$300K ARR, zero SDRs — how Amos Bar-Joseph's AI swarm replaced outbound

Amos Bar-Joseph, CEO of Swan AI, breaks down how his three-person founding team generated $300K in ARR in 30 days without hiring a single SDR or spending a dime on ads. Instead of relying on generic 'AI SDRs' to spam prospects, Amos built a bespoke 'AI swarm' around his unique strengths—specifically, his ability to tell stories on LinkedIn. By using AI agents to amplify his content, manage connections, and engage high-intent website visitors, he effectively scaled his own output by 100x without sacrificing quality. Amos argues that most companies fundamentally misunderstand AI in go-to-market motions. Instead of automating existing clunky processes (which only creates a cheaper, lower-quality output), he advocates for reimagining the entire GTM engine with human-AI collaboration at its core. He warns against 'skeuomorphic' AI implementation, likening current AI SDR tools to Barnes & Noble just putting their physical catalog online, while the true winners will build digital-native models like Amazon. Beyond automation, Amos shares his contrarian views on startup growth. He prioritizes building a movement before building a product, relies on intuition over slow A/B testing to preserve decision-making velocity, and strives to build a 'Swan' instead of a Unicorn—focusing on ARR per employee and sustainable value creation rather than massive funding rounds and inflated valuations.

Discussed in this episode

• How Swan AI generated $300K ARR in 30 days with three founders and zero SDRs.
• The danger of using off-the-shelf AI agents that just create a cheaper, lower-quality version of yourself.
• Amos's specific LinkedIn AI funnel: Shakespeare, Observer, Connector, and Hunter agents.
• Why go-to-market alpha comes from being fundamentally different, not just executing more generic activities.
• The difference between 'skeuomorphic' first-wave AI applications and truly reimagined AI-native business processes.
• Why building a movement and telling a compelling story matters more than building a product first.
• The necessary shift from zero-sum siloed metrics like MQLs to optimizing for full-lifecycle sticky revenue.
• Why startups should avoid A/B testing to preserve their single biggest advantage: decision-making velocity.

Episode highlights

1. 0:00 — Intro to Amos and Swan AI
2. 2:15 — $300K in 30 days without SDRs
3. 4:30 — Why off-the-shelf AI agents fail
4. 7:00 — The LinkedIn agent swarm breakdown
5. 11:45 — Painless vs. painful AI implementation
6. 15:20 — The AI SDR spam cannon era
7. 20:10 — Building a movement before product
8. 25:30 — Why A/B testing kills startups
9. 28:45 — The Swan vs. Unicorn playbook

Key takeaways

• Scale with intelligence and agents, not headcount.
• Build AI workflows around your unique founder strengths.
• Reimagine processes from the ground up instead of automating broken ones.
• Focus on sticky revenue instead of siloed SDR and CS metrics.
• Avoid A/B testing early on; prioritize decision-making velocity above all else.

Transcript

Welcome back to another episode of the Bridge the Gap podcast powered by Revenue Reimagine. Today's guest is Amos Bar Joseph, who is the CEO and co-founder of Swan AI and one of if not the sharpest builders in the AI GTM space right now. He's sold two startups, scaled B2B revenue with automation and is building a small $30 million ARR company with get this just three founders and a stack of AI agents that happen to have some pretty cool names. But he isn't just chasing scale, he's actually questioning what gets lost in the process.

This isn't going to be your typical hype conversation about replacing sales teams, go use AI, fire everyone. We're not talking about any of that shit. We're going to have a real look at what breaks when you go too fast, what works better than expected, and what the future of go-to-market might actually look like. Amos, thanks for joining, man.

Wow, uh, Adam, thank you for that intro. I wish I could, you know, just take you with me to like, you know, dinners and, you know, social gatherings. I I'm in. I will be, I will be your hype man.

I will just get stand up there and do the intro. Let's do it. Let's do it. This is where you talk, Dale.

Yeah, well. You messed up the script, so I was, I didn't know what you were doing. So, Amos, thanks for joining, appreciate it, man. So, um, 30k in 30 days with no SDRs, like let's start where everyone's like whispering about.

How would you generate 30k 300k? Sorry, I said 30k. I clipped myself. 300k.

You can be accounting here at revenue reimagine. Exactly. I don't do any operations by the way. That's not my, that's not my thing.

No SDRs, no ad spend. Walk us through how you did that. Yeah, um, so, you know, I am a one-person GTM powerhouse. I move at, uh, you know, startup speed but at enterprise scale.

