$1.3B AI CEO: "You ONLY Need 2 People and 90 Days to Build a $1M Business" | Higgsfield Founder

0:00 A lot of businesses can really scale to tens

0:02 of millions of dollars today profitably with AI.

0:05 This is Alex, founder of Hexafield,

0:07 an AI company that hit a $200 million annual recurring revenue in just 9 months,

0:13 faster than Slack or Zoom.

0:15 And what he told me about starting a business today completely blew my mind,

0:19 and you can copy his strategy, too.

0:21 Focus on bringing like the first dollar by day 30 of product development,

0:27 and maybe 1 million ARR by day 90.

0:29 That's a lot.

0:30 I just think it's the next industrial revolution.

0:32 It's probably more powerful than the internet.

0:33 For many, many young people, AI becomes social elevator.

0:37 For someone who still has fear, like this is moving so fast,

0:40 I don't know how I can start.

0:41 Can you give them one piece of advice?

0:43 First, I would start from I have an amazing guest today.

0:49 I am so excited to learn from you.

0:52 Let's get very practical right away.

0:54 You built Hexafield and achieved $200 million in revenue in 9 months.

0:59 Let's imagine every I don't want this to happen,

1:02 but let's imagine a scenario when you have to start from scratch tomorrow,

1:06 and you have 90 days to launch a business idea.

1:10 From what you've learned with your experience at Hexafield, what would you do?

1:13 I think it all starts with maybe a team of two,

1:17 someone who is builder, who can go within 24 hours from idea to a product.

1:24 And now it's all becomes possible.

1:25 There are so many databases, there are so many payment systems,

1:29 and so on, which simplify creation of MVP.

1:33 And then someone, as I call it, go-to-market person,

1:36 who has this natural empathy maybe

1:39 or understanding of the sort of target distribution,

1:42 whom they're selling to, and who can come

1:44 up with interesting kind of new content formats,

1:49 which can resonate with the target audience on social media.

1:52 And I think this is a very different skill

1:54 set from the like marketing roles of the previous decades.

1:58 And how many times should they be ready to iterate?

2:01 How many ideas?

2:02 For example, for us last year, we were iterating every day.

2:05 So, it was six um days a week

2:09 and um every day we were putting new product release.

2:14 As we were trying to find workflows and use cases

2:19 which have high frequency and which matter for our target audience.

2:23 And then, once the technology gets there,

2:25 it's important to develop sort of the workflow,

2:28 which is easy enough but gives enough configuration as well.

2:31 This dilemma of the perfect interface is still not solved, frankly.

2:36 So, uh this is another reason why we embrace daily iteration.

2:40 And on top of all of that, every month the whole industry resets.

2:44 They completely push the boundaries in terms of the capabilities.

2:48 There are probably, let's say, five leading research labs.

2:53 And each lab is pushing massive updates every quarter.

2:57 So, at some months we have even two major updates.

3:00 And it typically requires to substantially

3:04 rebuild the whole product around those models.

3:06 So, it's exciting time today cuz product builders, like ourselves at Hicksfield,

3:12 we we just try to evolve the product so that it

3:17 highlights the best possibilities of these models to our customers.

3:21 But, that's a constant embrace.

3:22 Yeah, it sounds like a very challenging race.

3:24 And I think you mentioned that last year was one

3:26 of the hardest for you when a lot of things were not working.

3:30 Can you talk to me about that one thing that actually worked?

3:32 In 2024, we really started from the mobile apps.

3:38 And things were not working well cuz

3:40 retention for mobile apps is relatively low.

3:42 Things drastically changed for Hicksfield when

3:46 we started to constantly iterate with creatives.

3:50 And we just asked them very simple question like,

3:53 "Did you see this video?" This was

3:55 a cool AI-generated video and they said, "Oh, no.

3:57 How is this possible?

