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Michel Tricot is the co-founder and CEO of Airbyte, the open-source data movement platform he launched in 2020. Before Airbyte, Michel led integrations and served as Director of Engineering at LiveRamp, where he scaled the teams and pipelines that synced massive data volumes. He also helped build rideOS as a founding engineer and Director of Engineering. Michel has spent 15+ years in data infrastructure, with a focus on commoditizing data pipelines and giving teams control and sovereignty over their data.
Discussed in this episode
- Why Airbyte launched open source first (catching engineers “at the search”)
- Project-market fit vs. product-market fit, and why they’re different
- The content engine: founder-led writing, shipping slides, and radical transparency
- Turning interest into community: 25k+ Slack, champions, and hiring from within
- The near-misses: hiring ahead of PMF, support-heavy community, cloud complexity
- Going upmarket: enterprise motion, longer cycles, and team ramp realities
- AI wave → agents as “data consumers” and what it means for pipelines
- Replatforming for control & sovereignty, not just “more connectors”
Episode highlights
00:15 — Airbyte’s rise: open source, community-first, and a billion‑plus valuation.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=15
01:57 — Michel explains Airbyte in two lines: open data movement into warehouses (and now agents).
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=117
02:53 — Why launch open source on GitHub: capture engineers at the “write a painful script” moment.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=173
06:53 — COVID reset: from a marketing‑focused product to an OSS platform that hit a hockey‑stick curve.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=413
11:01 — Project-market fit vs product-market fit: adoption is not monetization.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=661
14:41 — How Airbyte turned Slack into a rapid product feedback loop (ship next‑day fixes).
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=881
19:22 — The community trap: when your Slack becomes support, and how they course‑corrected.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=1162
23:53 — Cloud the hard way: why customers wanted control/sovereignty more than a hosted version.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=1433
29:22 — Building an enterprise motion: hire earlier, expect 6–9 month ramps, many more stakeholders.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=1762
33:26 — Fast path to Series A: publishing the deck, OSS adoption surge, and choosing investor fit.
Watch: https://www.youtube.com/watch?v=x3ahpXoaaVc&t=2006
Key Takeaways
1. Shrink scope to find signal.
Airbyte didn’t try to boil the ocean; it launched open source to solve one gnarly, universal pain: moving data from silos to value. By catching engineers “at the search,” they earned usage before monetization.
2. Separate project-market fit from product-market fit.
Community love ≠ revenue motion. Airbyte treated the GitHub traction as project-market fit, then built the monetization engine separately to reach true PMF.
3. Ship transparency as a growth channel.
Publishing fundraising slides, writing deeply technical posts, and narrating the build created trust at scale. Transparency reduced perceived risk and generated consistent inbound.
4. Community needs design, not just support.
Letting Slack become a help desk capped upside. Designing for champions, peer-to-peer help, and recognition programs turned users into advocates and contributors.
5. Control beats convenience in data infra.
Enterprises adopted Airbyte not just for connectors but because it runs where they need it. Control, sovereignty, and security often trump a pure cloud pitch in data movement.
6. Don’t hire ahead of platform complexity.
Moving from OSS to hosted cloud is a different business with operational drag. Hiring too fast created noise; starting small and iterating would have preserved product velocity.
7. Content compounds when founder-led.
For the first 18 months, Michel and co-founder wrote the playbook in public. Founder voice clarified positioning, attracted contributors, and set a high bar for later content ops.
8. Use community for real-time product discovery.
Posting lightweight polls/questions yielded 100+ responses in minutes, compressing research cycles. Community became an always-on signal router for roadmap decisions.
9. Enterprise motion is human-time, not server-time.
Longer cycles, more stakeholders, and ramp time are physics, not flaws. Hire earlier than feels comfortable, but in small, validated steps to avoid overextension.
10. Build for agents, not just analysts.
Agents are new “consumers” of data, demanding low-latency access and different interfaces. Replatforming around this shift is a multi-year moat, not a feature.
This episode is brought to you by our sponsor: ZoomInfo
ZoomInfo is the GTM Intelligence Platform built for sales, marketing, and RevOps.
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It’s trusted by the fastest-growing companies and has become the category leader in GTM Intelligence.
Learn more at zoominfo.com.
Follow Michel Tricot
- LinkedIn:https://www.linkedin.com/in/micheltricot/
- X (Twitter):https://x.com/MichelTricot
- Website:https://airbyte.com/Airbyte
Recommended books
- High Output Management by Andrew S. Grove — A systems-first lens for building teams and measuring managerial output that informed Airbyte’s “window into the build” culture.
Referenced
- Airbyte: https://airbyte.com/Airbyte
- Airbyte GitHub org:https://github.com/airbytehqGitHub
- Airbyte OSS repo:https://github.com/airbytehq/airbyteGitHub
- Airbyte community hub (Slack/forum/events):https://airbyte.com/community/developersAirbyte
- Airbyte “Getting support” (Slack + forum):https://docs.airbyte.com/platform/community/getting-supportdocs.airbyte.com
- Accel:https://www.accel.com/
- Benchmark:https://www.benchmark.com
Host links
- LinkedIn: https://www.linkedin.com/in/sophiebuonassisi
- X (Twitter): https://x.com/sophiebuona
- Newsletter: https://thegtmnewsletter.substack.com
- Website: https://gtmnow.com
Where to Find GTMnow
- Website: https://gtmnow.com
- LinkedIn: https://www.linkedin.com/company/gtmnow
- X (Twitter): https://x.com/GTMnow_
- YouTube: https://www.youtube.com/@GTM_now
- Podcast Directory: https://gtmnow.com/tag/podcast
GTM 169 Episode Transcript
Michel Tricot: 0:00
People are willing to put time into the project and the product that we are building. How do you actually commercialize it? It’s a different story. And to me, that’s what PMF actually is, where everything goes super fast, every deal gets closed in like a week, two weeks, one month max.
