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Swan AI hit $1M ARR in 9 weeks with just 3 founders · AI for Founders with Ryan Estes

• 0:00
  Welcome back to AI for Founders. I'm Ryan Estes.
• 0:02
  Today's guest is Amos Barr Joseph Co founder and CEO of
• 0:06
  Swan AI, what he calls lovable for go to market.
• 0:10
  Imagine this, a three person team, no sales reps, no paid
• 0:14
  marketing, scaling to 1,000,000 ARR in just nine weeks, and now
• 0:18
  serving over 200 customers. Amos is pioneering what he calls
• 0:22
  the autonomous business, where AI agents supercharge your team,
• 0:26
  turning every employee and into a 100X version of themselves.
• 0:30
  From identifying anonymous website visitors to writing
• 0:33
  personalized outreach and running nuanced GTM workflows
• 0:37
  right inside Slack, Swan is flipping the script on how
• 0:40
  startups scale. We're going to unpack how Amos
• 0:43
  built a 1.5 million monthly pipeline solo while storytelling
• 0:48
  became his zone of genius, and how he's challenging the entire
• 0:51
  startup playbook with contrarian high risk, high reward growth
• 0:55
  strategies. This is going to be fun, it's
• 0:58
  going to be big, and it's going to be insightful.
• 1:00
  So let's dive in. But first, some business.
• 1:02
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• 2:51
  Shine stars computer life AIAI take the flight in the glow with
• 3:07
  me. All right, Amos, welcome to the.
• 3:12
  Show, Thank you very much, Ryan. I'm excited to be here.
• 3:17
  Yeah, absolutely. So excited to talk to you
• 3:18
  because your product is so cool. So if you would briefly describe
• 3:23
  Swan and who you who you work with?
• 3:26
  Yeah. So we're building Lovable for
• 3:31
  GTM. Basically it's an AI go to
• 3:35
  market engineer. It's a technical resource that
• 3:38
  helps sales and marketing teams turn any go to market idea into
• 3:44
  an agentic workflow in seconds from prompt to pipeline.
• 3:49
  So they could scale revenue with intelligence, not headcount and
• 3:53
  really iterate at their go to market at the speed of thought.
• 3:58
  And you know, we're going to talk about it today, Ryan.
• 4:00
  We're just a small team of three people and already scaling.
• 4:04
  We have 200 customers, most of them are startups that are, you
• 4:09
  know, looking to just move faster with their existing, you
• 4:13
  know, sales team. And we're seeing some incredible
• 4:17
  things with AI Ages and I'm excited to talk about it today.
• 4:20
  Yeah, absolutely. So give us kind of step by step
• 4:23
  what Swan AI is doing for your customers.
• 4:28
  Yeah. So basically Swan lives within
• 4:31
  Slack. It's, it's kind of like a Co
• 4:34
  worker that you add to your Slack workspace and you can just
• 4:37
  chat with it there and you can just talk to Swan and explain to
• 4:43
  your bottlenecks basically and the challenges that you have
• 4:46
  right now and how you want to solve them.
• 4:49
  And so one can turn that idea into an agentic workflow right
• 4:53
  in second. So our hottest use case actually
• 4:57
  is reaching out to 1st party intent, basically to these
• 5:02
  anonymous visitors that come to your website but don't convert
• 5:07
  and you don't know who they are. It's likely 95% of them, but
• 5:10
  it's very complicated to build all these workflows to really
• 5:14
  engage them in very nuanced and intelligent way.
• 5:17
  So you can just describe the swan, how do you want to do
• 5:19
  that? And every time you have an idea,
• 5:21
  you just still swan. Look, this is how we want to do
• 5:23
  it. Go about that.
• 5:23
  And if it's in our pipeline, just notify the owner and give
• 5:27
  them like a quick brief about, you know, what's been the latest
• 5:30
  in the previous engagements. If it's a closed loss returning
• 5:34
  swan, actually I want you to dig up all the engagement and if
• 5:39
  there's a good reason to reach out, actually write a
• 5:41
  personalized message and reach out.
• 5:44
  Make sure that the contact is still there, right?
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  You can just tell it and it would just perform all these
• 5:49
  actions for you. And So what you start building
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  out is these very nuanced and tailored scenarios for every
• 5:58
  different use case. And instead of building spam
• 6:00
  cannons, you can just, you know, turn your existing team into
• 6:04
  super sellers and make sure they focus on the best opportunities
• 6:09
  out there. And both spend their time like
• 6:11
  on the mundane and, you know, boring stuff basically.
• 6:17
  Incredible. And that's what I know Swan for,
• 6:19
  but it sounds like you've got additional workflows, a
• 6:22
  different additional products coming down the pipeline.
• 6:24
  Talk about some of those. Yeah.
• 6:26
  So lovable for GTM is really about removing all the
• 6:32
  complexity that go to market teams have, you know, working
• 6:36
  with their existing tech stack. So for the last 20 years, every
• 6:40
  time came and you, you know, go to market tech vendor promised
• 6:45
  more human interactions, but eventually led to more system
• 6:48
  interactions. And you know, we've seen that
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  with sales floors and you know, the CRMS and then sales
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  automations with sales loft and outreach and these companies,
• 6:58
  etcetera. Each, you know, incremental
• 7:01
  improvement on the tech stack actually brought non incremental
• 7:05
  work for the sellers to actually spend their time working with
• 7:09
  these systems. But then finally comes Swan to
• 7:14
  remove all that technical complexity so that go to market
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  teams don't need to bend around their tech stack.
• 7:20
  There's tech stack and finally bend around their business.
• 7:23
  So Swan is deeply connected to your CRM.
• 7:26
  It can read and write and perform like complicated actions
• 7:29
  within your CRM. It it has a wealth of B to B
• 7:32
  data sources that it can use independently that we partner
• 7:36
  with. So it can find and enrich
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  contacts and you know, enrich accounts, research online,
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  monitor for intense signals, all these things.
• 7:45
  It can write personalized messagings.
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  It can initiate and create personalized sequences on
• 7:51
  LinkedIn and e-mail and send them on your behalf.
• 7:54
  And it can send Slack messages, alerts and approvals for the
• 7:59
  team so that you can keep a human in the loop flows for
• 8:03
  specific, you know, emotions that you want to run.
• 8:06
  And so you take all that wealth of capabilities and you just
• 8:09
  package it into solving a challenge that you have.
• 8:12
  It could be that, you know, no shows, for example.
• 8:15
  Yeah, I have a lot of no shows in my company.
• 8:17
  Some book it, someone books a demo, but people don't show up.
• 8:20
  OK, Talk to Swan. Tell it what you want to do.
• 8:22
  You can tell Swan, you know what if it's a qualified lead, find
• 8:26
  all the buying committee for within that account.
• 8:28
  And if there's a no show, send actually an e-mail to all the
• 8:31
  buying committees. Tell them about the interest
• 8:33
  that they've shown. Make it personalized and suggest
• 8:35
  that you know, let's rearrange a call.
• 8:38
  But if it's a demo booked, I want you to research that
• 8:41
  account and to send a brief to the person that is meeting with
• 8:44
  that demo 5 minutes before the call.
• 8:47
  So everything basically can becomes accessible to you and
• 8:50
  you can start iterating at your go to market at the speed of
• 8:53
  thought because you don't have all that technical complexity
• 8:56
  that stands between you and your ideas.
