EOIN (00:00):
One important lesson I've learned is that, yes, you should be married and dogmatic about the vision, but you should be extremely flexible to how you achieve that vision.
VO (00:11):
Welcome to Spotlight on a podcast about how companies are built from the people doing the building one messy, exhilarating decision at a time.
LUCA (00:20):
Welcome to Spotlight On. I'm Luca. I'm your host for today. It's great to have Oin Ichi, senior founder of Tines O. Let's start with the basics. So for the people that might not know you or Whatt is all about, tell me more.
EOIN (00:36):
Thank you for having me. Honestly, it's a real pleasure to be here. So I'm the founder and CEO at Tines, and we're an automation platform for mission critical teams. So think for cybersecurity, automating things like phishing response, security alerts, compliance violations for IT teams, things like employee onboarding and offboarding for product teams, things like infrastructure management, those types of use cases. Company is about seven years old now. I have to say that part really fast because it freaks me out a little bit. Course about seven years old I founded in 2018. Previous to that I spent about 15 years as a security practitioner.
LUCA (01:09):
Yeah, I know that very well. So you spend 15 years as a security expert across a few incredible technology companies such as IGN and eBay. What did you learn throughout that journey that ended up giving you more insights, ended up really building times together with tk?
EOIN (01:27):
Yeah, I never had any ambitions or grand plans to be a founder or an entrepreneur. I loved technical work, so my engineering degrees are in computer engineering and electrical engineering. So that was the world that I loved to inhabit. And I got a job at a college helping to build and run eBay's instant response team. So receiving all the telemetry from our various security systems, figuring out and understanding which alerts needed to be investigated in what way, and then responding in the event of a real threat. And that was an amazing job and I loved it. And I got to work with some of the most cutting edge technologies. So I always had this real passion for exploring new technologies and trying to apply it in ways to solve these novel problems that we were dealing with, especially in these kind of cutting edge technology companies that were dealing with very sophisticated attacks.
(02:21):
We needed to have these very complex and accurate and modern tools. In about 2017, I was running cybersecurity at DocuSign and was responsible for everything that wasn't strictly compliance related. So our soc, security engineering teams, threat hunting, threat management, all those teams kind of rolled up to me and my team were amazing practitioners all knew their jobs inside out could respond to any type of incident, but they were security practitioners, not software engineers. And increasingly as that company was growing and as our ability to detect malicious behavior in our environments was improving, the amount of ops work on that teams, those teams' plate was increasing really quickly. And by ops work, I mean like running out phishing emails, responding to making sure that compliance infrastructure was stood up correctly, et cetera. And they were just completely overwhelmed with all these different alerts, all these different systems.
(03:17):
And when we benchmarked it, we found that about 80% of my team's time was spent doing something they'd already done that day. And as a people manager, that's really, really heartbreaking because we spend six to nine months finding these people, getting them really excited, convincing them to join the company, and then we just have them do the same mundane stuff over and over and over again. And that leads to human error, it leads to mistakes, it leads to risk, it leads to incidents. And frankly, it's also a reason we invented computers so people wouldn't have to do this monotonous stuff over and over again. And so the genesis of to it's really out of those jobs. And we tried to find an automation platform that would allow my team, again, knew their jobs inside out, could respond to any type of incident, but would allow them automate their own repetitive manual tasks quickly, easily at massive scale without having to be software engineers and without having to know how to do things like GI and deployment and credential management and logging, take all that stuff off their plates and allow them focus on their jobs and the things they wanted to do better.
(04:25):
And long story short, we couldn't find anything that came close to me in our requirements. Nothing came close. They were too hard to use, couldn't handle the complexity of our workflows or their pricing models were punitive for how we wanted to use the tool. And so I said, you know what? I can do a better job of this myself. And so founded times really to scratch my own itch, I would say in that this is a problem I experience firsthand and I wanted to go and build the company to solve this problem. I'd experienced myself.
LUCA (04:55):
That's very spy. And you met tk.
EOIN (04:57):
I met TK for years. You're the founder, right? Yeah, my soulmate.
LUCA (05:01):
Exactly. So how you guys decided to build on together? What was the trigger for the two of you to decide to partner up?
