.
Then use the free one and start there.
There's no object.
If you want to do it.
And I think that's where the scrappy entrepreneurs are going to come out of the woodwork.

(31:19):
And I think that, you know, Sam Altman talks about this a lot of that one person is going
to be like, you know, you're going to be like, you know, you're going to be like,
one person billion dollar company.
I don't know when that's going to happen, but I'm sure it's going to happen
because I'm just looking at and we're nowhere near that to be clear.
But I looked at how much work three people have outputted in the last year of four.
And it's incredible.

(31:39):
But I'll give you an example.
Like we, we looked at hiring really seriously because we probably should hire.
We have a key man problem.
My friends are like, we know.
Yes.
But we also move at a speed that is like a greatest of binge.
So we're trying to figure out what to do.
But instead of hiring another software developer, we hired what we call and my organized chaos

(31:59):
director, Sarah, and she like, I don't, as of today, don't write my own emails.
I don't manage my inbox.
I don't do calendars.
I literally sell and build and I do the two things of Gouda and she enables me to do more.
So the gut feel would be, we'll hire a software developer to get more features out.

(32:20):
But we don't need that right now.
What we need is I need to build more tools because the more tools we have out there,
more people know about us.
The more we are providing undeniable social proof that we're awesome.
That's an analyst or a mozi thing.
And then the more people are going to come to us and the more I'm going to sell, the
more I'm going to bill.
And the cycle just continues.
And so that's really like we're a company of three and I chose to grow organized chaos

(32:45):
director over a tech role.
That's a very untraditional choice.
And we're bootstrapped.
Like just to put that all into perspective, right?
Like, and, but you realize where your opportunities for finding time are and you get
very good at maximizing your meetings.
Like, for example, we won't do a meeting that's not on teams because we get the

(33:09):
transcript, the transcript goes to one of our AI's we put together and it knows what
to do based on whatever the outcome of that meeting was supposed to be.
And so anything that is manual, we try not to do and we try to automate, but there are
some things that just are better for humans right now.
Anyway, some things that are better for AI and some things that are both.
And so, yeah, for us, like if, if Chris gets hit by bus tomorrow, the, the old adage, I

(33:36):
mean, are we screwed?
Yeah.
But that's a choice we're choosing to make right now.
And a risk, there's risk in everything you do.
There's risk in hiring, there's risk in not hiring.
So we, we've chosen the path that we're on and maybe one day this year we'll change that.
Certainly could be.
I don't, I can't tell the future quite yet, but yeah, you don't have to be technical.
I think a dream pairing is you have a 10X engineer that gets together with a hacker

(34:00):
generalist that's pretty good at sales and you've got yourself a company that that's
really what it comes down to.
That's a recipe.
I like that.
I mean, I just found to downplay Ryan too.
Like you need the marketing too.
Like there's, I realize that sounds like you could be Chris's, like, you could be
Chris and I, and that's not at all what I meant, but I think if you had to, those were the
two skills that you absolutely need to get going and then how to position yourself in

(34:22):
the market obviously helps.
So ideally it's a great person to you.
And you said something there that I thought was really interesting where some things,
even though you have automation in your business processes, you reserve for humans.
Would you say a little bit about what you've done there and what decisions, like what factors
influence your decisions?
Yeah.
So I think a clear example is like managing my inbox.

(34:43):
I would have easily gotten an AI to answer my emails.
But here's the thing.
I, the, it's hard to program the logic that you apply to every, like a blanket logic to
every single email.
And so by the time I tried to spend my time building that, I might as well have just been

(35:06):
answering the emails.
And so Sarah understands me, understands how I think.
And so because of that, she checks in with me when she's not sure or when she is sure
she runs and she manages my calendars and like, yes, could I use Calendly?
Absolutely.
But here's the sneaky little thing that I don't like about Calendly.
Because I tried it.
I don't like giving people control over my calendar because now all of a sudden I'm getting

(35:30):
meeting invites for times that I don't want.
And I'm busy and I forgot to block it out.
Like it doesn't, it's a good idea, but it doesn't work in my opinion for how I needed
it to.
Obviously they're big market cap, so it must work to some degree, but it doesn't work for
me.
And so now I might say to Sarah, I don't want to meet anybody for the rest of the week
because I have so much to do.
And then somebody walks in, I'm like, Sarah, I'm meeting, clear my calendar whenever they

(35:54):
want to meet I'm in.
Well, how do you do that in Calendly?
And how do you tell an AI to do that?
Again, it's where are you going to put rewards versus effort and for how much is that role,
how much is that role of the business and what's the upside?
And Sarah, you know, always she listens to me rant and sometimes I just need to get stuff
off my chest.