• 9:01
  Incredible. And I want to talk about go to
• 9:03
  market for Swan. Now something about me.
• 9:08
  I only say dude when I'm serious, and I only say bro when
• 9:11
  I'm impressed. So I want to say this dude bro.
• 9:16
  Hey, OK, yeah, I'm listening. I'm all ears.
• 9:19
  You you hit. Your one million annual run rate
• 9:24
  in nine weeks, how did you do it?
• 9:27
  Yeah. So it's not my first rodeo
• 9:31
  basically, OK. And I've built on scale 2B to B
• 9:35
  startups before and you know, took them from zero to 1 and
• 9:40
  scaled them all based on kind of the Unicorn growth at all cost
• 9:43
  playbook where you, you know, you raise a big fat seed round
• 9:48
  before you get to product market fed.
• 9:49
  Then you scale to 3040 people before you got to your first
• 9:53
  $1,000,000 in revenue. And then from there on, instead
• 9:57
  of generating value, you inflate the story and the Tam and the
• 10:01
  vision to get to the next round. That's how you kind of like pass
• 10:04
  the torch. And with Swan, I felt like I had
• 10:08
  enough with that playbook. It wasn't for me, you know, all
• 10:11
  of a sudden in, in, in the previous runs and I thought to
• 10:15
  myself, how can we do things differently?
• 10:17
  And more importantly now with the AI agents, it's must, you
• 10:22
  know, the, the playbook for scaling a company must have been
• 10:25
  completely changed, right? It, it couldn't be the same.
• 10:28
  And so when we started Swan, I've partnered with my two Co
• 10:32
  founders who were with me in my previous companies and we told
• 10:36
  ourselves, you know what, we're going to scale with
• 10:38
  intelligence, not with head cap. We're going to try to build a
• 10:41
  different company that is really designed around human AI
• 10:45
  collaboration rather than human to human coordination.
• 10:49
  So we're not scaling a monster of manpower.
• 10:53
  What we're trying to do basically is to build the first
• 10:56
  autonomous business, right? And an autonomous business is
• 11:01
  actually a business has autonomous agents and autonomous
• 11:04
  employees basically. And each employee has an army of
• 11:10
  agents around them to turn the employee into the 100X version
• 11:15
  of themselves. And so how we grew so fast and
• 11:20
  how I generate as a single person, you know, and go to
• 11:24
  market team, you know, a $1.5 million pipeline every month and
• 11:31
  you know, just closing more than 300 KRR in, in a single month,
• 11:36
  just my, by myself with 0 marketing spend and 0 SDRS.
• 11:41
  It's because we're really designed to correct that human
• 11:44
  AI collaboration framework, but not by replacing ourselves or
• 11:48
  automating our work, Ryan. It's really about trying to find
• 11:53
  where is my zone of genius and how can we build an army of
• 11:57
  agents to empower me so I can sit within that zone of genius
• 12:01
  100% of my time, that area where my passion and skills intersect
• 12:06
  to create disproportionate value and where we cracked that
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  finally when we did that, that's how we scaled so fast.
• 12:12
  And I'm happy to dive deep into what does that really mean and
• 12:16
  how do we really build like a genetic system that can help us,
• 12:19
  you know, and one person go to market team move at enterprise
• 12:22
  scale, but at start up speed basically.
• 12:26
  Yeah, maybe start us with what is your specific realm of
• 12:30
  genius. Yeah, so my zone of Jesus and I
• 12:37
  discovered it, I think is like just in this company for the
• 12:42
  first time in my life because I had the opportunity to actually,
• 12:45
  you know, explore that territory finally with the freedom and
• 12:48
  autonomy to do it. And it's basically storytelling
• 12:52
  on social media, OK. I love storytelling at large.
• 12:56
  And I think that's like something that I really enjoy
• 12:58
  thinking about a narrative and how can people can emotionally
• 13:02
  relate to that narrative and what makes a strong narrative
• 13:05
  and a viral narrative. That was always something of
• 13:07
  interest to me. But when that hit social media,
• 13:11
  what we realized is that from the under the go to market hat,
• 13:16
  that area can create disproportionate value for the
• 13:19
  company. And I started posting on
• 13:22
  LinkedIn and that started, you know, to create engagement and
• 13:25
  to create excitement from the the audience.
• 13:28
  And we realized that if we build an agentic system around that
• 13:33
  motion of storytelling on LinkedIn, then we can create
• 13:38
  disproportionate value in terms of pipeline generation and
• 13:43
  revenue creation. Credible.
• 13:47
  Yeah. And you seem to have like this
• 13:49
  natural talent, I can already tell.
• 13:51
  And it's it's gone to create a gigantic LinkedIn presence.
• 13:55
  And I mean, you have a huge following there, but it's
• 13:59
  interesting to hear that like it took a while to find your zone
• 14:03
  of genius. You know, now that you feel like
• 14:05
  you're in the pocket and you're doing well.
• 14:08
  This show has an audience of about 25,000 founders and CE OS
• 14:12
  interested in building with AI there.
• 14:15
  But a step before that is maybe they don't know how to define
• 14:20
  their zone of genius. Maybe they don't know what it
• 14:22
  is. Do you?
• 14:22
  Is there a process that that this audience can take to to
• 14:27
  kind of discover for themselves, discover what their zone of
• 14:30
  genius might be? Yeah, So you can, you cannot
• 14:34
  talk about zone of genius without AI in it.
• 14:37
  And I'll tell you why. And we going to connect these
• 14:38
  two questions like how do I use AI in my data?
• 14:41
  Then what's my zone of genius? These questions are kind of
• 14:45
  intertwined. And the the reason for it is
• 14:49
  because it all starts with two things.
• 14:52
  One is identifying bottlenecks. OK, nothing has changed in that
• 14:58
  sense. So it all starts from
• 14:59
  identifying bottlenecks. You cannot understand your zone
• 15:01
  of genius without starting to ask yourself, where is my
• 15:04
  bottlenecks? Because you spent your time and
• 15:07
  your day-to-day try to create value.
• 15:10
  And then there's these areas that you feel like create more
• 15:14
  friction, right? They have a lot of friction in
• 15:17
  them. And these areas are areas that
• 15:20
  have very much outside of your zone of genius.
• 15:24
  OK. And finally, we have an
• 15:27
  opportunity to actually try to solve these friction points with
• 15:32
  AI and automation, OK. And so it starts becoming an
• 15:36
  iterative process. You identify your bottlenecks,
• 15:40
  then you start supplying AI and automation to solve them.
• 15:43
  But you don't do it in the context of automating your work.
• 15:48
  You're doing it in the process of finding your zone of genius.
• 15:53
  So what does that mean, right? I think that's a fundamental
• 15:56
  shift that people need to take is that instead of looking at
• 16:00
  processes and asking themselves, how should we automate this
• 16:03
  process? Can AI replace this process?
• 16:05
  What we should start asking is, OK, there's a human being here.
• 16:09
  How can we 100 X that human being?
• 16:12
  What will happen if AI will replace that process?
• 16:15
  What will the human do in that case?
• 16:18
  How would that affect their job, their day-to-day?