Sophie Buonassisi: 0:15
You launched in 2020. Now you’re valued at over a billion dollars. Michelle didn’t play the typical fast launch playbook. He went open source first, community first, and GitHub first. And it ignited one of the fastest bottoms-up adoption curves in modern data infrastructure. Today, AirPyte is valued at over a billion dollars, powering data movements for thousands of teams, including over 20% of the Fortune 500. And they got there in a really interesting way. They built in public, compounded through community, and turned contribution into a distribution mode. In this conversation, we break down the stories and lessons behind all of this growth, including a really important lesson on separating product market fit from project market fit. All right, let’s get into it. Michelle, welcome to the podcast.
Michel Tricot: 1:11
Thank you for having me. Great to be there.
Sophie Buonassisi: 1:13
It is a pleasure. And it hasn’t been long since we saw each other earlier this week, in fact. So it’s great to see you again.
Michel Tricot: 1:19
Yeah, no, that was a good, a good event. Like that was the Tech Crunch one that was very solid.
Sophie Buonassisi: 1:25
Yeah, that was great. And your your uh session was highly attended. Sounded fantastic. Excited to pick your brain a little bit more intimately than at the event itself. And you launched in 2020. Now you’re valued at over a billion dollars. Take us back. We want to know the how behind this type of growth.
Michel Tricot: 1:43
Yeah.
Sophie Buonassisi: 1:44
And before we even get started from the beginning, a lot of our audience aren’t engineers. A lot of operators, a lot of founders. Give us a high level of AirBite. What does Airbite do? Kind of the two-liner for everyone listening.
Michel Tricot: 1:57
Yeah. So AirBite is an open data movement platform, meaning that we can take any pieces of data across any system and we can deliver it into a place where it will deliver value. So a very strong use case is going to be everything related to analytics. How do you go across your company, look at all the services that you have, all the data sources that you have, all the silos that you have, and how do you make it seamless to move that data into warehouse so that your analytics uh team can actually extract insight from it and make decisions from it. And that’s really how we started. There is a ton of use case when it comes to moving data. You know, we’re talking about agents these days, is like how do you get the data into agents? So that’s very much what the very high-level value of Airbite is.
Sophie Buonassisi: 2:44
Super helpful. And now let’s go back to the beginning. You launched on GitHub. Why open source as opposed to a traditional product launch?
Michel Tricot: 2:53
Yeah. So when you’re thinking about, let’s take the analytics use case as an example. You go from like the outcome you want to drive, which is I want to be able to understand my business. The first thing you think about is okay, I will need to have dashboards, I will need to have a team, I will need to have a warehouse. And the moment you have these two, what you realize is that you also need the data, obviously.
Sophie Buonassisi: 3:18
Yeah.
Michel Tricot: 3:19
And this is a very organic um behavior from people, which is it’s not thought through so much as a strategy, but more as an enabler. So they’re gonna go bit by bit thinking, oh, I need this particular silo, I need this particular silo. And it is very hard to actually think about the pain that it will be if you build it yourself, or it will be very hard also to find platforms that can support every single silos that you have. And for us, when we did open source, what we wanted is to go and talk to the team that are building all these different connectors. So when you’re an engineer and you’re being asked, oh, I need Stripe data to be in the warehouse, the first reflex that an engineer will have is go online, check how do I move data from Stripe, Salesforce, HubSoot or you name it, into my warehouse. And we wanted to catch these people exactly at that time. We wanted to provide them value the moment they have that little painful script that they have to write and give them something. So open source at that point is generally the best solution because I mean I’m an engineer, I’m a little bit lazy when it comes to if I can avoid building something, I will.
Sophie Buonassisi: 4:42
Yeah, fair.
Michel Tricot: 4:42
And open source is generally the solution for that, and that’s really why we went for like open source. The other reason is there’s an infinity of places where data can be. So it is impossible for a single company to make a product that will address all the long tails of data connectors. What we need is, and what the community needs is like, in a way, all working together in a goal of like addressing all these use cases. And that’s why open source for us was a solution. Like you, you know, you can think about the Linux kernel. Well, all the drivers are being built either by the community, either by by vendors, but the Linux project is not building all these drivers. They are asking the community to build those, and that’s how you just get to the best uh uh product on the market.
Sophie Buonassisi: 5:34
And it feels like we’re seeing more and more companies open source. Do you feel that also?
Michel Tricot: 5:39
Yes. Um, yes, and I think it’s because the technology, especially this, you know, open source is very, very present in AI, for example, because there is almost like a complete stop of the old world versus the new world. Like everything has to be reinvented. And people who are making decisions today have to catch up on a lot of context. So, what they do is actually they go talk to their team and ask them we I we need to create an agent for this particular use case. What technology should we be using? And open source generally works really well with technical profiles. And I think that’s one of the reasons. There are also a lot of things around sovereignty and control that comes with open source and also future proofing because you can always update the project yourself if you want to. And to me, that’s a direction that we’re seeing. And having a community that backs a project just you cannot beat that velocity.