(36:14):
And, you know, she's good at being like, yeah, no, I hear you, but you're going to do this
anyway.
And there's some meetings I don't want to take and she forces me to take.
She's like, I rescheduled them three times.
You're going to that meeting and you need that.
Like you need somebody to keep you accountable.
And I think by the time I build my own Jarvis to be able to do that, I think I would be,
I think it would just be way too much work and not as much fun.

(36:35):
So that's where that's a clear one that we saw that a human being was a better fit than
an AI.
You said something just then too, that you've mentioned a couple of times in the story for
Gambit, which is the fun factor.
And I feel like that was a big factor in your success as Gambit and what drove you to do
it and so on.
Do you have any advice for applying that for other people?

(36:57):
So it's funny because we just, so we went to, we're non-traditional as you've kind of
probably picked up and so we're big on Russian bonyas, which bonyas are basically like super
hot saunas and then very cold water.
So we did our 2025 planning on the 27th at the bonya in Mississauga.
And we're like, what do we want to do?

(37:17):
Like what, like you would think that we'd have all these answers.
The reality is we don't.
We're like, well, what really matters?
And we said, well, we want to have fun.
Like that, that's, we just want to keep having fun.
And like this NASCAR thing, I love racing.
So it's kind of into, we kind of fell into, but somewhat accidentally on purpose got into
things that we like doing.

(37:39):
And like, I'm so excited.
I want to be at the Daytona 500 in the pits.
Like I'm literally going to watch the guys work on the cars.
The girls were working on the cars pretty proud of us.
And again, we're going to make some big announcements.
So I got to be careful on what I'm saying here, but the it's, if it's not fun, then
it's just a lot of work.
And if it's just a lot of work, then you might as well go get paid somewhere where

(38:00):
you're guaranteed a salary because you're not guaranteed a salary here.
So if you're going to risk it and you're going to risk salary, et cetera, then it has
to be fun.
Like it just has to.
And so it's going to be profitable too, to be clear.
But the, I think, you know, that's where you get to choose what kind of projects you
want to work on.
What do you say yes to?

(38:21):
Like in year one, we pretty much said yes to just about anyone who would give us money
wasn't all of it.
Like I mentioned the word a couple of examples, we said no to, but we were just like, oh,
they want to pay us for this.
Okay, well, we'll just do that.
And then you realize that's a really bad idea after like year one, because you're like,
we're stretching like 90 different directions and like, we're not actually like building

(38:42):
solid ground anywhere.
But again, choice you make when you bootstrap is you got to find a way to make money.
So here we go.
So now in 25, we were a lot better at knowing what we want and what makes, what's the recipe
to make it a really good positive outcome and then how to position that value.
And so yeah, that's kind of just try stuff and be a little bit crazy and just somehow

(39:09):
like check your shame and you're like, I might fail at the door and just just try it and
be like, well, if this fails and goes to hell, I can always get a job.
So I mean, I mean, good news is usually McDonald's is hiring if I have to go or hello,
drive Uber.
That was my thing to my wife all the time was I should go drive Uber.
She's like, you're not going to do that, but fine.

(39:32):
But I think one thing we should probably talk about is how to get involved, how to get into
AI because I get that question a lot.
Please.
That's one big thing.
And I'd love to help people understand with this podcast is it's not something that is
outpacing you that you're just going to obsolete your job right away.
You can get into it now.
You're not too late.
Oh, you're definitely not too late.
And I think the only, okay.

(39:54):
Yeah, there's so many layers here.
So the, if you follow the media of AI is going to take your job, then the number one way
to fight against that is to learn how to use AI because the reality is adoption and enterprise
has been really low relative to what all of the AI companies were hoping.

(40:16):
And there's one really big reason.
According to, I was just at a conference, I won't name names, but a high up, a very
high up and a massive company was sharing with me that the problem is they can, 30%
of the job more efficient.
And then the CEOs go, okay, well, but I'm still paying a hundred percent of the salary
plus your solution.
So now I'm paying more to not get any more output because it's a real headache to try

(40:41):
to retool this person or rejig the art, the org to make them do different things.
Like, yes, that sounds easy.
When you have three people, try having 3000 or 30,000 people.
This is going to take three years just to reorganize.
And so the magic is the people that learn how to use the AI that can get themselves
30% more efficient or 15 or 10 or five, whatever the number is, but can materially show that

(41:05):
become these like whisperers of like, how do they do that?
Like how are they getting all this stuff done?
Reality, that individual is probably going, I'm not even working that hard.
Generally speaking, I just had kind of figured it out, but this was always true.
Like I remember when I, you know, be careful like name names, but I was at a job and they
were like, yeah, this is going to take you a ton of time to do.