3:58 What's the cost?" And we say,

4:00 "It actually cost maybe less than $500 to make this video." And then we ask,

4:05 "Did you actually try these models?

4:07 What's your experience with AI?" And and obviously everyone tried AI by then.

4:13 Even by maybe February last year, everyone tried AI,

4:16 but everyone had some issues with that.

4:19 Back then, we realized that the core limitation was around camera control.

4:25 Like a lot of creative directors,

4:26 they really want to control all the camera effects, camera angle, and so on.

4:32 Back then, there was no system to achieve that.

4:35 So, that's the initial traction of Hixfil.ai came from these camera controls,

4:42 which we implemented on engineering side based on the feedback from creatives.

4:46 So, how many interviews did you have to conduct to come up with this feature?

4:49 This is a very good question,

4:50 but it kind of puts me on a weak spot, frankly, cuz we interviewed eight people.

4:55 Eight out of eight said the same thing.

4:57 And we talked from Hollywood level movie

5:00 directors to like regional producers of commercials.

5:05 Everyone had the same feedback.

5:07 And how did you select those people?

5:08 Were they customers already or you just

5:09 wanted to talk to people in the industry?

5:11 Actually, this was probably a challenge as we wanted to talk to people

5:16 who we don't have a very close relationship to just get an unfiltered opinion.

5:20 But, the feedback was very consistent.

5:22 Everyone was missing these camera controls.

5:25 So, that's what we delivered March last year.

5:27 Then in April, we delivered a library of visual effects.

5:31 And then, I think in June, industry completely changed.

5:35 We saw the emergence of AI native marketing agencies.

5:39 So, essentially those agencies, they completely go end-to-end with AI.

5:46 And very often, they try to bypass incumbent tooling like

5:50 for example Adobe or something else and go end-to-end with AI.

5:54 On the one side they are very limited because

5:59 AI capabilities back in June were a little limited.

6:04 On the other hand, they drastically improve their margin profile and they

6:09 kind of show their clients that they can build ads within days.

6:14 A lot of brands actually want to have constant content

6:18 flow on their socials and they want to embrace AI.

6:21 And then from June to December last year,

6:25 this um this new industry of AI native agencies completely exploded.

6:30 But basically you said the the start of your growth was the multi-angled

6:36 uh camera view and it came from talking to people in the industry.

6:39 I love that.

6:40 And also the number eight is actually very consistent

6:43 from what I'm getting uh talking to other founders.

6:46 It's normally like 12 to 20,

6:47 but it's not too many interviews cuz I feel like a lot of people

6:50 think they need to talk to thousands of people to figure out the problem,

6:52 but it's actually like around 10 interviews.

6:55 Yeah, absolutely.

6:55 So eight people who actually helped us to shape

6:58 the product and then I think we hired four of them.

7:01 Oh, you also Yes.

7:03 So now we have this feedback loop within the team.

7:05 That's awesome.

7:06 And that's how we realized that probably

7:08 the best products in creative AI is going to be built in symbios uh like

7:13 in collaboration between engineers and between cre- creators.

7:17 So today roughly half of our maybe 40% of the team are um engineers,

7:24 maybe 40% are creators.

7:25 Like you said, two founders, right?

7:27 One is technical, one knows the consumer.

7:29 It's basically reflected in your team.

7:31 Okay, let's let's get back to that tough year because I

7:33 feel like for a lot of people that's what they're scared of.

7:36 So when you were building this and nothing was

7:38 really working and then Google releases the new video model.

7:42 Did you ever think about giving up on that particular

7:45 market and starting something else because this was getting so crowded?

7:48 I think we were committed to figure this out.

7:51 There are two reasons why we had a conviction.

7:54 First, is that prior to that I was at Snapchat,

7:58 I was running Genie I there, and I saw the uprise of TikTok and CapCut.

8:03 CapCut became top five apps in the world.

8:07 And it's unprecedented says it's not a messenger, it's not a social media.