EOIN (05:08):
Yeah, so he and I had worked together for the best part of a decade. We had worked together even before eBay in Deloitte for a couple of years. He and I then worked in eBay together. We went on to build a security team at DocuSign together. And so we really had a very, very good grasp of what our individual strengths were. And as security practitioners, we had been in extraordinarily stressful instant response situations, working together 24 hours a day type thing. And so we had a lot of trust and I could never imagine doing a startup without him. It's just like I just wouldn't have done it. And so it wasn't a case of, Hey, I'm going to do this startup and I'm going to convince TK to maybe join me. Or hey, if I do the startup, maybe TK will join. Or if TK does something, regardless of what my next job was going to be, it was going to be with TK in some way, shape or form. And so it wasn't kind of like a light bulb moment that, Hey, we should do this together. It was like, of course we're going to do this together. Partners, we know each other really well. And so we continue to argue like cats and dogs, I kind of know this, you've seen it, but it's always from a place of enormous trust and we have huge respect for each other's strengths and weaknesses. And it's because of that. I think it's one of the reasons we've been successful.
LUCA (06:39):
That's great.
EOIN (06:39):
Yeah.
LUCA (06:40):
So Taiwan's vision has been very clear from the get go.
EOIN (06:44):
Yeah.
LUCA (06:44):
Do you think that early customers that you've been pitching the call it the vision and the alpha product that you had in mind at the same, or you had to evolve, you had to adapt, you had to take some turns and listen to some feedback that maybe help out you shaping up maybe the early products?
EOIN (07:01):
I think the core vision and the North Star has been unwavering for the last seven years, hasn't changed, and the mission has always been the same, but the way we thought we would get there has evolved enormously based on customer feedback and insight. And a lot of the instincts that we held true in those early days, our customers convinced us that they weren't correct for various reasons. And I think that's one important lesson I've learned is that yes, you should be married and dogmatic about the vision, but you should be extremely flexible to how you achieve that vision and the technology choices and hiring decisions you need to make to get there. Because as you know, the world changes so quick. Indeed. So quickly. And when we were starting the company seven years ago, we didn't know that LLMs were going to be a thing.
(07:55):
We didn't know that Gen AI was going to come on board. We didn't know Covid was going to happen, but we always knew that there should be a platform to power the world's most important workflows. And so our vision has always been to power of the world's most important workflows, but we've always been exceptionally flexible to how we achieve that mission. I'll give you an example. I'm going to get in the weeds a little bit here, but one of the initial categories that times kind of played in was soar. So security orchestration, automation and response. And SOAR was kind of a technology that began to evolve while I was a practitioner, like 20 15, 20 16, there was a couple of early companies and we looked at those platforms when we were trying to find a platform solution for DocuSign. Exactly. And we didn't, we felt the vision needed to be a little bit differently.
(08:43):
But SOAR was this combination of four technologies. It was kind of like a workflow automation product, a case management product, a thread intel product and an analyst collaboration product. That was kind of how Gartner and Forrester and those folks bucketed it. And we only did workflow automation. That's all we did. We had this very strong belief that what really mattered were workflow automation, and you shouldn't have case management. They should be completely separate and segmented. And there was a certain cohort of customers that absolutely believe that as well. They were like, yes, you're completely right. And these were my people. They looked like me, they dressed like me, they came from the same companies as me. But over time, we heard from more and more of our customers, I totally get it, understand your vision, but here's my world and here's the day-to-day challenges that I face
LUCA (09:30):
And my needs and the way my organization
EOIN (09:32):
Works. Bingo. Oh yeah, I've actually never lived that. And so as a result, we completely changed our mind on how case management and T should work together. And we released our case management product as a direct result of that. And I had to tell the team, I just got this wrong. I got it wrong. Here's what I believed, here's what I've heard. Here's why we're changing. And now the vast majority of our customers also use our case management product. So it is just a good example of, yes, stay true to your vision, but don't be shy about, you've been wrong in certain ways.
LUCA (10:08):
But going back for a second to the early days.
EOIN (10:10):
Yes, sir.
LUCA (10:11):
What was the first customer? How did you sell it?