(41:28):
And then I realized that I could write a macro to do like 90% of that job for me because
it was just moving numbers around basically.
And so in a spreadsheet, so I basically automated my way out of that job.
And that was pre AI.
So it's not like automation is new and it's not like software being more efficient.
The people is new.
It's just a different iteration of it.

(41:49):
You know, what does super intelligence looks like?
That's a whole different thing and AGI and we don't have to get into that.
But I think how you get into it is because everybody's like, what book should I read?
What fundamentals do I need to understand?
And I think how we think about education has to fundamentally change because you don't
need to be prompt engineer to use AI because guess what?

(42:11):
That's a made up term that is like two years old.
So the reality is if people that are good at making the AI do something that they want
it to effective, that's a prompt engineer.
Okay.
That's a pretty fancy title, but you know, I'll take it.
And I think that the, you don't have to understand how it works because guess what?
Most people don't understand how the AI actually works.

(42:32):
Truly like low level actually work.
Okay.
So the experts that work on it don't really know what it is.
There's made up titles like how many left, right and center or AI.
Okay. So what does that leave you to do?
Well, my thing would be find something that annoys you in your day that you wish there
was a solution for and start thinking about how would I, how would I use AI to do this?

(42:59):
And I'm going to give you an example that I hope won't bring this thing home.
My son loves stories of bedtime.
Dad is only so creative when he's spent his entire day working and tired.
My son now knows how to talk to Gemini and GPT-40 to ask it for stories and tell me a story about,

(43:22):
and he gives them the characters and they do it.
Now what he doesn't know is I put in some things in the background so that it does STEM related
things and whatever, but the point is my four year old is using it because the use case
we identified is he wanted stories.
So, but now he understands, cause I've watched the internet.
I've watched the iteration of how he talks to it.

(43:42):
It started with, he didn't know what to say.
Well, now he knows to say, I want a bedtime story because that's different than a regular story.
He knows to say for a four year old, because then it's a story that he understands.
He knows that he needs to give the characters that he wants.
Like watching a four year old start to understand how to actually work with this thing was the
magic. And if he can do it, anybody can.

(44:03):
Now, obviously I'm a biased parent.
I think he's the smartest kid in the world, but probably not true at scale.
But I think that that's what you need to do is I wanted to help people with breast cancer.
That's all it was.
Like there wasn't some big grand, like, I want to build a machine that does all these things.
No, it was just like this one thing that we wanted to do.

(44:25):
And then we got really good at doing that thing.
And I think that's the trick.
Yes, you can watch YouTube, but I wouldn't even bother anymore because now with GBT search,
I would just be like, this is what I want to do.
Help me.
Now that you can custom configure a GPT, I would just work on doing that.
And because they've done all the software for you.
All you got to do is the prompt engineering.
And I'm doing air quotes because you can't see me on video, but like the prompt engineering

(44:47):
side of the show that gets to be you and do own.
No one's watching for something that you think is fun.
Make it, make a joke maker.
I don't care what the use case is.
It doesn't matter.
You're not trying to make, make money on this.
Build something that's fun for you that makes it fun to learn more and be like, wow, I wish
you could search the internet.
Okay.
Well now that wasn't a thing before.
Models started with a knowledge cutoff and now there's perplexity, there's search, there's

(45:11):
all kinds of things.
And there was rag.
And as your use case grows, your desire to integrate more things will grow.
And then you'll get more and more interested as it sort of continues to go.
So the short answer is pick something you want to see.
Something you want to see done differently or something you want to build for yourself.

(45:32):
Like pick a, make it do a movie, you know, category guessing game for the family.
I don't, it doesn't have to be, make it be a tutor for your kid that like when they come
home with science homework that you know how to do it.
Like build one to help you with that.
But the use case does not have to be big.
Just start using it.
And you're like, oh, wow, that didn't work.