8:12 And this was a strong signal for me that the needs

8:17 of social media creators are simply unmet in the markets.

8:20 And the second reason why we had conviction,

8:23 we constantly heard that creators feel a burnout from sort of feeling

8:32 pressure to record multiple videos a day for socials with their own face.

8:38 Mr.

8:38 Beast, he spoke very openly about that.

8:41 But that's I think that that has been a primary

8:44 challenge for the whole industry over last four or five years.

8:47 And then what was surprising to me is that advertisers have the same problem.

8:52 Most of the advertisers talk about like maybe mid-market brands,

8:56 they can be spending hundreds of millions of dollars

8:59 on marketing and they don't have any production team.

9:03 So you chose the right part of the market.

9:04 This is what I'm hearing.

9:05 So I feel like for every entrepreneur who's watching,

9:08 uh when you see a big opportunity in the market,

9:10 you also have to spot who's paying the most.

9:13 Not just go after each user, right?

9:15 Absolutely.

9:16 We live in a very interesting um era where

9:20 all the powerful companies try to give AI to everyone.

9:25 Literally, Meta, XAI, Google, Microsoft, OpenAI,

9:32 Anthropic, ByteDance, and many, many more.

9:35 Think each of those companies want to give a yacht to all its customers really.

9:39 That's why startups have to have more nuanced view

9:43 of the world and have to have more nuanced set of customers.

9:48 And I think um startups today are sort of incentivized

9:53 to stay cash flow positive and build real business from day zero.

9:58 This is what I see across Higgsfield and other top application AI companies.

10:04 So, I think this also creates a very

10:06 interesting dynamic that the target audience should be

10:10 maybe tens of millions of users who are

10:12 willing to spend hopefully couple thousand dollars a month.

10:17 So, this is not for everyone,

10:19 but the delivered value should be so strong so the product

10:24 should be so good so that it kind of sells itself.

10:27 I love that and I love that you have a concrete number, $2,000.

10:31 Yeah, $2,000.

10:33 I'm not sure like with Higgsfield, for example,

10:35 this is the core metric which we are tracking.

10:38 Like how much of the value we believe we provide,

10:43 which is more like through the user interviews,

10:46 but also how much we charge users annually.

10:51 So, this is one key metric and we

10:52 are not chasing just monthly active users, for example.

10:56 Cuz the monthly active users number can be inflated through some viral effect.

11:00 Monthly active user doesn't really speak to the frequency

11:03 of the usage and the value delivered.

11:06 So, that's why for us really daily active users and average ACV,

11:11 average contract value, those two metrics are the most important ones.

11:14 One of the reasons I was so excited to sit down with Alex

11:17 is that our team has actually been using Higgsfield for a while now.

11:21 My producers and editors absolutely love that all

11:25 the top AI models are in one place.

11:27 Man and bananas, seed ants, clean veal, Sora.

11:30 And I love that they don't need 10 different subscriptions.

11:33 And it's kind of incredible.

11:34 Alex just told us that last year they were

11:37 shipping a new product release 6 days a week.

11:40 And now everyone knows them, but they haven't slowed down.

11:43 They keep launching new features.

11:44 And one of the latest ones is Sora 2.0.

11:47 Sora 2.0 is Hex Fit's own image model,

11:50 and it's not like anything else out there.

11:53 Most AI image generations, you type a prompt, you get something that looks fine.

11:58 Sora was built specifically for creative work, fashion, editorial, content.

12:03 It actually understands aesthetics.

12:04 You give it a reference photo, and it doesn't just copy it.

12:07 It reads the lighting, the grain, the mood,

12:09 the era, like a creative director would.

12:12 There are three models.

12:13 Sora, that's the core model.

12:15 You prompt, you get a beautiful image with real aesthetic awareness.

12:19 Sora reference, you upload a reference and it

12:21 generates new images that match the vibe, not just the composition.

12:25 Same visual DNA, different shots.

