A lot of businesses can really scale to

tens of millions of dollars today

profitably with AI.

>> This is Alex, founder of Hicksfield, an

AI company that hit 200 million annual

recurring revenue in just 9 months

faster than Slack or Zoom. And what he

told me about starting a business today

completely blew my mind. And you can

copy his strategy, too.

>> Focus on bringing like the first dollar

by day 30 of product developments and

maybe 1 millionaire R by day 90. That's

a lot.

>> I just think it's the next industrial

revolution. It's probably more powerful

than the internet. For many many young

people, AI becomes social elevator.

>> For someone who still has fear like this

is moving so fast, I don't know how I

can start. Can you give them one piece

of advice?

>> First, I would start from

>> I have an amazing guest today. I am so

excited to learn from you. Let's get

very practical right away. You built

Hicksfield and achieved $200 million in

revenue in 9 months. Let's imagine every

I don't want this to happen, but let's

imagine a scenario when you have to

start from scratch tomorrow and you have

90 days to launch a business idea. From

what you've learned with your experience

at Hicksfield, what would you do?

>> I think it all starts with maybe a team

of two. Someone who is builder who can

go within 24 hours from idea to a

product. And now it all becomes

possible. There are so many uh

databases, there are so many payment

systems and so on which simplify

creation of MVP. And then someone as I

call it go to market person who has this

natural empathy maybe or understanding

of the sort of target distribution whom

they're selling to and who can come up

with interesting kind of new content

formats

which can resonate with the target

audience on social media. And I think

this is a very different skill set from

the like marketing roles of the previous

decades.

>> And how many times should they be ready

to iterate? How many ideas?

>> For example, for us last year we were

iterating every day. So it was six

uh days a week and um every day we were

putting new product release as we were

trying to find workflows and use cases

which have high frequency and which

matter for our target audience and then

once the technology gets there it's

important to develop sort of the

workflow which is easy enough but gives

enough configuration as well. This

dilemma of the perfect interface is

still not solved frankly. So uh this is

another reason why we embrace daily

iteration. And on top of all of that

every month the whole industry resets.

They completely push the boundaries in

terms of the capabilities. There are

probably let's say five leading research

labs and each lab is pushing massive

updates every quarter. So at some months

we have even two major updates and it

typically requires to substantially

rebuild the whole product around those

models. So it's exciting time today cuz

product builders like ourselves at

Hicksfield, we we just try to evolve the

product so that it highlights the best

possibilities of these models to our

customers. But it's a constant race.

Yeah, it sounds like a very challenging

race and I think you mentioned that last

year was one of the hardest for you when

a lot of things were not working. Can

you talk to me about that one thing that

actually worked

>> in uh 2024?

We really started from the mobile apps

and things were not working well cuz

retention for mobile apps is relatively

low. Things drastically changed for

Hicksfield when we started to constantly

iterate with creatives and we just asked

them very simple question like did you

see this video? This was a cool generate

video and they said oh no how is this

possible? What's the cost? And we say it

actually cost maybe less than $500 to

make this video. And then we ask did you

actually try these models? What's your

experience with AI? Um and obviously

everyone tried AI back by by then. Even

by maybe February last year, everyone

tried AI but everyone had some issues

with that. Back then we realized that

the core limitation was around

camera control. Like a lot of creative

directors they really want to control u

all the camera effects, camera angle and

so on. Back then there was no system to

achieve that. So that uh the initial

traction of hickfield.ai AI came from

these camera controls which we

implemented on engineering side based on

the feedback from creatives.

>> So how many interviews did you have to

conduct to come up with this feature?

>> This is a very good question but it kind

of puts me on a weak spot frankly cuz we

interviewed eight people eight out of

eight said the same thing and we talk

from Hollywood level uh movie directors

to like regional uh producers of

commercials everyone had the same

feedback. And how did you select those

people? Were they customers already or

you just wanted to talk to people in the

industry?