(45:54):
And you kind of, oh, well, when I did this, it kind of worked a little better.
And like, that kind of worked.
That's how I would get involved with it.
And don't quit your day job now.
Do that, like do all these free things to make your life better and more interesting
now.
Get good at it.
And then start telling people what will you build.
That's my big thing.
Show people what you build and then let them go, wow, well, wait, you know, I'd give you

(46:16):
like 10 bucks a month for that.
Okay.
Then maybe you have a business.
And then, you know, somebody wants to solve hard problems is just the right to solve a
much harder problem after.
And that's what it is.
Like first, you don't have product market fit.
Then you have product market fit.
Then you don't have enough salespeople.
Then you don't have enough marketing.
Then you don't have enough cash flow.
Then you don't have enough bandwidth.
Like the problems don't go away and they keep getting harder and bigger.

(46:39):
Yeah.
So it sounds like the basic advice is have fun solving problems.
Yeah.
Big stuff you care about.
Like, and don't try to make a business out of it.
We didn't.
And I think we're doing it right now.
Our goal wasn't like, how do we get customers and whatever.
It was just, you know, how do we work with it?
And how do we solve a problem?
And yeah, that's all it was.

(47:01):
And you haven't missed the bow.
Like anybody, again, people are very good at making excuses in their heads.
You have not missed the bow.
In fact, you're probably still early.
Like maybe not literally, but figuratively in the grand scheme of it, AI is not very
old and AI is not going to.
And like you said, there's 10 years left of opportunities to explore with AI.

(47:22):
Oh, and it's probably more like a hundred, just that would sound insane.
But then yeah, at least 10 if it all stopped right now.
And so yeah, you haven't missed it.
You're not too late.
It's not incredibly technical.
Like it can be, but I mean, there are stages like everything else.
But the point of entry is willingness.
Like there's never been a point in time where that's true.

(47:44):
That you could just go in a free thing that offers you insane intelligence that you can
just use for free.
And even if you just made yourself a little prompt and stayed in the chat thread, like
that's fine too.
Like it doesn't have to be complicated.
In fact, the simpler, the better if it works, quite frankly, but pick something you want

(48:05):
to do.
Rethink what education means because like, so Ask Ellen gets, I think the latest stats
was 35% return rate to the site.
So that means someone who uses it, they come back.
It's actually, I would venture a guess it's more than that.
So here's a couple of things we don't track for privacy reasons.
We don't track what you are.

(48:26):
Just Google tells us who comes back and forth.
If I could delineate by only people who were there to use it because they are going through
a breast cancer journey, it would be higher because a lot of our competitors and prospects
I know are on our tools beating them up.
So if I could take those out of the equation, it would be better.
But why is that?

(48:46):
And my thesis is it goes back to a theory from the 1960s from Malcolm Knowles on adult
learning and it talked about personalized learning.
And if you think about it, we used to have to conform to how the author wrote the book.
And what do I mean by that?
Well, we usually read chapters one, two, three, four, five, six in order.

(49:07):
So if Ellen chose to talk about how she told her kids in chapter four, and it's Wednesday
and I want to tell my daughter on Friday, and I'm a slow reader and I'm just not going
to read four chapters, then I might just never get to it.
And it's not that the information wasn't there.
It's just the way, the means by which I had to consume the information did not match what

(49:27):
I was looking for.
And now with AI, you could just ask your very specific question.
It will go look at the entire document and bring you back the parts that matter and form
an answer.
That's the magic.
And like, it's not knowing how to do something, in my opinion, was never a real objection,
but it's really not now.

(49:48):
If you're listening and you're going, I just don't know how to do it, dig deeper because
there's another underlying reason that's not allowing you to get there.
And that's the excuse you're telling yourself.
And it's fine if there are other reasons, it's not it, but that there's no shame, but
it's not knowing how to do it is not a real, it's not a real reason.
Well, one thing I wanted to ask you is the question I think is on everybody's minds for
a podcast like this, which is Patrick, are you an AI?

(50:14):
That's funny.
I've been, that's so funny.
I thought about making myself an ASPAT for Sarah.
I think how you know that I'm not an AI is I make mistakes.
And that's, I think I misspell things all the time.
I'm a terrible speller.
And I think that will be the way to know.
But I mean, you can also instruct an AI to make spelling mistakes.

(50:34):
So who knows, I guess.
And the last thing I wanted to say was just listening to your story and helping your friend
through that really tough time.
It feels like to me, I just want to say, do you know that God loves you?
Like that's such an amazing story.
Well it's a, you know what, it's one of those things we, if you just try to do enough good

(50:57):
things that then good things start happening.
And my grandpa had always taught me this that, he always taught me this.
It was funny because I'd proved this so many times.
The more you give, the more you receive from a generosity standpoint.
And I'll never forget this because this is just a ridiculous example.
And like, yes, I understand that some could argue probability logic and I get it.