EOIN (10:13):
Yeah, so for the first two years we were bootstrap and self-funded. So myself and TK working in this tiny little office under a bridge in South county, Dublin in Ireland. And we just wrote code, talked to customers 12 hours a day, seven days a week. That's all we did. And we were first time founders, first time entrepreneurs, had no real understanding of how things like this worked except from the practitioner or buyer's point of view. And so we found ourselves talking to people from our network as those initial kind of prospects for want of a better term. So we would reach out to people that we knew that we had worked with that trust us and say, Hey, we're building this product. It's going to do X, Y, and Z. Here's the reason we're building it. And they're like, okay, sure. We'll give you a shot.
(11:02):
And so one of the opportunities we found ourselves in as a result of someone we'd worked with previously was a bit of a charity layup. Honestly. They were evaluating a product from a 60 billion company and a 30 billion company, and this company from Ireland with two people and a hundred euros in the bank. And we had no concept that you can't do that. That's not how these things work. You shouldn't be doing it. But we did a bake off against these three products. And what was kind of cool about it was the company we were working with, they were a Fortune five pharmaceutical, they're still a company customer today. And they had three globally dispersed socks. And they were evaluating these three products and each product was assigned to an individual sock. So one sock got tines, another SOC location got product A, another one got product B.
(11:57):
And the challenge was everyone got the same automation use cases, and it was a very fair fight in that sense, and we absolutely destroyed everybody else. Those other companies didn't even get a single use case stood up. And of the three use cases we've been tasked, we did all three in two weeks and an extra one on top of that. And that's when we started to realize, yeah, okay, this is going to be something that we're building that's actually going to make sense, that's solving a real problem. And I think it also really drove home to us the fact that how big these problems were that a company of the size we were talking about was willing to take a risk on a two person company with no financial backing whatsoever to solve and
LUCA (12:47):
The solution
EOIN (12:48):
To solve what solve pain points solve these. Exactly.
LUCA (12:50):
So pain points were pretty high, the space very well. You have a good network, but you were only UNTK.
EOIN (12:57):
Yes, sir.
LUCA (12:58):
Who was the first hire? How did you think back then about hiring the first few people?
EOIN (13:03):
So we did our series A with Excel and Blossom Capital and Index in late 2019, I think it was. So just two years after we'd been founded. And we then started to grow the team and so on. And we were security practitioners and so on, but we always felt really strongly that we needed to have the best product and the best customer experience. And if we had those two things, the rest would kind of take care of itself. And so we very much focused on that. So our first couple of hires were rather than usually a designer, a guy called Johnny, who still leads our design teams today because we felt an important differentiator was going to be the look and feel of the product and how user-centric it was going to be. We hired a guy called Martin, who was a customer success engineer who knew automation and security absolutely inside out.
(13:58):
And then we hired a woman called Annmarie, who was our first kind of sales person. And we'd worked with all these people previously. And so we had a really strong relationship. We knew each other really well, and they were excited to come and join this startup and work together. And so we were five people in March, 2020. We were really, really excited. And then this weird thing called Covid began to happen. And the funny thing is we had just moved into an office, so March, 2020, we had signed a three year lease on this 20 person office. And we always knew it was going to be too small. We were going to outgrow this thing after a year, but we just felt so strongly that it was important to have these people co-located the first 10, 20 people, but we never even got to use a fricking thing. We closed the door and we all had to go home and then so on. But yeah, that was
LUCA (14:54):
Ages ago. But those days brought through you a lot of excitement, of course in early team, but I'm sure also some mistakes.
EOIN (15:02):
Oh yeah.
LUCA (15:03):
Some mistakes that you like to share, especially with funders or fellow entrepreneurs that are something you think strongly about even today.