Sophie Buonassisi: 6:42
Yeah, so true. So true. And okay, so you launched in 2020. When you uploaded the repo, did you know that it would take off the way that it did?
Michel Tricot: 6:53
No, we didn’t know. We are so in the story of Hairbyte, like Airbyte started really just two months before COVID really hit the world.
Sophie Buonassisi: 7:02
What a time to start. Yeah.
Michel Tricot: 7:04
And we had an initial product at the time, which was also related to data integration, but more geared toward marketing teams. And what happened with COVID is boom, all the marketing team got frozen, laid off, etc. etc. Because company had to figure out, okay, what does the world look like now? And you know, as a founder, you put your life into uh a company, into building a product, and you don’t want to be a vitamin that I like to joke about that is not going to survive a global pandemic. So what we did is we actually went back to the drawing board. And in July, like during the period of like March to July, we were building prototypes, etc. etc. But but we’re also talking a lot with the audience that we wanted to build a product for, which was data people. And all these people, they were always having a solution that they would buy, a solution that they will build, another solution that they would build, another solution that they would buy. So it was like a collection of tools everywhere just to move data. And what we’ve done is just keeping in touch with all these people and keeping them in the loop of what we were building, what product. So at the time during COVID, everybody, I think a lot of people were very available on LinkedIn. Yeah. So we’re very, very active on LinkedIn. So we were always trying to talk to the right people, going on a Zoom with them for like 15 minutes, 30 minutes, and then we would ask them, Do you want to be following what we’re doing? And say yes. And then we created the first mailing list that we had, and every time we had updates, we would just say, Oh, this is what we’re building. If you want to, we can give you a quick demo of what it looks like, and you can give us feedback. That was before we published the repo. And I think it was in November we actually put the um the repo out. And suddenly, first of all, like this initial group of people started to download the software, started to give us like real feedback, and from there it just went uh in hockey stick.
Sophie Buonassisi: 9:11
Yeah, incredible. How did you feel just seeing that growth after you said it yourself when you’re a founder? You put you put everything into a company.
Michel Tricot: 9:19
Yeah. It’s uh I felt very good in a way, which is people are willing to put time into the project and the product that we’re building, and yet it is super immature. And you know, we always talk about PMF in the the founder founding sphere. PMF, my definition, having seen that, is it’s when people are willing to go above and beyond to make something that is not yet mature, that is not yet working, and they are willing to put the effort to make it work because it is solving such an intense problem for them that this little pain of making it work is better than the big pain of having to do it yourself. Um, and yeah, it felt good. After that, yes, I knew that the technology needed to become better, but you have to launch.
Sophie Buonassisi: 10:08
Yeah, yeah, exactly. Usually, if you’re at a point where you feel like it’s good enough, it’s too late from a launch perspective.
Michel Tricot: 10:15
Exactly. Like you want to get the feedback as fast as possible. You just want to build what is actually going to deliver value for your community.
Sophie Buonassisi: 10:22
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Michel Tricot: 11:01
I’m actually splitting it because there are two paths in the life of Airbytes. There is what I call project market fit, which is we managed to create a project that was very much resonating with an audience, data engineers, data analysts, etc. And they were just taking the project and using it and contributing to it. Product market fit for me also comes when you start pulling the foundation also of uh monetization. And this is a different story because it’s easy to take a product from GitHub. How you actually commercialize it, it’s a different story. And to me, that’s what PMF actually is. So I would say open source was project market fit.
Sophie Buonassisi: 11:45
Got it. Okay. Well, take us through a little bit of the evolution then. Because you got project market fit. What kind of go-to-market decisions did you make along the way that helped you to get to product market fit from project market fit?
Michel Tricot: 12:00
We were not using regular channels. It was all about content. I mean, at the time content marketing was a thing, but I don’t think it was as uh as popular as it has been like in 2023, 2024. But we were just always pushing articles, giving details about how the what the company is doing, what the project looks like, and just getting people to be part of our adventure. And that created trust, that created curiosity, that created a lot of awareness. You know, we published our fundraising slides, for example. So that was a way for us of like engaging the community into what we are doing. So that uh that to me is something that not a lot of people have done in the past. So it was very uh, I think very I’m I’m pretty proud that we’ve done that. It’s very, very innovative. And then, yeah, like we’ve always been very strong on content, engaging with the community.
Sophie Buonassisi: 12:57
So but it is time consuming content. So how do you think about that as a founder? How do you balance your schedule? When do you work it in? What’s your actual cadence or was at the time for any kind of founders or operators listening that are looking to up level their content?
Michel Tricot: 13:11
Yeah. It is time consuming, but you know, if it’s working and you feel it’s gonna be working better than any other solution, you just continue and you you exploit that uh that channel as much as you can. Um after that, we yeah, we are now we’re doing we continue to do a lot of content, but we are also a lot more like traditional channels like ads, uh SEO, GEO, etc. etc.
Sophie Buonassisi: 13:39
So yeah. And did you write it all yourself? Did you hire a ghostwriter? Like when did you actually physically put kind of uh pen to paper, if you will, or fingers to keyboard?
