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Dan Wright (Co-founder & CEO of Armada) joins GTMnow to unpack what it actually takes to bring AI infrastructure to the places the cloud was never built to reach.

The cloud covers about 30% of the world. The other 70% (think: oil rigs, the Arctic tundra, military ships, remote mines) is where some of the most critical decisions happen, making latency a life-or-death and billions of dollars difference. Armada is building the infrastructure for that part of the world: modular, ruggedized AI data centers that go to the data, instead of the other way around.

From the first offshore edge computing deployment with the US Navy, to cutting avalanche response times in Alaska from over a day to real time, to sovereign AI installations in Saudi Arabia with Aramco and Microsoft, Armada is redefining what operating at the edge even means.

Discussed in this episode

• Why cloud infrastructure was built for a pre-AI world and what that gap costs
• How Starlink turned every remote location into a potential AI cluster
• What “distributed intelligence” means and why it’s the founding principle behind Armada
• The global race for AI sovereignty and why modular compute is the linchpin
• How Armada goes to market when a product demo involves shipping a 40-foot container to a desert (yes, really)
• Why customer champions are better than any sales rep
• The Microsoft partnership and how Armada extends Azure to places Azure could never go on its own
• Category creation lessons from building a company before the market had a name for the industry
• What’s next: SpaceX, sovereign AI, and why Dan thinks humans are on the moon in two years (yes, REALLY)

Episode highlights

00:00 – Why the cloud only reaches 30% of the world and what Armada actually builds

03:11 – From Saudi Arabia to the Arctic: recent deployments that redefine the edge

04:12 – AI’s physics problem: why distance from data breaks everything

05:31 – How Starlink turned every remote location into a potential AI cluster

07:14 – What distributed intelligence means and why it’s Armada’s founding principle

08:14 – The global AI race: sovereign compute as a national security strategy

09:00 – The Genesis Mission, the White House, and Davos: why sovereign AI is mainstream

12:49 – GTM for a hardware company when the demo involves shipping a 40-foot container

15:18 – Why Armada’s customers do the selling for them (and do a better job than some reps)

17:35 – The Microsoft partnership and extending Azure to the places it can’t reach on its own

18:51 – Category creation: the lesson Dan learned about specificity and business value

21:02 – What’s next for Armada, SpaceX, and why Dan thinks we’re two years from the moon

25:34 – The founder advice Dan wishes more people took seriously

Key takeaways

1. The cloud was built for a world before AI.
Every major cloud provider built their infrastructure 25 years ago, before large models existed, before sensors were on everything, before data lived on oil rigs or in the Arctic. The world has changed but the infrastructure has not. That mismatch is a massive market opportunity.

2. Connectivity unlocked the edge, but without infrastructure it’s useless.
Starlink changed the game for connectivity. But without compute, all you have is faster access to a problem you still can’t solve. Every time Starlink goes live in a new country, Armada is the first mover on infrastructure. Connectivity + compute = the edge finally works.

3. Sovereign AI is here and the US and China are in a global AI race.
We’re in a global AI race. And infrastructure is the battleground. For companies like Aramco and the US Navy, data sovereignty means the data cannot leave the site – by law, by security protocol, by necessity. You can’t send classified sensor data from an oil rig or a Navy ship to a data center thousands of miles away and wait for a response. You need compute where the data lives (that’s what Armada builds).

4. Category creation is about problems, not technology.
Nobody wakes up wanting to buy infrastructure. Dan’s approach from day one was to get specific about the problems (avalanche response in Alaska, split-second decisions on a battlefield, catastrophic failure prevention on an oil rig) and let the technology follow.

5. Write your manifesto before you do anything else.
Before a single hire, before an office, before raising a dollar. Armada had a manifesto – this is why we’re building, here’s where the world is going, here’s why it matters. Dan calls it an unfair advantage. When you can articulate exactly why your company needs to exist, recruiting gets easier, fundraising gets easier, partnerships get easier. You’re not selling a product. You’re building a movement. A 10-slide pitch deck might get you to Seed, but it won’t build a generational company.

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Follow Dan Wright

• LinkedIn: https://www.linkedin.com/in/wrightdh
• X: https://x.com/danwrightSF
• Armada’s LinkedIn: https://www.linkedin.com/company/armadaai
• Armada’s website: https://www.armada.ai

Follow Sophie Buonassisi (Host)

• LinkedIn: https://www.linkedin.com/in/sophiebuonassisi
• X (Twitter): https://x.com/sophiebuona
• Newsletter: https://thegtmnewsletter.substack.com

Where to Find GTMnow

• Website: https://gtmnow.com
  
• LinkedIn: https://www.linkedin.com/company/gtmnow
  
• X (Twitter): https://x.com/GTMnow_
• YouTube: https://www.youtube.com/@GTM_now
• Podcast Directory: https://gtmnow.com/tag/podcast

GTM 182 Episode Transcript

00:00

Dan Wright: We call ourselves the hyperscaler for the edge. Rather than having the data sale to some very far away data center, we can actually bring these data centers to the data. Saudi Arabia. The state of Alaska in the Arctic, US Navy everywhere beyond the cloud providers networks where there’s data.

00:16

Sophie Buonassisi: Dan Wright is the CEO of Armada deploying AI data centers to the most extreme places on Earth. When an AI model is too far from a data source, what starts to actually fracture?

00:27

Dan Wright: It just doesn’t work. Oil rigs, mines, ships. The way infrastructure has been is that it was built for a world before.

00:35

Sophie Buonassisi: AI, and you’re operating in extreme remote environments. And previously these were data desert. How has satellite connectivity like Starlink helped enable this edge first approach?

00:45

Dan Wright: Starlink totally changed the game and now everywhere is a potential AI cluster, a potential AI hub.

00:51

Sophie Buonassisi: We’re now in the age of AI sovereignty. It’s no longer just about who has the best model. It’s more about who owns the infrastructure stock.

01:00

Dan Wright: It is a global AI race and the countries that move the fastest. Those are going to be the big winners. There’s going to be data centers in space. We are going to go to the moon. We are going to go to Mars.

01:10

Sophie Buonassisi: How many years away do you think we are from seeing that on the moon?

01:13

Dan Wright: I would say.

01:15

Unknown:

01:26

Sophie Buonassisi: Dan welcome to GTM now.

01:27

Dan Wright: Thanks for having me on.

01:28

Sophie Buonassisi: Absolutely. It’s a pleasure to have you here.

01:30

Dan Wright: Great to be here.

01:31

Sophie Buonassisi: And I want to start off with what you’re building

01:33

Sophie Buonassisi: because the cloud is king. Narrative has hit a bit of a wall now in extreme environments, even a few milliseconds of latency, the delay it takes to send data to

01:44

Sophie Buonassisi: the data center is

01:45

Sophie Buonassisi: can really be a deal breaker. And Armada seems to be that solution to the problem.

01:51

Sophie Buonassisi: Yeah. So for anyone unfamiliar with Armada, how do you explain what you’re building?

01:55

Dan Wright: Yeah, we call ourselves the Hyperscaler for the edge. And what I mean by that is we are building a new type of cloud company

02:01

Dan Wright: the cloud, if you think about what it is, it’s these massive hyperscale data centers,

02:06

Dan Wright: they’re great, but they only cover about 30% of the world. And so we’re building the infrastructure for the rest of the world, which is really needed because a lot of the biggest problems happen there in that area of the world.

02:20

Dan Wright: We call that area the remote edge. Everywhere beyond the cloud providers, networks where there’s data.

02:25

Sophie Buonassisi: I’ve heard Armada mentioned in so many different contexts

02:28

Sophie Buonassisi: from extreme environments, everything from Alaskan drone imagery through to the military. Is there a particular extreme environment that you feel like

02:35

Sophie Buonassisi: showcases this edge first approach best?

02:38

Dan Wright: What’s exciting is that the edge is now constantly being redefined with Armada. When we started the company,

02:45

Dan Wright: people thought of the edge as the edge of the cloud providers networks. When we say the edge, we mean the edge in terms of wherever the data is. And then when I say wherever, I mean,

02:55

Dan Wright: literally anywhere. The reason that we named

02:57

Dan Wright: company Armada is that rather than having the data at Sail to some very faraway data center, we can actually bring these cutting edge modular AI factories, AI data centers to the data, and just a few recent examples.

03:11

Dan Wright: We were the first ones to do that in the middle of the summer in Saudi Arabia with Aramco in partnership with Microsoft.

03:19

Dan Wright: Extending all the things that,

03:21

Dan Wright: you know, Aramco likes about Azure to the edge, but then also bringing cutting edge models,

03:25

Dan Wright: from, you know,

03:26

Dan Wright: the leading new model providers, anything they want to this remote edge, doing the same thing with the state of Alaska in the Arctic, focused on emergency response, helping them cut latency to process data from,

03:41

Dan Wright: drones for responding to avalanches and floods from over a day to real time to save lives.

03:47

Dan Wright: And then we also did the first offshore edge computing ever with the US Navy.

03:52

Dan Wright: taking all of the data from drones, taking these really powerful AI models, bringing them to the middle of the ocean, where you can go on a ship, you can put it in a weapons bay, you can port for, deploy it in a C-17 C-130.

04:04

Dan Wright: those are a few recent examples, but it seems like every week,

04:06

Dan Wright: you know, we’re constantly redefining the edge.

04:09

Sophie Buonassisi: Always pushing the boundaries. Yes. And speaking boundaries.

04:12

Sophie Buonassisi: AIS often talked about is this a serial thing? But in reality it’s governed by the laws of physics. And when an AI model is too far from a data source, what starts to actually fracture?

04:23

Dan Wright: It just doesn’t work.

04:24

Dan Wright: the problem with the way infrastructure has been is that it was built for a world before I. Right? All of the cloud providers built for a world, you know, 25 years ago when we,

04:36

Dan Wright: didn’t have AI in any meaningful sense, we certainly didn’t have these really large, powerful models that we have today.

04:43

Dan Wright: And on top of that, the data was in more centralized, you know, urban locations. But that’s not true anymore either, because now all the data is on oil rigs, mines, you know, ships, you name it, where they’re sensors all over these things. And so the problem is, if you don’t have something like Armada,

05:03

Dan Wright: you can’t actually use AI where you need it most, where the data is.

05:07

Dan Wright: that’s where we come in, is we can take

05:09

Dan Wright: these really powerful models, as you said, you know, they’re not magic. There’s physics involved. So you actually need the infrastructure to run them. We take that full stack to the data and then we solve, you know, really important problems like saving lives or,

05:22

Dan Wright: preventing,

05:22

Dan Wright: catastrophic events at oil rigs, mines, you know, enabling split second decisions on battlefields in a way that can really,

05:30

Dan Wright: solve important problems.

05:31

Sophie Buonassisi: And you’re operating in extreme remote environments. And previously, these were kind of data deserts. Yeah. How has

05:38

Sophie Buonassisi: satellite connectivity like Starlink? Yeah. Helped enable this edge first approach.

05:43

Dan Wright: first of all, I like that term data desert. I think I might steal that from you if that’s okay.

05:46

Sophie Buonassisi: I like my yes.

05:48

Dan Wright: so we have seen that that is one of the big trends that is happening. That was always a blocker to AI at the edge. If you don’t have the internet, then how are you going to get these really powerful AI models to the edge? Right. You have to have them at least to be able to push them to the edge.

06:05

Dan Wright: Then you can run them what’s called air gapped, you can run them disconnected from the internet, but you have to have the internet to push them there. And usually what people want to do is run them and then send the insights or the metadata

06:16

Dan Wright: back to the cloud so they can benefit at all their other sites as well.

06:19

Dan Wright: So Starlink totally changed the game, and most people don’t know. They only launched in public beta in November 2020. So it’s a relatively new product.

06:28

Dan Wright: Now. They’re in, I think, 155 countries right around there,

06:31

Dan Wright: and they’re rolling out in new countries every week,

06:34

Dan Wright: and the service is getting better. When it first came out, it was primarily a consumer product.

06:38

Dan Wright: Then it went into enterprise a couple of years later. And then there was Star Shield for the government. Initially it was being used as a backup, and now the service has gotten so good that it’s being used as a primary source, increasingly

06:49

Dan Wright: the internet.

06:50

Dan Wright: And so what that means is if I get a call like I did the other day and somebody says, hey, can you deploy one of your galleons, which is what we call our modular factories in Antarctica?

06:59

Dan Wright: I could say, yeah, we can do that because Starlink’s in Antarctica, we don’t even need fiber in the ground.

07:05

Dan Wright: And that’s important because

07:06

Dan Wright: everywhere is a potential, AI cluster, a potential AI hub, because you have Starlink and you have reliable internet everywhere.

07:14

Sophie Buonassisi: what is the term distributed intelligence need to you?

07:17

Dan Wright: Yeah. I mean, distributed intelligence is the

07:20

Dan Wright: founding principle of armada. And

07:22

Dan Wright: what that is, is

07:23

Dan Wright: the world

07:24

Dan Wright: moving from a situation where you have these really large hyperscale data centers that just train these big, you know, AI models, right?

07:33

Dan Wright: To a world of inference, a world where you can use those models anywhere and you can have it distributed the same way that,

07:42

Dan Wright: energy is distributed.

07:44

Dan Wright: Right? Because there’s lots of stranded energy around the world that can be used to power these high data centers. That’s also been a big block or too I,

07:51

Dan Wright: I talked about the connectivity, but then energy as well.

07:54

Dan Wright: But also data is distributed because of the rise of IoT devices and the fact that cameras and sensors and drones have gotten so much less expensive, about ten less expensive over the last five years, now, it only makes sense that you would have distributed intelligence, because, again, that’s where the power lives, and that’s where the data lives.

08:12

Dan Wright: And that’s where the most important problems live.

08:14

Sophie Buonassisi: And Dan,

08:14

Sophie Buonassisi: we’re now in the age of AI sovereignty.

08:18

Sophie Buonassisi: It’s no longer just about who has the best model. It’s more about who owns the infrastructure stock, a theme that we see with your work on the D.o.e. use Genesis mission. That’s right. And in your AI dominance whitepaper, you actually framed this as a global race between the US and China.

08:35

Dan Wright: Yes.

08:36

Sophie Buonassisi: Why is modular compute such a linchpin in the global race for AI domination?

08:41

Dan Wright: first of all, we live in such an interesting time. Like is as an entrepreneur,

08:45

Dan Wright: it’s like, this is the time.

08:46

Sophie Buonassisi: Yeah, this is.

08:47

Dan Wright: What you want to be building best.

08:48

Sophie Buonassisi: Us.

08:48

Dan Wright: And

08:49

Dan Wright: this past year, obviously we’re in 2026 now, but 2025 was kind of mind blowing. And,

08:55

Dan Wright: you know, there was an event, the winning the AI race, summit that I went to in July, and that was for the US,

09:04

Dan Wright: kind of a coming out party for sovereign AI. The fact that we were declaring that we’re really serious about beating China in this global AI race,

09:13

Dan Wright: really serious about AI dominance.

09:15

Dan Wright: you know, there’s a few pillars to the AI action plan that was announced that day which match almost exactly our white paper, which we had already written. You know,

09:24

Dan Wright: we were talking to the say, some of the same people, but we didn’t know that they were going to release it at that event. And we just happened to do ours the same day.

09:31

Dan Wright: But it was very aligned. And the first pillar of the action plan is all about rapidly 

deploying infrastructure domestically,

09:38

Dan Wright: using these really powerful AI models on critical industries, you know, oil and gas rigs, manufacturing mines,

09:46

Dan Wright: to

09:47

Dan Wright: boost GDP, improve our economy, create jobs,

09:51

Dan Wright: but then also to have a really fast R&D loop

09:54

Dan Wright: on our AI stack

09:56

Dan Wright: from the silicon all the way through these, you know, models themselves.

09:59

Dan Wright: Right?

10:00

Dan Wright: then the third is, okay, once we do that, we need to also export ROI stack to allied nations faster than China can buy a wall way primarily.

10:09

Dan Wright: when that happened, I was like,

10:11

Dan Wright: we knew that the world was going in this direction. But like, Armada is the perfect enabler of this.

10:16

Dan Wright: the second thing that happened is Genesis mission. And there was a,

10:20

Dan Wright: event that I attended at the white House

10:22

Dan Wright: were there with some other partners, collaborators on Genesis Mission as well as Secretary. Right. Dario Gil,

10:28

Dan Wright: And what we talked about was this need to create a common AI platform across all of the national labs, leverage the decades of data at these national labs, and then have huge leaps forward,

10:43

Dan Wright: in science and engineering, which would again enable all the things that I’m talking about.

10:48

Dan Wright: It would boost GDP. It’s going to solve diseases that were never possible before.

10:52

Dan Wright: But it’s also going to make sure that we have the best models and the best AI stack in the world so that we can then export that to other countries.

11:00

Dan Wright: to kick off 2026, there was a moment just last week when I was in Davos and Sovereign.

11:06

Dan Wright: I was like the new hotness. Everybody wanted to talk about sovereign AI. And I’m thinking, right, we’ve been doing sovereign AI. That’s what we do. Yeah, you know, and so it was really cool to be able to talk about

11:18

Dan Wright: level,

11:19

Dan Wright: that most people haven’t even thought about. Like, for example, the work that we’re doing with Aramco and a lot of these state backed energy companies or with the US Navy,

11:28

Dan Wright: they talk about data sovereignty, they don’t just mean data sovereignty.

11:30

Dan Wright: It’s like a country level,

11:32

Dan Wright: or even a state level. They mean it at a state level.

11:35

Dan Wright: Like the data cannot leave the site because you have things like cyber attacks that are becoming more and more prevalent.

11:42

Dan Wright: Because a lot of those sites are,

11:44

Dan Wright: critical national infrastructure. They’re classified in such a way so that

11:47

Dan Wright: by law it can actually be moved off the site.

11:50

Dan Wright: So when they talk about sovereignty, they mean sovereignty down to the site level.

11:54

Dan Wright: And that’s where the world is going. I think, you know, people are still thinking about data sovereignty the way that we talked about it, you know, five, ten years ago. But now,

12:02

Dan Wright: way the world is now, you’re going to have these on every one of your sites.

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12:49

Sophie Buonassisi: how do you make a case for sovereign? I was such a wide variety of customers. Are they already quite a lot in.

12:53

Dan Wright: Well, that was the great thing about Davos is

12:56

Dan Wright: I’m not the pitch sovereign AI. Everybody knows that they need to do sovereign AI.

12:59

Dan Wright: The question is who’s going to move the fastest? Again, it is a global AI race, and AI is not one of those technologies where it’s like a little step change.

13:08

Dan Wright: It’s a complete game changer.

13:10

Dan Wright: And so the companies, and the countries that move the fastest to adopt this infrastructure and then put those

13:18

Dan Wright: powerful AI models

13:20

Dan Wright: to work fine, tune them for their data, for their workflows.

13:25

Dan Wright: Those are going to be the big winners. And the thing about AI is it has a compounding advantage, right? Like the leaders

13:31

Dan Wright: just will absolutely dominate, and then the laggards will, be left in the dust.

