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.
“Ultimately as a revenue leader… you’re not really looking for the sale. You’re really looking for loyalty. The ultimate end of journey is 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:
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.
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.
This report unpacks the findings from 619 B2B buyers, sellers, and marketers to uncover the exact types of customer proof that actually build trust and boost buyer confidence. The TL;DR? They want data, relevance, and actual proof.
67% of sellers have watched deals slip through their fingers because they couldn’t provide relevant, specific customer proof. Learn how to avoid this fate.
Grab this report and learn how to give them the evidence they need.
Design tool Figma IPOs and within minutes of trading hit a $45 billion market cap.
Vanta just raised $150M at a $4.15B valuation. The leading AI-powered trust management platform announced its $150 million Series D funding round at a $4.15 billion valuation. Look out for a deep dive on Vanta’s GTM and growth with their CRO on The GTMnow Podcast soon!
John Fernandez is SVP at Datasite, with a track record as GTM leader at Glia, ContentWise, and Diligent, having scaled teams through IPOs, acquisitions, and $1.4B in equity events. At Glia, John pioneered revenue marketing’s impact, driving 71% of pipeline and 60% of new business revenue from marketing. Connect with him for real-world GTM lessons, scaling playbooks, and unique frameworks for aligning marketing with revenue.
Listen on Apple, Spotify, YouTube, or wherever you get your podcasts by searching “The GTM Podcast.”
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)
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”
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.
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.
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.
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”
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
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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.
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
A quick pause to tell you about a company you need to know. ZoomInfo is the go-to-market intelligence platform built for sales, marketing, and rugoffs. By unifying data, workflows, and insights into a single system, ZoomInfo helps revenue teams find and engage the right buyers, launch go-to-marketplace 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 go-to-market intelligence. Learn more at zoominfo.com. So, how long did it take to hit PMF in your definition project market fit?
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.
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.
“Ultimately as a revenue leader… you’re not really looking for the sale. You’re really looking for loyalty. The ultimate end of journey is 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:
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.
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.
This report unpacks the findings from 619 B2B buyers, sellers, and marketers to uncover the exact types of customer proof that actually build trust and boost buyer confidence. The TL;DR? They want data, relevance, and actual proof.
67% of sellers have watched deals slip through their fingers because they couldn’t provide relevant, specific customer proof. Learn how to avoid this fate.
Grab this report and learn how to give them the evidence they need.
Design tool Figma IPOs and within minutes of trading hit a $45 billion market cap.
Vanta just raised $150M at a $4.15B valuation. The leading AI-powered trust management platform announced its $150 million Series D funding round at a $4.15 billion valuation. Look out for a deep dive on Vanta’s GTM and growth with their CRO on The GTMnow Podcast soon!
John Fernandez is SVP at Datasite, with a track record as GTM leader at Glia, ContentWise, and Diligent, having scaled teams through IPOs, acquisitions, and $1.4B in equity events. At Glia, John pioneered revenue marketing’s impact, driving 71% of pipeline and 60% of new business revenue from marketing. Connect with him for real-world GTM lessons, scaling playbooks, and unique frameworks for aligning marketing with revenue.
Listen on Apple, Spotify, YouTube, or wherever you get your podcasts by searching “The GTM Podcast.”
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)
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.
Founding a company is hard enough. Navigating payroll, benefits, and compliance shouldn’t slow you down. That’s where TriNet comes in. They work with startups and scaling businesses to help take HR off your plate, so you can stay focused on building product, growing revenue, and hiring great people – the go-to-market engine. B2B companies like Hivebrite and Equilend trust TriNet to help handle the infrastructure of their workforce, so their teams can focus on execution.
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.
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.
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
“You can predict the terminal value of your startup by mapping the frequency and breadth of your 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
Engineering, product, and design is a 1999 idea.”
Today’s most effective teams include six functions from day one:
Product
Engineering
Design
Product Marketing
User Research
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
“People won’t switch unless your product is 3x better – faster, cheaper, or both.”
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
“We’re building faster, but customers aren’t absorbing faster.”
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
“Take only one unproven layer at a time.”
This is a mistake even seasoned founders make: layering a new market, new tech, new GTM motion, and unproven infrastructure… all at once.