12:28 And Sora ID, you upload 10 or more photos of yourself,

12:32 it learns your face structure, skin tone,

12:35 expressions, then it generates you in any style.

12:37 Y2K, editorial, film photography, Polaroid, 20 different presets at launch.

12:43 And here is what actually got me.

12:45 You can specify the camera medium.

12:47 Say, shot on Kodak Portra, or disposable camera,

12:51 and it changes the grain, the color science, everything.

12:53 It doesn't slap on a filter, it actually shifts the entire feel of the image.

12:58 And the same thing works with color.

13:00 They just added hex colors, so you can pull the exact palette from any

13:03 photo and apply it straight to your generations.

13:06 If you want to try Sora 2.0, I'll leave the link in the description.

13:10 And now, let's get back to Alex.

13:12 Can you give advice to people who are watching who haven't started yet,

13:16 but they haven't started because they think

13:19 a large company is going to take over?

13:20 How should they think about their defensibility?

13:23 I think each company can really keep

13:25 their focus on maybe two or three top priorities.

13:28 Interestingly enough,

13:29 people like to say about Anthropic that their major success

13:34 from MCP and Claude Cods actually was not like a top-down, but really bottom-up.

13:40 And it like Claude Cod's success was not sort of planned.

13:44 And I think it's true that like these large companies,

13:47 they definitely can benefit a lot

13:49 from applying top-down approach from two to three

13:53 initiatives and really consolidating all the resources

13:57 to make the most progress there.

13:59 I just think it's the next industrial revolution.

14:01 It's probably more powerful than the internet.

14:03 So, the number of products and ideas to be built,

14:06 I think just outweighs uh uh number

14:10 of ideas which OpenAI or Anthropic can push internally.

14:14 That's why I would encourage builders to build.

14:17 Especially today when like quite small team

14:19 of maybe 10 people can build like high-scale products.

14:23 Do you think there is that we have a certain gap of in time when we can build?

14:27 So, for example, I've been hearing a lot in social media that we

14:29 only have 2 years to build something new because then we're going to have

14:33 some companies that reach AGI and it's going to be impossible to find

14:38 a gap in the market because those companies are going to be filling those gaps.

14:41 This is a good question.

14:42 We definitely make um tremendous progress as an industry

14:47 to automating uh work in digital worlds.

14:52 And for sure, maybe next decade,

14:55 there are going to be a lot of applications of AI in physical worlds.

14:58 It's difficult to forecast how much progress we all are going to make there,

15:04 but this decade is definitely the era

15:07 of digital economy completely changing with with AI.

15:12 That's for sure.

15:13 I really don't want to believe in the future when there are going to be

15:17 maybe three labs who have the best

15:19 models and these models controlling all the worlds.

15:21 This could happen.

15:23 That would be very difficult future.

15:24 So, I would I try to stay optimistic and encourage everyone

15:28 to stay optimistic and really focus on building and delivering value.

15:32 Like, for example, um today I just want to give you a very concrete example.

15:37 So, I recently spoke to a very large,

15:42 very, very large like property management company,

15:46 which actually uses Higgsfield to to sort of advertise their buildings,

15:50 their uh apartments, and so on.

15:53 Like, no one is building for this industry.

15:56 Like, in this industry, there is a very specific um workflow of a customer.

16:02 Like, customer needs to learn about about the property,

16:07 then they need to go to the website and get all the details,

16:10 then they need to call, then they need to show up,

16:12 then they leave deposit, and the whole customer journey.

16:15 No one is actually building solution specifically for this industry

16:20 to like cover this journey end-to-end with agents.

16:24 And the reason why agents are going to deliver a lot of value

16:27 in this specific business is that uh customers who want to, maybe,

16:32 let's say, rent apartment, especially in certain price points,

16:36 they want to make a decision rather quickly.

16:38 So, every day of delay, every day of just moving from one stage to another,

16:43 is just is just lost revenue.