EOIN (15:11):
Yeah, I think a couple of things that we did wrong were, because we were so inexperienced in this space, we would try to apply playbooks for want of a better term in a very prescriptive way. So hey, here's how you do B2B, SAS sales, step one. And we'd be like, okay, step one, it's like almost following a cooking recipe or something like that. And even though instinctively some of these things didn't feel right for us, we were kind of like, oh, this must be how it's done. This must be how it's done because this is what the book says to do. Even though we didn't necessarily instinctively agree. And that led to us making some mistakes around the way we do demand generation and lead gen and the type of people we would hire and so on. And I think the lesson out of that was, yes, follow the playbooks. Yes, understand what's worked for other companies, but also combine that with your instincts because again, your company best the product, the buyers, you've lived these pains, so don't do stuff that the playbook says that contradicts your instincts and gut. And I think great investors will help you with that, right? They'll kind of recognize, Hey, look, here's a playbook that I've seen work really, really well, but you guys, you should do something a little bit different here because you guys know the space and
(16:40):
Trust your gut in these areas as well. I could literally sit here talking all day about the mistakes that we made as well. I think the other thing that we did was not investing early enough in the story, and this is advice that I give founders all the time, is you're in a demo and you're talking to a prospect and you're really proud of the technology that you've built. It's really good and you're really proud of the product. And as a result, when you're talking to a CISO or a buyer or a CIO or something like that, you go straight into the weeds and it's like, oh man, check out this widget that this feature has and check out this amazing cool thing rather than talking about the story and why you founded the company and your vision and so on. And there's a time and place for talking about the widgets and so on, but you really need to have your narrative, your story down pat first. And I wish we'd spent more time perfecting that, perfecting
LUCA (17:38):
Earlier
EOIN (17:38):
On. Makes sense.
LUCA (17:40):
Then we often say Excel, the great companies can be built anywhere.
EOIN (17:43):
Sure.
LUCA (17:43):
You alluded to earlier, you built in Dublin, your own country, Ireland. Looking back, given that early on you had a lot of customers who were not exactly based in Dublin, but were global and many of them in the us in fact, how would you say was kind of a bit of an exploration mode for you starting your company from Dublin to the world and alluded to Covid, but beyond Covid, even today have a global organization. How is it, what's advantages, what disadvantage, some learnings that you like to share?
EOIN (18:15):
I love the question because there's this whole narrative between European startups and US startups and so on, and it has never entered our mind that that should be a consideration. I, myself and Thomas both lived and worked in the Bay Area for a number of years, and I think as a European person of my generation, you grow up with companies like eBay and Yahoo and Google, and they have this mystique about them that there's this utopia where technology is built and that's only where technology is built. And then you work for these companies and you live here and you're like, oh, they're just like us. And so once the curtain has dropped around that, you begin to realize, why can't I build a company from over here? And we ran teams where we had direct reports all over the world reporting to us in Dublin.
(19:05):
So we were very used to doing crazy hours and just getting what needed to be done when it needed to be done. And so when we founded times, we were always going to build the company, or at least found the company in Ireland. And we never tried to hide the fact that we were based in Ireland or based in Europe. We were always really honest with people when we were talking to us, we were like, oh yeah, we're in Dublin, you're in the Bay Area, awesome. So on and so forth. Now, when we did our series A, that was one of the things we started to talk about in early 2020 was like, okay, does it make sense for myself or Thomas to move to the US and help establish a team? At that stage, 80%, 90% of our customers were in the US and we were supporting them from Ireland and doing a good job of it.
(19:56):
But then Covid happened. We were in the middle of these conversations, COVID happened and the option was just taken off the table. And so we had to hire people from Dublin. So we hired our head of product who was based in Boston. We hired our head of US sales who's based in Vancouver, bc, and we ended up end to a state where we had people in 23 states in the us. And so by the time the option began to rear its head again, where TK and I could physically move to the US again, it was no longer necessary because we had all these very strong established operators on the ground. Now, don't get me wrong, we still spend a bunch of time out here. We're recording this in San Francisco.
LUCA (20:40):
I know that
EOIN (20:40):
We're here at least once a quarter. And so I think it's really important to do everything from a customer first point of view and be as close to your customers as you possibly can be. But now everybody is everywhere. Everywhere. Our customers, even though their offices is in San Francisco, the person who's using the product is in Florida. And so there's limited value even being in one particular place as long as you're willing to travel and meet them and so on and make time. And I think the access to talent is now a very different prospect. Like 20 years ago, even when Stripe was started and John and Patrick from Dublin, they had to move to Bay Area because the people that they needed the engineers and so on had to be based in the Bay Area. That's where that talent was a decade later.