Stream Qualified’s first annual AI SDR Summit on-demand and hear how leaders from companies like G2, 6sense, Salesforce, and so many more are leveraging the power of AI SDR agents to scale their inbound and outbound pipe gen motions.
Check out candid conversations about the state of the AI SDR agent landscape, inbound and outbound playbooks, and real results from marketers at the forefront of the agentic marketing era.
This episode explores how AI is transforming the world of revenue operations.
Navin Persaud, VP of Revenue Operations at 1Password, unpacks the evolving intersection—how AI is impacting ops, team structures, tech stacks, and execution strategies. With over 20 years of experience leading ops, Navin has seen firsthand how operational strategy went from backend support to mission-critical.
Listen on Apple, Spotify, YouTube, or wherever you get your podcasts by searching “The GTM Podcast.”
Startup to watch
Zoca – announced their $6M Seed round. Salons, spas, and wellness other local business entrepreneurs are expected to post daily, run ads, and learn SEO – while juggling clients, staff, and operations. Zoca solves for that. Its AI engine drives demand, boosts visibility across Google and GPT, follows up with leads, and rebooks past clients. Already, it’s powering over 1,000+ small businesses.
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:
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.
In 2023, we saw a surge of SaaS brands adding anything “AI-powered” or “AI-driven” into their website headlines. A quick use of Wayback Machine for the top 100 SaaS brands will show you just how pervasive it was.
The optics were that if AI wasn’t integral to your roadmap and marketing, you were losing relevance.
Many venture capital firms shifted their investments almost entirely into AI startups.
As this flood of AI messaging hit, a lot of people quickly became numb to it.
Now in 2025, AI promises have simply become baseline expectations. Describing your product as “AI-powered” is like saying it’s internet-connected in 2005. It’s expected, not a value add.
With this expectation, we’re now seeing companies ditching AI messaging in their website headers.
Companies are testing, and the results are showing. We see brands, such as Notion, testing the impact of:
AI in the hero headline
AI in the hero headline and hero sub-header
AI just in the hero sub-header
In the test example below, AI messaging in the sub-header won out over having it in the header.
They kept the focus on the core value proposition of helping teams write, plan and collaborate to create better workspaces, while still having the AI inclusion.
This trend of AI reinforcing and amplifying the core UVP (unique value proposition) is gaining momentum.
We see this shift towards having no AI in the hero header (but including it in the sub-header) across dozens of top SaaS brands: Klaviyo, Monday, Freshworks, MongoDB, Snowflake, Braze, Cloudflare, GitLab, ActiveCampaign and countless others.
For example, here is how Freshworks positions it:
3-step AI messaging differentiation framework
In a market where almost every product claims to have AI, differentiation can’t come from the tech itself. It has to come from the outcome, the problem you solve, and the clarity of your message.
If you’re building or marketing an AI product, use this simple 3-step framework to test and refine your positioning:
1. Start with the pain (what’s broken?) Don’t lead with tech. Lead with the real problem your buyer is facing. Make it visceral, specific, and urgent.
For example: “Sellers spend 40% of their time manually triaging email.”
2. Move to the outcome (what improves?) Next, show what your product actually helps people achieve.
For example: “Our users reclaim 4+ hours per week and use it to close deals.”
3. Then show how AI enables the outcome Now that the user cares, you can explain how AI helps make that happen. But avoid buzzwords, make it visual and concrete.
Bad: “We use AI to streamline sales workflows.”
Better: “Our AI automatically categorizes, prioritizes, and drafts replies – so reps can focus on revenue.”
A quick cheatsheet for better AI messaging:
Replace “AI-powered” with outcomes – what does it enable?
Use your customer’s language – not your internal jargon.
Get specific – “launch campaigns 2x faster” beats “transform workflows.”
Anchor with proof – even directional data builds credibility.
Show, don’t tell – demos and workflows > buzzwords.
Leading with “AI-powered” used to signal innovation. Now, it risks blending you into the noise. Companies are putting product value back at the center and letting AI show up only when it adds clarity to that story.
Stream Qualified’s first annual AI SDR Summit on-demand and hear how leaders from companies like G2, 6sense, Salesforce, and so many more are leveraging the power of AI SDR agents to scale their inbound and outbound pipe gen motions.