16:46 So, and this business owner just said to me

16:49 that no one is building for their industry.

16:51 And And I'm confident there are many more examples like that.

16:54 Yeah, so riches are in the niches, as as they say.

16:57 From your experience, when you pitched VCs with another AI idea,

17:02 what makes a pitch stand out these days?

17:05 I think today, um there is definitely fear that OpenAI, Anthropic,

17:10 and other labs are going to just uh be uh very acquisitive

17:15 and uh just trying to expand

17:17 their product offering to multiple different verticals.

17:20 Pretty much every week there is cloud for X launched and stocks go down.

17:25 That definitely happens and that creates a lot of fear.

17:28 And I would just say that the core inside for me personally was that most

17:33 of these hot and the hyped AI companies they are actually cash flow positive.

17:40 Like maybe it is a wrong mindset to go and raise venture capital today.

17:48 I think there is plenty of pre-seed capital available today.

17:52 But I'm not sure every everyone needs like to raise series A, B, C, D and so on.

17:57 How much revenue did you have when you raised your first round?

18:00 For me with Kickstart AI it was probably

18:04 easier cuz I had previous exits and we basically

18:07 raised $16 million without having any revenue just

18:13 with maybe having like million users for our mobile app.

18:16 But this is not exactly the way how I would recommend to build today.

18:21 I would recommend to focus on bringing like

18:24 the first dollar by day 30 of product development

18:29 and maybe 1 million ARR by day 90

18:32 and then decide if someone needs VC funding or doesn't.

18:36 I mean a lot of businesses can really scale

18:39 to tens of millions of dollars today profitably with AI.

18:43 And for such businesses there is no need to attract VC funding.

18:46 I can give you very simple example.

18:47 So there are so many websites which just allowed

18:51 to make professional photo shoot like for basically for for passport.

18:55 Many of them make tens of millions of dollars.

18:57 None of them are going to be Yeah,

18:58 none of them are going to be venture capital backed business.

19:02 Well, and you said something $1 million by day 90.

19:05 ARR meaning like 80K a month.

19:07 80 80K a month in 3 months that's a lot.

19:11 And so the the playbook to achieve that is basically generate ads

19:14 and launch them and test whether

19:16 whether they're landing with your target audience.

19:18 Paid ads are very difficult today, I think.

19:20 A lot of distribution come through

19:21 organic social media and creator integrations.

19:24 And just make sure that by day 30, uh there is monetization in place,

19:31 and then there is a way to constantly grow to revenue to, let's say,

19:36 1 uh million ARR by day 90.

19:38 Many successful uh companies scale very quickly today.

19:42 Just different verticals have different capacity.

19:45 Some In some verticals, the ceiling could be just 50 million.

19:50 In other vertical, 1 billion.

19:52 In other verticals, like 100 billion.

19:54 Any tips on landing first customers in the first 30 days?

19:58 Initially, especially last year,

19:59 Twitter has been the social media where the distribution starts from.

20:06 It starts from like small communities, then it goes to AI news pages on X,

20:10 then from AI news pages on X,

20:12 it goes to Instagram news pages, then from Instagram news pages to creators,

20:18 then it goes to Telegram and like other social media.

20:21 That's what we have seen with Higgsfield and with many other products as well,

20:25 that they went through the same sort of journey

20:28 of popularity and news through various social media.

20:31 But it all originated on X.

20:33 I think now it's being kind of changed.

20:36 Today, a lot of hype is like a lot of companies,

20:40 they sort of try to use X to boost their product.

20:44 Uh sort of signal-to-noise ratio just drops.

20:48 Twitter becomes less relevant,

20:50 but still it's it's the main place for new AI products launch.

20:54 That's awesome.

20:54 I'm still trying to crack the the X strategy.

20:57 I feel like if you add a word breaking

21:00 or just in to whatever you're posting in the beginning, it should be in caps.