(21:36):
Those folks are now all over the world. They're in Ireland. We've got engineering hubs for all the top 19 tech companies on the planet. So people that have seen web scale and have worked with cutting net technologies live in South County, Dublin, and they live on the west coast of Ireland and all around the world. And for a lot of those people, they don't want to have to travel or go to an office or whatever. So I think it is worth asking yourself, and this goes in general as a founder, it's worth asking yourself, what's the problem you're trying to solve? What's the problem I'm trying to solve by being based in San Francisco or what's the problem I'm trying to solve by being based in New York or Boston? And if the problem you're trying to solve truly means that you need to be in this location, then you have to go there. For us, the problem that we were trying to solve, it didn't matter where we were as long as we were willing to get on a plane and spend time with our customers.
LUCA (22:34):
Speaking of customers, you said earlier you started with tackling organization. Even today you go on your website of times you'll see amazing logos of the most beautiful tech companies in the world, but over time you've been serving also enterprise. What does it mean for product? Because you had to add some functionalities as you alluded to before, but what else you had to do because you had to strike strong trade offs effectively, right? You wanted to play the beautiful technical excellence of the product, but also the usability and some other credentials that you needed to add. Tell us more.
EOIN (23:07):
So you're absolutely right. Our ICP, our ideal customer profile in those early days was like a cloud native software companies, high growth, et cetera. And that's the world we came from and so on.
LUCA (23:19):
People dress like you,
EOIN (23:20):
People dress like me. Exactly right. And over time, what would happen was our champion or main user from one of these hyper companies would move to a very different industry. So they'd move to banking, finance, they'd move to manufacturing, they'd move to chemicals, whatever, and they'd be like, Hey, I want to bring toss into these companies. And we'd be having a conversation with a company that makes something that rusts as our CO would say, and they would have very different requirements around governance, hosting capabilities, et cetera. One of the rules that we, it's not necessarily a rule, but one of our modes of operation is we almost always build things that the customer asks us to build. And this is kind of contradictory to a lot of advice you will hear as a startup founder, often you're told like, Hey, don't go too big too soon because you'll be building these weird features for company and they're the only people that will use it.
(24:22):
I think that advice is trash, honestly. I think if a customer wants you to build something and they're willing to pay for it, build, if you've got a good enough engineering team and good enough product instincts, you'll be able to build that feature in such a way that it's not just applicable to them. It's also applicable to 200 other companies that look and feel just like them. And so we were never shy about a large enterprise or somebody outside our traditional ICP asking us for something and us building it as quickly and fast and efficiently as we possibly could. And that's really paid off. We have all these kind of weird features that we would never thought would make sense for other companies, but you find out that, oh, well this actually particular company, they also need it and they also need it and they also need it. And so I think when I hear founders say, we don't want to work with this company, the requirements are going to be very customer specific. I'm like, have they got money? Are they going to pay for the product? Build it. That's what you do. If you're not going to build the product that your customer wants, why do you do it?
LUCA (25:28):
Customer, you have a very wide variety. You said it also enterprise tech, cleaning startups, all of them are automating tasks. Bear with you. You now pass what 1 billion automation tasks perform per week. Correct? Right, which is amazing. Can you tell us more about some examples? Because you started of course, deep insecurity and then you move pretty quickly into IT ops and now even broad areas, some use case that you love something that is a bit out of the comfort zone for security professionals.
EOIN (25:56):
Yeah, so we have this saying internally, which is we've always been very opinionated about being unopinionated about how people use the product. So we don't tell 'em, this is how you should use our product. We kind of give them this blank state and a slate and a ton of examples for them to get started. And as a result, we tend to see this massive long tail of use cases. Now, there are a handful of ones that are extremely common that we see our customers like to start with. Could be phishing automation, it could be something along the lines of response to CrowdStrike alerts or remediation of wiz alerts, those types of use cases. My favorite type of use case is what we call distributed decision making. And this is the concept where if you are a mission critical team, security IT infrastructure, you'll often have to respond to an event of some description, a server's on fire, the CEO's laptop has malware, you need to do something.