13:36

Dan Wright: And that is true at a country level and is true at a company level. And now we’re seeing that play out in real time.

13:41

Sophie Buonassisi: Let’s shift gears and talk about your go to market. Because damn selling software is one thing. But shipping ruggedized solutions to remote areas is a complete other. And what does your go to market look like when a product demo is shipping a giant 40ft container to, say, a desert?

13:58

Dan Wright: The beautiful thing about our platform is it’s a very flexible. Right. So we can show a demo,

14:04

Dan Wright: of the platform, you know, remotely. We have these data centers all over the place. If somebody wants to run one of their own models or one of our

14:12

Dan Wright: kind of cutting edge AI models,

14:14

Dan Wright: we can run it on one of our existing galleons.

14:16

Dan Wright: We also,

14:17

Dan Wright: have smaller form factors. Even something the size of a suitcase called a beacon. We can do some stuff with that.

14:22

Dan Wright: we have a series of these, and then usually what will happen is we will go hands on with the customer and do like a workshop and catalog all of their different problems at the edge.

14:35

Dan Wright: And then we’ll pattern match. We’ll say, okay,

14:37

Dan Wright: well that problem is exactly like this use case that we did with this other very similar type of company or country. And here is the value that we were able to deliver, because ultimately,

14:48

Dan Wright: there’s a little bit of like AI fatigue. I think a lot of people have,

14:52

Dan Wright: tried different things and haven’t gotten to value.

14:55

Dan Wright: We view our job is helping them accelerate time to value, get value from these,

14:59

Dan Wright: models. And we do that again full stack. So we make it easy. And we also do it,

15:05

Dan Wright: with both our technology and our team. And we have the expertise of having done this with a lot of others.

15:09

Sophie Buonassisi: So you’ve got the proof points of doing it with other people. How do you showcase that ROI that you clearly have. But when you’re operating in really hostile remote environments?

15:18

Dan Wright: Yeah. The best thing is,

15:20

Dan Wright: our customers do it for us. So we just came out with, a partnership,

15:24

Dan Wright: video with Alaska,

15:27

Dan Wright: they talked about the work that we were doing with them. We didn’t say a word in the whole thing. And if you listen to it, they’re talking about

15:34

Dan Wright: how they had all of this latency to process this huge amount, you know, terabytes of unstructured data in remote areas throughout a very remote state.

15:45

Dan Wright: You know, they say in Alaska, the edge has real meaning. That is the edge trend. And,

15:50

Dan Wright: that’s important because otherwise it would take them

15:53

Dan Wright: days or weeks or even in some cases, like an entire season, to be able to go through all of this data that they get from drones throughout the state.

16:02

Dan Wright: what’s really great is when you watch that video, they, they say that it’s going to save lives, and they say that they have a moonshot goal of having hundreds of these all throughout the state.

16:16

Dan Wright: you’ll see more and more of that from us

16:18

Dan Wright: each of our target areas. And we really focus on,

16:21

Dan Wright: you know, defense. We focus on,

16:23

Dan Wright: you know, sovereign AI critical industries like oil and gas and mining and then critical national infrastructure. You’re going to see more and more of these types of customer testimonials that tell the story for us so that we don’t have to sell.

16:36

Sophie Buonassisi: I mean, that is the ideal scenario, social proof. When customers will actually do the selling for you.

16:41

Dan Wright: That’s the way to go.

16:42

Sophie Buonassisi: And it’s always indicative of a fantastic product. At the end of the day you can’t manufacture that.

16:46

Dan Wright: Well, and what’s cool about us is we’re not selling like a SaaS application. We’re not selling like,

16:52

Dan Wright: something that, you know, maybe is a slightly better chat bot

16:55

Dan Wright: we’re selling something dead

16:56

Dan Wright: is completely game changing. So when our customers talk about what we’re doing, it’s like the Alaska video, where it’s emotional. They talk about saving lives, right?

17:05

Dan Wright: Or, you know, a lot of the ones that you’ll see coming out in some of these other industries, like oil and gas and mining, it’s talking about hundreds of millions or billions of dollars in value.

17:15

Dan Wright: that also gets an emotional response, you know, and so, like, that’s what I love is that we’re we’re doing something that is very needed.

17:22

Dan Wright: It’s solving critical problems. And then, you know, as our customers talk about it,

17:26

Dan Wright: it’s a huge win for them. They feel a sense of of pride. And then, you know, they’re

17:30

Dan Wright: excited to tell the world.

17:31

Sophie Buonassisi: That is fantastic. And you mentioned partnership earlier.

17:35

Sophie Buonassisi: You also have a partnership with Microsoft. And Satya Nadella can be seen on stage shouting out Armada. Yeah. How did the Microsoft partnership come to be?

17:43

Dan Wright: Yeah. So we’ve been talking to Microsoft from the early days of the company, even when we were still in stealth.

17:48

Dan Wright: Well, and I think that’s due to a couple of different things.

17:52

Dan Wright: One is

17:53

Dan Wright: they have realized for a while that the edge is going to be very important. Right? So if you talk to,

18:00

Dan Wright: Satya

18:01

Dan Wright: I remember the first time I met him up in, in Washington,

18:04

Dan Wright: you don’t have to convince him on edge.

18:06

Dan Wright: You don’t have to convince him that the edge is important,

18:07

Dan Wright: they were more focused on. Okay, well, how can we make this,

18:11

Dan Wright: a win for Azure customers, as you would expect. Right. And so what what we did is we talked to Satya and we talked to a lot of the leaders at Microsoft,

18:20

Dan Wright: we sort of,

18:21

Dan Wright: made our platforms very, very complementary in a way that, as Satya likes to say.

18:27

Dan Wright: And he says in that video that you saw, yeah, they, you can take Azure local, you can take these really powerful models,

18:34

Dan Wright: agents capabilities, even hardware like Azure Stack. And we extend them to these more remote locations to the edge and do it in a way where it is local, which people want for data sovereignty reasons they wanted for cyber security reasons,

18:48

Dan Wright: and then they want it for cost and latency reasons.

18:51

Sophie Buonassisi: And

18:51

Sophie Buonassisi: as you scale Armada, you know hyperscale isn’t new to you. You’ve seen that through Appdynamics through Datarobot. But our motto, it feels different. You know, you’re not scaling

19:01

Sophie Buonassisi: an existing category. You’re really creating a new category. What have you learned about the category creation process while building our model?

19:09

Dan Wright: we knew that we were going to be redefining the edge, right? The edge. It’s it’s not a new thing like it’s been talked about for a really long time. But again, it’s been talked about in terms of the edge of the hyperscalers networks. Right. And

19:22

Dan Wright: what we’re doing is, is beyond that. And so,

19:25

Dan Wright: we knew that we would have to do some category creation.

19:28

Dan Wright: I think the the biggest thing that we learned through that process

19:31

Dan Wright: you need to get as specific as possible, as early as possible with customers talking about use cases and business value. Ultimately, people don’t buy technology for the sake of technology. Like nobody jumps out of bed and says, you know what, I want to buy some great tech today like that doesn’t happen.

19:48

Dan Wright: People are people and people and companies and countries. They have problems and they buy technology and they buy partnerships to solve problems. And so I always tell our

19:59

Dan Wright: team, like, we’re in the business of solving our customer’s most important problems. And as you do that, then they become champions. Then they’re wanting to tell

20:09

Dan Wright: not only everybody internally, hey, we need to lean into this and do way more with Armada.

20:13

Dan Wright: But they’re telling everybody else they know.

20:15

Dan Wright: that’s what I always thought is like category creation is around building a movement. It’s around,

20:22

Dan Wright: creating a group of people that understand that these very important problems that were previously unsolvable are now solvable with technology and the value associated with that. And that’s why when I talk about the Armada, you know, the Armada originally referred to our galleons is modular data centers.

20:41

Dan Wright: And then we expanded that and we’re like, no, the Armada is actually also our team, you know, and it’s our investors. It’s everybody this bringing this change to the world. But also it’s it’s our customers. You know, we’re all the Armada that’s making,

20:53

Dan Wright: this happen and solving these important problems at the edge.

20:55

Sophie Buonassisi: Dan, we were fortunate to meet in 2023 when you were raising your seed round. We’re sitting here in 2026 now. A lot has

21:02

Sophie Buonassisi: changed which is talked about. What’s next for Armada?

21:05

Dan Wright: Yeah. It’s wild. I mean, you think about how much the world has changed in a very short amount of time. I was

21:09

Dan Wright: talking to somebody the other day about the founding story of Armada. And, you know, we started working with,

21:14

Dan Wright: you know, space X from the beginning. Right. And then, yeah, I could tell what they were thinking.

21:19

Dan Wright: They were like, well, didn’t you also maybe work with like X, I

21:22

Dan Wright: I was like, no, actually I didn’t exist. Right? Okay. I wasn’t around when we started the company, which is crazy to think given how fast that is growing,

21:31

Dan Wright: And so the world has fundamentally shifted since we started the company, but it’s shifted in ways that are directly aligned with our,

21:38

Dan Wright: kind of founding principles for starting the company.

21:40

Dan Wright: We knew that connectivity was going to become ubiquitous. We knew that there was going to be more and more data generated at the edge, and it’s sort of trapped until you get the infrastructure there. So

21:52

Dan Wright: that had to be resolved because there’s so much value in that data.

21:55

Dan Wright: And then we also knew that things like sovereign AI, you know, data sovereignty, cyber security, they were going to become increasingly important.

22:04

Dan Wright: So in many ways we feel like,

22:06

Dan Wright: it’s gone the way that we thought, maybe even faster than we thought it might. And that’s, you know, a good place to be.

22:12

Sophie Buonassisi: And can you talk a little bit about your relationship with SpaceX?

22:15

Dan Wright: So we’ve been partnering with SpaceX since we founded the company.

22:18

Dan Wright: the whole idea is that Starlink is bringing connectivity,

22:22

Dan Wright: all over the world, you know, and we think in the next five years, I mentioned to send around 155 countries today and next five years, there will be internet everywhere on Earth that is as good as fiber in the ground,

22:32

Dan Wright: and that’s a pretty cool world to think about.

22:34

Dan Wright: But unless you actually complement that connectivity with infrastructure, then you can’t do anything with all that data that’s trapped at the edge, right? Other than,

22:44

Dan Wright: things that are not

22:45

Dan Wright: latency sensitive, things that are not,

22:48

Dan Wright: you don’t have to worry about data sovereignty, cybersecurity.

22:50

Dan Wright: for

22:51

Dan Wright: a lot of the most important problems, you need the infrastructure as well as the connectivity to solve the problem.

22:57

Dan Wright: What we do with SpaceX is we sort of lock arms with them. And every time they they launch in a new country, we’re a first mover with the infrastructure.

23:05

Dan Wright: you’re gonna see that continue to play out. You know, they just went live in South Korea. They’re going live in like a new country every week. They’re lighting up,

23:12

Dan Wright: remote

23:13

Dan Wright: locations in Africa.

23:15

Dan Wright: I mentioned Antarctica. Yeah. And our goal is to always be the first mover on the infrastructure. And then what you’ll see us do,

23:23

Dan Wright: is continue to highlight

23:25

Dan Wright: these killer high value use cases that Starlink with Armada unlocks for the first time, things that were never possible before suddenly being possible.

23:36

Sophie Buonassisi: Is there anywhere that you think is not reachable?

23:39

Dan Wright: No, I don’t think so.

23:41

Dan Wright: I mean, I think that,

23:42

Dan Wright: certainly, like, I guess adversaries, like, we don’t go to China or Russia or North Korea, right? But that’s a choice. You know, I was talking to somebody the other day. I said, I’m very I’m very grateful that SpaceX is an American company because it’s like an unfair advantage that we have with the Starlink and his Star Shield.

23:59

Dan Wright: You know, on the, on the government side.

24:01

Dan Wright: we make a conscious choice that we are a proud American company and we’re going to be a first mover with the US and allies. And hopefully that enables,

24:10

Dan Wright: a dominance, right, to make sure that we, we win this global AI race that’s going on.

24:14

Dan Wright: there are no limits to the edge. You know, I think about,

24:17

Dan Wright: even where we’re going over the next few years, you know, we are going to go to the moon, we are going to go to Mars. There’s going to be data centers in space because you’re going to need them in order to,

24:27

Dan Wright: create bases using armies of Optimus robots to build.

24:32

Dan Wright: You’re going to need local compute. You’re going to need it in order to do things that we do here on Earth that you’ll need to do there. Like, yeah, you know, mining, right? You’re going to be automating all of that.

24:42

Dan Wright: You’ll probably have The Boring Company. They’re building these underground tunnels. You know, it’s going to be

24:47

Dan Wright: just an insane, insane few years ahead.

24:49

Dan Wright: I mean, I said earlier, like, what other time would you want to build? This is the best time.

24:54

Dan Wright: it really does feel like there are no limits to what we can do. I think the only limits that we have is, the limits of our imagination. And then, you know, focus. We got to focus on the right things to to make sure that we,

25:05

Dan Wright: accomplish with technology things that serve humanity, in the best possible way.

25:09

Sophie Buonassisi: And you said a few years. How many years away do you think we are from seeing man on the moon?

25:14

Dan Wright: I would say two years.

25:15

Sophie Buonassisi: That’s not long at all.

25:16

Dan Wright: Not long. I mean, it used to be when people talked about going back to the moon or based on the moon, it was like, you know, a decade out,

25:24

Dan Wright: there’s like five years out, it’s a couple years.

25:26

Sophie Buonassisi: And then if you could leave listeners, anyone building probably an infrastructure, but really any founder, one piece of advice, what would that be?

25:34

Dan Wright: clarity around what you’re building and why is extremely important and underrated.

25:41

Dan Wright: I was,

25:41

Dan Wright: watching something with Mark Andreessen recently where he’s talking about how people who write things down have a lot of power, and I truly believe that. And so with

25:50

Dan Wright: Armada, before we hired one employee, before we had an office, before we did anything with the company,

25:57

Dan Wright: we wrote our manifesto, we wrote,

26:00

Dan Wright: this is why we’re building the company.

26:02

Dan Wright: Here’s where the world is going, here’s why it matters

26:06

Dan Wright: how we’re going to do it.

26:07

Dan Wright: that clarity of thought

26:09

Dan Wright: is extremely important. And I find it’s an unfair advantage because you’re able to build a movement when you talk to people that you’re trying to recruit, or if you want to get investors or if you want people to work with you as a customer or a partner, being really clear about the value of what you’re doing, why it’s important

26:27

Dan Wright: is

26:28

Dan Wright: critical.

26:29

Dan Wright: And it seems like an obvious thing. But like most companies don’t do that. I

26:32

Dan Wright: know a lot of startup founders and, you know, a lot of times it’s like, I’ll do a ten slide pitch deck, whatever is good enough to get, you know, my seed funding in the bank, right? That might get you to your seed funding, but it’s not going to help you build a generational company.

26:44

Sophie Buonassisi: The power of writing it down. That’s great advice. And where can people find you and follow along if they’re interested?

26:50

Dan Wright: I’m on X, I’m on all the social platforms. Not all of them. Some of them, but I’m on X. I also,

26:57

Dan Wright: I’m at a lot of events. I’m spending a lot of time in DC.

27:00

Dan Wright: Yeah. These days. So,

27:02

Dan Wright: hit me up at Armada Sky if you want to email me or just, you know, drop me a DM on X and let’s meet up.

27:08

Sophie Buonassisi: I love it, Dan. Thank you. This has been wonderful.

27:11

Dan Wright: Thank you. Great talking to you.

27:12

Sophie Buonassisi: Likewise.

The post

appeared first on GTMnow.

The GTM Podcast is available on any major directory, including:

• Apple Podcasts
• Spotify
• YouTube

Michel Tricot is the co-founder and CEO of Airbyte, the open-source data movement platform he launched in 2020. Before Airbyte, Michel led integrations and served as Director of Engineering at LiveRamp, where he scaled the teams and pipelines that synced massive data volumes. He also helped build rideOS as a founding engineer and Director of Engineering. Michel has spent 15+ years in data infrastructure, with a focus on commoditizing data pipelines and giving teams control and sovereignty over their data.

Discussed in this episode

• Why Airbyte launched open source first (catching engineers “at the search”)
• Project-market fit vs. product-market fit, and why they’re different
• The content engine: founder-led writing, shipping slides, and radical transparency
• Turning interest into community: 25k+ Slack, champions, and hiring from within
• The near-misses: hiring ahead of PMF, support-heavy community, cloud complexity
• Going upmarket: enterprise motion, longer cycles, and team ramp realities
• AI wave → agents as “data consumers” and what it means for pipelines
• Replatforming for control & sovereignty, not just “more connectors”

Episode highlights

00:15 — Airbyte’s rise: open source, community-first, and a billion‑plus valuation.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=15

01:57 — Michel explains Airbyte in two lines: open data movement into warehouses (and now agents).
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=117

02:53 — Why launch open source on GitHub: capture engineers at the “write a painful script” moment.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=173

06:53 — COVID reset: from a marketing‑focused product to an OSS platform that hit a hockey‑stick curve.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=413

11:01 — Project-market fit vs product-market fit: adoption is not monetization.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=661

14:41 — How Airbyte turned Slack into a rapid product feedback loop (ship next‑day fixes).
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=881

19:22 — The community trap: when your Slack becomes support, and how they course‑corrected.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=1162

23:53 — Cloud the hard way: why customers wanted control/sovereignty more than a hosted version.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=1433

29:22 — Building an enterprise motion: hire earlier, expect 6–9 month ramps, many more stakeholders.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=1762

33:26 — Fast path to Series A: publishing the deck, OSS adoption surge, and choosing investor fit.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=2006

Key Takeaways

1. Shrink scope to find signal.
Airbyte didn’t try to boil the ocean; it launched open source to solve one gnarly, universal pain: moving data from silos to value. By catching engineers “at the search,” they earned usage before monetization.

2. Separate project-market fit from product-market fit.
Community love ≠ revenue motion. Airbyte treated the GitHub traction as project-market fit, then built the monetization engine separately to reach true PMF.

3. Ship transparency as a growth channel.
Publishing fundraising slides, writing deeply technical posts, and narrating the build created trust at scale. Transparency reduced perceived risk and generated consistent inbound.

4. Community needs design, not just support.
Letting Slack become a help desk capped upside. Designing for champions, peer-to-peer help, and recognition programs turned users into advocates and contributors.

5. Control beats convenience in data infra.
Enterprises adopted Airbyte not just for connectors but because it runs where they need it. Control, sovereignty, and security often trump a pure cloud pitch in data movement.

6. Don’t hire ahead of platform complexity.
Moving from OSS to hosted cloud is a different business with operational drag. Hiring too fast created noise; starting small and iterating would have preserved product velocity.

7. Content compounds when founder-led.
For the first 18 months, Michel and co-founder wrote the playbook in public. Founder voice clarified positioning, attracted contributors, and set a high bar for later content ops.