Michel Tricot: 13:51
I would say the first year and a half, it was my co-founder and I writing. The team also was writing. So we really created that cute that internal culture of let’s write something. My VP of engineering wrote an amazing article about the pain of building connectors that we keep referring to, even five years later, uh, because it really explains the pain.
Sophie Buonassisi: 14:14
Yeah. Well, it’s funny too. Five years later, and the pain is still the pain.
Michel Tricot: 14:18
The pain is still the pain, and uh yeah.
Sophie Buonassisi: 14:20
Yeah. Incredible. Okay. So you lean into content early, and that helps sounds like create a bit of a tribe, and you have a very strong following of people that are passionate about the product and the space and the solution that you built. How did you think about actually taking that interest generated from your content and other means and turning it into more of a community motion?
Michel Tricot: 14:41
Yeah. For me, at that point, so we we also created a Slack community at the time. I think today we have about 25,000 people on it. And the way we created the community was in twofold. One is we were helping the community a lot, we are doing a lot of support because we are building the platform, and so every time someone had an issue, that was a product feedback for us. So we spent a lot of time in 2020, like end of 2020, beginning of 2020, like all of 2021, and uh we we continued after, but that was very, very intense, a year and a half, where we were always on Slack. Every single issue that was reported, we would just have something shipped the day after or like the week after. So I think that created that’s that was one thing that helped uh building the community. And then what we did is we also identified a lot of champions within the community, like people that wanted to help other people. And yeah, we really engaged with them. We actually hired one of the first community managers that we that we’ve had at uh at Airbite, is someone that we actually brought from the from the community that was he started to build an airflow connector, like an airflow integration, and say, Oh man, that’s amazing. And we didn’t ask him anything, and at some point we asked him, like, do you want to uh to do it your full-time job, like to engage with the community, write content, etc. etc. And they’re like, Yeah, let’s do it.
Sophie Buonassisi: 16:12
So it’s amazing.
Michel Tricot: 16:13
That to me is like the community engagement is is absolutely key. That’s how you create that tribe, that’s how you create that snowball effect. It’s it’s not something that you put on, you say, I’m building community, and it’s gonna happen by itself. No, it is something that has to be worked on, and you have to be intentional about what you want to do uh with the community.
Sophie Buonassisi: 16:34
If you were to look back now with the benefit of hindsight, it sounds like community and content are two pillars that helped with your go-to-market motion. Yep. Is that correct? And also are there other pillars that you’d say were really pivotal in your growth?
Michel Tricot: 16:49
Um we did a lot of events, actually, very specialized events around uh data, whether they were open source events or like Snowflake or Databricks events, it’s just always getting where the people were. And that was something that worked pretty well. It allowed us to get a lot of people, new people interested, or just to engage in real life with people. Yeah um yeah. I would say, and here’s really what what happened between 2020 and 2023. After that, we had we added a few other things on top of uh like how we engage with the community, etc. etc. But that to me was very very much like the three pillar of what we’ve done. It’s like giving a window into the company to people, giving in a window into how the the engineering team is building, giving a window into everything we’re doing.
Sophie Buonassisi: 17:49
And do you still operate that way?
Michel Tricot: 17:51
Uh a little bit less. Um but we continue to have that constant engagement with uh with people. Like, you know, when the the great thing that when you have a community like that is someone in whether it’s a customer, whether it’s uh it’s a user, is going to ask you a question or a feature, and then you’re it’s gonna go into your head and say, okay, is that really useful? Or is it just for that person? And so what you do is you go in your on your community and you you just post a very simple question, like is that something that resonates with you? And in 30 minutes, you have like hundred people that are replying, yes, no, yes, but in that way. So it really accelerates how you do product discovery, how you do uh product development. So that’s uh that’s more like how we’ve changed a few things uh along the way. It’s like we’re we’re leveraging the the community a lot more for like what new features we should be building rather than really the the the core value proposition of the ambite.
Sophie Buonassisi: 19:00
Right. It’s uh a feedback loop, yeah, essentially. Yeah, great, and a very, very rapid one too.
Michel Tricot: 19:06
Very rapid one.
Sophie Buonassisi: 19:07
So content, community events, pillars that you did incredibly well to reach the point you are now. There’s always the other side of the story of you know, what were the the areas that didn’t quite hit as well or almost the near-death experiences along the way that every startup goes through.
Michel Tricot: 19:22
Yeah, so as I said, like the beginning of the of how we are engaging with the community was very a lot of support, like helping them be successful with the product. And there was this moment where even in our in how we were working, our community became very much of a like support channel rather than like building a uh a community that was just helping each other. Um, and that to me was uh is something that we could have been more intentional at the beginning around how do we um how do we get to like community members helping each other, community members like meeting each other outside of just like rather than becoming a very much like support-oriented um uh community. And the thing is, once this habit is taken, it’s very hard to shift uh into a different direction. I think we succeeded, but it took us a lot of time. We should have been more proactive thinking about okay, the community is amazing, but what is the future? Like, how do we make it more vibrant, more um yeah. How do we create a community of professionals that work in data and that are just gonna learn from each other and not just from us?
Sophie Buonassisi: 20:42
Yeah, it completely makes sense. It’s kind of the the the tell all tales, the tell all tale story of community is a lot harder in practice, and it does require some really deep intentionality around fostering.
Michel Tricot: 20:55
It does, it does.