(26:55):
But often in those situations, there'll be a piece of tacit knowledge required that you don't have access to in some system or data. And some end user elsewhere in the company will have that knowledge. So for example, let's say you sign on to the Excel VPN from Shanghai, an alert is sent somewhere and the security team needs to know was that you, right? Hey, did you do that? And traditionally what will happen in those cases is they'll send you an email that's like, Hey, Luca, we've noticed something weird here. Could you confirm this was you just reply yes or no, and then you're asleep, you don't get it. Whatever. They have to do a follow up, they have to send another one. Maybe you overlooked it. They have to find out who your manager, reach out to the manager. And it's such a waste of time.
(27:43):
Everybody's time. And I had to do this myself for years, these types of interactions. And so with tines, we have this capability to collect those types of responses in an automated way. So instead of the email or the notification landing on an analyst's plate, it goes to tines. Tines does all the heavy lifting of finding out who you are, what your email address is, what your Slack ID is collect enough context to be able to draft a beautiful lightweight message to you saying, Luca, letting you know we've detected this. Here's the time that happened that here's the location here was the device, press yes or no.
(28:19):
And if it was you, cool, I'm going to go and send a second factor to make sure it was definitely you and that your account hasn't been compromised. If it wasn't you, then I'm going to ring the bells, alarm is going off, et cetera. And that's a really unglamorous use case, right? But it saves, I'm not joking, millions of hours of our customer's times every single year. And I think that is the beauty of automation is that there's so many of those use cases, there's so much human mind power and ingenuity being wasted on this muck work as we call it. And you can just apply it to times and have the end users then begin to focus on the business impactful stuff that's really going to make a difference for your company. So that's the kind of category of use case I like in terms of kind of fun use cases and things that when you see it, you kind of blow your mind and you're like, I never would've imagined seeing people use that. We've got customers using tins for everything from opening their garage door from their car. They sir, open my garage door. We've got customers and users using tins to remind them to take their diabetes medication.
LUCA (29:29):
We've got serious six years.
EOIN (29:31):
We've got customers using tins to optimize the solar usage within their houses. We've got customers using tines to onboard offboard employees, and it's the flexibility of the platform that really gives it its power. We're never going go to you and say, here's how you should use tines. We're like, you know your problems way better than we do. Here's the tools that are going to allow you to solve those problems in a quick, easy, joyful kind of way.
LUCA (30:01):
Great. We haven't talked yet about ai. So you've been doing, what's
EOIN (30:04):
That ai,
LUCA (30:05):
I've never heard, never heard, but workflow automation, positioning yourself, entrenching processes that, I mean, can take the customers direction they want, but at the end of the day, you're sitting in some core processes around enterprise and startups. How have you been embedding AI in your product and where do you see the broader opportunity for clients?
EOIN (30:24):
Yeah, I love this question because it comes back to something we spoke about a second ago, which is be dogmatic about the mission, but be flexible to the technology and open to how you achieve that mission. So when L LMS and Gen AI began to enter the public consciousness two-ish years ago, a little over two years ago now, we were inherently very skeptical.
LUCA (30:46):
I remember that
EOIN (30:49):
We had seen lots of promise around AI going back a decade only for it to be complete fabrication and didn't actually solve any problems. But as we began to play around with chat GPT and so on, we pretty quickly realized this is different and this is going to be changing how everybody works, but again, we don't ship product for the sake of it. We don't bolt technologies onto check a marketing checkbox. We want to really understand what is the problem we're trying to solve for our customers using this technology. And so as a result, we spent a year, at least a year and 70 plus failed experiments trying to figure out how we could add this technology to times in a way that added real value to our customers and wasn't just part of the hype train.
(31:37):
And that was really hard. We were getting pressure from the market. We were having board meetings talking about our AI plans, and we were like, look, we're going to build something, we just don't know what it is yet. We haven't found the right thing. And eventually we landed on this fundamental understanding about our customer's usage of AI and what it mattered to them. And what we realized was the very first thing we need to do before we build any magic sprinkles within the product is we need to figure out how to secure this data, how to secure these models, and that's going to be fundamental for these mission critical use cases. So the first thing we did was like six months of unglamorous work, right? By just building the foundations that allowed us to run these models in such a way that there was no training, there was no fine tuning, there was no logging, there was no new subprocess, there was no sending information to random places.