8. Use community for real-time product discovery.
Posting lightweight polls/questions yielded 100+ responses in minutes, compressing research cycles. Community became an always-on signal router for roadmap decisions.

9. Enterprise motion is human-time, not server-time.
Longer cycles, more stakeholders, and ramp time are physics, not flaws. Hire earlier than feels comfortable, but in small, validated steps to avoid overextension.

10. Build for agents, not just analysts.
Agents are new “consumers” of data, demanding low-latency access and different interfaces. Replatforming around this shift is a multi-year moat, not a feature.

This episode is brought to you by our sponsor: ZoomInfo

ZoomInfo is the GTM Intelligence Platform built for sales, marketing, and RevOps.

By unifying data, workflows, and insights into a single system, ZoomInfo helps revenue teams find and engage the right buyers, launch go-to-market plays faster, and drive predictable growth. With industry-leading accuracy and depth of data, it gives your team the intelligence advantage to win in competitive markets.

It’s trusted by the fastest-growing companies and has become the category leader in GTM Intelligence.

Learn more at zoominfo.com.

Follow Michel Tricot

• LinkedIn:https://www.linkedin.com/in/micheltricot/
• X (Twitter):https://x.com/MichelTricot
• Website:https://airbyte.com/Airbyte

Recommended books

• High Output Management by Andrew S. Grove — A systems-first lens for building teams and measuring managerial output that informed Airbyte’s “window into the build” culture.

Referenced

• Airbyte: https://airbyte.com/Airbyte
• Airbyte GitHub org:https://github.com/airbytehqGitHub
• Airbyte OSS repo:https://github.com/airbytehq/airbyteGitHub
• Airbyte community hub (Slack/forum/events):https://airbyte.com/community/developersAirbyte
• Airbyte “Getting support” (Slack + forum):https://docs.airbyte.com/platform/community/getting-supportdocs.airbyte.com
• Accel:https://www.accel.com/
  
• Benchmark:https://www.benchmark.com

Host links

• LinkedIn: https://www.linkedin.com/in/sophiebuonassisi
  
• X (Twitter): https://x.com/sophiebuona
  
• Newsletter: https://thegtmnewsletter.substack.com
  
• Website: https://gtmnow.com

Where to Find GTMnow

• Website: https://gtmnow.com
  
• LinkedIn: https://www.linkedin.com/company/gtmnow
  
• X (Twitter): https://x.com/GTMnow_
• YouTube: https://www.youtube.com/@GTM_now
• Podcast Directory: https://gtmnow.com/tag/podcast

GTM 169 Episode Transcript

Michel Tricot: 0:00

People are willing to put time into the project and the product that we are building. How do you actually commercialize it? It’s a different story. And to me, that’s what PMF actually is, where everything goes super fast, every deal gets closed in like a week, two weeks, one month max.

Sophie Buonassisi: 0:15

You launched in 2020. Now you’re valued at over a billion dollars. Michelle didn’t play the typical fast launch playbook. He went open source first, community first, and GitHub first. And it ignited one of the fastest bottoms-up adoption curves in modern data infrastructure. Today, AirPyte is valued at over a billion dollars, powering data movements for thousands of teams, including over 20% of the Fortune 500. And they got there in a really interesting way. They built in public, compounded through community, and turned contribution into a distribution mode. In this conversation, we break down the stories and lessons behind all of this growth, including a really important lesson on separating product market fit from project market fit. All right, let’s get into it. Michelle, welcome to the podcast.

Michel Tricot: 1:11

Thank you for having me. Great to be there.

Sophie Buonassisi: 1:13

It is a pleasure. And it hasn’t been long since we saw each other earlier this week, in fact. So it’s great to see you again.

Michel Tricot: 1:19

Yeah, no, that was a good, a good event. Like that was the Tech Crunch one that was very solid.

Sophie Buonassisi: 1:25

Yeah, that was great. And your your uh session was highly attended. Sounded fantastic. Excited to pick your brain a little bit more intimately than at the event itself. And you launched in 2020. Now you’re valued at over a billion dollars. Take us back. We want to know the how behind this type of growth.

Michel Tricot: 1:43

Yeah.

Sophie Buonassisi: 1:44

And before we even get started from the beginning, a lot of our audience aren’t engineers. A lot of operators, a lot of founders. Give us a high level of AirBite. What does Airbite do? Kind of the two-liner for everyone listening.

Michel Tricot: 1:57

Yeah. So AirBite is an open data movement platform, meaning that we can take any pieces of data across any system and we can deliver it into a place where it will deliver value. So a very strong use case is going to be everything related to analytics. How do you go across your company, look at all the services that you have, all the data sources that you have, all the silos that you have, and how do you make it seamless to move that data into warehouse so that your analytics uh team can actually extract insight from it and make decisions from it. And that’s really how we started. There is a ton of use case when it comes to moving data. You know, we’re talking about agents these days, is like how do you get the data into agents? So that’s very much what the very high-level value of Airbite is.

Sophie Buonassisi: 2:44

Super helpful. And now let’s go back to the beginning. You launched on GitHub. Why open source as opposed to a traditional product launch?

Michel Tricot: 2:53

Yeah. So when you’re thinking about, let’s take the analytics use case as an example. You go from like the outcome you want to drive, which is I want to be able to understand my business. The first thing you think about is okay, I will need to have dashboards, I will need to have a team, I will need to have a warehouse. And the moment you have these two, what you realize is that you also need the data, obviously.

Sophie Buonassisi: 3:18

Yeah.

Michel Tricot: 3:19

And this is a very organic um behavior from people, which is it’s not thought through so much as a strategy, but more as an enabler. So they’re gonna go bit by bit thinking, oh, I need this particular silo, I need this particular silo. And it is very hard to actually think about the pain that it will be if you build it yourself, or it will be very hard also to find platforms that can support every single silos that you have. And for us, when we did open source, what we wanted is to go and talk to the team that are building all these different connectors. So when you’re an engineer and you’re being asked, oh, I need Stripe data to be in the warehouse, the first reflex that an engineer will have is go online, check how do I move data from Stripe, Salesforce, HubSoot or you name it, into my warehouse. And we wanted to catch these people exactly at that time. We wanted to provide them value the moment they have that little painful script that they have to write and give them something. So open source at that point is generally the best solution because I mean I’m an engineer, I’m a little bit lazy when it comes to if I can avoid building something, I will.

Sophie Buonassisi: 4:42

Yeah, fair.

Michel Tricot: 4:42

And open source is generally the solution for that, and that’s really why we went for like open source. The other reason is there’s an infinity of places where data can be. So it is impossible for a single company to make a product that will address all the long tails of data connectors. What we need is, and what the community needs is like, in a way, all working together in a goal of like addressing all these use cases. And that’s why open source for us was a solution. Like you, you know, you can think about the Linux kernel. Well, all the drivers are being built either by the community, either by by vendors, but the Linux project is not building all these drivers. They are asking the community to build those, and that’s how you just get to the best uh uh product on the market.

Sophie Buonassisi: 5:34

And it feels like we’re seeing more and more companies open source. Do you feel that also?

Michel Tricot: 5:39

Yes. Um, yes, and I think it’s because the technology, especially this, you know, open source is very, very present in AI, for example, because there is almost like a complete stop of the old world versus the new world. Like everything has to be reinvented. And people who are making decisions today have to catch up on a lot of context. So, what they do is actually they go talk to their team and ask them we I we need to create an agent for this particular use case. What technology should we be using? And open source generally works really well with technical profiles. And I think that’s one of the reasons. There are also a lot of things around sovereignty and control that comes with open source and also future proofing because you can always update the project yourself if you want to. And to me, that’s a direction that we’re seeing. And having a community that backs a project just you cannot beat that velocity.

Sophie Buonassisi: 6:42

Yeah, so true. So true. And okay, so you launched in 2020. When you uploaded the repo, did you know that it would take off the way that it did?

Michel Tricot: 6:53

No, we didn’t know. We are so in the story of Hairbyte, like Airbyte started really just two months before COVID really hit the world.

Sophie Buonassisi: 7:02

What a time to start. Yeah.

Michel Tricot: 7:04

And we had an initial product at the time, which was also related to data integration, but more geared toward marketing teams. And what happened with COVID is boom, all the marketing team got frozen, laid off, etc. etc. Because company had to figure out, okay, what does the world look like now? And you know, as a founder, you put your life into uh a company, into building a product, and you don’t want to be a vitamin that I like to joke about that is not going to survive a global pandemic. So what we did is we actually went back to the drawing board. And in July, like during the period of like March to July, we were building prototypes, etc. etc. But but we’re also talking a lot with the audience that we wanted to build a product for, which was data people. And all these people, they were always having a solution that they would buy, a solution that they will build, another solution that they would build, another solution that they would buy. So it was like a collection of tools everywhere just to move data. And what we’ve done is just keeping in touch with all these people and keeping them in the loop of what we were building, what product. So at the time during COVID, everybody, I think a lot of people were very available on LinkedIn. Yeah. So we’re very, very active on LinkedIn. So we were always trying to talk to the right people, going on a Zoom with them for like 15 minutes, 30 minutes, and then we would ask them, Do you want to be following what we’re doing? And say yes. And then we created the first mailing list that we had, and every time we had updates, we would just say, Oh, this is what we’re building. If you want to, we can give you a quick demo of what it looks like, and you can give us feedback. That was before we published the repo. And I think it was in November we actually put the um the repo out. And suddenly, first of all, like this initial group of people started to download the software, started to give us like real feedback, and from there it just went uh in hockey stick.

Sophie Buonassisi: 9:11

Yeah, incredible. How did you feel just seeing that growth after you said it yourself when you’re a founder? You put you put everything into a company.

Michel Tricot: 9:19

Yeah. It’s uh I felt very good in a way, which is people are willing to put time into the project and the product that we’re building, and yet it is super immature. And you know, we always talk about PMF in the the founder founding sphere. PMF, my definition, having seen that, is it’s when people are willing to go above and beyond to make something that is not yet mature, that is not yet working, and they are willing to put the effort to make it work because it is solving such an intense problem for them that this little pain of making it work is better than the big pain of having to do it yourself. Um, and yeah, it felt good. After that, yes, I knew that the technology needed to become better, but you have to launch.

Sophie Buonassisi: 10:08

Yeah, yeah, exactly. Usually, if you’re at a point where you feel like it’s good enough, it’s too late from a launch perspective.

Michel Tricot: 10:15

Exactly. Like you want to get the feedback as fast as possible. You just want to build what is actually going to deliver value for your community.

Sophie Buonassisi: 10:22

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Michel Tricot: 11:01

I’m actually splitting it because there are two paths in the life of Airbytes. There is what I call project market fit, which is we managed to create a project that was very much resonating with an audience, data engineers, data analysts, etc. And they were just taking the project and using it and contributing to it. Product market fit for me also comes when you start pulling the foundation also of uh monetization. And this is a different story because it’s easy to take a product from GitHub. How you actually commercialize it, it’s a different story. And to me, that’s what PMF actually is. So I would say open source was project market fit.

Sophie Buonassisi: 11:45

Got it. Okay. Well, take us through a little bit of the evolution then. Because you got project market fit. What kind of go-to-market decisions did you make along the way that helped you to get to product market fit from project market fit?

Michel Tricot: 12:00

We were not using regular channels. It was all about content. I mean, at the time content marketing was a thing, but I don’t think it was as uh as popular as it has been like in 2023, 2024. But we were just always pushing articles, giving details about how the what the company is doing, what the project looks like, and just getting people to be part of our adventure. And that created trust, that created curiosity, that created a lot of awareness. You know, we published our fundraising slides, for example. So that was a way for us of like engaging the community into what we are doing. So that uh that to me is something that not a lot of people have done in the past. So it was very uh, I think very I’m I’m pretty proud that we’ve done that. It’s very, very innovative. And then, yeah, like we’ve always been very strong on content, engaging with the community.

Sophie Buonassisi: 12:57

So but it is time consuming content. So how do you think about that as a founder? How do you balance your schedule? When do you work it in? What’s your actual cadence or was at the time for any kind of founders or operators listening that are looking to up level their content?

Michel Tricot: 13:11

Yeah. It is time consuming, but you know, if it’s working and you feel it’s gonna be working better than any other solution, you just continue and you you exploit that uh that channel as much as you can. Um after that, we yeah, we are now we’re doing we continue to do a lot of content, but we are also a lot more like traditional channels like ads, uh SEO, GEO, etc. etc.

Sophie Buonassisi: 13:39

So yeah. And did you write it all yourself? Did you hire a ghostwriter? Like when did you actually physically put kind of uh pen to paper, if you will, or fingers to keyboard?

Michel Tricot: 13:51

I would say the first year and a half, it was my co-founder and I writing. The team also was writing. So we really created that cute that internal culture of let’s write something. My VP of engineering wrote an amazing article about the pain of building connectors that we keep referring to, even five years later, uh, because it really explains the pain.

Sophie Buonassisi: 14:14

Yeah. Well, it’s funny too. Five years later, and the pain is still the pain.

Michel Tricot: 14:18

The pain is still the pain, and uh yeah.

Sophie Buonassisi: 14:20

Yeah. Incredible. Okay. So you lean into content early, and that helps sounds like create a bit of a tribe, and you have a very strong following of people that are passionate about the product and the space and the solution that you built. How did you think about actually taking that interest generated from your content and other means and turning it into more of a community motion?

Michel Tricot: 14:41

Yeah. For me, at that point, so we we also created a Slack community at the time. I think today we have about 25,000 people on it. And the way we created the community was in twofold. One is we were helping the community a lot, we are doing a lot of support because we are building the platform, and so every time someone had an issue, that was a product feedback for us. So we spent a lot of time in 2020, like end of 2020, beginning of 2020, like all of 2021, and uh we we continued after, but that was very, very intense, a year and a half, where we were always on Slack. Every single issue that was reported, we would just have something shipped the day after or like the week after. So I think that created that’s that was one thing that helped uh building the community. And then what we did is we also identified a lot of champions within the community, like people that wanted to help other people. And yeah, we really engaged with them. We actually hired one of the first community managers that we that we’ve had at uh at Airbite, is someone that we actually brought from the from the community that was he started to build an airflow connector, like an airflow integration, and say, Oh man, that’s amazing. And we didn’t ask him anything, and at some point we asked him, like, do you want to uh to do it your full-time job, like to engage with the community, write content, etc. etc. And they’re like, Yeah, let’s do it.

Sophie Buonassisi: 16:12

So it’s amazing.

Michel Tricot: 16:13

That to me is like the community engagement is is absolutely key. That’s how you create that tribe, that’s how you create that snowball effect. It’s it’s not something that you put on, you say, I’m building community, and it’s gonna happen by itself. No, it is something that has to be worked on, and you have to be intentional about what you want to do uh with the community.

Sophie Buonassisi: 16:34

If you were to look back now with the benefit of hindsight, it sounds like community and content are two pillars that helped with your go-to-market motion. Yep. Is that correct? And also are there other pillars that you’d say were really pivotal in your growth?

Michel Tricot: 16:49

Um we did a lot of events, actually, very specialized events around uh data, whether they were open source events or like Snowflake or Databricks events, it’s just always getting where the people were. And that was something that worked pretty well. It allowed us to get a lot of people, new people interested, or just to engage in real life with people. Yeah um yeah. I would say, and here’s really what what happened between 2020 and 2023. After that, we had we added a few other things on top of uh like how we engage with the community, etc. etc. But that to me was very very much like the three pillar of what we’ve done. It’s like giving a window into the company to people, giving in a window into how the the engineering team is building, giving a window into everything we’re doing.

Sophie Buonassisi: 17:49

And do you still operate that way?

Michel Tricot: 17:51

Uh a little bit less. Um but we continue to have that constant engagement with uh with people. Like, you know, when the the great thing that when you have a community like that is someone in whether it’s a customer, whether it’s uh it’s a user, is going to ask you a question or a feature, and then you’re it’s gonna go into your head and say, okay, is that really useful? Or is it just for that person? And so what you do is you go in your on your community and you you just post a very simple question, like is that something that resonates with you? And in 30 minutes, you have like hundred people that are replying, yes, no, yes, but in that way. So it really accelerates how you do product discovery, how you do uh product development. So that’s uh that’s more like how we’ve changed a few things uh along the way. It’s like we’re we’re leveraging the the community a lot more for like what new features we should be building rather than really the the the core value proposition of the ambite.

Sophie Buonassisi: 19:00

Right. It’s uh a feedback loop, yeah, essentially. Yeah, great, and a very, very rapid one too.

Michel Tricot: 19:06

Very rapid one.

Sophie Buonassisi: 19:07

So content, community events, pillars that you did incredibly well to reach the point you are now. There’s always the other side of the story of you know, what were the the areas that didn’t quite hit as well or almost the near-death experiences along the way that every startup goes through.

Michel Tricot: 19:22

Yeah, so as I said, like the beginning of the of how we are engaging with the community was very a lot of support, like helping them be successful with the product. And there was this moment where even in our in how we were working, our community became very much of a like support channel rather than like building a uh a community that was just helping each other. Um, and that to me was uh is something that we could have been more intentional at the beginning around how do we um how do we get to like community members helping each other, community members like meeting each other outside of just like rather than becoming a very much like support-oriented um uh community. And the thing is, once this habit is taken, it’s very hard to shift uh into a different direction. I think we succeeded, but it took us a lot of time. We should have been more proactive thinking about okay, the community is amazing, but what is the future? Like, how do we make it more vibrant, more um yeah. How do we create a community of professionals that work in data and that are just gonna learn from each other and not just from us?

Sophie Buonassisi: 20:42

Yeah, it completely makes sense. It’s kind of the the the tell all tales, the tell all tale story of community is a lot harder in practice, and it does require some really deep intentionality around fostering.

Michel Tricot: 20:55

It does, it does.

Sophie Buonassisi: 20:56

Yeah, and what does that team kind of composition look like right now at Airbite?

Michel Tricot: 21:01

Um so we have we have a we have a DevRel person, and this this person is more um focused on the like the content strategy geared, oops, geared toward the community. And we have a community manager, meaning someone that just engages, identifies champion, uh, gives them access to um early features, etc. etc. And we also have people um in internally we call them like customer engineering, where their focus is to make sure that every product feedback around connectors is being funneled through the team to make sure that our connectors keep getting better and better and better. So this is more like for the contributors of the platform. So we really have a difference between like the users of the platform and the contributors of the platform, and we handle these two groups differently.

Sophie Buonassisi: 21:58

Gotcha, gotcha. Okay. What are some other areas that you know along the journey, again reflecting back, have just been some of the most pivotal things that maybe you don’t you don’t see or talk about as much?