>> Actually, this was probably a challenge

as we wanted to talk to people who we

don't have a very close relationship to

just get unfiltered opinion. But the

feedback was very consistent. Everyone

was missing these camera controls. So

that's what we delivered March last

year. Then in April, we delivered a

library of visual effects. And then I

think in June industry completely

changed. we saw the emergence of AI

native

marketing agencies. So essentially those

agencies they completely go end to end

with AI and very often they try to

bypass incumbent tooling like for

example Adobe or something else and go

end to end with AI. On the one side they

are very limited cuz

AI capabilities back in June were a

little limited. On the other hands, they

drastically improve their margin profile

and they kind of show their clients that

they can build ads within days. A lots

of brands actually want to have constant

content flow on their socials and they

want to embrace AI. And then from June

to December last year, this um this new

industry of AI native agencies

completely exploded. But basically, you

said the the start of your growth was

the multi- angled uh camera view and it

came from talking to people in the

industry. I love that. And also the

number eight is actually very consistent

from what I'm getting uh talking to

other founders. It's normally like 12 to

20, but it's not too many interviews

because I feel like a lot of people

think they need to talk to thousands of

people to figure out the problem, but

it's actually like around 10 interviews.

>> Yeah, absolutely. So eight people who

actually helped us to shape the product

and then I think we hired four of them.

>> Oh time. Yes. So now we have this

feedback loop within the team.

>> That's awesome.

>> And that's how we realized that probably

the best products in creative AI is

going to be built in symbios like in

collaboration between engineers and

between creators. So today roughly half

of our maybe 40% of the team are um

engineers, maybe 40% are creators.

>> Like you said, two founders, right? One

is technical, one knows the consumer.

It's basically reflected in your team.

>> Okay, let's let's get back to that tough

year because I feel like for a lot of

people that's what they're scared of. So

when you were building this and nothing

was really working and then Google

releases the new VO model,

>> did you ever think about giving up on

that particular market and starting

something else because this was getting

so crowded?

>> I think we were committed to figure this

out. There are two reasons why we had a

conviction. First is that prior to that

I was at Snapchat. I was running geni

there and I saw the uprise of Tik Tok

and kept cap became top five apps in the

world

and um it's unprecedented says it's not

a messenger it's not a social media and

this was a strong signal for me that the

needs of social media creators are

simply unmet in the markets and the

second reason why we had conviction we

constantly heard that creators feel a

burnout

from sort of feeling pressure to record

multiple videos a day for socials with

their own face. Mr. Beast, he spoke very

openly about that. But that's I think

the that has been a primary challenge

for the whole industry over the last

four or five years. And then what was

surprising to me is that advertisers

have the same problem. Most of the

advertisers talk about like maybe

mid-market brands, they can be spending

hundreds of millions of dollars on

marketing and they don't have any

production team.

>> So, you chose the right part of the

market. This is what I'm hearing. So, I

feel like for every entrepreneur who's

watching, uh when you see a big

opportunity in the market, you also have

to spot who's paying the most, not just

go after each user, right?

>> Absolutely. We live in a very

interesting um era where all the

powerful companies try to give AI to

everyone literally MetaMai,

Google,

Microsoft, OpenAI, Anthropic, Bidance

and many many more. I think each of

those companies want to give AI to all

its customers really. That's why

startups have to have more nuanced view

of the world and have to have more

nuanced set of customers. And I think um

startups today are sort of incentivized

to stay cash flow positive and build

real business from day zero. This is

what I see across Hicksfield and other

top application AI companies. So I think

this also creates a very interesting

dynamic that the target audience should

be maybe tens of millions of users who

are willing to spend hopefully couple

thousand dollar a month. So it is not

for everyone but the delivered value

should be so strong. So the product

should be so good so that it kind of

sells itself.

>> I love that. And I love that you have a

concrete number $2,000.

>> Yeah. $2,000. uh I'm not sure like with

Hicksfield for example this is the core

metric which we are tracking like uh how

much of the value we believe we provide

which is more like through the user

interviews but also how much we charge

uh users annually. So this is one key

metric and we are not chasing just um

monthly active users for example because

the monthly active users number can be

inflated through some viral effect

monthly active user doesn't really speak

to the frequency of the usage and the

value delivered. So that's why for us um

really daily active users and average

ACV average contract value those two

metrics are the most important ones. One

of the reasons I was so excited to sit

down with Alex is that our team has

actually been using Hicksfield for a

while now. My producers and editors

absolutely love that all the top AI

models are in one place. Nana, Banana,

Seance, Cling, Vio, Sora, and I love

that they don't need 10 different

subscriptions. And it's kind of

incredible. Alex just told us that last

year they were shipping a new product

release 6 days a week. And now everyone

knows them, but they haven't slowed

down. They keep launching new features

and one of the latest ones is Soul 2.0.