• 16:20
  And when we start looking, asking these questions, our
• 16:23
  entire point of view on AI implementation changes from
• 16:28
  minor efficiency gains to looking at 100 X productivity
• 16:33
  improvements. And so when we asked ourselves,
• 16:36
  it didn't, it wasn't like, OK, storytelling was the B area and
• 16:42
  that unveiled all the agents that we need to build.
• 16:44
  It didn't happen in one day. It was an iterative process of
• 16:48
  of asking ourselves, OK, we're spending a lot of time on
• 16:52
  actually writing these posts. So how can we use AI agents to
• 16:56
  maybe help with the research process?
• 16:58
  And if they will automate the research process, what will that
• 17:00
  vacate for Amos? What will he be able to do more
• 17:04
  if he had more time? So it's not just getting that
• 17:06
  efficiency gain, it's looking at what opens up when you have that
• 17:11
  data available to me at, you know, 24/7.
• 17:14
  So easy to get it right. And, and you look at the upside
• 17:17
  of that and you can leverage that even more.
• 17:19
  So it's not about automation, it's about leverage.
• 17:23
  And if you look at it from an iterative process, you look at a
• 17:26
  bottleneck, you look at AI and automation, and you ask yourself
• 17:30
  how can we combine these bottlenecks with AI and
• 17:33
  automation so that the person will try to grow 100 X and their
• 17:38
  productivity output? Love that.
• 17:42
  You know, the, I think a lot of times people struggle with what
• 17:45
  their zone of genius is because they're not being honest with
• 17:48
  themself of what it really is. And I'm really interested
• 17:53
  honestly in what I'm interested in, if that makes sense.
• 17:56
  Because I could be like, you know, if you ask me if we're
• 18:00
  sitting here, somebody's interviewing me, they asked me.
• 18:01
  I'm like Rev OPS. I'm a sales dog.
• 18:03
  I love closing business, but if I really think about my zone of
• 18:06
  genius, it's like what I really like to do is like right now I'm
• 18:10
  making movie scripts and making little short videos.
• 18:14
  It's like, that's what I love to do.
• 18:16
  Now I tend to believe that if you're falling into like, let's
• 18:19
  call this your zone of genius, then the connections aren't just
• 18:24
  what I'm doing when I'm making a screenplay.
• 18:26
  Rather it spills into everything.
• 18:28
  There's kind of like a an intoxicant, for lack of a better
• 18:31
  word, that happens when you're really diving deep into
• 18:34
  something you're into that pours over into absolute everything
• 18:38
  else. You know, it's let's not even
• 18:40
  say an intoxicant. It's like an enchantment, you
• 18:43
  know. So when when people are thinking
• 18:45
  about my zone, a genius, what is it?
• 18:47
  It's, it's not, it's not RFPs, that's for sure.
• 18:51
  You know, so if you can find ways to your point to reiterate
• 18:55
  what you're saying, you know, use agentic support to take the
• 18:58
  stuff out of the way so that you can actually do what you really
• 19:01
  love. And then that will pour into the
• 19:03
  projects that ultimately are going to drive revenue for your
• 19:06
  company. Now, you and I know startups are
• 19:09
  built in board rooms. They're built in the wild during
• 19:12
  3:00 AM. Bug fixes, botched launches, and
• 19:15
  that one meeting where everything almost fall apart.
• 19:18
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  break moments behind their products, What went wrong, what
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  went right, and what nearly wrecked everything.
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  Hosted by Noah Labhart, Code Story goes past the highlight
• 19:32
  reel and into the honest stuff, Late pivots, brutal bugs, and
• 19:36
  somehow coming out alive with a product people actually love if
• 19:39
  you're in the build. Stage or the scale stage?
• 19:41
  Or the Please let this feature work stage.
• 19:43
  I can relate. This show will speak to your
• 19:46
  soul. Listen to Code Story at
• 19:48
  codestory.co or wherever you get your podcast.
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  Just search Code Story. It'll be right at the top
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  because great startups aren't born, they're forged one hard
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  moment at a time. Code story.co This episode is
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  Actually, Ryan and So what we actually believe it's one that
• 21:24
  the problem is not, you know, the people, the humans that
• 21:27
  don't know what their zone of genius.
• 21:29
  It's actually the system it's the business itself.
• 21:32
  The architecture that traditional companies are built
• 21:35
  around is what we call a cog culture architecture.
• 21:40
  It means that you are designed to just be a cog in the wheel.
• 21:43
  There's a system that is designed to grow regardless of
• 21:47
  what humans are in it, right. That's the system that's that's
• 21:51
  the architecture of the business.
• 21:52
  These are the processes that we actually operate in and that's
• 21:55
  the hierarchy, that's the org chart.
• 21:57
  And it's faceless, right? It doesn't matter which people
• 22:01
  are within that architecture, within that system.
• 22:04
  That's how it should operate. And then you just put as a cloud
• 22:07
  in the wheel, you should be a Rev OPS person and that's the,
• 22:10
  you know, the JD. These are the responsibilities.
• 22:13
  Either you fit in it or you don't.
• 22:15
  And Swan, an autonomous business has autonomous employees.
• 22:20
  What we actually do is we're flipping the script.
• 22:22
  We're asking ourself, we're looking at Ryan.
• 22:24
  We're looking at, OK, Ryan is good at Rev OPS, is good at GTM,
• 22:27
  but it's also is also really good at, you know, content
• 22:30
  creation and writing scripts and screenplays and these short
• 22:34
  clips. So, OK, how can we build a
• 22:36
  system around Ryan that will put Ryan within it's go to zone of
• 22:42
  Genius? Does that make sense for us?
• 22:43
  Does that fit? If so, let's do it.
• 22:45
  If not, maybe we should focus on a different talent.
• 22:48
  But the system is built around a specific person.
• 22:52
  In that sense, we always ask ourselves, who is that talent?
• 22:55
  What would what do they have? Let's try to figure out how
• 22:58
  their zone of genius looks like in an iterative process and
• 23:01
  build a system around them. So the power dynamics and an
• 23:04
  autonomous business are different because the business
• 23:08
  is a system that is designed around their employees, not
• 23:11
  employees that are designed to power that system.
• 23:15
  And so we believe that this is a model that all start-ups will
• 23:18
  adopt eventually and they will need to let go of some control
• 23:22
  in that sense, have autonomous employees.
• 23:25
  But if they crack it, they can create disproportionate value
• 23:28
  from a much smaller team and compete with the incumbents in a
• 23:32
  much better way. Incredible.
• 23:35
  OK, I want to, I want to test this theory.
• 23:37
  I'm, I'm sitting here thinking about the stuff that drives me
• 23:39
  nuts. My inbox is unreal.
• 23:43
  I, I've got probably 4 e-mail addresses that I tend to and try
• 23:46
  and get to inbox 0 immediately. And I've tried a bunch of tools
• 23:50
  to like try and minimize that. But really it just comes down to
• 23:53
  like in in in order for important emails not to be
• 23:57
  missed, I've got to go through all this mucky muck.
• 24:01
  So, you know, if that's my central problem, how would I set
• 24:05
  out about to create automation in in kind of like agentic
• 24:10
  support to kind of put me into the zone of genius I'm looking
• 24:13
  for? Great question.
• 24:14
  So I'll answer it in like very similar example that I actually
• 24:22
  use Swan for, okay, and I use AI for that.
