Building High-Performing Teams in the AI Era with Charles Guillemet & Sandra Schwarzer

Speaker A: If you hire a very important key senior person in your team, somebody who will influence culture, who will influence the talent that comes your product, you better make sure that you slow down.

Speaker B: Big welcome to everyone. Thank you so much for being here for what is a very special live recording of 40 minute mentor with two of the ultimate goats of the talent ecosystem, friends of mine, wonderful supporters and um, just incredible people, Charles and Sandra. So thank you very much for being here. They're going to share their insights on a topic that is incredibly important, which often will make and break the success of a startup, which is all around building high performing teams, which is a passion topic for myself and many people in this room. And I can't wait to dive into it, particularly in this new world, this AI era that we're in. Two people that have seen it up close and personal, super excited to dive into everything. I've known you both for a little while now, but our audience may not. So I thought we could start with some intros. We'll go. Ladies first. Uh, Sandra, if you don't mind just introducing yourself and your current role at Index.

Speaker A: You will hear the accent as we go through, but it changes depending on who I'm talking to. So I currently lead Index Talent function here in Europe. Joined Index almost five years ago. I don't think I have to tell you more about this organization, what we do, but we're celebrating 30 years this year. So I find it's like one of those milestones in the VC industry where you really can reflect back on all the things that have been achieved and what we're seeing right now. I started my career in the wrong place and relatively quickly figured that out and have then shifted into all kinds of different roles that go around people and talent. I've advised over 6,000 people on their career while I was at INSEAD. I was a chief people officer. So I know how hard it is when you have the theory and then you actually have to apply it into practice. Went to the headhunting and came here and you can see it from the fact that I am prepared. I'm originally German. I have come via France to the US and then the uk. So I also bring like perspectives from different markets and different backgrounds.

Speaker C: Thank you.

Speaker B: And Charles, over to you.

Speaker D: Yes. So my name is Charles. I'm um, from France. You can hear my accent. That's uh, very true. So I spent about 17 years in SF in the Bay Area. One of the couple of like highlights there is I built a company called Gusto, which is a payroll Provider. It's a YC bag company. And when I say built is like, I helped to hire those folks from 30 to about 1,000 by the time I left. Now the company is like much bigger. So that's kind of like what I was doing there then. I work for a company at uh, Elon Musk company called Neuralink. It's a brain machine interface. So if you don't know what a brain machine interface is, it's a brand, uh, that's connected to your computer and basically two years there working directly with like uh, Elon and his uh, CEO office to hire the best talent in engineering in different fields that are needed. And then I worked at Meta at the corporate office in Menlo park and I was doing exec and leadership recruiting there mostly on like the analytics side, data engineering and data engine, uh, staffing for VPs and their directors. And then I worked at a VC here in London called Local Globe, which is like an early stage investor. Many companies that you aware of. And then I recently started at Lovable, uh, so I work in Stockholm, but I'm currently based in London and relocating to Stockholm in a, uh, few weeks. And I'm married and I have a son. My wife is American and my son is French American.

Speaker B: Awesome. Thank you both so much and I'm so glad we were able to get you Charles before you relocated. So thank you for making the time. Clearly those are uh, unbelievably distinguished careers and you've worked with some of the greatest entrepreneurs that have ever graced this planet. We should probably start with Elon Musk. A polarizing figure of course, but no doubt has an eye for talent. So I'd be very keen to hear your learnings from working with him and any particular things that have stood out to you from that experience.