Michel Tricot: 22:11

Um I think that was the the realization of why are so many companies using airbite. Is it just connectors or is it something else? And connectors is a is level one, but there is a second level to it, and it took us a little by a little bit of time to figure it out, is people were also using data, uh airbite, because there was so much red tape around the data that they had internally, that having a platform that they fully control that runs within their infrastructure, it’s a byproduct of open source. And we did not realize uh I would say like fast enough that that was one of the key reasons why so many teams were adopting airbytes. So, you know, when we started to to do the airbyte monetization, we said, okay, we’re gonna follow the we’re gonna skip the step of doing support for people that are deploying airbytes, and instead we’re gonna go directly to a cloud product. And very quickly we realized, yes, cloud is getting traction, but we are not able to convert every person that is using airbite to using airbite cloud. And at that point, we just went back to the drawing board, started to talk to them, and that’s when we discovered that in that case, like product market fits was not just connector. It was the fact that these pipes were under their control. And that was a big, a big thing, and I would say we we wasted a little bit of time on trying to build something fully cloud when what people needed was control and sovereignty.

Sophie Buonassisi: 23:53

Got it. Okay.

Michel Tricot: 23:55

More like, you know, when you’re searching for PMF, it’s not a straight line.

Sophie Buonassisi: 24:00

Never linear, never linear, no. And what are you most excited about thinking now forward?

Michel Tricot: 24:06

Yeah. Well, you know, every time I hear about how do I make I mean to me, like the AI wave that is happening right now is just one of the most exciting things for me and for the for the company. Like analytics is very much a core part of what we’re doing, but we’re getting so much pull into different types of data access. And that is something that we’re today encoding into the platform and into our connectors. It’s not just humans consuming data today. Yeah, it’s agents that can discover what’s available, discover what it looks like, and make decisions. So, yes, the technology is not yet completely mature on either side, whether it’s airbite, whether it’s like agency platform, etc. etc. But you can see how fast it’s moving, and I think it’s very energizing, especially in the infrastructure world, to see that that energy being uh being injected. So that yeah, I I I talk about it all the time.

Sophie Buonassisi: 25:06

So Yeah, no, that’s fantastic. And I mean you mentioned that at the very beginning around how now it’s agents consuming this type of data. How does that transition in the overall industry? What does anyone need to know about what this transition actually means?

Michel Tricot: 25:22

Yeah. You need to you need to forget about a lot of your existing patterns. You know, I was chatting with uh with a CTO uh last week, and he told me very bluntly, I don’t know, maybe he was trying to uh to be a little bit uh uh provocative here, but he said he told me, Michelle, all the technical knowledge I had stopped two years ago. I had to fully reinvent myself and reinvent my team. Uh so yes, some things are still transferable, but your default should always be thinking about how do I build in that new world? Is there a solution? No. Okay, maybe I go back and use the techniques of the of the the older world. But that’s really what what I’m seeing is people have to rethink how they are doing their job. Because one thing that is happening in Teams is a lot of people are using AI today to remove from their play the thing that they don’t like doing. That’s very easy. Like people have a very strong uh willingness to stop doing the things they hate doing. So for that, like AI is is is amazing. Like, you know, if you’re an engineer, right like writing unit tests, writing integration tests, that’s great, but that’s just level one. The moment you actually start changing your mindset is when you’re looking at the things you like doing and how can you leverage AI for those. But those are hard because the things you like doing are the things also that can bring you a lot of energy in your in your day-to-day. And those are the things that people should really be focusing on. On okay, this thing that I’m doing every day, I love doing it, but can I do it using AI, using an agent? Can I ask my engineering team to build an agent to solve that particular problem? Is there an AI product that exists that can do it and removes that from my plate? And then I can focus on more things and I can become faster. But to me, it’s really about reinventing um reinventing it. For data, the way you access data is very different. Yeah. Um but just having a warehouse doesn’t cut it. Like you need to have like an agent does live processing, it needs to have like little pieces of data here and there. You need to provide access to the agent in a different way. So that’s and that’s what that’s what we’ve been building.

Sophie Buonassisi: 27:54

Yeah, absolutely. How did that change your product roadmap overall? Did you have like this crazy moment in a way where it was like the realization that you entirely have to pivot? Or is it gradual?

Michel Tricot: 28:07

I I wouldn’t say it’s a it’s a pivot because it’s more like a an extension, but also sometimes we like to talk about replatforming, which is we’ve we’ve built the plat the platform for like a specific use case in a specific course, but there are new ones that are coming that are going to pick up massively over the next few years. And we need to be thinking about taking all the learnings that we’ve had here, and how do we think about replatforming it to just have a larger breadth of use case? So that’s that’s more how we’re thinking about it. Uh, I don’t know, I would say 2024 is when we even even before like summer 2023 is is when we started to like tippito into it. But 2025 is a moment where we we went all in on that. So we still have the the analytics product, it’s a it’s an amazing product, but we are really building on top of that, like leveraging part of it, but also rebuilding a platform that allows agents to uh to interact with data. So it’s pretty pretty cool.

Sophie Buonassisi: 29:12

Super cool. And you’re hitting the ground running, tons of growth, you’re hiring lots of folks on the team. Like, how do you think about developing that team to take it to the next stage of growth?

Michel Tricot: 29:22

Oh, you have to be hammering, yeah, using AI every single day, every single or-ens that I do every Wednesday morning. It’s about putting the spotlight on new uh new way of leveraging AI. And not just the layer one, which is do the thing you don’t like doing. It’s really about how are people building things that change their, actually change the the definition of their job. So well, if it’s if it’s on sales, it’s gonna be around like how do they do uh like discovery of account, it’s gonna be how they connect, um Like different news together, how do they connect to like past conversations that’s happened on support? So it’s really about like aggregating all this information in one single place and have like all the context available to them at the right time. On engineering, well, we talked enough about engineering and how agents are transforming the lives of engineers, and that’s what we’ve been doing at Airbytes for the yeah, for the for the past year.

Sophie Buonassisi: 30:26

Yeah. And so it sounds like you disseminate this information internally. You said weekly.

Michel Tricot: 30:31

Weekly.

Sophie Buonassisi: 30:32

What does that look like? Everyone’s on a team call weekly, or how are you spotlighting people?

Michel Tricot: 30:36

Yeah, so the whole company we’d spend like 30 minutes together and we go over like some updates, but then we always have like one presentation that is just about AI. And myself, like I generally start the whole hand and I always have a few slides around like the wins of the week. Yeah. And well, we have a channel on Slack where people just write their wins and I just gonna pick one or two. And that’s why I mean like pulling the spotlights on specific individuals that have done something innovative with it. And I think that creates like a good dynamic. Like people want to be on the win slide, etc. etc. So it creates a little bit of like internal competition.

Sophie Buonassisi: 31:14

Yeah, internal competition and also ideation. Exactly. I find sometimes the biggest blocker is the inspiration and ideation around like what can I actually do with AI?

Michel Tricot: 31:23

Exactly.

Sophie Buonassisi: 31:23

So seeing other people’s use cases is helpful.

Michel Tricot: 31:26

So that’s why like it’s always a topic every single week. And then we have like tons of sharing uh channels where people just every day we have one that’s called My Life with AI. And every day there are like 10, 20 posts on it of people saying, like, oh, Cloud Code was terrible on this one. Oh, Cloud Code was amazing on this one, and people just build that context internally on like what is good at today, what is becoming good at today, etc. etc. So like you you need to create like this very, very strong connection.

Sophie Buonassisi: 31:57

It’s such a cool period of time. It’s like a level setting where no matter how senior you are, everybody’s on the same learning plane, which is so, so cool.

Michel Tricot: 32:04

Yeah, and that goes back to what my friend was telling me. My knowledge, I need to just re-relearn.

Sophie Buonassisi: 32:12

Relearn. That’s a good way of putting it. We’re all relearning, rewiring ourselves.

Michel Tricot: 32:16

Rewiring, yeah.

Sophie Buonassisi: 32:17

And Michelle, you have a technical background. Your technical founder. What was it like to build a go-to-market engine as a technical founder?

Michel Tricot: 32:27

Very good question. Um so the first thing is I’m not alone in this adventure. My co-founder is uh is uh a little bit more on the on the marketing team, on the marketing side. It was actually the in a way it was the first devrail of airbite. So we’re working together on like technical papers and technical articles, but otherwise he was doing a lot of the heavy lifting when it comes to to writing to writing content. I go for like I I understand pretty well like the the psychology of users. So we started with a very, very strong uh bottom-up motion. And this is a place like even if I don’t have experience like building a go-to-market engine, we did pretty well at building that bottom-up motion. The place where I needed a little bit more support uh was on like how do we do the the top-down, how do we go to toward enterprise.

Sophie Buonassisi: 33:26

How did you get that support?

Michel Tricot: 33:28

So I I actually hired um uh a CPO that had been working solely on enterprise um um companies. But I took someone that is not just a product person, but really someone that has a very good, that has a lot of breast in terms of like both product, but also like how do you actually create this engine, this enterprise engine. So to me that was the the first step there. Uh it started in um 2024, I believe. Yeah, that was January 2024. And from there we started to like bit by bit build the enterprise engine, starting small at first, because you need to learn. Yeah, and yeah, when uh went all in there uh at the beginning of the year, because yeah, 2024 is really when we we launched the the enterprise product and very, very quickly picked up. So we had to uh we had to um to expand there. We did do a a few a few mistakes along the way, which is selling to enterprise takes time. And when you’re used to like bottom-up motion where everything goes super fast, every deal gets closed in like a week, two weeks, one month max, suddenly you are like in this longer sales cycle, a lot more stakeholder, like hiring people, you need to rent them, etc. etc. So what I’ve learned here was like you have to be a lot more proactive in thinking about hiring over there. So that that was that was a big learning for me.

Sophie Buonassisi: 34:59

And the ramp time proactive, do it earlier.

Michel Tricot: 35:01

Would that be the distilled lesson for everyone? Yeah, while still being like because it takes like six to nine months to actually deliver, you want to also edge your bet a little bit. But that’s the that’s the idea. Like it’s not gonna happen from one week to the next. It’s gonna take a lot more time.

Sophie Buonassisi: 35:21

It’s a a great piece of advice for anyone listening to. Because most of the time companies are wanting to go a little bit more enterprise, and it’s challenging to to cross that chasm unless you’re intentionally planning for it, which sounds like a big lesson on your side.

Michel Tricot: 35:37

And there are more physical limits. When you go bottom up, there is a lot of things that you automate. Like you have Saleserve, you have like a very automated uh sales cycle, but when you go to to enterprise, well, it’s a lot of like human time. Um so yeah.

Sophie Buonassisi: 35:53

And did you feel like you went enterprise? Why did you go enterprise? I guess. Were you seeing signals or was it that you wanted to go enterprise?

Michel Tricot: 36:01

No, we we have about uh 20% of our um of the Fortune 500 that are using AirBuy today, we’re working like with like very, very big media company or banks. And I could feel like the the lack of maturity of the team on like how do we how do we sell to that audience, how do we sell the the product, and also what is missing in the product. Like when you’re selling to uh data teams, well they have their own requirements, but when you start selling like across different uh business units or across different teams, like there are suddenly a lot more things that you need to be adding to the product that are not directly tied to the value that you provide, but that are actually tied to how this uh company actually buys software and actually uh leverage software. So that was it’s it’s both on the go-to-market side, but it’s very, very tied to the to the product.

Sophie Buonassisi: 37:00

Okay. Michelle, you raised your Series A two months after your seed round. Take us through that process.

Michel Tricot: 37:09

Yeah. So we started the like raising our seed round in November 2020. All was finished in uh in January. By the way, we had to uh delay the announcement because we’re trying to buy the domain. And we didn’t want to pay the the premium of uh being funded.

Sophie Buonassisi: 37:29

So you had your round, you just didn’t have the domain. Did you have a website on a different domain?

Michel Tricot: 37:34

Yes, we did.

Sophie Buonassisi: 37:35

Okay, but you’re trying to get the main domain for the announcement. How did you get it? Did you have to just work out the money or did you go negotiate?

Michel Tricot: 37:41

No, but we it we we had it for like a a good uh a good price. Okay. Perfect. You got it. Secure lots of tract action here. Um and the thing that happened after we actually announced our series uh our seed, this is the first time we had put our slides um live. And it really created a lot and lot of traction on the open source product. Like people, because it was really solving a very, very, very painful problem for that audience. And our numbers went like through the roof between like January and May. And that’s also when we started to build the engine to make sure that contributors could be also involved in the project. Before it was just us building because there was a lot of foundational work that needed to do. But we opened up the repo for external contribution. I don’t know, it was around March or beginning of April, and it picked up really fast. And I think at that point, when you see an industry that is moving so fast, like data, uh at the time it was not even AI, it was it was just data, you see that boom, suddenly we are present in like 5,000. Um I don’t think it was a little bit less. Um, it was maybe a thousand uh different companies after just releasing the the repo for like a few months. That creates a lot of uh of attention. And I think it’s a very innovative way of like solving the problem of how do you move data around. So that’s uh that was uh I think that I think they did a good move, like going for like and we did a good move on uh on on raising the series A here, and it also allowed us to just invest more into growing the community.

Sophie Buonassisi: 39:34

So are there any drawbacks to doing that? Yes. A lot of companies are evaluating timeline, and we speak to many companies and advise them around timelines, and two months is very quick.

Michel Tricot: 39:47

Yeah.

Sophie Buonassisi: 39:47

Now, what are the drawbacks or the pros to doing so?

Michel Tricot: 39:50

Well, the one that is very simple is when you release um an open source project, you don’t have you don’t get paid for it. Yeah. So the drawback is that suddenly it puts you on uh on um the expectations are high. That’s that I would say that’s pretty much it. But at the same time, you know, when we when we raise the series A, and even when we raise the seed, we chatted with these investors, and all the time we were pick we were picking the ones that had a very deep understanding of what it what it means to build open source. What it does it means to build an open source company. Because you don’t do open source for the sake of doing open source, you do it because you have a strategy. And ours was very strong bottom-up awareness, building a standard, and those can take a little bit of time. You know, you can look at you can look at Elastic, you can look at Ashi Corp, etc. etc. Like all of these, like you create a very strong base, yeah, and then you figure out like all the different basically your real product market fit. Um, and so I would say like not like that’s a risk of drawback. We did not have it because we had a a very uh knowledgeable um uh investor on that front.

Sophie Buonassisi: 41:17

Got it. So it sounds like a learning for anyone thinking about this kind of strategy or even just overall with the alignment around expertise with your investor.

Michel Tricot: 41:27

Exactly. Okay. The partner you’re working with, well, yeah, they’re gonna be here for a very long time. You better be very aligned with them on like what you want to do and also like their tolerance for yes, things don’t always go right.

Sophie Buonassisi: 41:44

And how do you evaluate that from the founder seat? Because naturally we evaluate it all the time from the other side.

Michel Tricot: 41:49

Yeah. Um, well, like always, when you in a way you you recruit someone, yeah, back channels is the best way. So you talk to other companies, you you you search for the company where it went well, the one that where it didn’t go well, and create a relationship with the with the people that have been working there and and see what they have to say. So excellent. And also you see, you know, you you also see like during the during the the fundraising process, like is how much are they um evolving your thinking? Uh, you know, when we raised with Axel. Yeah. Like I remember spending like two or three hours with uh with Amit at the time, and he asked questions that in a way helped us improve how we were thinking about the the future, the positioning of Airbag, and what to do. So there was already some very strong value on like working with uh with him or working with uh with Shetan at benchmark. It’s like they they help you think. And yes, they have their opinion, I have my opinions, but at the end of the day, like are they allowing you to see places what you don’t know about? Right. And if so, I think that’s a that can become a great partnership.

Sophie Buonassisi: 43:08

Great advice for anyone listening, thinking about that investor founder relationship. Okay, take us back to a little bit earlier. If we were to circle back to your product market fit, were there any kind of biggest challenges to that? I think there were some big kind of moments around that.

Michel Tricot: 43:30

Um yes. Um I would say like in 2022, that’s when we we started to work on the on the cloud product, which by the way, if you’re an open like for open source founders, like going from an open source product to an actual cloud product, it is super hard. Because hosting and managing something when what you’ve done is like providing something that you don’t need to really host and manage, etc. etc., this is very, very hard. And in 2022, we released like the let’s call it like the private beta of uh of Airbite Cloud. There was a ton of problems, and which by the way is completely normal, but we underestimated how complex it was to build a platform. And because we had this big plan of like how we’re gonna be monetizing airbite, etc. etc., I would say we we hired a little bit ahead. And that to me was uh was a mistake because it also creates a lot of noise internally. It like disrupts the product team, it disrupts engineering, it creates like a lot of noise around like building the best product. And that to me was uh I don’t know, I would say was a bad decision. Uh we we had to course correct, but I would say it’s like especially when you’re starting something new, just start small, expand rather than go go bottom up in terms of how you’re building your your your company and your organization rather rather than top down. There is a moment when you can do top-down when you have like a lot more predictability, but at the beginning it’s uh it’s a mistake.

Sophie Buonassisi: 45:14

So bottom up.

Michel Tricot: 45:15

At least for us it was a mistake.

Sophie Buonassisi: 45:16

Yeah, well, it sounds like in everything that you did, you were always looking at signals. Like I know I’ve heard you say that open source allowed you to have signal density. And through the community aspect, you’re talking about using that as signals and feedback too, and same with this bottoms-up approach.

Michel Tricot: 45:31

Yeah, yeah. I’m a I’m a very bottom-up person on that front. But at some point, yes, when I see it’s always the same thing, like we all build we’re building an engine. So we need to figure out what is the the MVP of that engine. Yeah. And to do that, you need to find people that are extremely driven, that are okay with uncertainty. But the moment you start getting like an initial version that is working, that’s when you can start like putting more uh like more thought into what it should actually look like. But first you need to validate something. Definitely.

Sophie Buonassisi: 46:05

Well, this has been fantastic, Michelle. Really, really appreciate the time. A couple last questions. You know, you have learned immensely throughout the journey, but are there any books that you’ve particularly been influenced by throughout your career and life?

Michel Tricot: 46:20

Yeah, you see, I don’t know if you remember, but I said giving a window into how things are working to the outside world. Yeah, I did not invent that. It’s like when I was I think it was in 2014, I was just um, or 2013, I was just starting to uh to manage my my first team, my first team at the time. And my CTO gave me this book from um it’s called Um High Output Management. I think it’s now it’s a standard. Uh and it really, you know, when you go from being an IC to starting to manage people, it’s very hard to find like the right feedback clue for like, are you doing a good job or not? Like what does it mean that you’re doing a good job? And also how do you build team as systems? And I think that book was just transformational for me because I like good theory, yeah, and that theory was very very strong, and like how you create, how you how you build, how you build the system, how you monitor these systems, and um and uh how you take pride of the work when you’re not the one always doing the work yourself.

Sophie Buonassisi: 47:31

Yeah. So great, fantastic. Well, that will be in the show notes for anyone curious to take read and pay it for it a little bit. Where can people follow along your journey in airbytes?

Michel Tricot: 47:40

Uh well, the I would say the entry point is always gonna be airbite.com.

Sophie Buonassisi: 47:45

There we go.