21:04 Like then then it will to perform.

21:06 then it's some something should be like claud, cooked.

21:09 Yeah, yeah, yeah.

21:09 It's like RIP, like something like that.

21:11 Yeah, just wiped this out of the market.

21:14 Yeah, it has to be very sensational next.

21:16 But you're so right.

21:18 I've heard so many and I know a lot

21:20 of creators who built their whole like email newsletter,

21:23 1 million subscribers just off viral X uh posts.

21:26 Yeah.

21:27 That's amazing.

21:27 I love this life hack.

21:28 Thank you so much.

21:29 Although this has been the primary life hack of the 25

21:33 and I do believe that's the media evolves itself as well.

21:36 So 26 could be different.

21:38 Well, I would see LinkedIn on the rise, though.

21:41 [laughter] Maybe LinkedIn.

21:41 Maybe LinkedIn.

21:42 You had a previous company.

21:42 You sold it for 166 million.

21:46 Were there any key learnings from that business or mistakes

21:51 that you made that you will never repeat in this one?

21:54 It it's it's like never say never, but one of the key learnings for me

21:58 and the key takeaways was to embrace meritocracy, sort of.

22:04 Like I'm [clears throat] 30 and I feel sometimes

22:07 that I am quite old for this new era of AI.

22:12 Like a lot of new ideas at in Hicks will

22:15 today come from these kind of fresh grads, maybe 23, 25,

22:20 who sort of maybe never worked in a large company,

22:23 who are doing like freelancing with some web coding tools,

22:26 who are doing web coding before the term web coding, basically.

22:30 And uh they they just think differently and I

22:33 think that's sort of maybe the right mindset.

22:35 So traditionally in any like corporation,

22:38 those people would be just simply no one would just simply listen to them.

22:42 So and the same applies to the creative role.

22:45 So there is definitely some resistance from people who especially build like,

22:51 let's say, like large Hollywood projects,

22:54 that's all AI is dangerous, it's not authentic.

22:58 And it's in the same time it's really exciting that for many,

23:01 many people, young people AI becomes social elevator.

23:05 And I sort of strongly relate to that personally cuz

23:08 for me I had to do a lot of competitive programming,

23:12 you know, like who solves more problem within like 5 hours,

23:15 you know, like and everyone in the world competes.

23:17 So, this was social elevator in 2010 maybe.

23:20 And this applies both to uh creative and to software engineering as well.

23:25 I love how you said that AI is a social elevator cuz I feel like

23:28 social media was the social elevator for me and now is the era of AI.

23:32 I think you mentioned that video models could be a path

23:36 to AGI and that you're also building a world model.

23:39 Can you talk to me about that?

23:41 And for everyone who's watching, just wanted to explain I was just in Davos

23:44 and everyone was talking about LLMs having a ceiling because basically

23:50 just describing our world with words is something that we're

23:53 used to and there's a lot of information on the internet,

23:55 but understanding the physics is the next level.

23:57 And once we understand the physics,

23:59 then we're going to have robots walking around

24:01 our house and doing chores if I'm explaining this correctly.

24:04 Absolutely.

24:04 I think Demis from Google and Elon from xAI, they started this narrative.

24:11 And definitely they are top influencers in the space,

24:14 that's why now the narrative goes to message to everyone.

24:19 It's still unclear if that's sort of the path to AGI,

24:24 although that's definitely a path to advanced robotic systems.

24:28 Like I think Elon proved to the whole world

24:30 that self-driving cars can work really well through just cameras.

24:35 And I think the same logic is going to apply to more advanced robots as well.

24:40 That's why developing perception and visual understanding

24:44 is critical for next wave of robotics.

24:47 And it's a top priority for a lot of research labs as it's the next frontier.

24:51 And there is no other way

24:53 to improve video generation without visual understanding.

24:56 Roughly it takes around I think people like to say

25:00 that in 1 minute we can read 200 words.