Check out candid conversations about the state of the AI SDR agent landscape, inbound and outbound playbooks, and real results from marketers at the forefront of the agentic marketing era.
Episode guest Marcy Campbell is the CRO at AppFolio, where she leads sales and client services with a focus on delivering unified, end-to-end customer experiences. With 30+ years of experience scaling revenue teams across FinTech, SaaS, cloud computing, and communications, Marcy has held executive roles at Boomi and PayPal—where she led an 800+ person global team. Her deep expertise in aligning sales, customer success, and operations makes her a standout leader in the GTM space.
Listen on Apple, Spotify, YouTube, or wherever you get your podcasts by searching “The GTM Podcast.”
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:
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.
In 2024, Sydney Sloan (CMO of G2, former CMO at Salesloft and Drata) noticed something strange. Traffic from search was down 10%. Then 20%. Then 25%.
At first, it looked like a blip. But then came the shift:
LLMs like Gemini started answering questions before users even clicked.
For a company like G2 that is built on ranking in search and capturing intent, this was an existential shift. Since then, it has also become one for most companies and is a common challenge we see.
Go-to-market teams need to rewrite the brand awareness playbook for a world where content marketing, SEO, and PPC all look very different. Here is Sydney’s framework for what no longer works and what to do instead.
The future of GTM is AI-powered. Join us and thousands of revenue leaders at ZoomInfo’s GTM25 virtual conference on May 7th to explore how high-performing teams are leveraging Go-to-Market Intelligence and AI to fuel their GTM strategies that help top teams crush their revenue goals. You’ll hear from industry experts, connect with peers, and learn about the latest AI advancements. Beyond insights, you’ll walk away with proven AI tactics that you can directly implement for your GTM team.
1. SEO and PPC are breaking (and most teams are still operating like it’s 2019)
“Content for the sake of content is dead. The rise of AI has changed the game – and not in the way most marketers hoped.”
Sydney saw it firsthand at G2 and Drata. Gemini answers started showing up at the top of search results. Click-through rates dropped by 25%. Even well-optimized SEO programs (like HubSpot’s) saw traffic fall by as much as 70%.
Why? Google’s UI has changed. Sponsored results are pushed below the fold. Organic results are buried. The “answer box” is the only thing that matters.
Writing content just to rank doesn’t work like it used to. Instead, start writing to serve personas and jobs to be done.
2. Enter AIO: AI Optimization > Search Optimization
“We used to write for keywords. Now we write for what the persona is trying to solve and how LLMs summarize it.”
Teams are now strategically feeding LLMs content that gets cited in answer boxes.
These are two tactics that are working:
Expert-driven listicles: Content written by or attributed to real operators is ranking more often in AI responses.
Jobs-to-be-done format: Structure content to match what the user is trying to solve, not what you’re trying to sell.
Tool recommendations to help with this from Sydney’s CMO AI Circle:
GrowthX.ai: LLM-aware content writing, focused on jobs-to-be-done.
Profound: Tracks brand visibility across LLMs and conversational AI.
3. Don’t sleep on PR. It’s back (and stronger than ever in LLMs)
“$1,400 for a Forbes contributor article might sound cringe, but it’s getting indexed and showing up in LLM answers.”
AI tools are biased toward high-authority domains. Fast Company, Forbes, and Reddit are showing up more in answer summaries (because OpenAI and Google inked content deals with those publishers).
Paid PR is no longer just for logos on your homepage. It’s how you show up in AI-powered search.
4. The rise of B2B influencers — and why you need one (or more) in your corner
Clay is a great example. They paid 50+ influencers to amplify their launch and backed it up with product. Influencers weren’t just pushing ads; they were part of the narrative.
Find creators who already have your buyer’s trust. Then partner with them before your launch.
5. Founder-led distribution still wins, but only if you commit
“Your brand is the company’s brand. People trust you more than they trust the logo.”
LinkedIn’s algorithm is noisier than ever. Sydney’s tactical tips for founder-led GTM:
Post 2x/week: Anything less and the algorithm ghosts you.