Michel Tricot: 47:46

I’m on I’m on LinkedIn, I try to post as much as I can.

Sophie Buonassisi: 47:49

Yeah.

Michel Tricot: 47:50

Uh content marketing. There we go. You’re very good at it. And giving and giving a window to uh to the to the people uh on what we’re doing. And and yeah, and after that, like you can go on Slack, on our GitHub repository, and just or just try the product.

Sophie Buonassisi: 48:06

There we go. There’s many ways. Many ways.

Michel Tricot: 48:08

Point of entry is going to be the website. Perfect.

Sophie Buonassisi: 48:11

The website itself. Well, Michelle, this has been fabulous. Really appreciate the time and you sharing your journey and insights.

Michel Tricot: 48:15

Yeah, thank you for having me. It was a great conversation.

Sophie Buonassisi: 48:18

Absolutely.

The post GTM 169: How Airbyte Hit $1B: The Open-Source, Community-First Playbook appeared first on GTMnow.

Hello and welcome to The GTM Newsletter by GTMnow – read by 50,000+ to scale their companies and careers. GTMnow shares insight around the go-to-market strategies responsible for explosive company growth. GTMnow highlights the strategies, along with the stories from the top 1% of GTM executives, VCs, and founders behind these strategies and companies.

When you look at the major software companies, Rob Giglio has been instrumental in building the go-to-market engines for most of them. He led at Adobe (during its pivotal shift to the cloud), DocuSign (during its explosive PLG growth), HubSpot, and now Canva, where he’s the Chief Customer Officer (including sales and success).

When we find someone with a track record like this of scaling companies, we dig in to uncover their foundational principles. After listening to Rob deconstruct his how he grew these companies, we’ve distilled three key lessons.

Lesson 1: Apply CPG discipline to de-risk your GTM

Lesson 2: Build a loyalty engine, not a sales funnel

Lesson 3: It’s all about humans, so focus on substance and simplicity

Below, we dive into each lesson. This is the first part of a new series on lessons from some of the top 1% leaders in B2B SaaS.

Lesson 1: Apply CPG discipline to de-risk your GTM

This lesson comes from Rob’s time in consumer packaged goods (CPG), where a marketing mistake is physically and financially costly. If you print the wrong label on a million cans of soup, you can’t just push a quick fix. This taught him that “it’s expensive to be wrong, so you better be thoughtful.”

While software allows for more iteration, Rob argues that B2B teams are often too reliant on gut feelings and skip the upfront rigor that de-risks a launch. His advice is to adopt two powerful tactics from the CPG world.

1. Master concept testing.

Before building anything, CPG companies create mockups of a new product, complete with packaging and pricing and test them with target consumers. This simple step validates demand and messaging before millions are spent on development and manufacturing.

Both product and message testing are key for implementing this lessons. Solutions like Wynter are helpful for getting messaging in front of your ICP quickly.

2. Win valuable segments, not the entire market

Rob uses a brilliant beer analogy: “Almost no beer manufacturer says to themselves, ‘I need to own the entire market of beer.’ They pay attention to segments.” They own ‘beach beer’ or ‘football beer’. Software companies, in contrast, often try to be everything to everyone, which leads to generic messaging that doesn’t resonate deeply with anyone.

Instead of defining your ideal customer profile (ICP) by firmographics alone (e.g. 500-1,000 employees in fintech), define a behavioral or psychographic segment. Who are you really building for? Is it the “compliance-first IT leader” or the “fast-moving marketing team”? Choosing a specific segment clarifies your product roadmap and makes your marketing infinitely more potent.

Lesson 2: Build a loyalty engine, not a sales funnel

Many revenue teams are obsessed with the ‘close,’ viewing the sales transaction as the finish line. Rob believes this is a critical error. The ultimate goal is not the sale, it’s loyalty.

This framework changes how you design your entire customer experience. At a former company, an intern who noticed it was incredibly difficult to sign up but took only a single click to cancel. They were inadvertently optimizing for churn.

A loyalty-driven model flips this. It removes all friction from onboarding and adds thoughtful friction to offboarding, not to trap users, but to remind them of the value they’re leaving behind.

At Canva, this is built into their GTM. Their customer journey framework doesn’t end at purchase, it extends all the way to loyalty.

Here’s an example a Canva’s cancellation modal:

A simplified version of Canva’s Loyalty Journey:

The key insight is that purchase is just a midpoint. The real work is driving adoption and growth to earn advocacy, which in turn fuels the top of your funnel.

Lesson 3: It’s all about humans, so focus on substance and simplicity

When asked for the single biggest mistake people make in B2B marketing, Rob’s answer was immediate: “calling it B2B marketing.”

You are never marketing to a building or a logo. You are marketing to a human inside that building. The moment you forget this, your marketing becomes abstract, filled with jargon, and ineffective.

To market effectively to people, Rob’s playbook is to focus on two things:

1. Substance over sizzle: Substance wins every time. While it might not win quick, it will win the most. A splashy campaign or a perfectly executed sales process might win a deal, but if the product doesn’t deliver real, tangible value to the person using it, you will never earn loyalty.
2. Drive substance through simplicity: The best way to deliver substance is through simplicity. A simple product is easy to adopt, a simple message is easy to understand, and a simple sales process is easy to train and scale. Rob’s test for simplicity is powerful: it must be measurable, describable, and trainable. If your own employees can’t explain what your product does in a simple sentence, how can you expect a customer to?

Rob’s lessons tear down the artificial wall between B2B and B2C to reveal a core truth: whether you’re selling software or soap, you’re in the business of earning a person’s loyalty. The path there isn’t through complex sales motions, but through a relentlessly simple, substance-driven experience.

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If you’re looking to scale your sales and marketing teams with top talent, we couldn’t recommend our partner Pursuit more. We work closely together to be able to provide the top go-to-market talent for companies on a non-retainer basis.

GTM industry events

Upcoming go-to-market events you won’t want to miss:

• INBOUND 2025: September 3-5, 2025 (San Francisco, CA)
• GTMfund Dinner SF (private registration): September 10, 2025 (San Francisco, CA)
• Pavilion GTM Summit: September 23-25, 2025 (Washington, DC)
• Dreamforce: October 14-16, 2025 (San Francisco, CA)
• GTMfund Dinner (private registration): October 22, 2025 (Austin, TX)
• GTMfund Dinner (private registration): November 18, 2025 (Toronto, ON)
• GTMfund Dinner (private registration): November 19, 2025 (New York, NY)

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This newsletter was written and edited by Sophie Buonassisi, Max Altschuler, Paul Irving and the GTMnow team (not AI!).

The post Lessons from Canva’s CCO appeared first on GTMnow.

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What’s actually working in go-to-market right now? In this live panel from the GTM Fund AGM, three early-stage leaders from three exceptional companies—Centari, Atrix AI, and Gaiia—break down how they’re closing enterprise deals in some of the most challenging verticals: legal, pharma, and telecom. From viral LinkedIn content and founder-led dinners to the now-infamous “donut drop” strategy, this episode is packed with practical, first-principles GTM plays you won’t find in a sales playbook.

Kevin Walker (Centari) – Founder & CEO of Centari, a legal tech platform providing deal intelligence to large law firms and, soon, financial services. A former M&A attorney at Paul Hastings, Kevin brings deep insider knowledge to solving complex legal workflows.

Vera Kutsenko (Atrix AI) – Founder & CEO of Atrix AI, a platform helping medical affairs teams at pharma and med device companies capture and operationalize real-world insights. Vera has become a thought leader in AI for regulated industries—recently authoring a viral book on AI in medical affairs.

Steven Farnsworth (Gaiia) – VP of GTM at Gaiia and early GTM leader at Workato and Outreach. Gaiia is an end-to-end ERP, billing, and CRM platform for independent internet service providers (ISPs), tackling a niche but high-value market with massive infrastructure needs.

Discussed in this Episode:

• Centari built trust with top law firms by pairing deep domain credibility with a thoughtful, relationship-driven sales approach.
• Atrix AI sparked inbound demand by turning a single viral LinkedIn post into a full-length book on AI in medical affairs.
• Gaiia chose not to hire SDRs, focusing instead on high-ACV deals and personalized outreach in a tightly defined TAM of telecom providers.
• Gaiia’s “donut drop” strategy—personally delivering treats to rural ISP offices—created brand awareness and unlocked new pipeline.
• Both Centari and Atrix AI scaled founder-led sales by hiring a Chief of Staff to operationalize and extend GTM efforts.
• Atrix AI uses educational AI workshops to qualify buyers, build trust, and stand out in a noisy vendor landscape.
• Centari combats pilot fatigue and skepticism in legal tech by showing deep empathy, hiring former lawyers, and proving value early.

If you missed GTM 151, check it out here: How to Scale Vertical SaaS in 2025 | Dennis Lyandres (Ex-CRO, Procore)

Highlights:

03:00 – Why Atrix AI scaled founder-led sales with viral content and thought leadership

06:00 – The accidental (and wildly successful) AI & medical affairs book launch

08:00 – Centari’s early GTM strategy: legal empathy, cookies, and product conviction

11:00 – Gaia’s high-ACV model and why SDRs don’t make sense for their TAM

20:00 – The Donut Playbook: creating pipeline by showing up IRL

23:00 – Why Chief of Staff was a critical early hire for scaling sales ops

27:00 – How Gaia is thinking about building community in a slow-moving vertical

28:00 – What’s next: repeatability, vertical expansion, and community infrastructure

Guest Speaker Links:

1. Vera Kutsenko LinkedIn: https://www.linkedin.com/in/verakutsenko/
2. Stephen Farnsworth LinkedIn: https://www.linkedin.com/in/stephen-farnsworth/
3. Kevin Walker LinkedIn: https://www.linkedin.com/in/kpwalker1/

Host Speaker Links (Paul Irving):

• LinkedIn: https://www.linkedin.com/in/paulsirving/

Where to find GTMnow (GTMfund’s media brand):

• Website: https://gtmnow.com/
• LinkedIn: https://www.linkedin.com/company/gtmnow/
• Twitter/X: https://x.com/GTMnow_
• YouTube: /@gtm_now
• The GTM Podcast (on all major directories): https://gtmnow.com/tag/podcast/

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Learn more at https://trinet.com/gtmnow

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UserEvidence is the Customer Evidence Platform that lets you collect feedback, curate success stories, and create content that credibly proves the value of your product.

Learn more at https://userevidence.com/gtmnow

GTM 152 Episode Transcript

Steven Farnsworth: We’re just kind of wowing the market with what we’ve built.

Kevin Walker: if you’re doing a strong founder-led sales motion, the hardest thing to scale is yourself

Vera Kutsenko: I did not expect it to go viral, and it did.

Steven Farnsworth: And the number of people who come up really excited about Gaiia, but are in year three of a 15 year contract, or a 10 year contract is shocking.

Vera Kutsenko: I’m only one person. I can’t be at every single trade show all the time. So I thought to myself, how do we scale this?

Steven Farnsworth: I’m not convinced s we’ll ever hire an SDR

Kevin Walker: Where we’re right now, kind of transitioning from that C to series, A stage of Go-To-Market motion.

Steven Farnsworth: I never thought to ask the question.

Sophie Buonassisi: Before we dive in today, a quick important message from our sponsor. Partner TriNet, a trusted HR provider to startups and scaling companies. Every early stage founder is told to focus on product and growth, but behind every product launch and revenue milestone is a team, and building that team is one of the hardest and most important parts of the journey.

Build the team that builds the company that is part of your Go-To-Market strategy, responsible for growth, hiring the right people, keeping them supported, and creating the infrastructure to help them thrive is critical. Trying to exist to make that easier. TriNet’s Full suite of HR Solutions is designed to support companies at critical inflection points from early traction to scale.

Learn more@trinet.com slash GTMnow to see what’s possible for your business. That’s TriNet, T-R-I-N-E t.com/gtm NOW. [00:02:00][00:03:00]

Wow. The feedback from last week’s episode where we pulled back the curtain on a private episode from GTM Fund’s annual general meeting, a GM was incredible. So. This is another special episode from the A GM and an extra special one because instead of my voice, this is a special host episode where GTM Funds partner and COO Paul Irving interviews three of our portfolio companies.

Vera Senco, founder and CEO of Atrix, ai. Steven Farnsworth, VP of GTM at Gaiia, and Kevin Walker, founder and CEO at Cent. These are three vertical SaaS startups talking about what is working in Go-To-Market. I think you’ll really enjoy it.

Paul Irving: It’s my honor to be up on the stage with three of three of my favorite people. We’re very lucky to work with, but also do this particular panel. We talked about it earlier, but we obviously don’t get to do panel discussions like this, but we also [00:04:00] don’t get to do the A GM celebration of the funding community like this without our GTM operators.

Um, the investors we’re lucky to work with. The same should be said, and maybe even more so of the founders that we’re very grateful to be working with as well. So we’re gonna talk about three of those teams and companies with a specific tone of what’s working in GTM for everybody right now. And then maybe even some stuff we’ll end at the end of what are the focus areas from here going forward?

Because we do have a lot of valuable people in this room, a lot of people who can make connections, introductions, hopefully unlock some of that value for you. So if we. Speak it into existence. Maybe we can get some connections made in the happy hour after this. I’m sure most people here have heard us talk ad nauseum about Atrix and Centari and Gaiia, but it is much more meaningful when we hear it directly from yourself.

So I’m gonna start with just some intros, if you don’t mind. Kevin, I’ll start with you at the end, just yourself, a little bit about Centari, what you guys are building and the stage you’re at.

Kevin Walker: Great. Well, great to see everybody. I’m Kevin Walker, founder, CEO at Centari. I started my career as a practicing attorney doing m and a at [00:05:00] Paul Hastings, and then went.

In-house for most of my legal career founded Ari primarily to tackle some of the problems I felt as a, as an attorney, and particularly around deal work. So ARI is a platform for deal intelligence, so it serves transactional practices at large law firms, and pretty soon financial services. So great to be chatting with all of you.

Paul Irving: Thanks Kevin. I’m gonna pass the same, I’m just gonna write down to Vera. Vera, if you could share a bit about Atrix yourself and what you are building.

Vera Kutsenko: Hi everyone. My name is Vera, founder and CEO at Atrix ai. So we work with the pharma and medical device industry with their medical affairs teams who are really important, critical function of a pharma company in helping capture real world insights when a drug goes out to market and we help them tap into that data so they can get insights and really measure the.

Impact of their efforts. So super excited to be here and, and share what works in, in a very regulated industry. So alongside you.

Paul Irving: Yes. No easy sales cycles, by the way, on the, on the panel, we got this on hard mode. last but not least, [00:06:00] Mr. Steven Farnsworth, a familiar face, I’m sure for some of the folks in the room.

Been in LP since day one, but also, uh, VP of GTM at Gaiia.

Steven Farnsworth: Thank you and yes, good to see so many familiar faces here. I worked for Max at Outreach a long time ago now, and thankfully he did take my money. I guess it wasn’t that hard to take when I, when I joined the GTM fund. But since then I’ve been at Workato, our motto, which is also a port.

I was there first Go-To-Market hire, and then Gaiia for about a year. Gaiia is. It is essentially for the people not involved super deep into the telecom industry. It is CRM website, ERP, and billing software for NISP. So it is like the critical backbone for how internet service providers, which is a very distributed space across the country, outside of the.

Top tier one at and t Verizons that you’re used to dealing with daily. It is a very distributed industry and we function as the backbone operating system for how they [00:07:00] operate. That’s us.

Paul Irving: Amazing. Well, we’re, we’re excited to dive in a little bit and Vera, I’m gonna go to you first. It’s a pretty open-ended prompt, but as an early stage company, I mean seed stage company, working with some of the biggest and best pharma companies in the world, what’s been working in GTM so far?

Vera Kutsenko: Yeah, great question. So as, as you guys know, probably pharma and medical device, very regulated industry, similar more to legal and, and FinTech very hard to sell into from an enterprise perspective. It’s a very, and, and for context, I’ve never, before Atrix done enterprise sales, so I’ve kind of had to, you know, to, to warrant through in this really unique industry what has been working and.

And pharma in particular, it’s very relationship driven industry, is probably, I would imagine is a across industries in, in the enterprise and what we’ve seen really be effective in building relationships outside of the in-person trade shows. Right. And all of that that you’ve probably already heard of is really starting to scale those relationships through producing things like content.

So when we initially closed our first [00:08:00] customer. I thought to myself, well, why did we close them? It was in person. I spoke on a topic of authority, which is AI in my case, and built credibility that way. I’m only one person. I can’t be at every single trade show all the time. So I thought to myself, how do we scale this?

So I started to create video content. And it’s very cringe if you go, I’m sure like way, way early on. But it, it’s been a very effective way to that. Over the last year and a half has built kind of a, a following in AI and medical affairs space that has started to not only add oil to the kind of end-to-end, top of funnel to, to contract phase, but also with customer success.

And then recently, about maybe a month or two ago, I decided to run this little experiment where I’ve done a lot of trainings in these, in these enterprises. Had all of this content. So I was like, let me create a LinkedIn post to talking about this book called AI in Medical Affairs. I did not have it written fully at the time.

I did not expect it to go viral, and it did. So [00:09:00] I think we had like over a thousand people that were very relevant, who commented, liked it, shared it. So that’s an example of just from thought leadership and kind of content perspective. One way that I’ve seen be effective in pharma. And scaling content. So it’s,

Paul Irving: the ebook story is one of my favorite founder led sales stories.

’cause honestly, Vera wrote this LinkedIn post about a very real book that didn’t exist about AI and medical affairs, and then had so many potential customers commenting underneath like, please send DM me, DM me, and various. Sent a screenshot over to us and said, I guess I need to write a book this weekend.

And she did. I mean, how, how many pages was it in the end?

Vera Kutsenko: I think it’s like 315. I was,

Paul Irving: I was expecting to get like a 35 page PDF and I got sent a 300 page book at the end of the weekend.

Vera Kutsenko: Yeah, it’s a, I mean, thank God for, for Chad g pt, but do not worry, it can came, he came through all my training content and I read it and I edited it.

So, you know, I can back all of the words that, that are in there, but I mean, that wouldn’t have been possible before AI, to be honest. So thank God

Paul Irving: it’s, it’s just really neat because you’re, you’re [00:10:00] experimenting a little bit before you go and do that work. ’cause you have limited resources to invest and Go-To-Market.

Of course. So where you focus your time is important. So you found the demand first and then back filled it and it’s been, I know, a pretty cool source of top of funnel for you and the team. Kevin, I’m gonna pass it over to you. ’cause in a similar state, I mean at the seed stage you were working with.

Some of the biggest and best law firms in the world. What was working in the early days of go-to-market for Centari and yourself?

Kevin Walker: Yeah, so it very, very similar. Those first deals being very relationship driven, lobbying, highly regulated, and very skeptical. Lawyers are skeptical of many things. If anyone here, are there any lawyers here?