• 24:25
  So I have the same problem, Ryan, but with my LinkedIn
• 24:28
  inbox, okay, with my LinkedIn game, because as you mentioned
• 24:31
  before, I have more than 30,000 followers.
• 24:34
  I get more than 300 connection requests each day and it's very
• 24:39
  intensive. So basically Swan created a
• 24:43
  workflow for me and a gentic workflow that monitors every
• 24:47
  incoming connection request and message that I get and then
• 24:52
  qualifies it and understands what that message is.
• 24:57
  And then I have different scenarios for different
• 25:01
  incoming, you know, people basically and messages.
• 25:05
  So if it's an investor, what do we want to do with if it's an
• 25:08
  investor? So I want to say, you know what,
• 25:09
  if it's an investor, qualify them if they fit into something
• 25:13
  that is interesting to us, start a conversation with them asking
• 25:17
  them about their investment strategy, OK.
• 25:19
  If it's a vendor, of course I don't want to, I don't, I don't
• 25:23
  want to hear it unless I'm looking for specific vendors at
• 25:26
  the moment, right? If it's a lead, OK, so I want
• 25:30
  you to qualify them, right? Research them online, etcetera.
• 25:33
  And if they are actually elites, start a conversation with them
• 25:37
  about AI agents. And what happens Ron, is I flip
• 25:41
  the script from actually thinking to myself, how should I
• 25:44
  reply? How should what should I do into
• 25:46
  only seeing relevant conversations that I want to
• 25:50
  conduct that I want to be involved in at the 1st place.
• 25:52
  So I look in my inbox, it only full, it's full with relevant
• 25:56
  conversation. That's like a very radical
• 25:58
  different than if I wouldn't have that ability to create all
• 26:01
  that incoming workflows with Swan.
• 26:04
  Incredible, I love it autonomous business.
• 26:07
  I never heard of that, but I now I'm obsessed.
• 26:10
  One thing I love about swan is is agentic support in Slack is
• 26:14
  where I already am. That's where I want it.
• 26:16
  So if we have you know, people are coming to the website and
• 26:19
  then it's a I'm able to talk about who they are.
• 26:22
  It can go enrich the data to find out like they're they're
• 26:25
  buying intent and then sends them a message.
• 26:27
  Fantastic get it give me on the phone, I'll close the deal.
• 26:30
  That's exactly where I want to come in, which is brilliant,
• 26:32
  which is to say that this is a very elegant conversion tool.
• 26:37
  Now, a big part of Go to Market though, is traffic.
• 26:41
  How can you help drive traffic to the website?
• 26:44
  What are maybe some hacks or tips or things that you've been
• 26:47
  successful with when you go to Market driving actual attention
• 26:51
  and traffic to the website? Yeah.
• 26:53
  So the $1,000,000 or billion dollar question sometimes could
• 26:57
  be right. That's definitely very
• 26:58
  difficult. I would say that instead of
• 27:01
  giving you a fish, I'll give you a hook.
• 27:05
  OK, So basically my number one rule is that I believe that
• 27:12
  every marketing tactic, the more popular it is, the less
• 27:17
  efficient it is, OK? So you should, you should,
• 27:21
  instead of trying to look for the best practices that are, you
• 27:25
  know, best of breed and everyone knows them, you should actually
• 27:28
  stay away from them, OK, because they are the least efficient
• 27:32
  tactics. And if you are an SMB, if you're
• 27:36
  an enterprise company and you're, you want to be in the
• 27:39
  conventional space and you don't want to take risk and you want
• 27:42
  to spend, you know, $1,000,000 on eyeballs and just get, you
• 27:45
  know, an X amount of predictable way of eyeballs, then you should
• 27:48
  stay at the conventional. But when you're a startup, you
• 27:51
  can't play the conventional game.
• 27:52
  You got to take risks and you got to be contrarian and the
• 27:57
  experiments that you run. And so at Swan, we always try to
• 28:02
  be different and everything that we do, we try to take, you know,
• 28:06
  not the King's Road, right? But we want, we're trying to
• 28:08
  take The Dirty Rd. that no one really wants to take that has a
• 28:12
  lot of warning signs. Don't enter.
• 28:14
  There's a crazy dog that is waiting here or a huge Cliff
• 28:17
  that you could fall from. These are the roads that we're
• 28:20
  actually looking for. And, and, and so I think this
• 28:23
  should be like your mindset when you're looking at marketing and
• 28:27
  growth, always stay away from the Kings Rd.
• 28:30
  Stay away from it. If you're in a start up and if
• 28:33
  you want to be at the Kings Rd. you should understand that
• 28:35
  you're playing an enterprise game and you're set to lose.
• 28:38
  But maybe you want to just get that predictability, get that
• 28:40
  stability for a second. It's OK to do it, but as long as
• 28:44
  you have all these crazy experiments that you run.
• 28:46
  So that's like, first of all, how you should think about
• 28:48
  marketing in my perspective, right?
• 28:50
  You should have like an army of, you know, huge amount of like
• 28:54
  crazy experiments that you're running.
• 28:56
  And I cannot tell you what, what, what are these crazy
• 28:59
  experiments? Because if I would be able to
• 29:01
  tell you that, then a lot of people are probably know that.
• 29:04
  So they're not really crazy experiments.
• 29:06
  Crazy experiments are about a nuanced understanding of your
• 29:10
  value proposition and your buyer and where they live and what
• 29:13
  they're interested at at today. And if you connect that, then
• 29:18
  you can get to very interesting places.
• 29:21
  So we, you know, I do a lot of social content, right?
• 29:25
  But it's because I've corrected something about what are my
• 29:29
  audience is really interested at.
• 29:30
  They want to learn about how to scale with intelligence, not
• 29:33
  with headcount. Today they are obsessing about
• 29:37
  all these small businesses that can generate outsized output and
• 29:42
  they want to get an inside view into these businesses.
• 29:45
  I know that today and I'm selling a tool that can help you
• 29:49
  generate the pipeline, but I talk about the behind the scenes
• 29:53
  of building an autonomous business, right?
• 29:55
  So it's completely far from my value proposition in some way
• 30:00
  to, you know, the way the things that I'm talking about on
• 30:03
  LinkedIn, but I'm able to connect it to my value
• 30:06
  proposition in such a strong way that it generates a lot of
• 30:09
  pipeline in that sense. So my advice to you is just be
• 30:14
  super unconventional. Look at social media as that
• 30:19
  exponent. If then if you can, you know,
• 30:23
  make an experiment work and social media, then you can
• 30:26
  achieve that exponent like that, ultra high ROI basically.
• 30:31
  But there are a lot of other ways to find them in communities
• 30:35
  and other places around the web. So be creative.
• 30:40
  I love that. I love that.
• 30:41
  Maybe it's a little discouraging though, because you're obviously
• 30:44
  like so enthusiastic and an energetic and talented, just a
• 30:48
  born marketer. You know, a lot of the folks
• 30:50
  that are listening to this podcast subscribe to the
• 30:53
  newsletter. They're on more of a technical
• 30:55
  side. They're probably a little bit
• 30:57
  more accustomed to glowing rectangles than to than to face
• 31:02
  to face interactions now. And that might be a perfect
• 31:04
  place for them on, on social media in different ways.
• 31:09
  Like for, for you, It's been unbelievable on LinkedIn.
• 31:12
  For some people, X is like huge for them.
