The a16z Show
00:20:26 · Mati Staniszewski
[00:20:26] S0: So when we launched, we had a lot of early inbound when we started kind of the classic PLG, a lot of inbound from enterprise. And I remember speaking with a16z team when they joined us, where our initial take was, of course, we want to be an engineering company, we don't want salespeople, we would like to reinvent that and have, like, engineers do the sales. We did hire one traditional salesperson and one non traditional salesperson, like an engineer, and we told them, like, do sales now, and that really, as you can imagine, didn't work out in this specific case. But we learned our lesson, and we now do invest in a combination of that. It's 80% sales, 20% engineering, so still a little bit of that. But this was, like, super important lever of understanding who are the customers, what they care about, and working deeply with them to bring it back. And then that kind of working with them was kind of opening of what we need to actually do on the product and research side. Munjal from Hippocratic is is is here. He was one of the the earliest incredible use cases in the health care space where they would create effectively agents that would take inbound calls that are calling the hospitals to take and schedule appointments, and beyond that they would do all the other parts of outbounding to the patients to remind them about taking medicine or reminding them about the appointment that's happening, and and to be able to do that, that suddenly shifts from using a one foundational model into combining the speech to text, the LLM, the text to speech to orchestrate them together, then the integrations you need to build, then you actually need to deploy, and they were one of the areas that was 2023, but then we've seen this repeated pattern across across a number of other customers and customer experience base and and many others, and and we decided to invest more into helping with the entire orchestration. So instead of just doing text to speech, we can help combining our research to make this whole whole combination of that more fluid. But then if you are thinking about enterprise, you do need to build the combination of knowledge base inside a system. You need to help deploy that with telephony providers, whether it's Twilio, the SIP trunking. Like, how do you do that in a templatized and easier easier way?
00:22:39 · Mati Staniszewski
And then, of course, the the biggest gap that's the most common, it's easy to do a demo, but how do you actually build it to production? How do you test? How do you version control? How do you evaluate, monitor over time, fine tune over time based on the results? And and all of that is... Has been a big big part. And underlying all of all of that, and we spoke a little bit with with Mat before coming here, the the foundation needs to be there, is the security, the compliance, serving serving the the customers across that will rely on that infrastructure. That's something that we want to shine through at ElevenLabs where if you are using the software, it's going to always be reliable and always the four nines or five nines, hopefully, one day will be will be there, which is tricky in AI space. But the the... That's the that's the goal. Of course, the the difference between the the one obvious difference between PLG and sales is the the cycle to work through and identify the right customers is much longer, and and I think that's where eagerness from our internal team was was interesting to observe, where you had a lot of people that didn't work in an enterprise setting, and then you had other side of the company that did, and the side that didn't was very skeptic about going enterprise and, like, kind of waiting the six months or twelve months to results, and in the early days we needed to shield them from that information and, like, trust us, we'll do this, and it will work, but they were very sceptic, and then, of course, after twelve months it worked out, but that was probably the hardest culture really of how you kind of still keep everyone jumping on same train.
00:24:16 · Jennifer Li
[00:24:16] S2: That's exactly right. A lot of companies actually, at least I observed, sort of slowed down after start adopting more of the enterprise sort of product launching and, like, building for the customers' request that started to thank you so much to delay sort of the product launches. Is that something you're seeing, or is there still, like, a good balance of like, we still want to be able to put out demos and POCs and early teasers quickly, but at the same time, we'll get to deliver a very robust and reliable product?
00:24:50 · Mati Staniszewski
[00:24:50] S0: So there are two parts. The first part is so we have a, like, a difference on the team structure and then we have a difference on the kind of external product structure. On the external product structure, we want to ship very quickly, but of course, you are shipping to enterprise, you want to make sure that it's stable and reliable. So we delineate very clearly what's alpha, what's not alpha, and then we go for that transition through that period. And then as we work with the customers, they can and then our partners, they can decide whether they want the access to alpha in the first place, and when they do, that's clearly shown that this is an alpha product, it might not be as stable, and so they get a choice, and I think that choice has been the most important lever, like do want it or not, and some are incredible in doing that innovation and showing some of their work or experimenting with that work. Deutsche Telekom, with John here, is creating some of the incredible new podcast experiences, and that came from, like, testing early models of turning a a text a text into, like, a more NotebookLM style of a podcast with incredible voices that you can select for German speaking voices, English speaking voices that that that sound good. And then there's a second, which is team structure piece, and that's something that we didn't do until until later when we had more than 100 of us, is that we delineate inside a company products that are pre product market fit and pro... Post product market fit. On the post product market fit, you are working for the long term. You test and evaluate a lot before. You you only deploy when it... When that's that's that's truly ready. The pre product market fit, your mission is is to ship until you think we've hit the product market fit. And usually, we give the six months period of, like, proving it out. If not, we kill the product, and we've killed product in the past this way. But that's, like, the the main important piece of, like, okay. Until we know there is a big potential user base, we we we will continue iterating.
00:26:49 · Jennifer Li
[00:26:49] S2: I've been able to observe some of those, I guess, hard decisions in the moment, but it's the right decision later on to let go of some of the products. This is one of my favorite questions. My partner Martin Casado always say companies go through three phases. There is the product phase, there's sales phase, and there's a scaling phase. Given you have been through some of those phases, what has been the hardest transition for you as a CEO?
00:27:15 · Mati Staniszewski
[00:27:15] S0: There is a lot of a lot of mini ones. Of course, I have my my co founder next to me across each of those, which is the... I know him for fifteen years. He's my best friend since high school, so I have, like, the the most luck to to to have that combination. Of course, you, Jennifer, and all the partners to help us through those transitions, which has been incredible. But I think the recent realization was when we are now a three fifty people company, and of course that means our go to market team and the incentive structure around that has evolved pretty strongly. And what wasn't clear to me, and now in hindsight is obvious, is that in early days everybody would just operate on a passion basis. They would just operate what they think is best for the company. As our go to market team enlarged, we realized that the incentive structure really matters if you are building that machine. And that transition where you shift from a lot of the people that are helping create that machine, are part of that machine, those incentive structures will eventually drive the behaviors, which might be slightly different to what you had in mind if you don't make it extremely clear. And in some ways, the quota, the commissions are effectively a lagging indicator of strategy, and then strategy is kind of leading of what will happen in the future. So you need to find a way to resolve those two together, where you want to make sure that quota and commissions and the strategy that you want to drive are closer together and they... And the kind of the disparity as close as possible. And so here, for me, the biggest realization was that we are becoming a bigger company because there are clear behaviors that happen based on the commissions, and then, two, to actually resolve those, we need to be very upfront in terms of making it explicit that sometimes, even if commissions are just this, and you think it's the wrong thing, come back to us, let's speak about it, and let's adjust course. So now we are explicit with all our sales teams that if they are seeing a deal that, let's say, might be competitive in nature, and our pricing table would suggest that they can go very low and earn higher commission, but they think it's wrong, it's better to come to us. We are happy to still grant commission but kill the deal and and go out with us.