Sophie Buonassisi: 20:56
Yeah, and what does that team kind of composition look like right now at Airbite?
Michel Tricot: 21:01
Um so we have we have a we have a DevRel person, and this this person is more um focused on the like the content strategy geared, oops, geared toward the community. And we have a community manager, meaning someone that just engages, identifies champion, uh, gives them access to um early features, etc. etc. And we also have people um in internally we call them like customer engineering, where their focus is to make sure that every product feedback around connectors is being funneled through the team to make sure that our connectors keep getting better and better and better. So this is more like for the contributors of the platform. So we really have a difference between like the users of the platform and the contributors of the platform, and we handle these two groups differently.
Sophie Buonassisi: 21:58
Gotcha, gotcha. Okay. What are some other areas that you know along the journey, again reflecting back, have just been some of the most pivotal things that maybe you don’t you don’t see or talk about as much?
Michel Tricot: 22:11
Um I think that was the the realization of why are so many companies using airbite. Is it just connectors or is it something else? And connectors is a is level one, but there is a second level to it, and it took us a little by a little bit of time to figure it out, is people were also using data, uh airbite, because there was so much red tape around the data that they had internally, that having a platform that they fully control that runs within their infrastructure, it’s a byproduct of open source. And we did not realize uh I would say like fast enough that that was one of the key reasons why so many teams were adopting airbytes. So, you know, when we started to to do the airbyte monetization, we said, okay, we’re gonna follow the we’re gonna skip the step of doing support for people that are deploying airbytes, and instead we’re gonna go directly to a cloud product. And very quickly we realized, yes, cloud is getting traction, but we are not able to convert every person that is using airbite to using airbite cloud. And at that point, we just went back to the drawing board, started to talk to them, and that’s when we discovered that in that case, like product market fits was not just connector. It was the fact that these pipes were under their control. And that was a big, a big thing, and I would say we we wasted a little bit of time on trying to build something fully cloud when what people needed was control and sovereignty.
Sophie Buonassisi: 23:53
Got it. Okay.
Michel Tricot: 23:55
More like, you know, when you’re searching for PMF, it’s not a straight line.
Sophie Buonassisi: 24:00
Never linear, never linear, no. And what are you most excited about thinking now forward?
Michel Tricot: 24:06
Yeah. Well, you know, every time I hear about how do I make I mean to me, like the AI wave that is happening right now is just one of the most exciting things for me and for the for the company. Like analytics is very much a core part of what we’re doing, but we’re getting so much pull into different types of data access. And that is something that we’re today encoding into the platform and into our connectors. It’s not just humans consuming data today. Yeah, it’s agents that can discover what’s available, discover what it looks like, and make decisions. So, yes, the technology is not yet completely mature on either side, whether it’s airbite, whether it’s like agency platform, etc. etc. But you can see how fast it’s moving, and I think it’s very energizing, especially in the infrastructure world, to see that that energy being uh being injected. So that yeah, I I I talk about it all the time.
Sophie Buonassisi: 25:06
So Yeah, no, that’s fantastic. And I mean you mentioned that at the very beginning around how now it’s agents consuming this type of data. How does that transition in the overall industry? What does anyone need to know about what this transition actually means?
Michel Tricot: 25:22
Yeah. You need to you need to forget about a lot of your existing patterns. You know, I was chatting with uh with a CTO uh last week, and he told me very bluntly, I don’t know, maybe he was trying to uh to be a little bit uh uh provocative here, but he said he told me, Michelle, all the technical knowledge I had stopped two years ago. I had to fully reinvent myself and reinvent my team. Uh so yes, some things are still transferable, but your default should always be thinking about how do I build in that new world? Is there a solution? No. Okay, maybe I go back and use the techniques of the of the the older world. But that’s really what what I’m seeing is people have to rethink how they are doing their job. Because one thing that is happening in Teams is a lot of people are using AI today to remove from their play the thing that they don’t like doing. That’s very easy. Like people have a very strong uh willingness to stop doing the things they hate doing. So for that, like AI is is is amazing. Like, you know, if you’re an engineer, right like writing unit tests, writing integration tests, that’s great, but that’s just level one. The moment you actually start changing your mindset is when you’re looking at the things you like doing and how can you leverage AI for those. But those are hard because the things you like doing are the things also that can bring you a lot of energy in your in your day-to-day. And those are the things that people should really be focusing on. On okay, this thing that I’m doing every day, I love doing it, but can I do it using AI, using an agent? Can I ask my engineering team to build an agent to solve that particular problem? Is there an AI product that exists that can do it and removes that from my plate? And then I can focus on more things and I can become faster. But to me, it’s really about reinventing um reinventing it. For data, the way you access data is very different. Yeah. Um but just having a warehouse doesn’t cut it. Like you need to have like an agent does live processing, it needs to have like little pieces of data here and there. You need to provide access to the agent in a different way. So that’s and that’s what that’s what we’ve been building.
Sophie Buonassisi: 27:54
Yeah, absolutely. How did that change your product roadmap overall? Did you have like this crazy moment in a way where it was like the realization that you entirely have to pivot? Or is it gradual?