Um, and, you know, we did that as a team. It was a team effort actually. We're, you know, as you mentioned here, we're three founders, you know, on a mission to get to $30 million ARR, uh, just, you know, us and AI agents. So that means that we can't throw bodies at the problem.

We can't hire SDRs. We don't have, you know, huge marketing budgets, so we don't have that, you know, ad spend war chest. Um, Does it even matter anymore? Does the ad spend war chest even matter anymore?

I guess not. We're trying to prove it. It doesn't, right. Um, what we did basically is, you know, we tried looking at intelligence as leverage.

Um, we're trying to scale with intelligence not with head count, but the way we we approached it is not by trying to automate, you know, ourselves away. It's not by, you know, hiring off the shelf AI SDRs to spam our market. Um, it was more about, um, how can we, you know, discover that 100x version of ourselves, that 100x seller version of me. Not like, what would be the 100x version of everyone?

Because we don't believe in that. So yeah, I want to, I want to hit this head on. I just posted about this yesterday and we've been talking about this. There's so many people out there that are just trying to buy like off the shelf agents, I'll go to n.

a.n, I'll go to Gumloop, I'll go to make. And I, and you want to, uh, just download something and get it running because people are lazy as shit. Like, let's be honest.

And like, that's not the easy button. Like, you have to customize and build it out to what you're trying to accomplish. Talk more about that. Yeah, definitely.

So, um, you know, it's nothing new with AI agents. You know, GTM alpha always comes from being different, not better. It always about, you know, leveraging a playbook that maybe you have a unique insight into it, maybe it's very hard to accomplish. It's always about that, you know, the fact that you're leveraging a playbook that others don't.

If everyone is on the same playbook, then you're all fighting over the same attention and it's hard for everyone. So, um, you know, those quick wins are, you know, problems that are built into the go to market DNA since forever. Um, and, you know, the best teams, they can, um, you know, just overcome it with, you know, just fighting hard and and actually discovering the unique playbooks that could drive the most ROI. And so, what we did at Swan is we realized that, you know, automating ourselves away, off the shelf AI agents, that's, you know, the generic playbook, it doesn't work.

We don't believe in that because what you'll get basically, it's like a very low glass ceiling of, you know, a cheaper version of yourself with poorer quality, right? So that's like the glass ceiling. Just, you know, Shit in, shit out. You know, worse.

Yeah, worse version of myself, just I pay less for that. Okay, wow, not that amazing. What we try, I gotta, I gotta tell the, the editors like to, to clip this and like post it everywhere because like people just do not get it. Yeah, 100% and I'm, I'm gonna double down how, you know, how, um, how important is it.

So what we did, um, we built our entire AI agents strategy and the go-to-market centered around the human being, not a replace it, but around a human being. And that human being is me. I have, you know, Ido, the CPO and Neve, the CTO, they are, um, AI agent wizards. They've built, you know, an agentic swarm around my strength and weaknesses.

And it all starts with, you know, my biggest passion, which is actually storytelling. So, um, you know, I'm not your regular seller, which most sellers are not regular sellers. Every seller has their own unique advantage that unfair advantage they could double down on. And so mine was storytelling.

And, and you know, I have great ability to write LinkedIn posts and my LinkedIn game is on fire. And so we realized that that's an amazing opportunity to double down on that, not by building agents that could just help me produce more posts in a shitty quality with less, um, you know, resources, but how can we build like a funnel of agents around my entire activity on LinkedIn. And so it goes like that. Um, folks, if you're listening, this is how the funnel goes with our AI agents.

I'm gonna go break it down. I want access to this. Oh, so yeah, and you can actually, you can actually build an AI agent that could teach you how to build it yourself, step by step. Um, and so if you want access to it, you can DM me on LinkedIn and I'll, uh, I'll give it to you.

Whole separate conversation. Yeah, definitely. So, um, if we look at the funnel, it all starts with actually, you know, writing the posts themselves. I have Shakespeare, which really kind of like helps me in a collaborative way to write, you know, viral posts that generate over 1.

5 million impressions on LinkedIn. Um, I it takes me less, you know, four hours, it takes me 30 minutes. I produce much better posts because I have like a thought companion that I can collaborate with on, okay, tell what arcs can we actually approach this narrative that I want to talk right now? Um, what, what amazing hook can we have?