(32:35):
And once we had that, then we could begin to think about what features do we want to build and so on. And that meant we went a little bit slow at the start, but it's meant since we've had that we've been able to really accelerate. And so now 70% of our customers are using the AI features we've built since we've established this trust. And it means when we go through these very strict, exhaustive AI review boards at our prospects and our customers, they love us because it's like no new suppressors, no new training, no logging. You're the only people doing that. Amazing we're it. So it's been worth it in the long haul. But in terms of the features that we built on top of this foundation, our mission is to power the world's most important workflows. So what we do is with some of our AI features, we allow our customers to build better workflows. So we allow 'em to use natural language to describe the type of workflow that they want to describe, the very intricate data transformations that they're trying to achieve using natural language. And that dramatically reduces the barrier to entry in these types of products that's trying to build better workflows. We started to ask our customers, why aren't you using AI more? We all agree that this is going to change the way everybody works, but the real business impact, at least that we're seeing has been fairly limited and unimpressive.
LUCA (33:55):
Very siloed. Right?
EOIN (33:56):
Exactly. And there was two things that consistently came up during those conversations that we'd have with customers. And the first was, look, yes, these models are amazing, they're incredible, et cetera, but they have no access to my real time and proprietary information. And so the actual value that they can provide to me is fairly limited because they have no access to my security data, they have no access to my firewall logs, they have no access to my Okta credentials, all this kind of stuff, and I don't have the time, energy, resources or desire to move all that data regularly into some fine tuning pipeline first problem. Second problem they had then was, look, we all again agree that these models are going to take action on our behalf at some point, but today I can't trust them, especially in these mission critical use cases.
(34:50):
They hallucinate and so on. And I just said, okay, totally get it. So these are the two challenges. And what we quickly realized was workflows are the perfect answer to both these problems. We spent seven years building tens of thousands of integrations. We spent seven years building a way for you to connect to any system in any site quickly, easily, and at massive scale so we can solve the real time access to proprietary systems and data immediately. And then the second challenge around predictable, accurate action on a customer's behalf, again, that's what we do. We do that a billion times a week for our customers. So we started to think, could we combine what we do really well, which is access authentication, enterprise security guardrails, deterministic action? Can we combine that with what workflows do really well? Or sorry, LLMs do really well, which is summarization of large amounts of data, contextual understanding, being able to determine what tool to execute at a certain time.
(35:58):
And so we released a capability within tines, which is now seeing our customers use tines workflows as the glue between these LLMs and their disparate systems and data. And that's been one of the reasons we've 10 x the number of events that we perform on our customers on a daily basis because we've gone from being an important part of everybody's technology stack to being the key ingredient of every enterprise technology strategy for the next three to five years. Because companies are like, this is going to be how I get real business value from these foundational models.
LUCA (36:39):
That's very exciting and it is also very exciting to celebrate your recent fundraising. You're now value more than a billion. You recently announced your series C and congratulations for this point. How does it feel seven years in role of the CE? Sometimes we say actually very often we say it's a bit of a lonely job. How has been the journey for you as a CEO? What
EOIN (37:02):
Say you're going to get me emotional. This is the part where I began to shed a here. And if you had told me seven years ago when I founded the company that this would be the position that we would be in, it is trite and a cliche, but I really wouldn't have believed it. This was never the ambition, right? The ambition was always to build a product that we wish we'd had and to make our customers widely successful and fall in love with the product. That's what we wanted to achieve. And we've kind of achieved all these massive milestones. We'll be 450 people at the end of this year and this huge valuation, and we've raised $300 million give or take. But the way we've always looked at these fundraising and these milestones is it allows us to do more of what we love, which is making our customers widely successful and building a product that we are so proud of.