25:04 1 minute of the video e can be described with maybe 10 60,000 words.

25:11 There is just so much going on.

25:13 If you and I were having coffee after this episode,

25:16 I'd certainly pull out my phone and say, "Look what I tried this week.

25:20 It changed how my tea works." This is what I do all the time.

25:23 To share these kinds of things that don't fit into the podcast,

25:27 I started my own newsletter.

25:28 Every week I write about AI tools, strategies,

25:31 and experiments I'm running in my own business with real numbers,

25:34 real results, templates that you can use, and also honest mistakes.

25:38 If you want to be in the loop, the link is waiting for you in the description.

25:42 So, where do you see yourself in 2 years?

25:44 Are you still working on videos or because I cuz I saw Menlo Ventures announce

25:48 their investment in you and they they said

25:50 that Hicks' field is building the next world model.

25:52 Do you feel like your focus is going to shift

25:54 to that or you still going to stick to the marketing with video?

25:58 I think that what differentiates us from many other is we

26:02 are from day zero we are focused specifically on short-form content.

26:06 And I do think that world model is going

26:08 to change the way how social media content is made.

26:12 So, for example, next decade is going to be the era of interactive media.

26:17 Uh basically when games and videos are sort of blurred in like

26:20 one experience where like it's kind of choose your own adventure.

26:25 So, a lot of marketing is going to go this way,

26:27 especially kind of premium marketing and customer loyalty programs.

26:31 I think this decade is all about

26:33 supercharging creators and marketing with those models.

26:37 You said you're seeing customers with marketing

26:40 budget over a hundred million dollars, 90% of their ads are AI generated.

26:45 As a creator whose 90% of my revenue is from large

26:48 corporations through from their marketing budgets, should I be afraid?

26:53 This is a good question and um this is definitely

26:55 where we should make sure that video AI can help personalities.

27:01 Like what's I would love to see is that creators like you, Mr.

27:06 Beast and so on, who are sort of AI native,

27:09 start to make like more channels and just expand

27:12 their media presence and be like the whole media empire.

27:17 So like the next media empire is going to be built maybe with like 300 people,

27:20 500 people and be worth like $10 billion.

27:23 So that's on the one side.

27:25 On the other side, what I see personally is that essentially

27:31 this high-scale AI content creation comes

27:36 after maybe platforms like TikTok marketplace, frankly.

27:41 So in the past those brands they could just hire sort of even programmatically

27:46 thousands of creators through TikTok marketplace just

27:50 to do kind of these templateized videos.

27:54 Like I use this product, it's so good, go buy that.

27:58 So like this entry-level marketing definitely gets democratized.

28:04 Although in my opinion, as we are seeing a lot of AI slop on social media and so

28:10 on the genuine connection and and understanding

28:14 of audience now matter more than ever.

28:17 So there are going to be just a lot

28:19 of average and above average contents on the socials.

28:24 And I think this is happening one way or another and just

28:29 deep understanding of the audience and authentic approach matter more than ever.

28:34 Okay, so you think social media a ladder, social ladder is not dead.

28:39 Definitely not.

28:40 I just think that authenticity is going to matter a lot.

28:45 And and the way how I think about that is

28:48 if let's say top creators now can make their own shows,

28:53 their own movies with AI.

28:56 And creators can drive a lot of traffic.

28:59 That's going to affect like streaming business a lot, I think.

29:02 So, I think the revolution is going to come at every level.

29:06 Although, I think clearly people who already understand their audience,

29:10 who have authentic approach,

29:12 those people are definitely going to be the winners.

29:15 Okay.

29:15 My last question.

29:16 For someone who's watching this still has fear.

29:20 Like this is moving so fast.

29:21 I don't know how I can start.

29:22 I started something today, it's outdated by tomorrow.

29:26 Can you give them one piece of advice so they can start?