Comment within 15 minutes: Signals engagement and boosts reach.
Batch posts: Block 30 min and write 5–10 at once.
Schedule ahead: Use LinkedIn’s native scheduling tool.
Test long-form: LinkedIn still boosts posts on its own blogging platform.
6. YouTube and Reddit are the new GTM edge
“YouTube has more indexed content than the rest of the internet. And Reddit is eating Google’s lunch.”
With Google indexing YouTube videos for AI responses and Reddit signing licensing deals with Google, both platforms are becoming essential brand surfaces.
YouTube: Expect a resurgence as brands prioritize LLM visibility.
Reddit: Highly relevant, cost-effective retargeting. If you serve a technical audience, it’s a no-brainer.
These aren’t fringe channels anymore. They’re part of the new organic stack.
7. Personalization isn’t just segmentation, it’s showing up
“Be a secret shopper. Try to buy from your prospect. Then send a 1-minute Loom on what sucked.”
Sydney’s favorite outreach trick is old-school: try the product, find what’s broken, and send helpful feedback. It works because it’s real and builds trust.
Combine this with referral programs (e.g., $1,000 for a meeting or opp) and you unlock distribution that paid ads can’t match.
TL;DR – The New Brand Awareness Playbook
AIO is the new SEO. Clicks are down 25%+ due to LLMs. Write for jobs, not keywords.
PR is back. Forbes, Fast Company, and Reddit are now signal boosters for AI.
Invest in B2B influencers. Be intentional and engage early.
Founders need to get on LinkedIn. Or, whichever platform the audience lives on. Post twice a week, comment early, batch-create.
YouTube + Reddit are GTM gold. They’re being indexed and converting.
Hyper-personal outreach still wins. Act like a customer. Record what’s broken. That gets attention.
Questions to ask yourself / your team
Ask these questions:
Are we writing for search engines or problems our buyer actually has?
Do we know where our content ranks in Gemini or ChatGPT responses?
What’s one piece of founder content we can publish this week that adds value?
Could we redirect $5K of PPC spend into creator partnerships or strategic PR?
Are we tracking brand mentions across Reddit, YouTube, and LLMs?
Tag GTMnow so we can see your takeaways and help amplify them.
More for your eardrums
Udi Ledergor is an iconic marketing leader and served as CMO during Gong’s rise from new SaaS startup to industry dominance. He helped Gong go from zero to hundreds of millions in revenue, while achieving a multi-billion-dollar valuation. His book Courageous Marketing is officially out and you can buy it in the show notes.
The future of AI, startups, and what’s coming in 2025. An exclusive fireside conversation with the GP of Foundation Capital, Joanne Chen. She breaks down why vertical AI solutions are gaining traction over horizontal applications, how to differentiate in an increasingly crowded AI marketed, how value is shifting to the application layer as foundation models become commoditized, and what top AI investors look for in pre-seed and seed rounds.
Customer Marketing Technology Landscape Report. Maps the core subcategories of Customer Marketing and Advocacy platforms, as well as adjacent technology categories that customer marketing leaders must at least be conversant in. In this first-of-its-kind report, you’ll get clear, unbiased data from 200+ real-world practitioners on exactly what these tools do best (and worst) —so you can confidently build a tech stack that works.
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:
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.
Every great Product-Led Growth (PLG) company eventually faces a crossroads: When and how to introduce a Sales-Led Growth (SLG) motion. Many make this shift reactively rather than strategically.
PLG and SLG aren’t competitors, they’re partners in growth. Companies that seamlessly bridge the two unlock incredible scale. Success requires a data-driven approach, a customer-first mindset, and a willingness to embrace change.
In this piece, GTM leaders share key lessons on how to navigate this transition effectively while keeping a customer-first approach.
Growth isn’t a choice, your customers decide it
“You don’t decide to make the shift from PLG to SLG, your customers do.”
—Jessica Gilmartin
Companies often reach a tipping point where users demand enterprise features, security, and team-wide adoption. Rather than resisting the transition, companies should follow customer behavior signals and build a sales motion that complements, rather than competes, with PLG.
3 key indicators that it’s time to introduce SLG:
Customers requesting enterprise features (SSO, security, admin controls).