(37:55):
And so we've never thought too much or too deeply about the valuation or the round or the amount raised or so on. It's always been what will this allow us to achieve and what's the next great milestone in terms of product and customer success that we'll be able to achieve as a result of this? And I think kind of anti intuitively, this is one of the great things about being out of the San Francisco bubble a little bit, is that we were never a company that was motivated or caught up in these huge valuations or those kind of paper achievements. We were always so focused on the customer, but this is the best job I've ever had. Genuinely the longest job I ever had before times was like three years, three and a half years. I tended to get bored really easily and want to do something new and exciting.
(38:48):
But every day in times is a new challenge. Every day I get to push myself in a different way every day. I'm humbled by the intelligence of the folks on the team and their desire to do right by customers. And so it is an honor and a privilege to get to lead this company and work with our teams. And I think what's most exciting for me is I genuinely feel as if we're about 1% done with what we're trying to achieve. We've been doing this for seven years, but in terms of what we want to achieve and the ambition of our vision, it feels as if we're like 1% of the way there. So we're going to continue to be focused on customers and product. And I always, again, coming full circle, I really feel as if you do that, build a great product, focus on customers. Everything else takes care of itself, the fundraising, the hiring, the culture, and you can just go and maintain energy and maintain humility and just really focus on
LUCA (39:53):
The team. Yeah, that's very much your leadership style. I think it is very clear, and I think throughout your words, it become awfully clear to everybody. But maybe a few more words about role as a CEO is also making sure that you maintain the culture and the core values of the company, the way you define them, but it's also maintaining the performance of the company. How have you been able to do that and how, because normally it's hard to do it, especially scale when you grow fast. Any advice will you recommend to younger funder or people that are ahead a bit early in their journey?
EOIN (40:23):
Yeah, I think so. My background is software engineering and electrical engineering. It's Logic Gates and c plus plus code. And so productivity models and organizational culture and structural boundaries within an organization, that was all stuff I had to learn on the job. And so I think the advice I would give founders or entrepreneurs of be really intellectually honest with what your strengths are and what your weaknesses are. And you don't need to have to be amazing at everything. You really don't. But you have to understand and be honest with yourself around what you're good at, what your strengths are, and what are the things that give you energy as a leader and as a founder. And for the other stuff. Hire people that are better than you, exactly. That are world class. And get energy from those things and give them the autonomy and give them the motivation and incentivization and purpose that they need to be successful as well. And once you do that, you can attract amazing people. You can attract incredible people that are drawn to the mission and drawn to the leadership style and so on. And then you need to be, again, honest with yourself that you're going to get it wrong all the time, and you're going to hire the wrong people. You're going to miss a quarter, you're going to ship the wrong stuff, and you have to own that. You really have to own. There's no point in fingers in this game.
(41:50):
You have to say, I got that hire wrong. We've let the person go, or I admit it, it was my bad. We missed a quarter. Those deals didn't come true. The marketing strategy wasn't right. I am responsible for that. And once you do that and you lead from the front in that way, it trickles down across the organization and you can do all the kind of motivational posters in the office that you want. What matters is that you embody the kind of behaviors you want to see within the organization.
LUCA (42:22):
Final questions. So what's next with that? You said so many good things about product. How much AI is giving you a chance to accelerate? How companies going to become able to be more productive? What excites you the most?
EOIN (42:35):
Oh, wow. I love that question. So what excites me the most is beginning to realize the vision we had seven years ago. So our vision was always this enterprise wide automation platform. We've been outrageously successful in security, we've had natural expansion into it. Now we're beginning to put the chess pieces where they need to be in order to start delivering on that strategy. And so the big bets that we made seven years ago are beginning to come true now. And watching that unfold, watching the pieces that you moved seven years ago begin to kind of stand up and bloom is extraordinarily exciting.
LUCA (43:13):
Thank you very much. That has been an amazing chat.
EOIN (43:15):
Anytime. I can't believe how fast this time went. If folks want to learn more about times.com, if you want to reach out to me, I'm on LinkedIn and all the social media platforms, always happy to provide advice to founders, to entrepreneurs, to
LUCA (43:31):
That's very kind.
EOIN (43:32):
CEOs always available.
LUCA (43:33):
And by the way, if they want to buy the product too.
EOIN (43:35):
Yeah, yeah, yeah, absolutely. Thank you, Lu. I appreciate it, man.
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