Speaker D: So I am a fanboy of Elon. My wife probably like complains about how much I love him, but I would just say I am a fanboy of Elon as an entrepreneur and I would leave it at that. I think he's done other things since then, but I really respect him and look up to him when it comes to become an entrepreneur and to be an entrepreneur. And some of the highlights working with him and for him I think is one he doesn't really play in the hype game, meaning that he goes down to. It boils down to the fundamentals with him and the principle and the first principle thinking. So I don't think he gets hyped by a logo or company or like what you've done in the past. I think he relies very heavily on, um, internal interview processes that we built. And those indicators are very important to him. Second thing is, I think he came to the office one day with a hammer and was like, you're not asking the question why, why and why, you know, so like peeling as often as possible why someone would make a career decision, answer a question a certain way. He was very pragmatic around, um, this and he wanted to boil it down to first principle thinking. Then he's got a couple of triggers. So this might be kind of like polarizing, but it's elon, so it's fine. But essentially he's not a big fan. Like the way to phrase it I would say is like, he is very careful about a ratio, like PhD theory versus actually producing things in real life and real time. So I think if you think about a ratio for like a product or like an AI thing or like a R and D project, you probably want to have one PhD higher for like 20 engineers who are actually going to ship and produce something. So he's very careful around this. He's also very careful around MBAs. I'm sorry if anyone has an MBA here, but he just basically boils down to actually people who are doers. He says that people who have an MBA usually make slides, but they're not always like a doer. So like, he really wants to vet for this. So this really kind of like stayed with me super, super strong because whenever I go to a new place and I help the place to hire, whether I'm at a VC or like, no, I'd loveable, uh, I sort of have that in the back of my mind that like he really cared about this and that came very strong for me. The last thing that I would say is that he's huge entrepreneur and he thinks that essentially like anyone who has worked at a company for under two years hasn't had the chance to actually build a legacy and leave a footprint. So if you see like a candidate who's gone from like, you know, one company to another over and over again, under two years, for him, that would be a major flag. And it would be like, look like if you work at a company and you really to leave a print, you probably have to spend more than two years at this company. So these were like some of the principles that we operated with to hire for him.

Speaker B: Super interesting. Thanks for sharing. Sandra, to you, uh, index best in class founders. You'll have seen them all across different stages. Geographies Industries. I know this Is like asking who your favorite child is. But I have to ask who are the founders that stand out to you and why, particularly when it comes to hiring exceptional talent?

Speaker A: Uh, I will answer the exact same way that I tell my children, I don't have a favorite child. But I did think back about like, are there any common traits that I see coming back over and over again in those founders that are able to attract like top talent? And for me it boils down to a couple. The first thing I would say is they're intensely creative. They probably also very intentionally about the creativity and the curiosity that comes with that. So they don't go in saying like, I have all the answers, I know exactly what I want. They really go like, what does best in class look like? Not just today and in the past, but tomorrow? What do we actually need? And they're able to shift around some of them way before they need really senior talent. So I have some very early stage founders who are already talking to people who might only join them when they are at 100 or uh, million plus in revenue. And in today's world, who knows how fast that will be. They build those networks, they might rope them in as advisors and they might bring them on board in some ways so that they can pull the trigger when they're ready to hire. And they will have made their selection already. So they kind of um, are winning at identifying top talent way earlier. They're intentionally in everything they do. There's a speed. And I'm sure we'll come back to how you hire and how you hire fast. But speed is intentional. How they make decision and what kind of decisions is really important. And how the candidate experience makes you experience the culture so that you can filter through who will actually work with us really well is there. And then I would say in today's time, they experiment and are not afraid to fail. So a lot of them, you know, playbooks are dead. What somebody else does, I don't think you should look into it anymore. It's like, what's the problem we're trying to solve? How does it work for us? And they iterate really, really fast in the same way they do on a product.

Speaker B: Mm, super, um, interesting. And really resonates with what we're seeing with our clients at the moment. Charles Lovable. I mean, is the one of the darlings, if not the darling of the European tech scene, one of the fastest growing companies in the world? I mean, what a cool place to be.

Speaker A: Mhm.

Speaker B: Heading up talent. What does building AI native teams actually look like at a place like lovable in 2026. And I'd love to hear your thoughts from someone that's been on the VC side recently working with founders. What has changed in the past two years and what's that like in practice?

Speaker D: So much has changed. I mean, I think a lot of what Sarah said to me resonated. Speed is the one thing where I'm blown away by Lovable is how fast they work and how fast they move. I think one of the things that surprised me the most is the agency that Anton, the CEO, is willing to give to his employees by making decisions on their own. There's no approval layers, meaning that if you want to make a decision you want to hire, you should go for it. So there's this funder mindset at Lovable. In fact, I think out of 130 employees that we have, 43 or 45 are ex founders, which just shows like the DNA of this company and almost operating a little bit siloed in making decisions on their own. We use quite a bit the probation period, which it's a good thing and a bad thing. I would say the good thing is we can actually make hires a lot faster and then we can let go of, uh, folks who are not working out and where Lovable is not the right fit, like very fast as well. I talk about this quite a bit, but like, I've never been in a place where acquisition and acqui hire matters so much. So technically, like Loveable is like a series A, Series B. Depends on how you want to look at it. It doesn't really matter, but it's uh, like very early on. The company has been around for 18 months and already has an M and a function which if you think about OpenAI entropic, they probably had an M and a function like three or four years after the company was created. So what this means is basically we look at Acquisition as a way to hit our hiring target as fast as possible. We look at it in both technology that we don't have, like a technology gap that we don't have on the team. And then how can we hire like 20, 30 engineers as fast as possible so that we can ship? The name of the game at Lovable is shipping as fast as possible. There is nothing else that matters, so we have to ship. Why is because if you don't ship new products, you don't get new customers. If you don't get new customers, you don't capture more market share and then Lovable will stop to exist at Some point, because competition will take over. So the way that we can stay on top of competition is by building as fast as possible, possible as shipping. And you see the speed in execution in shipping and hiring and everything that we do. I used to be at a company like Gusto or like other companies at Meta, we're like literally making a decision like, should we hire an exec would take like three months. You'd write a memo, you'd be like, this is the kind of profile that we need at, uh, Lovable is like, let's hire someone. Like, let's go. Like, you open the search, you don't even do a kickoff. You just like, let's go, let's just hire this exec. And we're talking about an exec where, like, they might relocate the family. Their comp package are insane. And that's kind of like a decision that you make, like, on the way, like, super fast.