Soul 2.0 is Hickfield's own image model

and it's not like anything else out

there. Most AI image generations, you

type a prompt, you get something that

looks fine. So, it was built

specifically for creative work, fashion,

editorial, content. It actually

understands aesthetics. You give it a

reference photo and it doesn't just copy

it. It reads the lighting, the grain,

the mood, the era like a creative

director would. There are three models.

So that's the core model. You prompt,

you get a beautiful image with real

aesthetic awareness. Soul reference, you

upload a reference and it generates new

images that match the vibe, not just the

composition. Same visual DNA, different

shots. And soul ID, you upload 10 or

more photos of yourself. It learns your

face structure, skin tone, expressions.

Then it generates you in any style. Y2K,

editorial, film photography, Polaroid,

20 different presets at launch. And here

is what actually got me. You can specify

the camera medium, say shot on Kodak,

Portra, or disposable camera, and it

changes the grain, the color science,

everything. It doesn't slap on a filter.

It actually shifts the entire feel of

the image. And the same thing works with

color. They just added hex colors, so

you can pull the exact palette from any

photo and apply it straight to your

generations. If you want to try Soul

2.0, I'll leave the link in the

description. And now, let's get back to

Alex. Can you uh give advice to people

who are watching who haven't started

yet, but they haven't started because

they think a large company is going to

take over. How should they think about

their defensibility?

>> I think each company can really keep

their focus on maybe two or three top

priorities. Interestingly enough, people

like to say about anthropic that their

major success from MCP and cloud codes

actually was not like a top down but

really bottom up and it like cloud code

success was not sort of planned and I

think it's true that like these large

companies they definitely can benefit a

lot from applying top- down approach

from two to three initiatives and really

consolidating all the resources to make

the most progress there. I just think

it's the next industrial revolution is

probably more powerful than the

internet. So the number of products and

ideas to be built I think just overwways

uh uh number of ideas which open AAI or

anthropic can push internally. That's

why I would encourage builders to build

especially today when like a quite small

team of maybe 10 people can build like

high scale products. Do you think

there's that we have a certain gap of in

time when we can build? So, for example,

I've been hearing a lot in social media

that we only have two years to build

something new because then we're going

to have some companies that reach AGI

and it's going to be impossible to find

a gap in the market because those

companies are going to be filling those

gaps.

>> This is a good question. We definitely

make um tremendous progress as a

industry to automating work in digital

world and for sure maybe next decades

there are going to be a lot of

applications of AI in physical world.

It's difficult to forecast how much

progress we all are going to make there.

But this decade is definitely the era of

digital economy completely changing with

with AI. That's for sure. I really don't

want to believe in the future when there

are going to be maybe three labs who

have the best models and these models

controlling all the world. This could

happen. That will be very difficult

future. So I would I try to stay

optimistic and encourage everyone to

stay optimistic and really focus on

building and delivering value. Like for

example um today

I just want to give you a very concrete

example. So I recently spoke to a very

large very very large like property

management company which actually uses

Hicksfield to to sort of advertise their

buildings, their uh apartments and so

on. Like no one is building for this

industry. Like in this industry there is

a very specific um workflow of a

customer like customer needs to learn

about about the property then they need

to go to the website and get all the

details then they need to call then they

need to show up then they leave deposit

and the whole customer journey. No one

is actually building solution

specifically for this industry to like

cover this journey end to end with

agents. And the reason why agents are

going to deliver lots of value in this

specific business is that customers who

want to maybe let's say rent apartment

especially in certain price points they

want to make a decision rather quickly.

So every day of delay every day of just

moving from one stage to another is just

is just lost revenue. So, and this

business owner just said to me that no

one is building for their industry and

and I'm confident there are many more

examples like that.

>> Yeah. So, riches are in the niches as as

they say from your experience when you

pitched VCs with another AI idea. What

makes a pitch stand out these days? I

think today um there is definitely fear

that open AAI, Anthropic and other labs

are going to just be very acquisitive

and uh just trying to expand their

product offering to multiple different

verticals. Pretty much every week there

is clo for X launched and stocks go

down. That definitely happens and that

creates a lot of fear. And I would just

say that the core insight for me

personally was that most of these uh hot

and hyped AI companies they are actually

cash flow positive like maybe it is a

wrong mindset to go and raise venture

capital today. I think there is plenty

of preede capital available today but

I'm not sure every everyone needs like

to raise series A B C D and so on. How

much revenue did you have when you

raised your first round?