• 31:14
  You know, some people kill it on YouTube.
• 31:16
  You know what, what kind of encouragement or where would,
• 31:19
  where would somebody start? What's a good starting place to
• 31:21
  start to think about running an incredible experiment with their
• 31:25
  marketing? Yeah.
• 31:27
  So I will give it something a little bit tactical, but then
• 31:32
  I'll give you like a big fat strategic advice that is a
• 31:35
  little bit harder to implement. OK.
• 31:37
  So the tactical 1 is that like in my earlier version of the
• 31:45
  marketeer that I was, I was like super analytical, OK.
• 31:49
  I was like trying to think always, OK, who is my persona?
• 31:53
  What is my value proposition? How should we market that value
• 31:58
  proposition to that persona? This is analytical thinking, OK,
• 32:02
  trying to reduce that, you know, buyer journey into arguments
• 32:08
  that you stack one upon the other into a conclusion.
• 32:13
  But the truth is that marketing is an emotional journey.
• 32:18
  Basically, marketing is much more about emotions than value
• 32:22
  propositions. And so you should always, you
• 32:26
  know, think and, and discuss and approach marketing from an
• 32:32
  emotional perspective rather than an analytical perspective.
• 32:35
  In that sense, always try to ask yourselves, what are the
• 32:38
  emotions that I'm inspiring with the buyer, if I'm going to say
• 32:43
  that. And what you ask yourself these
• 32:44
  questions, you can get to much more than just am I conveying
• 32:49
  the value proposition of my product.
• 32:51
  Because no one cares about value propositions and no one cares
• 32:55
  about problems in their day-to-day because they are so
• 32:58
  overwhelmed with so many solutions that the only way to
• 33:02
  capture the attention of someone today is by connecting to an
• 33:06
  emotion that they feel today to a feeling.
• 33:10
  And so that's like the number one advice that I will tell you.
• 33:12
  But from more strategic point of view, I would say that a good
• 33:17
  experiment starts with something deeper actually.
• 33:21
  Like you need to prepare the infrastructure to running these
• 33:24
  experiments. And it's basically a combination
• 33:28
  of two things, right? It's you need to have a strong
• 33:31
  narrative as a company that you're pushing for and you need
• 33:35
  to position yourself as a powerful narrator.
• 33:39
  OK, And I'm going to break these two elements right now.
• 33:43
  What does it mean to create a powerful and viral narrative
• 33:48
  while being a powerful and viral narrator?
• 33:51
  OK, so are you with me at the audience?
• 33:54
  They're listening, you have their attention.
• 33:56
  Let's go, let's go, let's do it. So basically a narrative, a
• 34:02
  strong narrative for a start up. I'm not talking about the
• 34:04
  incumbent, which has a lot of, you know, things to lose.
• 34:07
  And they're more like in the conservative space, when you're
• 34:12
  a start up of the narrative that you basically need to push for
• 34:17
  is what I call a narrative. That is the challenge the
• 34:20
  challenger. What does that mean?
• 34:21
  Challenge the challenger. So you should think about
• 34:24
  everyone in your space is challenging the status quo, OK?
• 34:29
  That's what everyone is doing. And that is boring.
• 34:31
  The buyer always listens to people who try to knock on their
• 34:36
  door and challenging their status quo.
• 34:39
  OK, so the buyer today has that status quo and then everyone is
• 34:43
  screaming at it. You know what?
• 34:44
  You should change that status quo basically.
• 34:47
  But you got to be different. You got to rise above that
• 34:50
  noise, right? So you need to challenge the
• 34:53
  status quo of the challengers. What does that mean?
• 34:56
  In our case, everyone is telling the buyer today, you know what,
• 35:02
  you should replace your existing processes and roles with AI
• 35:06
  employees, OK? That's the kind of like the
• 35:09
  status quo of the challenger today.
• 35:11
  All these digital workers and AI employees, you have SDRS.
• 35:14
  Here's an AISDR, take it. It would just be, you know, just
• 35:18
  a cheaper output to what you hire today and what we're saying
• 35:23
  that is the wrong appliance of the technology, right, just to
• 35:27
  get these small incremental gains.
• 35:30
  But you can just go to development countries and hire
• 35:33
  SDRS for, you know, very small, you know, percentage of the
• 35:37
  price and get poorer quality. Same thing as an AISDR.
• 35:41
  The real unlock comes from human AI collaboration.
• 35:45
  When you try to design processes around your employees to turn
• 35:48
  them into the 100X version of themselves.
• 35:51
  That's how you'd break the ceiling.
• 35:53
  And you can really differentiate from your competitors and get
• 35:56
  that unfair advantage, right. So we're challenging the
• 35:59
  challenger. Everyone is selling you AI
• 36:01
  employees F them. They're totally that's a huge
• 36:04
  mistake to do that. And if you're listening to all
• 36:07
  these guys, you're behind. Actually the winners are the
• 36:10
  ones that are listening to this approach, the challenging of the
• 36:14
  challenger. OK, so that's the narrative and
• 36:17
  most important things. If you remember the first tip
• 36:19
  about emotions, you, you, you got to make sure that your
• 36:24
  narrative is provoking good emotions and not negative
• 36:29
  emotions. And what we were lucky is that
• 36:32
  AI employees and digital workers are encouraging a dialogue of
• 36:37
  FOMO and of fear, basically of being replaced and anxiety, and
• 36:43
  that this is very negative discussion.
• 36:45
  And what we're telling them, you know, what the 100 X employee is
• 36:49
  about hope that humanity will prevail, is that we will stay
• 36:53
  here after the AI revolution and we will just evolve into a
• 36:57
  better version of ourselves. So you got to, you know, push
• 37:00
  for that hope and positive emotions that that narrative
• 37:05
  creates. So that's the narrative.
• 37:07
  OK. And now we're going to move to
• 37:08
  the narrator. Ryan, I hope that you're still
• 37:11
  with me and the audience is listening and not taking too
• 37:13
  much time of the podcast for that.
• 37:15
  We're with you. Keep it moving.
• 37:17
  I love it, Keep it moving. Okay, awesome.
• 37:19
  So we got a viral narrative here.
• 37:22
  Now without a viral narrator, nobody will listen to you
• 37:27
  because who care that Amos Barr Joseph is telling me that AI
• 37:32
  employees worth nothing and we should actually look at 100 X
• 37:36
  our human employees. Why should I listen to them
• 37:39
  right? Everyone is trying to tell me
• 37:40
  different things. Why should I care about Swan and
• 37:44
  why should I care about Amos Bar Joseph in that sense.
• 37:46
  So what do you need to make sure is that you connect that
• 37:50
  powerful narrative with a viral narrator.
• 37:53
  What does that mean? You got to be the most well
• 37:56
  positioned person, person not company.
• 37:59
  You got to be that well positioned person that to tell
• 38:04
  that story, OK, you got to be uniquely positioned on planet
• 38:08
  Earth to tell that story. And what we did at Swan and
• 38:11
  that's how you create that powerful formula is we're
• 38:14
  challenging the challenger with that 100 ex human employees and
• 38:19
  we're building the first autonomous business ourselves.
• 38:22
  So we have that point of view into that future and we can
• 38:26
  actually tell you that in that future that we're living in
• 38:30
  today, this is what brings you amazing results.