Give me five options, give, let's go that direction, let's go that direction. Um, let's try to work on the first intro, etc. So I have Shakespeare. We have 1.

5 million impressions, then, um, what we have basically is 15,000 reactions to every post that I have. So that's a lot of engagement. So we have the observer, which actually, you know, monitors these leads and surface up, you know, hot ICP leads from, you know, the posts that people are engaging with. If you go one step below that, we have the connector, which is basically monitors my connection requests.

I get 300 connection requests each day. Um, so basically, um, I have an agent that monitors these connection requests and surface hot opportunities, reaches out to them so I can pick it up only whenever there's a reply, basically. Um, then if you go one step below that, we have the hunter on our website. If you rented our website but you didn't sign up, the hunter is going to spot you.

If you're a hot lead, then expect a message, a personalized one from me, and if you reply, then I get into the loop and we can start a conversation. So R-R-R B2B on steroids. On mega steroids, it's like R-R-B2B and Clay, um, and OpenAI had a baby. Um, and and they had like a LinkedIn automation built into it.

So, um, that's the hunter basically. And, how do you stay out of, how do you stay out of LinkedIn jail with this? Because when when you listen to the gurus, you know, it's like any, any automation with LinkedIn, you're going to be effed. And I don't believe you got to 300k in ARR by breaking rules and, you know, getting shut off.

You're you're clearly thriving. How do you do it the right way? Right, so, first of all, you obsess over, um, you know, LinkedIn constraints. Uh, what we, like we have a very opinionated, uh, way of approaching it also within our product itself, because we sell, you know, agents to go to market teams as well.

They they operate on LinkedIn. We don't let you touch the capacity, the scale, anything. We have like an algorithm and a queue, and what it does basically, it always kind of like looks at your queue because you're always I'm always at maximum capacity, okay? So, like my state is like always maximum capacity.

I always have an algorithm on my queue that surface up the relevant leads in terms of like date relevancy and, you know, the the how hot they are, right? So if it's like an amazing opportunity, it can bump up other, you know, leads that are waiting in that queue, but this is something that we operate in our back end that we built for our customers and I use it for myself as well. I love it. It's it's super amazing.

Um, really quick follow up question on this, like, when you started, like what system did you have on day one? Like, when you when you're like, hey, I'm going to start this thing. Was it just LinkedIn? Or was it like LinkedIn and some, are you using like iPad in the background?

So are you referring to like our product, like the LinkedIn automation part or like the entire agent swarm? I think not the agent swarm, but like day one you're like, I'm gonna start this thing. Like people, like the agent swarm type of thing and people going down an agentic uh, path orchestration, like what's good for them, like their build different than what you built. But like day one, you're like, people are like, how do I get started on this thing?

Mhm. Yeah. So what what we we did was nothing new to AI agents. Um, we did, you know, maybe the opposite of 99% of the world.

We actually didn't look outwards, we looked inwards, okay? We didn't, yeah, you know, asked someone which agents should I build. We didn't look at the hottest AI startups out there because we knew that 99% of them are BS. We just looked inward and we had a challenge to solve.

We started with a constraint, that's the autonomous business model. We can't scale with head count. So, okay, we can't hire someone to do it manually. How can we unplug that bottleneck just using AI agents.

And it started as an iterative process. So every layer kind of like, you know, helped us discover another one. So, you know, I happened to have it all started actually with the connection requests. I started having so many connection requests and I said, okay, I'm just losing all of this volume.

I can't even, I can, I can't even go and accept them because it's too much. I can actually even go to my LinkedIn inbox and accept them. So we said, how can we solve that? So we went into Unipile, we went, there's an API for connection requests, etc.

The what people don't understand is that you don't need AI knowledge to become an autonomous business, to become an AI operation expert. You just need business processes, ops and no-code expertise. That's all that is required to actually start building that muscle. And people are always looking for answers and quick wins outwards, but it all starts with a bottleneck, and then, you know, someone who's like super clunky but and scrappy, but, you know, wants to just fix it with some no-low code automation and knows how to map that process.

And that's all you need. So you start iterating with prompts, etc. You don't need to be a prompt genius to create an agent that understands who's a hot lead or not, right? Amos, man, that that you're you're you're repeating everything Dale tells me every day, but that that.

I like we have to do the same thing in our business, right? Like a lot of the things that we do is go-to-market. It's all scalable. Like it's like how do you what what we started telling our clients is like and and it's a scary thing.