Michel Tricot: 28:07
I I wouldn’t say it’s a it’s a pivot because it’s more like a an extension, but also sometimes we like to talk about replatforming, which is we’ve we’ve built the plat the platform for like a specific use case in a specific course, but there are new ones that are coming that are going to pick up massively over the next few years. And we need to be thinking about taking all the learnings that we’ve had here, and how do we think about replatforming it to just have a larger breadth of use case? So that’s that’s more how we’re thinking about it. Uh, I don’t know, I would say 2024 is when we even even before like summer 2023 is is when we started to like tippito into it. But 2025 is a moment where we we went all in on that. So we still have the the analytics product, it’s a it’s an amazing product, but we are really building on top of that, like leveraging part of it, but also rebuilding a platform that allows agents to uh to interact with data. So it’s pretty pretty cool.
Sophie Buonassisi: 29:12
Super cool. And you’re hitting the ground running, tons of growth, you’re hiring lots of folks on the team. Like, how do you think about developing that team to take it to the next stage of growth?
Michel Tricot: 29:22
Oh, you have to be hammering, yeah, using AI every single day, every single or-ens that I do every Wednesday morning. It’s about putting the spotlight on new uh new way of leveraging AI. And not just the layer one, which is do the thing you don’t like doing. It’s really about how are people building things that change their, actually change the the definition of their job. So well, if it’s if it’s on sales, it’s gonna be around like how do they do uh like discovery of account, it’s gonna be how they connect, um Like different news together, how do they connect to like past conversations that’s happened on support? So it’s really about like aggregating all this information in one single place and have like all the context available to them at the right time. On engineering, well, we talked enough about engineering and how agents are transforming the lives of engineers, and that’s what we’ve been doing at Airbytes for the yeah, for the for the past year.
Sophie Buonassisi: 30:26
Yeah. And so it sounds like you disseminate this information internally. You said weekly.
Michel Tricot: 30:31
Weekly.
Sophie Buonassisi: 30:32
What does that look like? Everyone’s on a team call weekly, or how are you spotlighting people?
Michel Tricot: 30:36
Yeah, so the whole company we’d spend like 30 minutes together and we go over like some updates, but then we always have like one presentation that is just about AI. And myself, like I generally start the whole hand and I always have a few slides around like the wins of the week. Yeah. And well, we have a channel on Slack where people just write their wins and I just gonna pick one or two. And that’s why I mean like pulling the spotlights on specific individuals that have done something innovative with it. And I think that creates like a good dynamic. Like people want to be on the win slide, etc. etc. So it creates a little bit of like internal competition.
Sophie Buonassisi: 31:14
Yeah, internal competition and also ideation. Exactly. I find sometimes the biggest blocker is the inspiration and ideation around like what can I actually do with AI?
Michel Tricot: 31:23
Exactly.
Sophie Buonassisi: 31:23
So seeing other people’s use cases is helpful.
Michel Tricot: 31:26
So that’s why like it’s always a topic every single week. And then we have like tons of sharing uh channels where people just every day we have one that’s called My Life with AI. And every day there are like 10, 20 posts on it of people saying, like, oh, Cloud Code was terrible on this one. Oh, Cloud Code was amazing on this one, and people just build that context internally on like what is good at today, what is becoming good at today, etc. etc. So like you you need to create like this very, very strong connection.
Sophie Buonassisi: 31:57
It’s such a cool period of time. It’s like a level setting where no matter how senior you are, everybody’s on the same learning plane, which is so, so cool.
Michel Tricot: 32:04
Yeah, and that goes back to what my friend was telling me. My knowledge, I need to just re-relearn.
Sophie Buonassisi: 32:12
Relearn. That’s a good way of putting it. We’re all relearning, rewiring ourselves.
Michel Tricot: 32:16
Rewiring, yeah.
Sophie Buonassisi: 32:17
And Michelle, you have a technical background. Your technical founder. What was it like to build a go-to-market engine as a technical founder?
Michel Tricot: 32:27
Very good question. Um so the first thing is I’m not alone in this adventure. My co-founder is uh is uh a little bit more on the on the marketing team, on the marketing side. It was actually the in a way it was the first devrail of airbite. So we’re working together on like technical papers and technical articles, but otherwise he was doing a lot of the heavy lifting when it comes to to writing to writing content. I go for like I I understand pretty well like the the psychology of users. So we started with a very, very strong uh bottom-up motion. And this is a place like even if I don’t have experience like building a go-to-market engine, we did pretty well at building that bottom-up motion. The place where I needed a little bit more support uh was on like how do we do the the top-down, how do we go to toward enterprise.
Sophie Buonassisi: 33:26
How did you get that support?
Michel Tricot: 33:28
So I I actually hired um uh a CPO that had been working solely on enterprise um um companies. But I took someone that is not just a product person, but really someone that has a very good, that has a lot of breast in terms of like both product, but also like how do you actually create this engine, this enterprise engine. So to me that was the the first step there. Uh it started in um 2024, I believe. Yeah, that was January 2024. And from there we started to like bit by bit build the enterprise engine, starting small at first, because you need to learn. Yeah, and yeah, when uh went all in there uh at the beginning of the year, because yeah, 2024 is really when we we launched the the enterprise product and very, very quickly picked up. So we had to uh we had to um to expand there. We did do a a few a few mistakes along the way, which is selling to enterprise takes time. And when you’re used to like bottom-up motion where everything goes super fast, every deal gets closed in like a week, two weeks, one month max, suddenly you are like in this longer sales cycle, a lot more stakeholder, like hiring people, you need to rent them, etc. etc. So what I’ve learned here was like you have to be a lot more proactive in thinking about hiring over there. So that that was that was a big learning for me.