(51:20):
But we were at a bachelor party and I gave a hundred dollars cash to a homeless person
because we were on our way to the casino and I walked out of there with a grand and everybody
else lost.
And it's funny to me because I'm like, but guys, this happens to me all the time.
And I'm not advocating gambling at all, but it's just like, the more that I give away
then it's like, oh, I find, you know, $200 and a jacket and I forgot about it.

(51:43):
And they're not linked.
They're not necessarily causal, but it's incredible that if you can call it a coincidence, but
I'm like the 30th time it starts to look more like a pattern than a coincidence.
So yeah, so I appreciate that.
I love that.
And we just try to build, you know, cool things with our changemakers.
You know, we're building.

(52:03):
Okay.
Last example from like a, how do you position AI within certain things?
So we're working with, again, it's not, I gotta be a little cagey with the details,
but we're working with a suicide prevention organization who hopped on the call and we're
like, basically we're not using AI for that.
And I was like, I understand, nor should you.
They're like, oh.

(52:23):
And I said, I didn't think a youth in a situation of suicide needs a human being.
I don't think the AIs are not there yet.
Absolutely.
I'm about as pro-AIs you're going to find.
And I admit that.
And so they said, okay, well, thanks for your time.
I said, well, hold on.
Who's helping the parents through this?
And they're like, well, what do you mean?

(52:43):
I said, well, I'm guessing that you can go to school to have a child who's in an acute
mental situation.
No, that's true.
And where, who's helping them navigate this?
Oh, and now we're building a tool to help parents figure out like what to, cause a lot
of them don't know what to say.
So they say nothing, which sometimes is worse.
Oh, that's so bad.

(53:03):
They don't have these practical advice.
So AI can be a part of suicide prevention if you position it the right way.
And if you think about the user and you think about how is someone going to use this and
what's the best way to use it.
And so, you know, you look at that, just because it doesn't fit the obvious one, doesn't mean

(53:25):
it doesn't fit tangential things.
And that's a really, that was a big one for us.
It was, I'm passionate about it.
It's near and dear to me, but it was just an example of they were right that we agreed,
but that didn't mean that there wasn't a role for AI at all.
It just means the obvious way wasn't the right way at this point.

(53:45):
And I really like that, that essentially is looking at the human side of the problem and
then seeing more facets than just that one flow, that one problem that's already being
solved.
Yeah.
Like we get told from Ask Ellen, which like, again, is a tool that was met, unfortunately
breast cancer predominantly affects women.
It can affect men.
I've learned this.

(54:06):
I didn't know that truthfully, it's small percentage, but it does.
So we've had so many husbands thank us for building this because they didn't know how
to support their spouse.
Like that's pretty wild when you think about it, but that goes back to dignified answer.
We didn't set out, we didn't actually have them as a persona, quite frankly, and fairness,

(54:27):
shame on us, we probably should have.
But dignified answer is where it came through.
And like one, I feel like one last, there's so many examples I can give, but one that
like was just completely outside of the box that we did not ever plan for is Prosper Kim's
on and says, Hey, by the way, I used Ask Ellen.
And I was like, and he was like, yeah, it's fantastic.
Like, Oh, that's really cool.

(54:49):
He says, but I bet you didn't think of how I used it.
And I'm like, Oh, now you have my attention.
So he said, well, my good friend just got diagnosed with what breaks breast cancer.
So I figured, okay, we sent her the tool and it's not that original.
And he said, my friends and I wanted to give her a gift basket.
So I asked Ellen, Hey, I want to give my friend a gift basket.
We're going to do a gift card for food.

(55:10):
What do you think?
And Ask Ellen said, dietary changes throughout a chemo journey can really affect you.
And so if you're going to do a gift card, I wouldn't do it purely based on food.
He said, I spent the next 30 minutes building a custom curated gift basket for my friend.
So when our friends and we all gave her the gift basket, everybody balled because she

(55:35):
felt understood and they felt like they understood her.
Like AI can be the bridge to knowledge and understanding.
And that's really the magic of what we're kind of talking about here.
And just another example of like, that wasn't a, we didn't drop that use case.
We just told it to give dignified answers and boy it sure did.
Yeah.
And not just a bridge between knowledge and understanding, but empathy as well.