• 38:33
  That's how you generate, you know $1.5 million pipeline with
• 38:37
  0 marketing spend. That's how you one person team
• 38:39
  can generate 300 KRR in four weeks.
• 38:42
  In that sense, it's all about that viral narrator position,
• 38:48
  and when you connect viral narrative with the viral
• 38:51
  narrator, then you can start throwing these experiments all
• 38:55
  over the place, and when you hit something, you can really grow
• 38:59
  exponentially. Incredible.
• 39:02
  And you're doing that with such skill because it it takes a lot
• 39:07
  of bravery and you kind of got to wait until like some scary
• 39:10
  waters because not only are you talking about your product, but
• 39:13
  you're also showing behind the scenes of how you're building
• 39:16
  the business and how that can help other people bid, build the
• 39:18
  business, which in turn then build your business.
• 39:21
  How do you respond to somebody who says, like, I don't want
• 39:24
  people to know what we're doing? Someone's going to copy it.
• 39:26
  You kind of addressed that already.
• 39:28
  Or I'm just not comfortable sharing behind the scenes of
• 39:31
  what's going on because let's all face it, I'm kind of a
• 39:34
  basket case and I don't really know what's happening and I'm
• 39:37
  just putting the track down in front of the train while the
• 39:39
  train is coming ahead at me. Yeah.
• 39:41
  So first of all, I feel like in B to B, what we're all craving
• 39:46
  for is authenticity. And, you know, B to B marketing
• 39:51
  is so fake and is so obsessed about trying to frame the
• 39:59
  perfect picture for the reader. And today, the buyer is much
• 40:04
  more savvy. And it's not like we're like,
• 40:08
  you know, 30 years ago when you can put an ad in the newspaper
• 40:12
  saying, like, look how good our product is.
• 40:14
  And people would say, wow, it really is good.
• 40:17
  I should spend $20,000 and buy it because that ad on the
• 40:21
  newspaper told me it's good. It doesn't work like that.
• 40:24
  People are craving for authenticity.
• 40:26
  And when you show your vulnerabilities.
• 40:29
  People gain trust and can trust your good capabilities and your,
• 40:34
  your upsides and that well. And So what you need to make
• 40:37
  sure and you don't just need to, to, to share everything about
• 40:41
  our business. It's not about that.
• 40:43
  It's not like we share 100% of the things, but it's more about
• 40:47
  what's interesting for our readers.
• 40:49
  And if it's interesting for them and they can learn about where
• 40:52
  we're doing the mistakes and improving, then they would want
• 40:55
  to learn more about where we're winning as well.
• 40:58
  And then they will gain more trust and then eventually they
• 41:02
  will buy our product. And I think what people need to
• 41:05
  understand that in 2025, the buying experience is 90% built
• 41:12
  upon trust. OK, Because everyone in an AI
• 41:16
  world, everyone is selling you bullshit.
• 41:20
  Sorry for my language, but everyone is, is trying to sell
• 41:24
  you dreams. And you cannot believe anyone
• 41:28
  and the, the vendor that you will choose whether you're a big
• 41:31
  enterprise Oregon, you're a small startup.
• 41:33
  When you're buying a solution, you want to buy a solution from
• 41:36
  someone you trust from a brand you trust.
• 41:38
  And so start thinking about trust and how can you create
• 41:42
  that? And then you understand that
• 41:43
  being vulnerable and sharing losses and sharing mistakes
• 41:48
  creates trust, and that's what you basically want to optimize
• 41:51
  for. Love it.
• 41:53
  I love it. Now, one thing that kind of came
• 41:56
  up for me when you were talking about narrative is you said, you
• 41:58
  know, you want to make sure you're eliciting positive
• 42:01
  emotions and not negative emotions.
• 42:03
  And when you kind of simplify things down to this kind of
• 42:06
  polarity, it reminds me of this kind of philosophical principle,
• 42:10
  principle called emotivism, which is essentially saying that
• 42:14
  like, whether it's a moral argument or opinion, people
• 42:17
  basically boil down to like Boo or yay, that's it.
• 42:21
  And that if you can be kind of a, a moderator at that fulcrum,
• 42:25
  like you're the guy that that turns a Boo into a yay.
• 42:29
  This is just the beginning of like that narrative process that
• 42:32
  they're like, I'm coming to you with this feeling and I don't
• 42:35
  like it. If you're stuck there, then it's
• 42:37
  almost impossible to convert a customer until you kind of have
• 42:41
  some kind of like transformation or some kind of
• 42:45
  transmogrification of that feeling from negative to
• 42:47
  positive. Amazing.
• 42:49
  That's that's and I think it adds something that I missed a
• 42:52
  little bit. And you know, when I talked
• 42:54
  about the narratives and the emotions, that is super
• 42:57
  important trying to emphasize is that eventually what you're
• 43:02
  selling is not your product. It's a transformation in the
• 43:06
  buyer's life, OK. And when you frame it like that,
• 43:11
  it's even simpler to understand The transformation that I'm
• 43:14
  selling for my customer is from Boo to yay, right?
• 43:18
  That's what I'm trying to sell them.
• 43:20
  And if you look at actually what we're selling, it's interesting
• 43:24
  because if I look at that framework, the Boo is I'm, I
• 43:29
  tried to keep, keep up with all these AI startups that are
• 43:32
  trying to replace all my employees.
• 43:34
  And that's really Boo because I'm, I'm afraid of that.
• 43:37
  And I, I feel like everything is running away for me and I just,
• 43:40
  I I gotta keep up with all just just to keep up so I won't lose.
• 43:46
  That's like a very booze situation that the reader when
• 43:49
  engages my post. That's where they are.
• 43:52
  But what we're giving them is a very no BS approach to you know
• 43:56
  what? Nothing has changed.
• 43:58
  Look at your bottlenecks, look at your employees.
• 44:00
  Try to put turn them into that 100X versions and everyone
• 44:04
  you'll still be here and you just need to put your best
• 44:07
  practices and expertise into that.
• 44:09
  So that's like the transformation that people are
• 44:12
  experiencing when they're reading my content in that way.
• 44:15
  And, and I love how you simplify it.
• 44:17
  You know that transformation from Boo to yay, that's what
• 44:20
  you're trying to take the buyer when they're interacting with
• 44:24
  your content and with the buyer journey basically.
• 44:28
  Yeah, amazing. Pricing is a major concern for
• 44:32
  go to market. You're sitting there, you're
• 44:33
  wrestling with the pricing. Now we have usage based with all
• 44:37
  the AI tools or you have a subscription which is well tried
• 44:40
  and well worn. How did you kind of?
• 44:43
  Land on your pricing structure. Yeah.
• 44:46
  So, wow, that's a very difficult question, Ryan.
• 44:49
  And I feel like we're entering a new era in pricing of, you know,
• 44:56
  a lot of uncertainty and you know, and, and best practices
• 44:59
  that are being eliminated and people are just reinventing the
• 45:03
  wheel completely today. And I think first of all, one
• 45:07
  thing that completely changed about pricing in my opinion is
• 45:10
  that pricing becomes a core, core aspect of your product
• 45:16
  market fit. And I, you know, my previous two
• 45:19
  companies when I looked at pricing, I say, you know what,
• 45:22
  the first thing we should make sure is that our product
• 45:25
  delivers value. And let's just make, let's just
• 45:28
  iterate on that. We'll work with the buyers,
• 45:30
  we'll try to give them the most value possible.