Sophie Buonassisi: 34:59
And the ramp time proactive, do it earlier.
Michel Tricot: 35:01
Would that be the distilled lesson for everyone? Yeah, while still being like because it takes like six to nine months to actually deliver, you want to also edge your bet a little bit. But that’s the that’s the idea. Like it’s not gonna happen from one week to the next. It’s gonna take a lot more time.
Sophie Buonassisi: 35:21
It’s a a great piece of advice for anyone listening to. Because most of the time companies are wanting to go a little bit more enterprise, and it’s challenging to to cross that chasm unless you’re intentionally planning for it, which sounds like a big lesson on your side.
Michel Tricot: 35:37
And there are more physical limits. When you go bottom up, there is a lot of things that you automate. Like you have Saleserve, you have like a very automated uh sales cycle, but when you go to to enterprise, well, it’s a lot of like human time. Um so yeah.
Sophie Buonassisi: 35:53
And did you feel like you went enterprise? Why did you go enterprise? I guess. Were you seeing signals or was it that you wanted to go enterprise?
Michel Tricot: 36:01
No, we we have about uh 20% of our um of the Fortune 500 that are using AirBuy today, we’re working like with like very, very big media company or banks. And I could feel like the the lack of maturity of the team on like how do we how do we sell to that audience, how do we sell the the product, and also what is missing in the product. Like when you’re selling to uh data teams, well they have their own requirements, but when you start selling like across different uh business units or across different teams, like there are suddenly a lot more things that you need to be adding to the product that are not directly tied to the value that you provide, but that are actually tied to how this uh company actually buys software and actually uh leverage software. So that was it’s it’s both on the go-to-market side, but it’s very, very tied to the to the product.
Sophie Buonassisi: 37:00
Okay. Michelle, you raised your Series A two months after your seed round. Take us through that process.
Michel Tricot: 37:09
Yeah. So we started the like raising our seed round in November 2020. All was finished in uh in January. By the way, we had to uh delay the announcement because we’re trying to buy the domain. And we didn’t want to pay the the premium of uh being funded.
Sophie Buonassisi: 37:29
So you had your round, you just didn’t have the domain. Did you have a website on a different domain?
Michel Tricot: 37:34
Yes, we did.
Sophie Buonassisi: 37:35
Okay, but you’re trying to get the main domain for the announcement. How did you get it? Did you have to just work out the money or did you go negotiate?
Michel Tricot: 37:41
No, but we it we we had it for like a a good uh a good price. Okay. Perfect. You got it. Secure lots of tract action here. Um and the thing that happened after we actually announced our series uh our seed, this is the first time we had put our slides um live. And it really created a lot and lot of traction on the open source product. Like people, because it was really solving a very, very, very painful problem for that audience. And our numbers went like through the roof between like January and May. And that’s also when we started to build the engine to make sure that contributors could be also involved in the project. Before it was just us building because there was a lot of foundational work that needed to do. But we opened up the repo for external contribution. I don’t know, it was around March or beginning of April, and it picked up really fast. And I think at that point, when you see an industry that is moving so fast, like data, uh at the time it was not even AI, it was it was just data, you see that boom, suddenly we are present in like 5,000. Um I don’t think it was a little bit less. Um, it was maybe a thousand uh different companies after just releasing the the repo for like a few months. That creates a lot of uh of attention. And I think it’s a very innovative way of like solving the problem of how do you move data around. So that’s uh that was uh I think that I think they did a good move, like going for like and we did a good move on uh on on raising the series A here, and it also allowed us to just invest more into growing the community.
Sophie Buonassisi: 39:34
So are there any drawbacks to doing that? Yes. A lot of companies are evaluating timeline, and we speak to many companies and advise them around timelines, and two months is very quick.
Michel Tricot: 39:47
Yeah.
Sophie Buonassisi: 39:47
Now, what are the drawbacks or the pros to doing so?
Michel Tricot: 39:50
Well, the one that is very simple is when you release um an open source project, you don’t have you don’t get paid for it. Yeah. So the drawback is that suddenly it puts you on uh on um the expectations are high. That’s that I would say that’s pretty much it. But at the same time, you know, when we when we raise the series A, and even when we raise the seed, we chatted with these investors, and all the time we were pick we were picking the ones that had a very deep understanding of what it what it means to build open source. What it does it means to build an open source company. Because you don’t do open source for the sake of doing open source, you do it because you have a strategy. And ours was very strong bottom-up awareness, building a standard, and those can take a little bit of time. You know, you can look at you can look at Elastic, you can look at Ashi Corp, etc. etc. Like all of these, like you create a very strong base, yeah, and then you figure out like all the different basically your real product market fit. Um, and so I would say like not like that’s a risk of drawback. We did not have it because we had a a very uh knowledgeable um uh investor on that front.
Sophie Buonassisi: 41:17
Got it. So it sounds like a learning for anyone thinking about this kind of strategy or even just overall with the alignment around expertise with your investor.
Michel Tricot: 41:27
Exactly. Okay. The partner you’re working with, well, yeah, they’re gonna be here for a very long time. You better be very aligned with them on like what you want to do and also like their tolerance for yes, things don’t always go right.
Sophie Buonassisi: 41:44
And how do you evaluate that from the founder seat? Because naturally we evaluate it all the time from the other side.