Just outta curiosity? Just just two of us. Alright. Alright. Or there’s a few more. Okay. Good. Not to out everybody at once, but, but it was a matter of going to, it’s also a very closed network. So the large law firm space, there’s a hundred, 200 large law firms, they actually have pretty, pretty deep spend on, on software.

So much larger than people typically realize. So they go to the same conferences, they kind of go to the same dinners. So the first few deals was very just, you know, me building those relationships. I think we took. Uh, the [00:11:00] same cookies from Maman Bakery to every conference we went to. So we kinda became known as like, oh, it’s the cent entire cookies.

Uh, so that really worked and, and that got us our first Marques customers and then showed up with a product that we had conviction in that the customers believed in. It became a flywheel world, word of mouth. So that was the first cover, first few innings, and now we are in the mode of starting to scale sales and go to markets.

We just made. Uh, our first two strategic, you know, senior AE hires and building that playbook, kind of coaching them on my, you know, how did founder lead sales? I watched every GTMfund, you know, video and training and was talking to Paul, you know, every other week on how to approach this, you know, these first hires.

So I. That’s where we’re right now, kind of transitioning from that C to series, A stage of Go-To-Market motion.

Paul Irving: it’s a really interesting time I think for legal tech as well, generally, just because if you look at, from a technology perspective, it is a fairly intuitive application of some of, some of the ai, both foundational models, but some of the other I.

You know, options there are available to those individual law firms, but they’re probably having to make some difficult decisions. I’d love to get the sense of what you’re hearing of just build versus buy [00:12:00] for some of these enterprise law firms.

Kevin Walker: Yeah, so this, this has been really interesting and I’m, I’m sure this is gonna resonate with for other verticals as well, but we are seeing.

You know, those firms where there’s someone in the firm who has a pet project and really has the edge to build something, and maybe they used to be a PM somewhere and now they want to, you know, bring that skillset to their, to a large law firm that they wanna shake up. And eventually the firm realizes that they are not a software company, that they are, you know, not a product company.

They’re a services business for clients. So, and usually those projects fail from what we’ve observed, but we occasionally see. Firms try to do it, and then they come to us after it has failed and we’re, we’re kinda stepping in as the, as the buy decision. So that’s most common. There are a couple firms in our industry that are truly building like software teams from the ground up and hiring, you know, armies of data scientists and engineers.

That’s very rare. But we have seen a, a couple of examples of. Someone gets to be in their bonnet to go, you know, build a gen I tool end to end. And in our, in our case at least, usually it doesn’t work out for them. It’s,

Paul Irving: I mean, it’s something that we’re seeing I think, in a lot of different areas and verticals.

And I’m sure some of our, our, you know, [00:13:00] GTM operators that are in the crowd would say the same thing, where there’s a subset of customers that want to build it internally. They wanna try it themselves, but it’s not just the build, it’s the execution of it, the quality of it, but it’s the maintenance of it too.

And, and you need to invest, I think, far more than people think when you hack together something over the weekend to really be sustainable. Especially when you’re talking about. You know, really big customers and, and firms. Um, Steven, I’m gonna kick kick it to you here ’cause I think guys an interesting Go-To-Market approach and I, I remember talking to you a little bit about it in the early days of, you know, you’re building core infrastructure software for these telecom companies, but there’s not an infinite number of potential customers that are out there.

So how does it change the way you and the team have thought about Go-To-Market when it’s, you know, a smaller pool of water, so to speak, but still, you know, really big fish that you’re going after. Y

Steven Farnsworth: Yeah. Just for context, there are 2200 ISPs we can sell to in the us and that’s, I should say, that’s our tam in terms of who’s actually in a buying cycle and is maybe potentially in market this year, it’s probably just a couple hundred, [00:14:00] which is why traditionally this space is, it’s a very distributed space in terms of our competitors and when we go out and understand from the market how many logos they’re winning a year, it’s, it’s, they’ve got a rep or two and they’re winning.

Five to six logos a year. Like this is a very slow moving space and very few people are migrating. I talked to, we were just at this big conference in Nashville, it’s like our Super Bowl for this space. And the number of people who come up really excited about Gaiia, but are in year three of a 15 year contract, or a 10 year contract is shocking.

So like, it’s just, it’s becoming, you know, a few months ago, I never thought to ask the question. I’m still relatively new there, but now it’s like. Okay, you’re excited. Awesome. How long? How long? Because I can’t get creative on, on nine years left of your contract or whatever it is. And so we’re, we’re stuck.

So for us, we have to be really conscious of, okay, if there’s only a limited number, how do we, it is so [00:15:00] paramount for us to get in front of them and to figure out how to, how to get that consideration when we’re there. And so for us it’s the, the playbook, like outreach is where I, you know, met a lot of you from.

Where you hire a bunch of SDRs and you go to markets and I see Lars and a few other people looking like this. This is the playbook that that, that I think many people still run. I’m not convinced s we’ll ever hire an SDR like in in our world it is. I, I think I’m gonna have a few AEs and today, we’ll, we’ll have probably about one and a half to two AEs that we’ll do about 7 million a RR this year.

And so we’re doing high a CV deals. We can only do, we’ll do about a dozen a quarter, which is unheard of for the space. But it’s, it’s, so our velocity, our product velocity is really high and people are seeing that. But for us it’s, we have to be value every relationship so, so carefully. And so, you know, you mentioned the events and trade shows and get building relationships.

I don’t know yet the way that we’re gonna scale this to today, [00:16:00] because today it is just us on a plane constantly to go be at these trade shows, to go interact with these people so that they know who we are. And from there we’ve been able to somehow, we’ve been able to drive deal cycles very quickly, but I don’t know how long that’ll last today.

We’re just kind of wowing the market with what we’ve built.

Kevin Walker: Yeah, very, very similar. Just to echo that very, very similar feeling here with kind of. And maybe that’s a, I’m curious how much of that is a broader trend with sales today where that relationship does matter more and more As gen AI is, you know, more and more prevalent and firms are getting, you know, fatigued by pilots and by the deluge of, you know, AI generated email sequences, that relationship, personal touch showing up at the trade shows just feels so, you know, really feels like, you know, the way to get that, that mind share.

Steven Farnsworth: Yeah, I, I mean, I think a lot of that will be dependent on the tam itself. Like somebody, like, I don’t think Kyle Norton’s here, is he from like the, you know, we, we all see him on talking about owner online. There’s I think a quarter million restaurants or something in the us. Like they’re not gonna know all of [00:17:00] them by name.

AI and, and the way that they go scale is gonna be totally different. But in a, in a market, like, it sounds like the three of us are in, like, I can actually know the names of most of the accounts that we’re gonna go after, and I can know. By name and by face. A lot of the leaders that are gonna buy my product this year or next year.

And so it’s, it’s why bring in an SDR some other motion to try to like kinda create that middle layer today. It’s important for our whole executive team to know who these accounts are and to work with them. So it’s, it’s, it’s a big support system around the seller.

Paul Irving: I’m now just known I, I, take me out of it.

No one wants to hear from me. They’ve already heard enough from me. I, we should have named the panel Making unscalable scalable. I feel like this is the theme of what a lot we’re talking about. Vera, I’m gonna go back to you on one of the things that you’ve been doing, which has been really interesting, and it’s the same idea where, you know, a lot of these buyers at the accounts you’re going after, which accounts are, are sort of the qualified people you should be talking to, and you’ve been pulled in because there’s a lot of interest in AI and how they should be using it to do almost like workshops on AI and how it would work in their [00:18:00] organization as a way to create some top of funnel.

How have you found success, or how have you been thinking about turning that into urgency to actually buy, so like the excitement and the interest in getting in the door and building a relationship, but trying to transition that into real velocity on the buying part. It.

Vera Kutsenko: Yeah, I think that’s a great question.

I’m actually, you know, curious if anyone else has, has tried a similar emotion. So for this it is, it’s an experiment for us. So I, I don’t quite know if, if this kind of Go-To-Market model will be effective, but the reason why it came about was because we sell into medical affairs. They’re MDs Pharm, these, they’re very smart people, but they’re not tech experts.

So, you know, pharma as an industry, I would qualify them as a very sophisticated data buyer. They’re, they understand data, but they’re not sophisticated software buyers and especially medical affairs. So when we’re trying to sell a solution that is a sophisticated AI solution, the way that it has to be sold, there’s some educational components that have to be involved to [00:19:00] also create, uh, signals through noise of all the other vendors that are like, we have all these AI solutions and it’s just a GPT wrapper.

Right? But, but medical affairs isn’t. They don’t have the language or the framework to evaluate that. So anyway, so, so we started to get requests to do AI trainings for medical affairs teams within the organizations. And the hypothesis ultimately is, you know, one, would that help us get one into the account to meet everyone there and be on the ground within the organization.

You know them talking about their confidential stuff within those confines to be able to then gather intelligence to qualify or disqualify them. So I recently did a training for Alexion, which is an AstraZeneca subsidiary, and you know, what became clear for through that example is that I don’t think they’re ready for, for an AI solution.

That’s good to know. Because then maybe next year we dedicate our times because every relationship matters. And you know, if you have two people maybe building those [00:20:00] relationships, you want them to prioritize their time. So, so that’s kind of, you know, the high level there. So using it more as a qualification.

Yeah. Step

Paul Irving: and, and, and anyone too, if you have tips for VE on how to leverage some of the thought leadership work that you’ve done in your GTM works and turn it into buying urgency, I’m sure she would be all ears. We’ll see.

Vera Kutsenko: Yes.

Paul Irving: And Kevin, back to you. So I. I was interested ’cause I think when we, when we were originally talking to customers that you had been talking to was I guess a little over a year now with Centari.

I think one of the things we heard over and over again was the thoughtfulness of your approach and LA’s approach with the product and the way that you thought about the customer problems. And it felt a little bit like some of that stemmed from some of these big firms having to make a lot of technology decisions really quickly.

And wanting to feel like they’re being sort of heard or understood. I, I’m curious if you’ve heard, like what’s, what frustrations you’ve heard within, you know, the enterprise buyers and legal tech over the last little bit.

Kevin Walker: Yeah, it’s, it’s interesting because our, our market has, I mean, probably similar to other, other [00:21:00] verticals, your end users, associates and partners at these law firms and, and then your buyers, which are the innovation teams, knowledge management teams.

Sometimes teams have just been spun up in the last two years to kind of go. Explore gen ai. And of course there’s whole separate conversation around the risks of that and how you need to really prove value to the end user and make sure you stick the landing. ’cause the, you know, there is a cycle of innovation.

We have to think long term there. But I’d say for the, for the buyer profile, they are pilot fatigued, they’re inundated with vendors. The pain points that we’re solving there are demonstrating, you know, helping them look good to their stakeholders, which is firm management. That’s usually said, we have an innovation mandate, we’re gonna hire this innovation team.

If we can make them look good, help them demonstrate. ROI, we’ve, we’ve won that, that half of the equation. Then with the associates and partners, the practicing attorneys, and I go back to attorneys being skeptical. ’cause I, I am a very skeptical attorney myself. I was in the buyer’s seat before and was always very, you know, questioning what I was, what I was being sold.

So with that stakeholder, it’s demonstrating, look, we hear [00:22:00] you, people on our team have been in your seat. We empathize with your problem. And just really that, that personal touch of like. You know, we have formed our own organization around the identity of our, of our end users. So we’ve hired attorneys from top law firms like Kirkland and from Davis Polk and others.

And so we’re able to evangelize directly to. The pain points they care about. And that’s, that’s great. ’cause they’re getting pitched by a lot of, you know, vendors that don’t have that same, that same ethos and empathy for the problem. Uh, so it’s kind of been a two-sided equation for us in that way. Yeah,

Paul Irving: that’s really interesting.

And so a lot of it is that, yeah, the customer empathy and understanding as a way to accelerate some of the decision making that, you know, I, you can just, you can understand the position they’re in, where they feel overwhelmed, they need to make big decisions, but don’t know if they’re talking to a lot of vendors that understand truly what they’re going through, what their pain points are and what they wanna solve.

Steven, I’m gonna go to you. We, we got the Centari cookies and, and now we might get the Gaiia donuts. I think I had, I had dinner with Mark Andre, the founder of Gaiia last, last week, and he was telling me about the donut playbook. So I was [00:23:00] gonna ask what’s working for Gaiia, but I think I might need to spill the beans on the, the donut playbook as well.

Steven Farnsworth: Uh, probably not prepared to call it a playbook. Oh, hey, we just did. But what we’ve, there are again, a few number of accounts that matter to us. We just, I just tried this out. It was maybe a dumb idea, but I think it got us some really great exposure. Since we’ve hired our second rep, it’s allowed me to not have to be at every single trade show.

And so I asked, I’ve asked the reps recently, Hey, where can I be? Is there some account that you wanna break into? Or an account that if I could be on site that I could go accelerate the deal? Where should I go while you’re out at this next event? And so I’ve recently been down in a big drive through Southern Utah.

A, I showed up in Sioux Falls, South Dakota, and then done in Oklahoma City to Dallas Drive. And in each case, what I’ve done is before having planned any sort of trip, we’ve manufactured some interest with a key counter two by saying, I’m going to be in town, [00:24:00] and I’m sure everyone’s done this lots of times.

And then of course they say, yes, I’d love to go to dinner. And then I book my flight and say, okay, I’m gonna be there. And so I go and meet a two, one or two of these accounts. But if I’m gonna be there and I’ve got a. A breakfast and a dinner. I have a whole data fill. So this AI has been actually relatively difficult for us to apply in our small TAM business.

And I’d love ideas for many of you, but one thing it has been helpful for is when I have a specific location in mind, I can say, help me understand all the different accounts in their locations, their office locations. ’cause most of them have physical locations for us that are within an hour or two of this area.

I go call the local donut shop. I buy 15 to 20, do dozen donuts. I get a rental car and I am meeting for breakfast with one of these accounts. And then I spend the next nine hours driving around in a circle around these little, you know, rural areas in dropping off donuts with. Some brochures, my business card, [00:25:00] whatever, shaking the hands of the people at the front desk, who in many cases are our customer service reps who interact with a lot of what we do.

Again, these, in many cases, we may have a high A CV, but the business might be 50 people in many cases. And so if I do this right. The CEO, the leaders, they know about us and then if I go do this at multiple locations of the same account, they’re all sending each other messages. Hey, did you guys get donuts?

You, we showed up. And so we’ve driven some real interest and awareness at these accounts that. Just never would hear about us. They may never actually go to these trade shows through us just showing up in this random city that no vendor has any business showing up to. But the fact that we just we’re doing this in a a more efficient way around these other meetings has been something that’s allowed us to, I.

To drive some real pipeline and awareness for the future. And so that’s, again, it’s not, that sounds like a playbook. I’ve gotta

Paul Irving: figure out more. We, we can, we, we pulled it

Steven Farnsworth: around.

Paul Irving: That sounds like it’s certain to, we have, we have a

Steven Farnsworth: notion doc to try to capture what we think could become a playbook, but it’s, it’s something early we’ve [00:26:00] done and it’s, it’s allowed us to start getting in front of people that we just wouldn’t otherwise be able to capture and talk to.

It builds a lot of credibility for our, at least our brand in the space.

Paul Irving: And a very important follow up question. Did you bring donuts today, Steven? I didn’t, and I

Steven Farnsworth: tried. I put them in the trunk so that I don’t eat a whole box.

Paul Irving: I’m driving around. That was like a

Steven Farnsworth: learning from the, the first one.

Paul Irving: I, I didn’t, and, and Kevin Vera, I’m sorry.

I’m gonna do this. I didn’t prep you for this question, but I think it’s a really interesting one. ’cause we talked about how difficult it is to scale some of the founder-led sales stuff that you’re doing and both of you. Identified hiring a chief of staff is actually like one of the earlier hires that you did to help scale.

And I just would love to, not even the what, but like the why of, of sort of where that became a really important first hire. And Kevin, I’ll start with you.

Kevin Walker: Yeah. We, we just, we just made our first, you know, chief of staff hire about a month ago who’s fantastic and, and works here in New York with me. And we, it, it was that, that becomes, if you’re doing a strong founder-led sales motion, that is the hardest thing to scale is yourself of course.

And so having someone who you can really rely on too. Yeah, start to scale everything [00:27:00] else that you would be doing. And this particular hire we made was, uh, one of the first, uh, employees outta FinTech a number of years back, and kinda was there, you know, soup to nuts. So really saw that, uh, we, we looked for someone who had been on the zero to one startup journey in particular.

So we weren’t trying to find someone who was gonna learn startups for the first time as someone who really knew how to, um, you know, be successful at this stage of the business and hit the ground running. Because critically for me it was, I don’t want to have to. You know, train anyone on the job. At this stage, we’d meet someone who are, do you know, doers on day one.

So that’s been really, really effective and helpful for us.

Vera Kutsenko: That’s awesome. We should exchange notes ’cause we’re, we’re still recruiting. So if you guys have any good chief of staff candidates that have early stage startup experience please and, and also enterprise or B2B would be super awesome, but very similar.

I think I’m the one Go-To-Market person at our company. We’re very engineering product heavy from like a headcount perspective. And the hardest thing to scale with founder-led sales is your time. So really [00:28:00] having someone come in who can. Put processes around some of the things we see working like a donut playbook.

I’ll say, I tried candles, I did make candles for prospects. I’ll not say that, that’s a playbook to, to follow though, but, but I think in a similar vein, the chief of staff ideally could be someone to scale the Go-To-Market operations and if they can support the relationship management piece and really have executive presence, I think that’s a, that’s a nice to have.

But then I think maybe that veers a little bit more towards like the true. Sales aside from a higher perspective, so.

Paul Irving: It’s, it’s, we were worried about Steven eating too many donuts. I’m worried about you burning your car, or something like that. Carrying around too many candles. I know we just have a couple of minutes left, so I, I wanted to end on, on just sort of where you and the team are focusing most of your efforts or sort of what are the big strategic initiatives on the revenue side of the business that you’re spending a lot of your time on right now?

And, and I’ll, I’ll start Steven with you. And the idea is, I, I would love to hear if anybody in the room, you know, in the happy hour later has some ideas for these. [00:29:00] But yeah, I wanted to end on a note of. Of what’s the big initiative for the team right now?

Steven Farnsworth: One of the things I think we’ve done, and I, I honestly think this has changed the trajectory of Gaiia, and it may seem very simple, is.

At these events that we go to, these trade shows, we’ve been holding these really non-salesy operator focused dinners and everyone’s done dinners around events, so it’s, I, I don’t think we’re reinventing the wheel, but we’ve, I think that we’re at Workato, for example, where I was before we had a. Suite at the Warrior Stadium and Stadium, and we would beg people to come.

And you guys know what it’s like to sell to leaders in San Francisco. Nobody shows up. It’s crazy. It’s the finals. You can’t come on. Seriously, this space is just a, is different. We’ve, we’ve been able to get exposed to very, very senior folks through these dinners. Again, non-salesy, getting great people in a room.