Speaker B: Yeah, it's incredible, isn't it, how times have changed. The speed is exhausting and exhilarating and amazing to see. Today is interesting because Olix, who you very kindly introduced me to, announces huge 220 million round. We just placed their COO and that process was less than five weeks, probably four. A relentless intensity to it. Uh, and a huge amount of rigor went behind it. But the speed was unbelievable, unlike anything I've seen before.

Speaker D: I think actually the exec level, there's something new happening in executive searches. I think in the age of AI, which is that folks probably expect to either be layered or to know that things are not going to be the same. So I give you an example. Like lovable was at 200 million AR in December. I think we just crossed 300. This is public and this is a matter of months. And if you think about the exec that was the right person for like 100 million AR, might not be the person that's the right one for a company that's doing half a billion, for example. And everyone in the company should know this, myself included. Will I be the right fit to run talent in like two years at Lovable? Most likely not. You know, I just have to be very honest with this. And I think in the age of AI, given how things are moving so fast, I don't know if you see this, Sandra, as well, but basically there's either fractional Exec, where you kind of hire folks and you know that they are going to be good for six months and they might not be the right fit long term, or you kind of set the expectations that uh, there might be a different profile to come later on that could be layering them. I don't know if you've seen something like this.

Speaker A: Yeah, I definitely not only have seen this, but it comes back to this curiosity and ongoing learning from the founders. You need to stop from time to time and just reflect whether what you have is what you need for the future or whether you need to shift and change things. And that with the layering, I think that's a really important thing because we can miss the signals of the past. We don't have those anymore where everybody's inventing it new, everybody's doing things differently. And so you have to figure out when is that moment that we're breaking it and we're going to do it totally different again and we're going to try something new, even if you're already at scale. And I don't think we have seen this before. Before it was quite linear and the growth was quite linear.

Speaker B: That's really interesting. In this market where the velocity is unlike anything else and the competition for talent is so strong, particularly amongst the fastest growing businesses, what can founders do to stand out from the crowds to win that battle?