Michel Tricot: 41:49
Yeah. Um, well, like always, when you in a way you you recruit someone, yeah, back channels is the best way. So you talk to other companies, you you you search for the company where it went well, the one that where it didn’t go well, and create a relationship with the with the people that have been working there and and see what they have to say. So excellent. And also you see, you know, you you also see like during the during the the fundraising process, like is how much are they um evolving your thinking? Uh, you know, when we raised with Axel. Yeah. Like I remember spending like two or three hours with uh with Amit at the time, and he asked questions that in a way helped us improve how we were thinking about the the future, the positioning of Airbag, and what to do. So there was already some very strong value on like working with uh with him or working with uh with Shetan at benchmark. It’s like they they help you think. And yes, they have their opinion, I have my opinions, but at the end of the day, like are they allowing you to see places what you don’t know about? Right. And if so, I think that’s a that can become a great partnership.
Sophie Buonassisi: 43:08
Great advice for anyone listening, thinking about that investor founder relationship. Okay, take us back to a little bit earlier. If we were to circle back to your product market fit, were there any kind of biggest challenges to that? I think there were some big kind of moments around that.
Michel Tricot: 43:30
Um yes. Um I would say like in 2022, that’s when we we started to work on the on the cloud product, which by the way, if you’re an open like for open source founders, like going from an open source product to an actual cloud product, it is super hard. Because hosting and managing something when what you’ve done is like providing something that you don’t need to really host and manage, etc. etc., this is very, very hard. And in 2022, we released like the let’s call it like the private beta of uh of Airbite Cloud. There was a ton of problems, and which by the way is completely normal, but we underestimated how complex it was to build a platform. And because we had this big plan of like how we’re gonna be monetizing airbite, etc. etc., I would say we we hired a little bit ahead. And that to me was uh was a mistake because it also creates a lot of noise internally. It like disrupts the product team, it disrupts engineering, it creates like a lot of noise around like building the best product. And that to me was uh I don’t know, I would say was a bad decision. Uh we we had to course correct, but I would say it’s like especially when you’re starting something new, just start small, expand rather than go go bottom up in terms of how you’re building your your your company and your organization rather rather than top down. There is a moment when you can do top-down when you have like a lot more predictability, but at the beginning it’s uh it’s a mistake.
Sophie Buonassisi: 45:14
So bottom up.
Michel Tricot: 45:15
At least for us it was a mistake.
Sophie Buonassisi: 45:16
Yeah, well, it sounds like in everything that you did, you were always looking at signals. Like I know I’ve heard you say that open source allowed you to have signal density. And through the community aspect, you’re talking about using that as signals and feedback too, and same with this bottoms-up approach.
Michel Tricot: 45:31
Yeah, yeah. I’m a I’m a very bottom-up person on that front. But at some point, yes, when I see it’s always the same thing, like we all build we’re building an engine. So we need to figure out what is the the MVP of that engine. Yeah. And to do that, you need to find people that are extremely driven, that are okay with uncertainty. But the moment you start getting like an initial version that is working, that’s when you can start like putting more uh like more thought into what it should actually look like. But first you need to validate something. Definitely.
Sophie Buonassisi: 46:05
Well, this has been fantastic, Michelle. Really, really appreciate the time. A couple last questions. You know, you have learned immensely throughout the journey, but are there any books that you’ve particularly been influenced by throughout your career and life?
Michel Tricot: 46:20
Yeah, you see, I don’t know if you remember, but I said giving a window into how things are working to the outside world. Yeah, I did not invent that. It’s like when I was I think it was in 2014, I was just um, or 2013, I was just starting to uh to manage my my first team, my first team at the time. And my CTO gave me this book from um it’s called Um High Output Management. I think it’s now it’s a standard. Uh and it really, you know, when you go from being an IC to starting to manage people, it’s very hard to find like the right feedback clue for like, are you doing a good job or not? Like what does it mean that you’re doing a good job? And also how do you build team as systems? And I think that book was just transformational for me because I like good theory, yeah, and that theory was very very strong, and like how you create, how you how you build, how you build the system, how you monitor these systems, and um and uh how you take pride of the work when you’re not the one always doing the work yourself.
Sophie Buonassisi: 47:31
Yeah. So great, fantastic. Well, that will be in the show notes for anyone curious to take read and pay it for it a little bit. Where can people follow along your journey in airbytes?
Michel Tricot: 47:40
Uh well, the I would say the entry point is always gonna be airbite.com.
Sophie Buonassisi: 47:45
There we go.
Michel Tricot: 47:46
I’m on I’m on LinkedIn, I try to post as much as I can.
Sophie Buonassisi: 47:49
Yeah.
Michel Tricot: 47:50
Uh content marketing. There we go. You’re very good at it. And giving and giving a window to uh to the to the people uh on what we’re doing. And and yeah, and after that, like you can go on Slack, on our GitHub repository, and just or just try the product.
Sophie Buonassisi: 48:06
There we go. There’s many ways. Many ways.
Michel Tricot: 48:08
Point of entry is going to be the website. Perfect.
Sophie Buonassisi: 48:11
The website itself. Well, Michelle, this has been fabulous. Really appreciate the time and you sharing your journey and insights.
Michel Tricot: 48:15
Yeah, thank you for having me. It was a great conversation.
Sophie Buonassisi: 48:18
Absolutely.