• 45:32
  And if we land on that, then pricing will just take care of
• 45:35
  itself. It's going to be OK Today,
• 45:38
  pricing is a core part of your product market fit is a core
• 45:42
  aspect of your product, and you cannot test product market fit
• 45:45
  without testing pricing. That's the first thing you got
• 45:49
  to understand that it should. It's a huge part in your
• 45:51
  strategy. And what's happening in AI is
• 45:55
  that what AI creates is that everyone becomes a wholesaler.
• 46:00
  What does that mean? You're an intermediate if you're
• 46:04
  not building a foundational model.
• 46:05
  Of course, if you're open AI, you're not playing that game,
• 46:07
  but if you're building in the AI application layer, So basically
• 46:12
  what you do is you're using these AIAPIS and you're wrapping
• 46:18
  them and reselling them. So you have a cost to your
• 46:22
  business that is varying based on the usage and that is given
• 46:26
  every a company that uses these AP is has a varying cost of
• 46:32
  their operations. And that's a paradigm shift from
• 46:35
  SAS because SAS didn't really have a variance cost to it.
• 46:40
  You can just scale up your customers and your cost wouldn't
• 46:43
  really scale with them. It was super high margin
• 46:46
  businesses. But AI introduces that
• 46:49
  complexity. So you have that variance cost
• 46:51
  and now you need to ask yourself what happened?
• 46:55
  Do I push that complexity and variance cost to my customer and
• 47:00
  I will put on their responsibility to manage that
• 47:04
  variance cost based on their usage.
• 47:06
  And if I do so, then I create a lot of complexity and
• 47:10
  uncertainty for them, right? So if you look at models like
• 47:13
  Cursor, for example, if you're familiar with Cursor or like
• 47:16
  Lovable, you just don't know what you're paying for.
• 47:20
  And you just throw $50 and let's see what I get.
• 47:25
  And you finish these $50 and then it asks you want to
• 47:28
  continue the game. If you want to play more, just
• 47:31
  put, you know, $50.00 into the machine and we'll see what
• 47:34
  happens next. And you can't really predict
• 47:36
  what happens next. And So what they decided is to
• 47:41
  push all the uncertainty and complexity on the buyer.
• 47:45
  But then on the other side, basically what you can you can
• 47:49
  do is you can take that complexity on your side of
• 47:52
  things. So you can say, you know what,
• 47:53
  we will take care of that complexity and we will take care
• 47:56
  of that variance. So you enjoy the predictability
• 47:59
  and what we have at Swan is more of an outcome based pricing is
• 48:05
  what does that mean is that we try to attach it to a business
• 48:09
  outcome that the business can understand what the ROI for that
• 48:14
  outcome and then they know that they're buying 50 outcomes in
• 48:18
  that sense. And you know what, OK, I can
• 48:20
  spend $1000 for 50 outcomes because I know that I'm getting
• 48:23
  $10,000 if we'll get to these 50 outcomes.
• 48:27
  So for SWAN, it's more about qualified leads and the business
• 48:31
  can know conversion rates and things like that and they
• 48:33
  understand what's the price for a qualified lead.
• 48:36
  We have intercom, for example, that they have a successful
• 48:40
  resolution for support ticket. So it means that if I'm a
• 48:44
  support organization, I know what's the cost and ROI for me
• 48:48
  for a successful ticket resolution and I only pay if
• 48:52
  there's a successful resolution. That's great.
• 48:54
  So that's the dynamics that we're seeing right now being
• 48:58
  unfold in the AI application layer.
• 49:01
  Are you pushing the complexity on your customer and then what
• 49:05
  you enjoy is better margins, but the buyer has a lot of
• 49:09
  challenges with predictability? Or are you giving the buyer the
• 49:14
  predictability and simplicity, but then you need to manage all
• 49:17
  that variance and complexity on your side when you're building
• 49:21
  your business? Yeah, I love that about your
• 49:24
  product and the pricing because you know, all founders are going
• 49:27
  to understand their CAC. And if it's like, OK, I'll pay
• 49:29
  $500 all day long for a new customer.
• 49:32
  And you're saying with my your starter pack that you're going
• 49:34
  to give me 150 qualified accounts of like people that you
• 49:38
  know, have been on your website, maybe they were on your pricing
• 49:41
  page. So you give that to someone like
• 49:43
  me, it's like, cool, I'm going to get half of those on a call.
• 49:46
  I'm going to close 30% of them. So you do the math quick.
• 49:48
  You're like, this is this is no problem.
• 49:50
  So are where did that go into the consideration like, hey,
• 49:53
  what's the average CAC for the average our average customer and
• 49:57
  how do we price it in a place that's builds value for us, but
• 50:00
  becomes kind of like an easy yes for them?
• 50:03
  Yeah. So in in a perfect world, that
• 50:06
  was the only consideration, but a perfect world and is a world
• 50:11
  without competition. And eventually when you factor
• 50:15
  in competition, you want to look at two factors.
• 50:19
  One, the value that I'm providing for the buyer and how
• 50:24
  do I position a price that creates a great ROI equation?
• 50:27
  But what happens if you have a competitor that can suggest that
• 50:32
  the same ROI at a lower price point, right?
• 50:35
  So eventually you want to factor two of these things.
• 50:38
  So the price point that we landed on is kind of a
• 50:40
  combination of looking at the different ways that people can
• 50:44
  actually get to the same solution in some way.
• 50:47
  Maybe it's combining 5 different tools together, right?
• 50:51
  But still what we wanted to do is to look at the alternative
• 50:54
  pricing points that you have and then look at the ROI that we're
• 50:58
  getting. And that's how we got to the
• 50:59
  pricing that we have today. Amazing.
• 51:03
  Oh, but this has been so cool. OK, it's time for the founder
• 51:05
  Challenge question. Are you ready?
• 51:08
  I'm not sure that I'm ready, but let's see.
• 51:11
  All right, I've got 4. Categories that you can choose
• 51:13
  from unfiltered, intriguing, risky, or self reflective.
• 51:20
  I would, I would go for risky just because that's my agenda
• 51:25
  always, you know, choose the, the risky experiments.
• 51:28
  I love it. I love.
• 51:30
  OK, what have you said? In early pitches, that was a
• 51:33
  complete exaggeration. What did I say in early pitches?
• 51:37
  That was a complete exaggeration though.
• 51:40
  I would say the the conversion rates of like, what would I
• 51:46
  expect that people would convert these visitors into actually
• 51:50
  qualified pipeline? And what what happened is that
• 51:54
  over time I realized that it's really about building nuanced
• 51:59
  use cases for every specific scenario that you have.
• 52:04
  And customers, they don't really know about all these nuanced use
• 52:08
  cases because they had a lot of complexity in their tech stack.
• 52:11
  So they didn't really get to that type of thinking.
• 52:14
  So they they expected to just get Swan and get like all these
• 52:18
  conversion rates out-of-the-box. But what happened is that they
• 52:21
  needed to work with Swan and evolve their thinking about how
• 52:24
  they should actually treat every different scenario.
• 52:27
  If it's a closed loss, if it's a small account, if it's a big
• 52:30
  account, what happens if the C cell visits?
• 52:32
  But what happened if it's just a developer, etcetera.
• 52:35
  And that all that education was required.