>> For me, with Hicksfield AI, it was

probably easier because I had a previous

exit and we basically raised $16 million

without having um any revenue just with

maybe having like million users for our

mobile app. But this is not exactly the

way how I would recommend to build

today. I would recommend to focus on

bringing like the first dollar by day 30

of product developments and maybe 1

millionaire R by day 90 and then decides

if someone needs VC funding or doesn't

need. I mean a lot of businesses can

really scale to tens of millions of

dollars today profitably with AI and for

such businesses there is no need to

attract VC funding. I can give you a

very simple example. So there are so

many uh websites we just allowed to make

professional fat shoot like for

basically for for passport. Many of them

make tens of millions of dollars. None

of them are going to be Yeah. None of

them are going to be venture capital

backed business.

>> Well, and you said something $1 million

by day 90

>> AR meaning like 80K a month.

>> 80K a month in three months. That's a

lot. And so the the playbook to achieve

that is basically generate ads and

launch them and test whether whether

they're landing with your target

audience.

>> Paid ads are very difficult today. I

think a lot of distribution come through

organic social media and creator

integrations

>> and just make sure that by day 30 uh

there is monetization in place and then

there is a way to constantly grow to a

revenue to let's say one millionaire by

day 90. Many successful uh companies

scale very quickly today. Just different

verticals have different capacity. Some

in some verticals the ceiling could be

just 50 million. In other vertical 1

billion, in other verticals like 100

billion.

>> Any tips on landing first customers in

the first 30 days?

>> Initially, at least last year, Twitter

has been the social media where the

distribution starts from. It starts from

like small communities. Then it goes to

AI news pages on X. Then from AI news

pages on X, it goes to Instagram news

pages. Then from Instagram news pages to

creators, then it goes to Telegram and

like other social media. That's what we

have seen with Hicksfield and with many

other products as well that they went

through the same sort of journey of

popularity and news through various

social media, but it all originated on

X. I think now it's being kind of

changed

today a lot of hype like a lot of

companies they sort of try to use X to

boost their products

sort of signal to noise ratio just drops

Twitter becomes less relevant but still

it's it's the main place for new AI

products launch

>> that's awesome I'm still trying to crack

the the X strategy I feel like if you

add a word breaking

>> or just in to whatever you're posting

staying in the beginning and it should

be in top slug then then it performs

>> and then some something should be like

clo cooked.

>> Yeah,

>> like something like that.

>> Yeah. Just wiped this out of the market.

Yeah. It has to be very sensational and

X. But you're so right. I've heard so

many and I know a lot of creators who

build their whole like email newsletter

1 million subscribers just off viral X

uh posts.

>> That's amazing. I love this life hack.

Thank you so Although this has been the

primary life hack of the 25 and I do

believe that the media evolves itself as

well. So 26 could be difference.

>> I always see LinkedIn on the rise. So

maybe maybe LinkedIn.

>> Maybe LinkedIn.

>> Your previous company you sold it for

166 million.

Were there any key learnings from that

business or mistakes that you made that

you will never repeat in this one?

>> It it's it's like never say never. But

one of the key learnings for me and the

key takeaways was to embrace meritocracy

sort of like

I'm 30 and I feel sometimes that I'm

quite old for this new era of AI like a

lot of new ideas in Hicksville today

come from these kind of fresh grads

maybe 23 25 who sort of maybe never

worked in a large company who were doing

like freelancing with some VIP coding

tools who were doing VIP coding before

the term VIP coding basically and uh

they they just think differently and I

think that's sort of maybe the right

mindset. So traditionally in any like

corporation those people would be just

simply no one would just simply listen

to them. So and the same applies to the

creative role. So there is definitely

some resistance from people who

especially build like let's say like

large Hollywood projects that oh AI is

dangerous it's not authentic and in the

same time it's really exciting that for

many many pe young people AI becomes

social elevator and I sort of strongly

relate to that personally cuz for me I

had to do a lot of competitive

programming you know like who solves

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