It’s ended up being a huge source of pipeline for us of brand awareness. It’s been amazing for us. What I’d be really curious and something that we’ve been noodling on, and I think it’s finally [00:30:00] time for us to jump in, is we do this at these major events, but then in the, in, in between, these people clearly crave community.

They, they want it. And these are people who again, might be in year three of a 10 year contract, they have no interest in Gaiia in the near term, but we, they, they want to be part of this. They want this community and I. Again, in a B2B Tech world, say, great, let’s start another Slack group, and it’s one of my 10 that I’m in.

And I can see that that is not the case here. It’s, it’s, they’re, they’re using different tech. We’re, we’re not quite sure the best way to, to do this. And so I’m, I’m really curious for people who have created this, almost this feedback cycle of dinners and communities and local events. We, we need to do this.

And I’m not quite sure the right way to do so yet, but that is going to be an initiative that I take very, very seriously to. Take my accounts that will, you know, that I, I hope are friends of ours and prospects of ours for, you know, in five years and wanna work with us.

Paul Irving: I’m, I’m sure, I know we have some community builders in the house here, so I’m hoping we’re gonna have some, some [00:31:00] good ideas.

And even just the technology enablement side, which you mentioned is not what you would expect when you would build a tech company, a community, so to speak, and try to support it. Vera, how about yourself?

Vera Kutsenko: Well, I was gonna say, I would love to exchange insights. ’cause one of the things I’ve been thinking about pharma’s very in person, relationship driven as well.

So outside of doing dinners at trade shows, which everyone does, how can we enable kind of repeatability and consistency? Creating those types of environments, like in New York or, or wherever, throughout the year to kind of encourage pipeline. Although I will say I, I don’t think most of the pharma contracts are like 15 years, but maybe three years.

So a little bit more achievable. So from, from our perspective, what I’ve been really thinking about is just repeatability. So how do we. You know, pharma sales cycle is also very slow, but re referenceability or word of mouth is so critical. Like I, if you have an existing customer that speaks very highly of you, it just, it’s such a switch to like convert to a contract.

So almost just thinking of, okay, we have what we have [00:32:00] today. We know bits and pieces that are working, what can we do to enable repeatability in, in this kind of complex environment? So.

Kevin Walker: Great. Yeah. I think for, for us it’s, we are starting to pursue a market expansion, play into financial services. I think I mentioned earlier, and it’s a very interesting, you know, problem to solve where you have a kinda a playbook that’s working for one vertical.

You have a product that can very well be deployed at a different vertical. But, you know, trying to attack that in a way that’s not too distracting and doesn’t cannibalize the core market that you’ve, you’ve built. Uh, so if anyone has gone through that motion of, you know, spinning up a. An adjacent vertical for a similar product and found a good way to approach that all years.

Paul Irving: Amazing. Well, I, we were, you know, very appreciative of the applause earlier, but I think the largest applause of the day should go for our founders here. So thank you very much for coming. This has been fantastic.

Alright, Sophie here again. And that wraps up the special, special edition episode. Hope you enjoyed this style of conversation. If you have any feedback, drop me a line on email [00:33:00] responding to the GTM Now podcast email. It goes to our team. I do personally read and respond to every single email also, or on LinkedIn.

Would love to hear your thoughts. If you enjoy this podcast overall too, it would mean the world if you could leave us a review on the platform that you listen on. YouTube, apple, Spotify, wherever you tune in, you know the drill. This helps us continuously grow the podcast. We can continue to bring on the guests that you wanna hear from on the topics and areas that you wanna hear most about.

Thank you. Appreciate you. Have a great day and catch you next week.

The post GTM 152: What’s Actually Working in GTM Right Now: Lessons from Centari, Atrix AI, & Gaiia appeared first on GTMnow.

Hello and welcome to The GTM Newsletter by GTMnow – read by 50,000+ to scale their companies and careers. GTMnow shares insight around the go-to-market strategies responsible for explosive company growth. GTMnow highlights the strategies, along with the stories from the top 1% of GTM executives, VCs, and founders behind these strategies and companies.

Most startups die not because they move too slow. Rather, because they build the wrong thing, for the wrong customer, with the wrong team.

That’s why these frameworks from Oji Udezue, former Chief Product Officer at Calendly and Typeform, are so valuable. He’s also held product leadership roles at Twitter, Atlassian, and Microsoft, and recently co-authored a book on scaling high-growth product teams: Building Rocket Ships.

Here are five tactical, high-leverage lessons for early-stage B2B founders and operators:

1. Where to Fish: A framework for targeting the right workflow

This is a simple framework to assess if you’re building in the right zone. It’s a powerful filter to assess the strategic potential of the workflow your product targets. Oji maps them by two traits:

1. Frequency: How often the workflow is performed

2. Breadth: How many people across the company perform it

This creates four categories:

Look for workflows that are used daily, across teams.
Avoid building for low-frequency, narrow personas unless your wedge is razor-sharp.

So if you’re in a LiEv or LiNi zone, chart a clear roadmap toward HiNi or HiEv territory to increase market pull and enterprise value.

2. Ditch the EPD trio and build a 6-person “shipyard” team

Today’s most effective teams include six functions from day one:

1. Product
2. Engineering
3. Design
4. Product Marketing
5. User Research
6. Data

This prevents the old waterfall trap of “build → throw over the fence → launch.” Instead, you get faster iteration, tighter GTM integration, and fewer missed signals.

How these functions are built is continuously evolving with AI.

3. You need a 3x+ value delta to overcome switching costs

This one’s easy to overlook. If your tool is only 20% better than the incumbent, it won’t matter. Switching is painful, even if the new thing is technically superior.

You need to be:

• 5x cheaper, or
• 3x faster, or
• Undeniably simpler

For example, despite building a better internal Slack competitor at Atlassian, they couldn’t win because Teams was bundled for free and Slack was good enough.

4. AI is creating a tempo mismatch between product and GTM

AI tools have radically sped up development. But GTM motions – onboarding, enablement, comms – haven’t kept pace. This causes friction, feature fatigue, and missed adoption moments. GTM and product need to operate on the same cadence.

Teams are adjusting by:

• Rethinking what “version” means (rolling vs. batch releases)
• Slowing down outbound marketing to give customers time to catch up
• Building internal GTM muscle as fast as they build product

5. Don’t stack risk in your infrastructure

This is a mistake even seasoned founders make: layering a new market, new tech, new GTM motion, and unproven infrastructure… all at once.

Instead:

• New product → proven market
• New market → proven tech
• New everything → high failure rate

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Tag GTMnow so we can see your takeaways and help amplify them.

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4. Director, Solutions Engineering – MM & Enterprise at Vanta (Remote – US)
5. Mid-market AE (Central) at Writer (Hybrid – New York)

See more top GTM jobs on the GTMfund Job Board.

If you’re looking to scale your sales and marketing teams with top talent, we couldn’t recommend our partner Pursuit more. We work closely together to be able to provide the top go-to-market talent for companies on a non-retainer basis.

GTM industry events

Upcoming go-to-market events you won’t want to miss:

• Web Summit: May 27-30, 2025 (Vancouver, CAN)
• GTM 25 Roadshow Boston: June 3, 2025 (Boston, MA)
• Pavilion CRO Summit: June 3, 2025 (Denver, CO)
• GTMfund AGM: June 5-6, 2025 (NYC, NY)
• GTMfund Dinner: June 11, 2025 (London, UK)
• GTM 25 Roadshow San Francisco: June 12, 2025 (San Franciso, CA)
• GTM 25 Roadshow London: June 19, 2025 (London, UK)
• Pavilion GTM Summit: September 23-25, 2025 (Washington, DC)

Subscribe now

This newsletter was written and edited by Sophie Buonassisi, Max Altschuler, Paul Irving and the GTMnow team (not AI!).

The post How to build the right thing (before you scale the wrong one) appeared first on GTMnow.

The power of combining data and storytelling

With so much information available, how do you get your audience to care about your content? One way is through data storytelling. The practice of boiling down large amounts of information into clear, shareable graphics is driving incredible impact for some companies.

To learn more about it, we spoke to Peter Walker, head of the insights team at Carta. Peter is an industry veteran known for unearthing juicy information about the startup industry that people love to discuss. His posts on LinkedIn get thousandsoflikes and hundreds of comments and reposts. At Carta, his team draws upon proprietary data to produce social media posts, a newsletter, and a podcast.

We spoke to him about the importance of data storytelling, how to get started with it, and tips on how to run a successful data-driven content strategy.

Why data storytelling is so important

While Peter worked in data visualization at early stage startups, he moonlit at The COVID Tracking Project. This was during the early days of the pandemic, when everyone was trying to make sense of a lot of new information. There, he learned that data graphics can help create clarity out of noise. When they’re readily shareable, they can also contribute to a conversation and convince audiences who may have different viewpoints.

Data gives you a solid backing and credibility for what you say. That is the power of data. Done well, data storytelling brands you as a thought leader and instills trust. For customers, making a purchase from your brand is much easier when they already trust you.

Common misconceptions about data content marketing

Misconception 1: You need a lot of data

Good stories don’t necessarily need a ton of data to tell. You could focus on a space where there’s not a lot of data (either your own, or public data), and create content in that space. That way, there’s less competition for the topic you’re creating content around.

Misconception 2: You need proprietary data

You don’t need to produce a lot of your own data. You could also tell a data story by using publicly available numbers, but telling a clearer story using those numbers. For example, there are companies that have more data than Carta, but Carta’s posts go viral because they know the content their audience is interested in consuming.

Misconception 3: Less is more

Simply putting out one big quarterly data report won’t work. You need to put out content often in order to achieve visibility and engagement.

Carta puts out insights 4-5 times a week. Producing more content is more effective because you get more feedback, quicker. As Peter explains: “Each one of these graphics has a chance to go viral in a way that a quarterly PDF is just not going to.”

Misconception 4: Posting a lot is harder than posting quarterly

While it may seem counterintuitive, putting out more content is actually easier than creating less. If you’re in the data that much, then the story just becomes much more natural. You start noticing connections among the data. In the beginning, it took Peter more than an hour to create one LinkedIn post. Now, he can do it in 25 minutes.

If you’re struggling with this at first, try blocking off dedicated time every day to make a data graphic. When Peter was getting started, he had a block on his calendar from 8-8:40am simply titled “create something.”

How to get started telling stories with data

Now that we’ve established that any startup can use data to tell stories that promote their brand, here’s a step-by-step guide on how to do that.

1. Build one graphic for social media

Creating one simple data graphic and posting it on one or two social channels is the quickest way to enter a conversation in your industry. Peter advises trying to do this at least 2-3 times per week. The repetition of content creation will help you get better at it.

Don’t be worried if you have a few months of low engagement — that’s normal. Focus on just one or two channels and don’t switch courses before you have enough time to build your presence on those channels. In his first few years at Carta, for example, Peter’s team decided to just focus on LinkedIn and the newsletter. Now, they’ve only expanded to a podcast because they can trust that those two channels will continue to perform well.

2. Use both data and graphic design tools.

Effective data stories make sense of the numbers, but also look clear and well-designed. Here’s how Peter creates content for a post:

• Use SQL to get a clean data set. (Note that if you want to produce insights off your own data, you have to anonymize customer data to protect sensitive information).
• Upload that data and build graphics in a database tool. Peter prefers Tableau, but Looker and Flourish are other good options.
• Export the graphics to Figma. There, you can edit headers, footers, colors to make the design on-brand, and arrows pointing to areas you’d like to call attention to.
• Write the post that will accompany the graphic and post it on social media. These posts are usually a mix of fact and opinion.

3. Listen to people in your industry.

When you’re starting out, you can get story ideas by listening to sales calls, reading customer success reports, and talking to other founders. The point is to make sure you know what people are interested in talking and reading about, so you can have a better shot of creating stories that will get engagement.

There are two types of stories the Carta team tells:

1. Ongoing stories (such as how valuations change quarter-to-quarter).
2. “Newsjacking” stories (as Peter calls them), which jump into a public conversation. For Carta, that can be a debate on X about whether Miami is a good place to found a startup. For a newsjacking story, Peter builds a graphic within the hour and either posts it publicly on social or DMs it to the people having the conversation.

4. Engage with your audience.

Read the comments on your posts. Comments give you a sense of what people are curious about and discussing. They’ll also let you know if you’ve got something incorrect.

“The back and forth in the comments is where a lot of the magic happens.” Comments have become the basis of many of Peter’s posts. He has a Word Doc with 200 questions that can inspire future posts.

Another way to engage with your audience is to DM other thought leaders. Peter will create a graphic and DM it directly to a VC on X with a note saying he hopes it’s useful for them. He says while it’s impossible for him to track this, one sure sign of success is if founders and VCs share his graphics with their peers in private WhatsApp groups. That’s how he knows that he’s got his thumb on the pulse, and is contributing to the conversation.

Tips to make your insights strategy shine

Create content from a human, not a company.

If your primary distribution channel is social media, the algorithms favor humans over companies. Human authors can also take a personal view and engage with others in the comments in a way companies can’t. Peter’s own experience bears this out: While posts on Carta’s LinkedIn page generate dozens of likes, those on Peter’s personal LinkedIn will get thousands of likes.

Writing from an individual’s point of view allows people to establish their own voice. It allows other people to approach individuals with questions and ideas in a way they wouldn’t approach a company.

When hiring a data storyteller, look for passion and curiosity.

When looking to make your first data storytelling hire, you could hire either a marketer who wants to dive into data, or a data scientist who wants to become a storyteller. Whichever one you choose, the main quality to look for is someone who is excited and curious about the industry. For example, if that person doesn’t get the job, they would probably write a personal Substack about it anyways

Stay the course

Be prepared to shout into the void for at least 3-4 months. It’s an inevitable part of the process. Eventually, however, if you keep doing it and get better at it, some of the right people will find your content and you’ll gain traction.

Like many brand-building activities, the vast majority (80-90%) of startups will stop producing content after 3 months. But, according to Peter, 6 months is the minimum amount of time to put out data insights if you’re going to commit to it.

While it may seem like a lot of work, especially at first, data-driven content creation doesn’t have to be hard. The good news is, the more you do it, the easier it will become — a positive flywheel for a marketing practice that can be a really effective tool in building up your credibility and brand.

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GTMfund Toolkit

We spilled the beans on how we’ve become a Superhuman customer, and the response across our GTMfund community Slack and social channels was a clear testament to how Superhuman has been a game-changer for efficiency among leaders and teams. A few of the messages:

Superhuman is generously offering the GTMnow community exclusive access to 1 month free on the platform. If you add any teammates in January to your team, they’ll get a free month too.

To claim this offer, go to www.superhuman.com/gtmnow

More for your eardrums

Casey Woo is the Founder and CEO of Operators Guild, an invite-only community for professionals in strategic finance and operations roles. He is also the General Partner and Founder of FOG Ventures. He is a seasoned, multi-stage operator, bringing over two decades of experience in investment banking advisory, public equity investing, high-growth operational and military leadership roles. His last role was the CFO of Landing, where he oversaw the company’s Finance, Legal and People operations. Prior to Landing, he served as the Global Head of Strategic Finance at WeWork.

GTM 132: The Rise of the Operator + GTMfund $54M Fund Announcement

Listen on Apple, Spotify, YouTube, or wherever you get your podcasts by searching “The GTM Podcast.”

Startup to watch

Armada – announced a collaboration with Aramco Digital and Microsoft to deploy the world’s first Industrial Distributed Cloud to accelerate real-world AI and digital transformation efforts around the world. This marks a major milestone in advancing AI-driven automation, real-time computing, and digital transformation.

Closinglock – announced a $34M Series B round. This round will support their mission to power and protect real estate transactions in the U.S. To date, Closinglock has prevented over 8,250 fraud attempts and saved buyers and sellers more than $1.2 billion in avoided losses.

More for your eyeballs

How SaaS pricing evolves across different company stages. From first paying customers to enterprise, here’s how successful SaaS companies level up their pricing game to maximize growth and profitability at every turn.

If you learn something from every failure, you can take a win from something that initially seems like a loss. Because of what executive leadership learned from what seemed like cutting criticisms, Crunchbase is now improving their product in a more intelligent, intentional manner.

Why Net Retention Rates (NRR) are all the rage for AI investors. AI startups are reaching revenue milestones faster than previous generations, but investors worry many won’t sustain their growth and are looking for indicators of long-term viability. As a result, they are focusing on net revenue retention rates, with Writer standing out for achieving rates above 120% in the past year.

Hottest GTM jobs of the week

1. Revenue Operations Associate at OfferFit ((Remote – NA & LATAM)
2. Regional Vice President, Enterprise Sales (East) at Vanta (US)
3. Customer Retention Manager at Owner (Remote – US/Canada)
4. Account Director at Atlan (Remote)
5. Revenue Operations Manager – US at Crossbeam (Remote – US)

See more top GTM jobs on the GTMfund Job Board.

If you’re looking to scale your sales and marketing teams with top talent, we couldn’t recommend our partner Pursuit more. We work closely together to be able to provide the top go-to-market talent for companies on a non-retainer basis.

Upcoming digital live event

On February 26th (and available on-demand exclusively for registrants), seasoned operator-investors will share how they got started, how they source and evaluate opportunities, what they’ve learned from their best (and toughest) investments, and more.

Register

GTM industry events

Upcoming go-to-market events you won’t want to miss:

• The GTM Workshop for AI Founders (GTMfund event): March 25, 2025 (San Francisco, CA)
• More GTMfund 2025 Events TBA (global)
• Spryng by Wynter: March 24-26, 2025 (Austin, TX)
• Pavilion CMO Summit: April 17, 2025 (Atlanta, GA)
• SaaStr Annual: May 13-15 (San Francisco, CA)
• Web Summit: May 27-30, 2025 (Vancouver, CAN)
• Pavilion CRO Summit: June 3, 2025 (Denver, CO)
• Pavilion GTM Summit: September 23-25, 2025 (Dallas, TX)

Subscribe now

This newsletter was entirely written and edited by Sophie Buonassisi and Scott Barker (not AI!).

The post The playbook for viral data storytelling appeared first on GTMnow.

Hello and welcome to The GTM Newsletter by GTMnow – read by 50,000+ to scale their companies and careers. GTMnow shares insight around the go-to-market strategies responsible for explosive company growth. GTMnow highlights the strategies, along with the stories from the top 1% of GTM executives, VCs, and founders behind these strategies and companies.

7 CRO tips for smarter annual planning

1. Set core goals and bet on “S-Curves”

Owner’s 2025 plan revolves around two key elements:

• Core Initiatives: A set of seven essential strategies that, if executed well, will drive the planned revenue growth (for Owner in 2025, 2x revenue growth).
• S-Curve Bets: Three experiments designed to unlock future growth beyond the current year. They also future-proof the existing year.

“S-Curve bets help us anticipate market saturation or operational bottlenecks before they happen. If demand gen slows, conversion rates drop, or outbound outreach hits a wall, these bets ensure we have new growth drivers ready.”

2. Plan for attrition – talent planning is just as critical as revenue planning.

A major mistake companies make is assuming 100% of their team will hit 100% of their quota, which rarely happens.