• 52:38
  And we realized that's something that you learn while you use
• 52:41
  Swan and you just learn about your.
• 52:43
  Business basically incredible. I love it.
• 52:47
  Now, are you guys bootstrapped or did you raise when you're
• 52:51
  building the product? Yeah, so and building an
• 52:55
  autonomous business is not about bootstrapping.
• 52:57
  It's not, it's not like we're trying to tell people not to
• 53:00
  raise money, but it's really not about going the VC route.
• 53:05
  It's really about trying to focus on ARR per employee and
• 53:09
  not, you know, valuation, inflation.
• 53:11
  We have some investors that are supporting our efforts, but we
• 53:15
  didn't go through like this, you know, the VC route when we want
• 53:18
  to do Series C, Series A, Series B, Series C, we're trying to
• 53:22
  build like a different business model for investors as well.
• 53:26
  Oh amazing. How much did you raise?
• 53:28
  Are you comfortable talking about that?
• 53:30
  Dale, I'm not comfortable talking about that, right?
• 53:33
  Just because it's still kind of like under the hood, basically.
• 53:37
  100% I love it. OK everybody loves business
• 53:41
  ideas. If your only mission was to earn
• 53:43
  1,000,000 bucks in a year, what business would you build right
• 53:47
  now? Easy, easy.
• 53:49
  So start with a a lot of possibility that I'll choose
• 53:54
  one, But basically I think that we're at the phase of building
• 53:58
  service businesses, not product businesses.
• 54:01
  OK, So to build a product Business Today is super hard
• 54:05
  because you take all these amazing AI capabilities.
• 54:08
  But to really make it great for a customer, you need to layer on
• 54:11
  top a lot of services to actually make it work 100% for a
• 54:16
  customer when you start. And it's really hard when you're
• 54:18
  building a product business. But when you're building a
• 54:20
  service business, you can just take that AI expertise that you
• 54:25
  develop over time and just allow, you know, businesses that
• 54:28
  don't have it to leverage all these amazing capabilities and
• 54:32
  just implement them in your business.
• 54:34
  So if I was starting even I was like 20 years old or 30 years
• 54:37
  old or 40 years old, doesn't matter how old were I, I would
• 54:41
  just learn how to take these amazing AI, you know,
• 54:47
  applications that we have and just work with businesses to
• 54:50
  just implement that that in their business.
• 54:53
  And more specifically my because I have a lot of knowledge and go
• 54:56
  to market. So I would say, you know what
• 54:58
  you want to leverage all these AI agents.
• 55:00
  I will work with you. I will help you identify the
• 55:03
  bottlenecks that you have today and I will just connect that
• 55:07
  these AI capabilities to your bottlenecks and solve it
• 55:10
  together with you. And I've seen businesses today
• 55:13
  that are doing just that. They're not rocket scientists.
• 55:16
  They don't know a lot about AI and large language models, et
• 55:21
  cetera. All they really mastered is
• 55:24
  automation, no code tools. And all they do basically is
• 55:28
  they just, you know, throw themselves at the problem, Start
• 55:32
  learning how to solve it, spend enough time on that surface area
• 55:35
  and eventually get to a really good solution.
• 55:37
  And you can build a highly profitable business right now
• 55:41
  just by learning how to implement these AI solutions and
• 55:44
  these AI automation solutions in businesses.
• 55:47
  And you can just scale that to $1 million in like like 3-4
• 55:51
  months if you're really good at incredible.
• 55:56
  Cool. Are there CEOs or other founders
• 55:58
  that you follow closely? So first of all, Manny Medina
• 56:05
  from Paid AI, he was also the former founder of Outreach and
• 56:10
  built like a multi billion dollar company.
• 56:12
  He's a good friend and if you are, if you want to learn about
• 56:16
  the pricing complexity actually that AI brings to the world.
• 56:20
  So Manny is an amazing expert with everything that comes to
• 56:24
  pricing and also have a really a lot of knowledge around, you
• 56:28
  know, the use of AI and AI agents companies as well.
• 56:32
  And I would also follow Elias Taurus.
• 56:36
  He is the founder of Agency and was previously the founder of
• 56:40
  Drift, which was acquired for more than $1 billion.
• 56:45
  And he is also a good friend. And he is also preaching for
• 56:49
  building small businesses that can deliver outsized outputs.
• 56:54
  And he's building Agency to also become kind of like an
• 56:57
  autonomous business in the sense of staying lean, small, but
• 57:01
  generating a massive outcome. So go follow them.
• 57:04
  They are super smart and I love that.
• 57:07
  Amazing. If you were entering college now
• 57:10
  as a freshman, understanding what you understand now and as
• 57:14
  as you're looking to where the puck's going, what would you
• 57:16
  study? I would study philosophy and
• 57:23
  computer science, and I would say that we're entering a world
• 57:30
  where you need to understand intelligence and consciousness,
• 57:36
  and you need to improve your communication skills and how you
• 57:42
  build arguments. And all of that comes from
• 57:45
  philosophy, actually. But then on the other side, you
• 57:48
  still need to understand machines and systems and
• 57:53
  computer systems, and maybe you don't need to program a lot in
• 57:57
  the future that we're heading towards, but you still need to
• 58:00
  understand how these systems operate in the back of the
• 58:04
  scenes, basically. And if you combine that ability
• 58:06
  to work with intelligence, that's how you you gain by
• 58:09
  learning philosophy. And if you understand how that
• 58:12
  intelligence really work at behind the scenes and what is
• 58:15
  really happening here, this is not really intelligent.
• 58:17
  These are tokens, this is statistical model, there's
• 58:20
  software behind it, these are AP is etcetera.
• 58:22
  If you connect these two point of views together, then you're
• 58:25
  really well positioned for the AI revolution.
• 58:30
  Yeah, I love it. As we're wrapping up here a
• 58:33
  little bit, we're a good place for people to find follow you
• 58:36
  online. So of course, LinkedIn, search
• 58:40
  for Amos Barr Joseph on LinkedIn and I write, you know, a lot of
• 58:46
  content about, you know, the behind the scenes of the
• 58:48
  autonomous business and about, you know, the AI agent
• 58:51
  revolution. I also have a newsletter, it's
• 58:53
  called The Big Shift. So maybe we're going to share a
• 58:56
  link to that Ryan after the show, but it's if you're looking
• 59:00
  for to get a seat into a weekly session of behind the scenes of
• 59:04
  what does it mean to build an autonomous business, the wins
• 59:08
  and losses and the lessons learned.
• 59:09
  Then you can join the the big shift.
• 59:12
  And finally, I have a digital clone.
• 59:15
  If you want to ask questions after that call and you listen
• 59:19
  to that podcast and you have a couple of follow up questions so
• 59:22
  you can just ask autonomous and I'm I'll be there.
• 59:27
  My digital self will be there to answer every question.
• 59:32
  It's pretty good. I, I, I really appreciate that
• 59:34
  autonomous. Exactly.
• 59:38
  Thank you so much for your time. This has been awesome.
• 59:40
  Thank you so much. My pleasure, Ryan.
• 59:42
  Thank you so much. Hey founders, let me ask you
• 59:46
  this. Are you building with AI or
• 59:49
  getting left behind by it? If you're serious about scaling
• 59:53
  smarter, faster and bolder, you need to check out AI for
• 59:57
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