Do you go traditional go-to-market or do you do this hybrid AI agentic because they've already gone down the traditional route. Like they didn't build from the ground up like you guys did and and think about, I can't go hire 85 people. So that now they're now they're in this weird hybrid state where they're like, I I need more top of funnel, I need more awareness of my product and service, but I can do like so I I have this example, you can either go hire three content editors and build a bunch of derivative content off of a ebook, for example, or you can start playing around with the agentic side, let it generate content for you, but generate an AI system. Like don't just use ChatGPT, don't go use Claude, like you need to have a system in place to actually do that execution process for you.

And then you can start weaning yourself off of potentially high-cost hires that may or may not stay around, um, through that process. Yeah, I I think that, you know, most of the companies are playing the wrong game right now, which is like, looking at roles, functions, processes. How can we automate them with AI? That is not the right type of thinking actually.

And I think that type of thinking leads you to just trying to figure out outside who could help you with that without really developing that, you know, AI competency inside of the company. And second of all, it has again that low glass ceiling of all you can do is just, you know, have something a little bit, you know, worse but cheaper. That's what you're looking for, not what you try, you know, what you need to do is to reimagine fundamentally how can that process look like with human AI collaboration at the core. And so, you know, we believe that SMBs are actually much well-positioned for the, um, you know, LLM revolution.

That's the autonomous business concept. We believe that they have the ability to restructure their entire DNA around human AI collaboration, but enterprises as well, they have, as I see it, like two routes. They have the painless, um, route which leads to very mediocre performance, and they have the painful route which leads to exceptional performance. The painless is, you know, taking their same processes, not trying to really innovate from within, but taking the same system that they have and try to put AI on top of it so they can have fewer employees doing the same amount of output.

That's the painless, mediocre outcome. But the painful exceptional outcome comes from reimagining these processes from the bottom up. Maybe they need to open a new sub org within their go to market team. So a new SDR team that could actually build that, you know, culture from the ground up.

Maybe they can't even take their own team and change it, they need to start it from the bottom. That it's a painful route, but that would actually lead to that 100x improvement to the fact that they won't be left behind when their competitors become AI natives. People are too scared. It's a scare like the mindset shift is not like people are scared.

Sorry, Adam, I no, you're you're fine. this is all great. I I I want to I want to pivot slightly. Um, so I agree with everything that you're saying.

But there there's this kind of wave right now of teams that are jumping on this AI bandwagon specifically for like AI outreach, right? Like AI SDRs and even like whether it be AI LinkedIn responders, but like really taking it to the extreme of like AI cold callers, which by the way is illegal, um, AI SDRs, AI AEs, AI sales enablement, like you name it, it's AI. Um, where in your opinion, Amos, where where's the disconnect between like expectation and like reality of what should be versus like what people think they should be doing. People buy from people.

That's why companies who invest in meaningful connections win. The best part, gifting doesn't have to be expensive to drive results. Just thoughtful. Sendoso's intelligent gifting platform is designed to boost personalized engagement throughout the entire sales process.

Trust me, I led sales for a Sendoso competitor, and I can tell you, no one does gifting better than Sendoso. If you're looking for a proven way to win and retain more customers, visit sendoso.com. Yeah, so, um, first of all, this spam cannons, um, approach, it's nothing new.

So, um, you know, in the GTM space since, I don't know, like maybe 2010, like 15 years ago, we had the sales automation golden era, right? Um, so there was a specific point in time where spamming prospects were valuable, right? It was maybe 15 years ago, okay? And since then, it's not that valuable to spam prospects, and the value of spamming prospects just decreases, you know, very steadily over time.

And AI just takes that, you know, momentum and amplifies it. So, um, okay, spamming, we had, you know, personalization, we had actually, you know, SDRs at a lower cost, so you can always outsource your SDR function and have, you know, cheaper output for lower quality. That something that existed. So, it's nothing new.

It's just, um, you know, a continuation of a long-lasting trend. AI is the new offshore. Yeah, exactly. It's just I blame marketing for all of it.

It's always started like marketing automation started like this big trend and like marketing will completely destroy anything that is getting any little bit of like traction. Yeah, so I I actually, I actually think, Dale, that every software wave promised, you know, sales teams to give them more human interactions, but actually, um, you know, left them with more system interactions than human interactions at the end. And, um, it's all because these companies have great marketing and go-to-market teams that eventually try to educate the market about, you know, a way to approach it, but it's only a moment in time where you have that alpha and it just disappears. And so, I just want to get back to the AI SDR analogy here.