Teams organically growing within accounts.
Inbound requests for larger contracts and enterprise agreements.
PLG to PLS: Understanding the evolution
Growth strategies evolve as companies scale. Holly Chen breaks it down:
In the early days, PLG can feel like magic – users sign up and adoption grows without direct sales interaction. But as companies move upmarket, they often transition from PLG to PLS.
Complex customer needs: Larger customers demand more personalized support, security, and integrations.
Enterprise sales cycles: Moving upmarket means more stakeholders, approvals, and custom solutions.
Revenue potential: Without a sales motion, high-value accounts may remain untapped.
The PLG-SLG hybrid is harder than it looks
While hybrid PLG-SLG models offer massive upside, they also introduce complexity. Common pitfalls:
Resource allocation conflicts: Enterprise and PLG teams require different marketing, sales, and product support – creating an internal tug-of-war.
Website & CTA prioritization: Should the homepage push free trials, demos, or enterprise sales? Striking a balance is tough.
Product & engineering trade-offs: PLG requires simplicity, while enterprise customers demand customization. Prioritization is key.
Companies that succeed in hybrid motions are those that treat PLG and SLG as complementary rather than separate business units.
How to nail the PLG-SLG transition
1. Map the customer Journey from PLG to Enterprise
Identify patterns in how free users evolve into enterprise buyers.
Look for specific in-product behaviors that indicate expansion potential (e.g., integrations, increased seat count).
2. Define your Product-Qualified Lead (PQL) criteria
Reverse-engineer signals from past enterprise deals to define high-potential PQLs.
Use personalized, value-driven outreach when engaging them.
Avoid generic “Want to talk to sales?” emails—offer specific solutions based on their usage.
3. Unify PLG and SLG teams under a shared customer strategy
Marketing and sales shouldn’t work in silos; they should co-own growth.
Prioritize customer experience over internal attribution battles.
Build a single source of truth for customer data across marketing, sales, and product teams.
4. Create an operating and governance model for data and decision-making
Establish an Operating Committee of directors/VPs across departments to collaborate on major shifts.
Have a Governing Committee (C-suite) to provide executive alignment and unblock major roadblocks.
Ensure that data and analytics are centralized, accurate, and actionable.
Examples: Asana & Calendly’s PLG-SLG evolution
Jessica Gilmartin, former CMO and CRO at Calendly and Head of Revenue Marketing at Asana, shares insight to Asana and Calendly’s evolutions.
Calendly: Using product signals to drive enterprise sales
Calendly leveraged integration data to identify high-value users. If an executive-level user connected their calendar to Salesforce, it signaled serious intent. Instead of pushing an immediate sales call, they received a targeted outreach offering value (e.g., helping them optimize that integration).
Asana: The balancing act of enterprise and PLG
At Asana, the team initially kept enterprise marketing and PLG marketing completely separate. Over time, they realized this fragmented approach didn’t align with how customers actually purchased. The solution? A holistic view of the customer journey, ensuring that enterprise buyers had a self-serve experience before engaging with sales.
Tag GTMnow so we can see your takeaways and help amplify them.
More for your eardrums
Jaleh Rezaei is the CEO & Co-founder of Mutiny, a company reimagining the B2B buying experience by transforming transactional relationships into meaningful connections through AI-powered personalization. Mutiny helps enterprises restore the human element in modern buying at scale, and is used by some of the fastest growing companies in the world including Amplitude, Snowflake and Qualtrics. The company is backed by Sequoia Capital, Tiger Global, and CMOs of companies such as Uber, Condé Nast and Salesforce. Prior to Mutiny, Jaleh was the Head of Marketing and Business Development at Gusto, where she grew the company from 500 to 50,000 customers over 4 years. She was the Director of Product Marketing at VMware prior to Gusto.
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.
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:
The GTM Workshop for AI Founders – a GTMfund event: March 25, 2025 (San Francisco, CA) – private registration (email for details)
GTMfund Dinner: March 25, 2025 (San Francisco, CA) – private registration
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.
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:
Ongoing stories (such as how valuations change quarter-to-quarter).
“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.
Tag GTMnow so we can see your takeaways and help amplify them.
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.
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.
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.
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.
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.
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