29:29 First, I think I would start from a position that large companies,

29:35 Amazon, Microsoft, Google, OpenAI, Anthropic,

29:39 think they're all relatively well positioned to be winners in AI

29:45 era as they simply control data centers, GPUs, and so on.

29:50 But I'm not sure there is much

29:51 insurance policy for everyone else regardless, right?

29:55 Buy their stocks, yeah?

29:56 I don't know.

29:58 [laughter] Yeah.

29:58 You just buy their stocks.

29:59 Yeah, yeah.

29:59 Buying their stocks is a good idea.

30:02 But that's I think I'm not sure we can share that.

30:04 advice.

30:04 It's just personal chat.

30:06 Yeah, I do think that there is a a lot of value in these companies.

30:10 But I mean for for lots of others, right?

30:12 I mean we see the sell-off across SaaS.

30:14 We see the sell-off across cybersecurity.

30:16 And then there is an ultimate question.

30:18 If I want to like basically depend on someone else to figure out

30:23 AI strategy or I want to embrace AI myself and benefit the most, right?

30:28 I think that's a personal question for everyone.

30:31 And as we all know that these technology revolutions,

30:35 they're both fair and and unfair.

30:37 I think in long term every technology revolution is fair and GDP per

30:42 capita and quality of life goes up on the horizon of 10 years.

30:47 On the horizon of like 3 years, I think it's extremely unfair cuz market just

30:53 loves to pour money into companies which are winning.

30:56 And companies which are like not winning, they immediately go down.

31:02 But in the short term,

31:03 I think that it's going to be fair cuz people um both on the creative side,

31:08 marketing side, engineering side, those who are embracing AI,

31:12 they can propel their careers so quickly.

31:15 In the end of the day, net it's going to be net positive,

31:18 although I think um individually we all just need

31:22 to think how I can personally benefit the most from AI,

31:27 how I can become more efficient with the AI,

31:29 how the value of my skill set can actually grow with the AI.

31:33 And um this always require using those um agents and various

31:40 AI models several hours a day to to build this intuition.

31:44 Let's give them a home task.

31:46 What should they do right after watching this video?

31:49 Which tool should they start using and how?

31:51 For me personally, I'm an immigrant, so you know,

31:55 it just takes quite a bit of effort to come with a logical linear storyline.

32:02 All three mini became my coach, really.

32:05 This was the first aha moment for me.

32:08 The second aha moment was around Gemini 3 Pro model.

32:11 So, I felt that my economic productivity really depends

32:16 on like how much I use Gemini 3 model.

32:18 These capabilities of the model which can process voice, which can make image,

32:24 but which has also deep reasoning capabilities and deep research,

32:28 this was mind-blowing to me.

32:29 So, that's why I feel that my just economic throughputs

32:33 really depend on how much I use Gemini 3 today.

32:35 Do you use it to make decisions about your company, like strategic operations?

32:39 I really feel that communication with humans

32:45 becomes way more important skill set for me.

32:50 Cuz a lot of other decisions,

32:53 I'm sure Gemini 3 and Claude are going to be better than myself.

32:57 AI is not is not yet good in communication.

33:01 So, that's where I think I try to put a lot of my personal emphasis.

33:05 Mhm.

33:05 Think other than that, um a lot of process can actually be built with AI.

33:10 So, um just human-to-human communication and sort

33:14 of conflicts resolution and maybe goal set goal setting.

33:18 Yeah.

33:18 And like number-driven goal setting really is where I

33:21 put a lot of my time, my personal time.

33:23 For everything else, I'm trying to evolve Gemini as much as possible.

33:26 But also use Claude for Excel, Claude for X,

33:30 like for example, Claude for cybersecurity,

33:33 as it really increases the productivity.

33:35 Alex, thank you so much.

33:36 It was amazing.

33:37 I'm looking forward to reading your comments.

33:38 What was your key takeaway and what you're going to do right after this video?

33:42 Thank you so much.

33:43 Thank you.