Um, what we're seeing, it's the first wave of AI applications, okay? That is the first wave. So Steve Jobs calls the first wave of a technology revolution as, um, skeuomorphic design. What does it mean?

Skeuomorphic, it's a bad name, but, um, it means that the first wave tries to mimic what we have, um, just, you know, putting the new tech on top of it, basically. So it lacks the creativity and understanding of this new technology. When we look at websites, for example, when websites came, so the first wave, you know, we had Barnes and Noble, a bookstore, say, yeah, let's put all our books on a book catalog on the internet. It was like a read-only website.

And they were pretty early to that revolution, but they just, you know, they had a read-only website with look at our books, this is what we have. But then came the second wave of Amazon, who imagined a digital native bookstore. And we know where these two companies are. So what we're seeing here, it's the same unfolding of, you know, AI.

So the first wave, we have SDRs, let's create AI SDRs, right? We have support, let's create AI support agents, right? It's like, let's do the same thing, just, you know, in a shittier way, right? But the second wave, which is what Swan promised to bring to the world, is a different use of the technology when we try to reimagine that process with human AI collaboration.

And so, what we bring to the table at Swan that is extremely different than, you know, all these AI SDRs, is actually we look at ourselves as an AI go to market engineer. Okay. So we are actually a platform that it's an agent that can help you build agentic motions for your business specifically. What we believe is that GTM alpha comes from differentiation, not from being better or more activities, it's come from being different.

And so we're moving from an era where there was an app for this where SaaS, you know, solved use cases and built features for a use case to an era where AI agents build solutions for you, for your business. And the AI go-to-market engineer helps you build agentic GTM motions that fit your go-to-market DNA. If you're a cold calling organization, and you have a unique understanding of your buyers and messaging and positioning, etc, then you need that AI GTM engineer resource to build an agentic motion that supports your cold calling. You don't need an AI SDR that will replace your callers, because you're doing a good job.

You just need to amplify that. So how can you find something that will double down your cold calling efforts? You need an AI GTM engineer. And so what we're promising is finally from, you know, SMBs and and go-to-market teams that bent around their tech stack, finally your tech stack bends around your business.

To value equation, like this has always been a value equation thing. Um, and, you know, the differentiation piece, I think what is happening today, people are just trying to differentiate anyway they can. Like they don't know how to differentiate and they forget about like the fundamentals. Like why did your product or service come to market?

What's that value proposition and why should your buyer care about it? Now, how do you get that Come on, build it and they will come. Swan did that, right? Build it and they will come, right?

One of how many tens of thousands that actually have an idea and a product that is so good that people do see it and they're like, oh I'm out of time. I will actually disagree, guys. I will disagree. We didn't build it and they come.

Um, so, um, we had a an it's just because it touches a core aspect. When I talk to young founders, and the number one tip that I actually give them is product last, okay? So we've in the last, um, you know, 20 years, uh, it was all about building an MVP, right? That's the old startup playbook, right?

And so the old startup playbook was build an MVP, was built around it. And so what happened, it became more and more expensive to actually build that, you know, um, MVP. And so startups raised more and more money to actually do it, etc. And we ended up at that growth at all cost playbook.

But what's happening in the last five years, which is interesting, is building products became super easy, but going to market became super hard because the fight over attention is the hardest thing to do right now. And when you're what we're entering is an extreme mode of that situation when you have these, you know, AI developers like Lovable and Base 44, and you can build an app, everyone can build your app in no time. The hardest thing is actually to take it to market. And so we built Swan, our product, we built it last.

First we built the movement around the autonomous business concept. And we started by that. And I grew my LinkedIn followership not because people love our product, not because people use our product, but because they believe in this new concept of scaling with intelligence, not with head count. And the autonomous business movement when I talk about it, I don't mention Swan and how we leverage intent to to generate pipeline.

That's not what I talk about, that's boring. What I talk about is the future of, you know, of business operations and the the operating system of a business with human AI collaboration at its core. So we actually build the movement first and product last. It's the, it's the story arc that people get enamored with and you need to build that story arc so that they understand where they are and where they should be going.

And if they don't get there, their customers will get there and they'll eat their lunch. And so Yeah. Agree. And I want to double down maybe last thing on what Adam said that, you know, one out of tens of thousands of businesses can generate sustainable growth from a good product, okay?