Key capacity planning elements:

• Losing a mid-market rep can cost a company 35-40% of their quota capacity for the year. Even with a talent bench ready, ramp-up time significantly impacts revenue attainment.
• Quota buffers should range from 5% to 35%, depending on the company’s growth stage and risk tolerance.
• Retaining top performers is essential. As the job market heats up, assuming all top talent will stay is risky.

“If you lose a top performer, their quota still needs to be met. Without a strong talent bench and retention strategy, you’re scrambling to reallocate pipeline and onboard a replacement—losing valuable momentum.”

3. Design a plan with the future in mind, where you want to be

Help Scout’s annual revenue plan is a collection of activities that drive toward Iconiq’s Enterprise 5. By using these benchmarks, we ensure that the capital we’re allocating toward growth initiatives is efficient and keeps a longer-term view in mind:

• ARR Growth: How quickly are we growing and which growth levers do we need to add?
• Net Dollar Retention: How well are we retaining revenue?
• Rule of 40: How are we managing spend relative to our growth?
• Net Magic Number: How efficient is the Sales and Marketing spend?
• ARR Per FTE: How efficiently is the team scaling to support the revenue?

This plan is made possible by clear inputs (key activities) and outcomes (results) that drive the company towards those key metrics.

“A revenue plan without clear inputs and outcomes is not a plan.”

4. Set unreasonably ambitious goals (but know your team)

The best companies set aggressive goals – not because they always hit them, but because ambitious targets drive outsized outcomes.

That said, goal-setting is situational:

• Winning teams thrive on stretch goals. If a team has strong momentum, pushing for aggressive targets fuels performance.
• Struggling teams need confidence-building goals. If a team had a tough year, setting more attainable (but still difficult) targets can rebuild belief and execution discipline.

“Building a growth company is an unreasonably hard thing to do. The goals need to mirror that.”

5. Stay the course, communicate and make progress visible

Most companies announce their key initiatives early in the year and only revisit them quarterly. This isn’t enough.

Best practices for visibility:

• Frequent updates in all-hands & team meetings. Tie back discussions to initiatives—what’s coming up, what conflicts with them, and what needs realignment?
• Celebrate early milestones. Momentum matters. Showing progress keeps teams engaged and aligned.
• Make deliberate course corrections. If an initiative needs to be dropped, communicate why, what was learned, and where the focus is shifting.

“Stick to it. Too many companies change course too often – adjust deliberately, based on data and feedback.”

 

6. Align internal and external partners

Successful annual planning goes beyond the revenue team and requires alignment across all key stakeholders.

At GitHub, primary GTM plays serve as the foundation for not just Revenue, but also Product, Marketing, Finance, and other teams – all internal and cross-functional partners. These plays ensure that all functions are driving toward the same objectives.

External partners are just as critical. A well-aligned channel strategy ensures partners understand key objectives and GTM motions, making them more effective in the market.

GitHub runs a virtual Partner Kickoff, leveraging content from their Revenue Kickoff, so partners show up to customers fully aligned and prepared to add value.

“When internal teams and external partners are aligned, the entire GTM motion becomes more effective”

7. An annual plan is a living document

An annual plan is a hypothesis, not a rigid contract. The best CROs adapt based on market feedback, internal insights, and evolving priorities.

“No one expects their annual plan to be 100% right. The best planning processes treat the plan as a testable hypothesis—adjusting as new data emerges.”

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GTMfund Toolkit

We spilled the beans on how we’ve become a Superhuman customer, and the response across our GTMfund community Slack and social channels was a clear testament to how Superhuman has been a game-changer for efficiency among leaders and teams. A few of the messages:

 

Superhuman is generously offering the GTMnow community exclusive access to 1 month free on the platform. If you add any teammates in January to your team, they’ll get a free month too.

To claim this offer, go to www.superhuman.com/gtmnow

More for your eardrums

Kraig Swensrud is a serial entrepreneur, currently on his third company after two successful acquisitions. As the Founder & CEO of Qualified, he is working to shape the future of enterprise sales tech. Prior to founding Qualified, Kraig founded GetFeedback which was successfully sold to SurveyMonkey. Kraig also led marketing as the CMO of Salesforce during very formative years of the company’s history, working directly under Marc Benioff.

GTM 131: Being CMO Under Mark Benioff of Salesforce and the Innovator’s Dilemma

Listen on Apple, Spotify, YouTube, or wherever you get your podcasts by searching “The GTM Podcast.”

Startup to watch

Closinglock – announced a $34M Series B round. This round will support their mission to power and protect real estate transactions in the U.S. To date, Closinglock has prevented over 8,250 fraud attempts and saved buyers and sellers more than $1.2 billion in avoided losses.

More for your eyeballs

AI Agents Landscape & Ecosystem. This landscape map of 2025 features autonomous agents and AI assistants (co-pilots). We’ve found this interesting for discovering and comparing some agentic AI solutions by category.

Culture is Your Second Product. The early hires you make have a massive influence on the culture of the company, which is another reason why getting those hires right is so important. It’s easy to prioritize other things ahead of your culture, but it’s crucial to take time to invest in developing your culture.

The Show Me You Know Me Show is a deep dive on the impact of personal connection and empathy from the perspective of some of the world’s most successful executives. This unique angle surfaces conversations and insights that we haven’t seen done often and to this depth.

Hottest GTM jobs of the week

1. Senior Enterprise Sales Development Rep at Writer (UK – Dublin)
2. GTM Enablement Manager – EMEA at Vanta (Hybrid | Dublin, Ireland)
3. Senior Manager, Content Marketing at OfferFit (Remote – NA & LATAM)
4. Account Executive (Inbound & Outbound) at Owner (Remote – US/Canada)
5. Enterprise Account Executive at Atlan:
   1. Texas and Oklahoma | Hybrid
   2. Midwestern US | Hybrid
   3. Ontario & Quebec | Hybrid

See more top GTM jobs on the GTMfund Job Board.

If you’re looking to scale your sales and marketing teams with top talent, we couldn’t recommend our partner Pursuit more. We work closely together to be able to provide the top go-to-market talent for companies on a non-retainer basis.

GTM industry events

Upcoming go-to-market events you won’t want to miss:

• Spryng by Wynter: March 24-26, 2025 (Austin, TX)
• Pavilion CMO Summit: April 17, 2025 (Atlanta, GA)
• SaaStr Annual: May 13-15 (San Francisco, CA)
• Web Summit: May 27-30, 2025 (Vancouver, CAN)
• Pavilion CRO Summit: June 3, 2025 (Denver, CO)
• Pavilion GTM Summit: September 23-25, 2025 (Dallas, TX)
• GTMfund 2025 events TBA (global)

Subscribe now

This newsletter was entirely written and edited by Sophie Buonassisi and Scott Barker (not AI!).

The post 7 Top CRO Tips on Annual Planning appeared first on GTMnow.

Insight from a $1.3B acquisition and 7 startups

The most successful companies understand that product and go-to-market strategy must be deeply interconnected.

Too often, businesses treat these as separate domains—one focused on development, the other on selling. But sustainable growth requires a cohesive approach, where every decision about the product is made with its market fit, buyer journey, and expansion potential in mind.

Scott Gifis has led the growth of seven startups, including serving as President at AdRoll and as President and COO of Frame.io, where he helped drive the company’s $1.3B acquisition by Adobe.

Drawing from his extensive experience, Scott breaks down four key strategies to successfully align product and go-to-market execution for scalable growth.

 

The 4 key considerations for aligning product and GTM strategy to drive growth

1. Your product is the foundation of your GTM strategy

The biggest mistake companies make is thinking they can simply add a go-to-market (GTM) strategy to a product that wasn’t designed with it in mind. Instead, leaders need to plan from the start how customers will find, use, and grow with their product.

Key questions to ask:

• Who is your buyer? Is the person using your product the same one making the purchase decision? If not, a product-led growth (PLG) strategy may not be the right fit.
• Can your product grow on its own? Some products, like Twilio, naturally expand as customers use them more. If yours doesn’t, you’ll need a different approach to scaling.
• What is your customer’s journey? Think about how they first find your product, how they start using it, and what keeps them coming back. If your product is complex, a strong customer success team can make all the difference.

Your GTM strategy should complement your product’s natural strengths, not work against them. If your product isn’t designed for a certain growth motion, forcing it will lead to inefficiencies.

2. Pricing and packaging is the link between product and growth

Packaging and pricing are more than just setting a price – they define how customers perceive and use your product, influencing adoption and retention. Many companies overthink pricing or delay key decisions. Pricing is not set in stone, it should change as your business and customers’ needs evolve. It’s packaging, not just pricing, that needs to align with specific customer profiles. The right packaging helps define what features the product builds to win different customer segments and informs the GTM strategy. Pricing, in turn, follows from packaging decisions.

Best practices for smart pricing:

• Know your customer – Create your packaging around on who is buying your product and how their needs change over time. This helps inform your product strategy and your GTM strategy around these packages with end customers in mind.
• Offer value at every level – HubSpot is a great example: It adds new features as businesses grow, making it easy for customers to upgrade naturally.
• Make it easy to understand – Complicated pricing can turn customers away. Keep it clear and match how they like to buy.
• Don’t block key features – If integrations make your product more useful, don’t limit them. Instead, charge for extra.

3. Align the entire business around the customer lifecycle

Too many companies focus on internal functions (marketing, sales, CS) instead of aligning everyone around the customer’s lifecycle. Without a unified approach, marketing generates leads that sales can’t convert, product teams miss key adoption signals, and growth stalls at predictable revenue plateaus.

How to fix this:

• Map every internal team’s KPIs to customer lifecycle success – If sales, marketing, and product aren’t working towards the same customer outcomes, friction will stall growth.
• Clarify the difference between customer lifecycle and customer journey – The lifecycle is the overall relationship between customer and company, while the journey is how they experience the product and purchase process.
• Unify goals across teams – Every department should share a clear understanding of entry and exit criteria at each stage of the customer journey.
• Leverage cross-functional insights – Marketing, product, and sales must work in tandem. Product signals (e.g. feature usage, activation data) should inform sales outreach and marketing efforts.
• Define failure criteria – It’s easy to measure success, but companies often fail to predefine when to abandon an initiative. Set clear failure benchmarks to cut ineffective programs early.

4. Building the right teams and tools for growth

Great strategies fail without the right people and operational alignment. Many startups make critical hiring mistakes, such as hiring too conservatively (one person instead of two) or prioritizing “experience” over grit and adaptability.

Team building cheat codes:

• Never hire just one – Whether it’s sales reps or product managers, a single hire lacks comparison points. Invest in at least two people to create benchmarks and knowledge-sharing.
• Hire for the problem today, not three years from now – A common mistake is hiring someone for a future vision instead of solving immediate needs. Prioritize what will drive the next 12-18 months of growth.
• Look for T-shaped players—people with deep expertise in one area but cross-functional ability to collaborate across departments. These are the force multipliers who drive outsized impact.
• Invest in customer success over SDRs – A strong CS function improves retention and expansion more than outbound prospecting ever will. Onboarding is the highest-ROI investment you can make.
• Make revenue operations a strategic priority – GTM ops and finance must work from a single model of truth. If finance and sales teams present different revenue data, operational inefficiencies will slow growth.

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GTMfund Toolkit

We spilled the beans on how we’ve become a Superhuman customer, and the response across our GTMfund community Slack and social channels was a clear testament to how Superhuman has been a game-changer for efficiency among leaders and teams. A few of the messages:

 

Superhuman is generously offering the GTMnow community exclusive access to 1 month free on the platform. If you add any teammates in January to your team, they’ll get a free month too.

To claim this offer, go to www.superhuman.com/gtmnow

More for your eardrums

Rob Giglio is the Chief Customer Officer at Canva, where he oversees Canva’s sales and go-to-market functions. Rob brings to Canva over 20 years of industry experience leading and executing global marketing and sales initiatives.

Rob joins Canva from HubSpot, where he was also Chief Customer Officer, and before that, he was the Chief Marketing Officer at Docusign. Prior to Docusign, Rob spent over ten years at Adobe, leading the global sales and go-to-market teams for their Digital Media Business Unit and holding responsibility for over $7B in revenue.

GTM 130: Scaling to Billions: How DocuSign, HubSpot & Canva Built Winning GTM Strategies

Listen on Apple, Spotify, YouTube, or wherever you get your podcasts by searching “The GTM Podcast.”

Startup to watch

AI or Not – announced a $5M Seed round. AI or Not is an AI detector trusted by 200k+ users that checks for AI generated content in images, audio, KYC identity documents and more. They are building AI to detect AI and help businesses stop fraud, power content moderation and prevent KYC scams.

More for your eyeballs

Demystifying the AI sales landscape. The sales tech landscape has never been more confusing, here’s how AI has shifted categories and what that means for buyers.

Size of mind beats size of wallet. You can’t just spend your way anymore to winning customers. If you’re smart and thoughtful about how you go-to-market, you can use content to win customers.

Hottest GTM jobs of the week

1. Revenue Operations Manager at Crossbeam (Remote – US)
2. Account Manager, SMB at Vanta (Remote – US)
3. Growth Marketing Manager at Armada (San Francisco)
4. Head of Community at Owner (Remote – US)
5. Healthcare Account Executive, Full Cycle at Magical (Remote – US)

See more top GTM jobs on the GTMfund Job Board.

If you’re looking to scale your sales and marketing teams with top talent, we couldn’t recommend our partner Pursuit more. We work closely together to be able to provide the top go-to-market talent for companies on a non-retainer basis.

GTM industry events

Upcoming go-to-market events you won’t want to miss:

• Spryng by Wynter: March 24-26, 2025 (Austin, TX)
• Pavilion CMO Summit: April 17, 2025 (Atlanta, GA)
• SaaStr Annual: May 13-15 (San Francisco, CA)
• Web Summit: May 27-30, 2025 (Vancouver, CAN)
• Pavilion CRO Summit: June 3, 2025 (Denver, CO)
• Pavilion GTM Summit: September 23-25, 2025 (Dallas, TX)
• GTMfund 2025 events TBA (global)

Subscribe now

This newsletter was entirely written and edited by Sophie Buonassisi and Scott Barker (not AI!).

The post Insight from a $1.3B acquisition and 7 startups appeared first on GTMnow.

For example, an AI-powered video creation tool designed for viral social media content thrives through influencer and organic campaigns. Meanwhile, a collaboration tool with a high NPS can scale rapidly through Product-Led Growth (PLG) and word-of-mouth. On the other hand, an AI customer service platform targeting enterprise clients performs best in offline events or VIP dinners where relationships drive trust.

By narrowing your focus, you can concentrate resources where they matter most, making it easier to achieve sustained growth.

Three Approaches to Finding Product-Channel Fit

There are three primary ways to identify product-channel fit:

1. Identify Channels That Suit Your Product

Focus on what makes your product unique. Does it follow a PLG or Sales-Led Growth (SLG) model? Does it support single or multi-user collaboration? Are you targeting consumers or decision-makers? Each factor influences which channels will deliver the most growth.

Differentiate between keyword-based channels that target active searchers and interest-based channels that engage users passively. Prioritize channels that align with your product’s strengths and have the highest potential for success—this is key to avoiding wasted time and effort on channels that won’t work for your offering.

2. Adapt Your Product to Fit Major Channels

Some companies can adapt their product to make better use of high-potential channels. For instance, a video editing platform might release a suite of free, lightweight tools that scale SEO traffic, or an SLG company could create a self-serve option to generate leads more efficiently.

When you adapt your product to fit key channels, you not only make it easier to reach your audience but also increase the likelihood of channel success.

3. Create Your Own Channels

In some cases, companies can leverage their product’s unique strengths to create new channels or use existing channels in innovative ways. This might include integrating your product more tightly with other platforms, using your data to create valuable lead magnets, or finding creative distribution methods that go beyond traditional marketing.

Channels can be benchmarked by ARR stage:

The Benefits of Product-Channel Fit

Finding product-channel fit allows you to move faster and avoid wasting marketing budgets on channels that aren’t suited for your product. By bringing focus to your team, you enhance operational efficiency and set the foundation for long-term growth.

This approach isn’t about following a prescribed playbook – it’s about identifying the channels that work best for your specific product and market, then doubling down on them to achieve scale.

The post Product-Channel Fit: Finding the Right Growth Strategy for Your Product appeared first on GTMnow.

David Knight is the Co-founder and CEO of Avarra, an AI-powered platform that simulates human-to-human interactions to accelerate sales onboarding and training. With over 30 years of experience scaling companies from tens of millions to billions in revenue, including WebEx and Proofpoint, David brings a unique perspective on the intertwined nature of product and go-to-market.

Discussed in this Episode:

• The power of AI simulations in providing experiential learning for sales reps.
• Designing products backwards from the go-to-market motion.
• Strategies for aligning product and sales teams to drive revenue growth.
• Rethinking ramp time: it’s about at-bats, not arbitrary time periods.
• Shifting perspective from the sales funnel to the buyer’s journey.
• The future of AI in sales training and enablement.

Highlights:

(02:24) Simulating human-to-human interactions with AI avatars.
(07:44) Creating a fun, engaging environment for sales training.
(13:26) Designing products from the go-to-market motion backwards.
(19:32) Helping sales leaders win deals as a product leader.
(27:08) Listening for pain points, not feature requests, from customers.
(31:07) Completely changing the go-to-market motion at Proofpoint.
(37:43) Aligning motivations between product and sales teams.
(38:43) Rethinking the sales funnel as a buyer’s journey.
(41:50) Building customized simulations for qualified prospects.
(34:55) One thing revenue leaders believe to be true that David thinks is bull$***.
(41:50) One thing that is working for David in go-to-market right now.

Guest Speaker Links (David Knight):
LinkedIn: https://www.linkedin.com/in/davidrknight/

Host Speaker Links (Scott Barker):
LinkedIn: www.linkedin.com/in/ssbarker/
Newsletter: thegtmnewsletter.substack.com/

Sponsors:

• HG Insights. Feeling that AI FOMO? You’re not alone. That’s why HG Insights created The Next Generation of Sales AI report — to calm the FOMO and help you bring AI to your GTM teams. It includes a breakdown of the Sales AI landscape, adoption of GenAI and Sales software across buyer groups. Plus, an analysis of the top 75 trending sales AI tools. Why HG Insights? Simple. They’ve been writing market reports for years as the pioneer of tech adoption and market insights. Trusted by GTM leaders at the likes of Snowflake Five9 and Google Cloud to improve GTM efficiency. Thinking about AI for your sales team but unsure where to start? This free and ungated report has you covered. 

The GTM Podcast
Features conversations with the top 1% of tech executives, VCs, and founders – the experts who have ‘been there, done that’ to build some of the fastest-growing software companies. Every week, a guest joins Scott Barker to dissect their stories – revealing what worked, what didn’t, and how things actually went down.

The post GTM 119: Design Products Backwards From GTM: Lessons from Scaling to $1B+ with David Knight appeared first on GTMnow.