(55:59):
Oh yeah.
That's one of the things I never would have expected from AI.
And it wasn't obvious to get it.
They're getting better at it now.
But it's interesting when you can get it to understand the psychology of a conversation,
how much fun you can have with it.
And it's, they're so good.
Like they're so, I can't imagine a world.

(56:23):
I'd be so sad if AI went away.
Like I don't know how I would, like I use it to, like I talk to Steve Jobs and Steve
Wozniak every day.
Sounds insane.
I know.
And, but I have two of them that are acting like them and it's incredible the points that
they make.
Steve always wants to build new products and market them.
And Wozniak's always worried about how, what's the hardware compatibility between all these

(56:47):
markets.
It's hilarious.
Like, but it's really fun.
And it does it in their perspective.
I think that we're about to be rolling out.
2025 is going to be really big for us on the support side.
And we're about to be rolling out some really important things that I think are both going
to be, you know, this is a business podcast, so like profitable, but are also going to

(57:07):
help just a tremendous amount of people.
And I think we figured out a really interesting niche where we can help people and give them
the product for free, but help them in different ways that earn us, you know, some version
of money.
And that way we can keep doing what we're doing.
And like the cost of these things are going down and down and down and down, which is
incredible.
Like we were about to launch Ask Todd, which is a tool we built, was designed because not

(57:31):
everyone could just pick up the phone and call a senior partner at a law firm and get
really great advice.
I didn't think that was fair.
I didn't grow up with money.
So I think that that shouldn't be a differentiator.
So I told Todd, hey, we should build this thing.
We should scale you up.
And then without him knowing, because I'm big on doing things without permission, I
didn't launch this publicly, mind you.
I showed him first and it's about to launch.

(57:52):
I built a system whereby using the intelligence of Ask Todd and how I know he looks at documents,
you can upload an NDA and say, hey, I'm this person in this NDA.
What are the red flags?
What should I be thinking about?
And he will call stuff out and it will do everything and it'll walk you through it.
And you can say, okay, well, could you redraft it?

(58:13):
Oh yeah, sure.
Okay.
And then you can download the new revision of that document.
You're going to be able to do that for anything, but it's the way he'll ask Todd will ask you
questions about the document to actually inform himself on how to actually look at it.
Because you have asked him Chad GBT to look at an NDA.
Okay, fine.
But it's going to input output.

(58:34):
We want to break the input output and go, okay, cool.
You've inputted something, but we have to ask a couple of questions first to actually
lay it out for us to do this thing right.
And there's a small group of people that have seen it.
It's blowing their minds.
And if you want to ever have a more technical conversation in the backend, we get into it,
but it's pretty neat how it does all of those things.
But it's fun.
We don't have a big story.
We're not from the Valley.

(58:55):
We're not all millionaires.
We're not all millionaires.
We're not all millionaires in VC.
Yeah.
We're just kind of crazy enough and wanted to help some people and here we are.
So I mean, God, if we could do it, anybody can.
Yeah.
Okay.
Well, normally I ask people if they have anything they'd like to share or how to follow them,
is there anything else you would like to share about what you've been doing and what's coming

(59:17):
up and how can we follow you?
Yeah.
So I think definitely hit me up on LinkedIn, Patrick Belliveau.
B-E-L-L-I-B-E-A-U.
I'm there.
I'll accept.
And you can kind of see our journey going through that.
If you have questions, feel free to flip me an email, pat at gambitco.io.
As I said, I don't actually answer my emails so transparently or genuinely.

(59:38):
Sarah will look at them, but happy to help inspire where we can.
I think those are the big ones.
And if you're in a NASCAR though, February is going to be a really fun and outspit month.
And we have a tool for Parkinson's that's going to launch this year, which I'm super
excited about.
It's in closed beta right now.
And I feel like there's so many things that are coming that are going to be really fun.

(01:00:00):
Yeah.
Just start.
If you're interested, just start.
That's it.
Like it doesn't have to be fancy.
It doesn't have to be complicated.
Just start.
I started this podcast because I wanted to stand at the gate of businesses using AI and
see what separated hype from lasting impact.
Back when cities had walls, you had to go into the city to do business at the market.

(01:00:24):
So if you wanted to talk to someone, you waited by the gate until they came in or came out.
Do that enough times and you could talk to everyone.
That's what I want to do.
Stand at the gate of people doing business with AI and talk to them, see what they do
and why they do it.
If you know someone that's making an impact in the world of AI, would you connect them

(01:00:45):
with me?
You can find me on LinkedIn or shoot me an email at daniel at manary.haus.
That's daniel at manary.haus.
Thanks for listening.

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