That to generate sustainable growth from a very good product, that's like it's not even a unicorn. It's much much more rare than than that. And so, um, what people need to invest more, and I feel like it's getting a lot of really overlooked in GTM specifically, is in your story. People today fall in love with the story, they fall in love with the people behind that story.

They don't care about brands anymore. And people should start embracing that because if you're not doing a really good job on your story and on the people behind that story, the faces of your story, then you're leaving a very hard work for your sellers. Totally agree. Totally we we we talk about this all the time.

It's it's the origin story, it's the value prop, it's tying it together, what is the problem you solve for your prospects in 30 seconds or less and what made you want to do this? I I couldn't agree with you more. And we talk in sales, like forget like founding a company and building a product, but we often say the best sellers are the best storytellers. They're able to take a a complex or simple problem, build a story around it that resonates and makes makes you feel deeply.

Sales is the transference of feelings. So like exactly what you're saying. The story, yes. Don't get me wrong.

Although I I will say I was going to say you don't have to have a great product. Um, but you do. You can't have a shit product. There are some companies that have shit products that can be successful for a certain amount of time, but eventually that comes out.

Put a great product with a fantastic story, a charismatic founder, a great sales team, use AI to leverage that. And I I love what you said about, um, not having AI for the use case, but having AI for you. So you the difference of using AI versus building AI. Um, this is where I think go-to-market is going, um, and I think very few people are getting it right.

Awesome. Um, one more question then we'll go do a couple fun things. Um, I I'm trying to decide what question I want to ask you and I think this one makes makes more sense first. Um, so rebuilding GTM from first principles.

Um, we talked about this a little bit. Um, my understanding is you built GTM the rebuilt GTM many many several times. Um, how's how's it changed in how you approach it? And I'm gonna follow it up with a couple of of questions.

What beliefs about GTM have you completely dropped? Like, what is like that's complete bullshit? What did your team not do that most startups do? And I think I know a lot of that that answer.

And then, um, what would you never outsource again? Mhm. Interesting. Okay, so, uh, let's let's break them down one by one.

These are big questions. That's what I was gonna say. One at a time. Big big questions.

I feel the pressure, I feel the feel the heat. Um, so, first of all, one thing that I've learned, um, maybe the most fundamental one is that playbooks can if playbooks can take you very short distance, right? So if you're always looking at others people playbook, then you're always, you know, a step behind everyone, basically, or maybe you're the competitors. Um, it depends where you want to be.

And if you feel like, you know, being the 10th or 100th player in your space, then that's okay. And then learning playbooks is important and you need to keep up. Um, and so, you know, depending on what is your goal as a company, you need to actually align to that. When you're building a startup, then usually you're trying to be, you know, the best, right?

And if you're not, maybe if you're building like a regular business, a lifestyle business, then learning the playbook is okay, okay? But, um, what I realized is that when you try to become the number one player in your space, everything becomes easier, okay? So that being number one mentality unlocks everything for everyone, basically. And if you try to settle down from being number five, then everything becomes harder, basically.

And just becoming number five is much harder. So the playbook will get you to the 10th number number 10th at maximum, right? So you need to actually reinvent the playbook by understanding your unfair advantage as a founder, as a GTM leader and as a company. And so if you don't understand what is your unfair advantage and you don't build your playbook according to that, then you'll end up number 10, number 100, maybe you'll just close the business.

I like that. Yeah, I I think the playbook is a is a it can be surperrogated. Um, what what will you never outsource again? Um, so I will never outsource, um, you know, like pipeline generation, um, as kind of like a as a service, right?

If someone promised me leads, right? So like, I will I I will generate pipeline for you, right? It's like outsourcing your product manager. Like, yeah, maybe I'll have a like a product manager that just, you know, tells me what to build for my company and, you know, yeah, you should build an AI SDR.

I will say, okay, you're right. I will build an AI SDR, that's a good advice. Thank you. It's not like that.

Basically, um, you need to understand the top of the funnel. In a it's like building like so Brian Halligan, you know, CEO and founder of Hubspot, he has this notion of looking at go-to-market as a product. I love it, okay? And I feel like, um, you know, you have this notion of go-to-market market fit, right?

Like product market fit. And you need to iterate on that. You always need to understand, how do you find the perfect motion, right? And that starts from the top of the funnel.

And so you can't outsource that top of the funnel to someone who just, you know, brings you lead. You can work with experts, with consultants to help you develop that in-house. Maybe you want to use, um, you know, a specific capabilities outside of the company. So like if you want to reach massive scale, and you have an agency that can send, you know, millions of emails a month, so you can outsource that and use that capability if you'd like.

But don't ever think about, you know, just letting someone, you know, generate pipeline for you. I I would venture to say even doing what you do and your company doing what you do, you still get those pitches all day long of, hey, Amos, I could generate 10 leads for you per day and you only have to pay $22 per lead. Like, and it shows like if if if your targeting is this piss poor, I'm certainly not going to trust you to do it for me. 100%.

Um, all right, we are we're coming up on time. Let's jump into some fun fun rapid fire. Um, I feel like we could go for another hour. Um, unfortunately the show's only supposed to be 30 minutes, but we're uh we likely need to change that.

Amos, what's uh what's one part of your tech stack other than Swan that you would never trade or give up? Um, so that's easy, uh, I would say Claude from Anthropic. Like it's the ChatGPT alternative. So, without it, I will feel like I would lose my arm, basically.

I just recently started doing a lot more in Claude than ChatGPT. I used to be the opposite. Um, and I think they each have their use cases. ChatGPT can't design shit, like can't format anything for its life, whereas Claude gets it right almost every single time the first time.

Claude is really good at content writing, by the way. Yeah. Okay, good to know. Finish this sentence.

In three years, sales development will be Will not be called sales development. What will it be called? So I believe that, um, the future is like full life cycle growth operators that they care about what I call sticky revenue, okay? So sticky revenue is the end goal of every business.

And when you have sales development, and you have MQ people, like marketing are in charge of MQLs and that's it. And sales development are in charge of meetings booked, and AEs are in charge of meeting quota, and CS are in charge of retention. What you get is like this misalignment of incentives that really breaks the funnel down into like a zero sum game. And when you look at like the persona that can orchestrate, you know, context around different types of places, but all they care is about sticky revenue.

Like I do as a single person operator, I care about if I look at a bad lead, I will never close that meeting. I can look at it as a demo and I see that's a bad lead. I won't I won't close it as a customer actually. And also if I'm a CS and I see a customer that reaches out for a question, I can understand this is an opportunity for an upsell.

So the fact that I have that context all across the board because I use AI agents, not because I'm a Superman, brings the ability to increase sticky revenue. And that's what you really want as a business. Sticky revenue. Love it.

What uh what's one common startup best practice that you would absolutely actively avoid and stay away from? AB testing. Um, AB testing is a a terrible, uh, idea for startups. Um, so, uh, basically the only, uh, advantage of a startup, um, the only one, there's only one advantage to a startup has against an enterprise, like against the incumbents.

And that's decision-making velocity, okay? A startup can make much more decisions in a given week than an enterprise. All the rest, an enterprise has an advantage over a startup, okay? And so the fact that your only unfair advantage is having better decision-making velocity, AB testing hurts that ability, because it slows down your ability to make decisions.

So instead of doing an experiment, measure it over a period of time, and then deciding what to do, go with your intuition, try to measure it, if it failed miserably, do not do something different. But decide, decide, decide. You could do You could do that with AI much easier than you could do that with hiring three people. So, I I think that is a, uh, a really key part of moving fast and going forward.

Um, what scares you more? Going too fast or going too slow? Um, no, going too slow, going too slow. Definitely, going too slow is, um, you know, not from even from a like a CEO perspective, from a personal perspective, that's my biggest fear, you know, just just drowning in stagnation.

Um, it's where I feel like I'm at the least of my, uh, pros. And when it's hyper growth, that's where I shine. I'm good, I'm I'm very resilient, so I don't really, I'm not afraid with hyper growth. I love it.

You have two little swans behind you, yes? Yeah, they just flew in. Second, I I I I noticed them about halfway through. Uh, are there more swans in the house?

Yeah, they're everywhere, basically. And, you know, every day passes, um, you'll see more and more swans. We believe that, um, the unicorn playbook is dead. No one really wants to build a unicorn.

It's about valuation inflation. It doesn't really about value. Building a swan, it's actually about value creation. It's about ARR per employee.

It's about, you know, starting as the ugly duckling where you don't get these massive funding rounds and massive TechCrunch, you know, headlines, but you grind, you build real value, real ARR per employee, and then you become this elegant, aerodynamic beast. And that is a great place to end it and that is a take I agree with. Almost, thank you so much for joining. Folks can find you, of course, on LinkedIn.

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