Speaker A: I must say, personally, I'm very opposed to using all this war terminology that is very prevalent in San Francisco and is kind of coming over from time to time here. But we have been in these situations before where the market was so buoyant and hot that the employee and candidate actually had the upper hand. And you needed to hire incredibly fast and you needed to find the right people and they had usually multiple offers and you needed to tell them a story of one, why they had to come to you. And that hasn't changed. What's changed right now is the speed and the number of companies who are doing it concurrently. And I think in Europe, what has changed, which is actually great, but wasn't the same before, you have a lot of US native AI companies pushing into the market. You have a lot of established players pushing into the market. They're all coming to Zurich and to Stockholm and to London and to other places. And then you have this wonderful crop of European companies that are going at scale and they're winning globally. So all of a sudden, European brands are being recognized in Silicon Valley way before they would have been, uh, previously. So all of this is happening at the same time. The way I think about it and I talk about it, for founders, for me, there's like three big things. As a founder and the person who's hiring, who needs to. It's three areas to tackle. One is you need to understand your usp. You actually need to sit down and not just say this is what we're building, but this is how we're building it. And therefore you need to define what kind of person works incredibly well in my organization. And if I boil it down and then on in our portfolio at cur, it's you don't go to meetings, you do things and you have the autonomy to do things. So if something bothers you, you just build it yourself and off you go. So the autonomy and people who don't want to waste their time in meetings work incredibly well in the cursor process. Anthropic doesn't have titles like you're all the same. Like there's no distinction and there's a Engineers do research research do engineering project. There's a boundary that gets blended in a way. So you need to be comfortable with that. One of our portfolio companies, wonderful. If you go on their careers page, there's like a one sentence that distills everything they are looking for in a person that will work well. And I can tell you the majority of people will read this and go like no thank you. So instead of saying this is why you shouldn't work at Google or this is why you should not go to OpenAI, really think about why should you come to us and what is it? So that's the first thing. The second thing is the show don't tell. If you say that it's fast decision making, it's not a lot of meetings and then your process takes forever and there's new meanings being added on and the culture gets experienced in these fast processes. Right. So you need to be really intentional about how you're doing that. And then to win and this is going to get harder is like you can't win on compensation, you have to win on Mishva. So you need to understand compensation and you need to understand the different levers and you need to be able to explain them, which includes explaining how does this role contribute to our outcome that I'm telling you about and why you should accept and be excited about the exact. But you also need to know for yourself what's the cliff for the vesting period so that you can make a decision on whether they're the right person or not before that cliff hits. You need to understand that sometimes giving them more equity and backdating it so that the vesting schedule isn't linear is great because it buys you a couple more years to figure out how much they really contribute. And most importantly you need to understand what motivates the person because it might be totally different things, it might be your mission. We see the kind of people Anthropic attracts, uh, are different than the kind of people OpenAI attracts in many ways. And so you need to really talk about what, what is it that makes you unique in your building and how can they contribute to it. And you need to understand their motivators and relate everything back to that.

Speaker C: And I'm certain that pensions probably isn't a word that you expected to hear at an AI focused event on scaling high performing teams. And what we see is that uh, businesses are spending thousands if not millions of pounds on their most expensive employee benefits, which is pensions. But it's driving no engagement and no interaction actually from that business. So that's why we built Penfold. Penfold is the modern day workplace pension platform that actually drives incredibly high engagement rates with employees. We're now trusted by thousands of UK businesses and loads of names in the tech sector, uh, the likes of Anthropic, Airwallex, Lendable deal capital on tap and 11 labs are using US because they know that we're the solution that will improve engagement with their workforce as they scale their business. And luckily we're free to the employer, no cost and you can switch to penfold within a 30 minute phone call. So very easy to do that. So what we want to do is we want to ensure that your money that you're spending on this benefit is working as hard as your employees are with a pension benefit that really works.

Speaker B: I guess when it comes to moving at this sort of pace, I'd love to hear your thoughts on how you can avoid making expensive mistakes. Clearly probation is one aspect, but I think balancing the rigor, uh, uh, to make these really key hires, the speed that you need to, that's a really challenging thing to do. And often we've seen historically getting the wrong exact hire for instance, can be terminal. So what are your both your thoughts? I uh, don't know which whoever would like to take this one first but how do you balance those two things?

Speaker A: So for me quality and speed are actually not opposable forces. You can have incredible quality and go very fast. It's when it's unstructured speed that I think a lot of things break. So again it comes back to the being intentional. So really thinking about like what do you want to do? So be disciplined in your process, know who's going to contribute, know how you're doing these kind of Things front loading. The calibration I think is really important rather than having a vast amount of cv. I can't remember the number, but I think Synthesia and Elevenlabs recently published how many people apply for each of the roles. It's insane and you can't really filter through all of the AI applications anymore and you don't really know. If you don't know what you're looking for in a person for a specific role, it's going to get a lot harder to sit. So if you front load the calibration and really go like what do we need? What are the characteristics, what are the nice to haves versus the must haves, how are we going to make a decision including who is giving us an opinion in the interview and who's giving us a decision making criteria. That's important, compressing the decision making process. I would always try and get as fast as possible to the do we interview and if yes, do we move them to the next stage and communicating that back? Because they are likely in many, many processes and they're getting approached by many people and we were just chatting about this. I haven't seen it in Europe as much, but in Silicon Valley people are getting job offers without ever meeting the company and being interviewed. They're landing in their inbox. We have scoured the market. We know exactly that it's you we need. We've already taken back channels and references. This is your salary, this is the role. Would you like to come to a conversation? Call me. And it works. It's very different, but it works with some, I would say, not with others. So you need to know that that's what's happening in the market and then really separate what is recoverable versus what is irrecoverable. If you hire a very important key senior person in your team, somebody who will influence culture, who will influence the talent that comes your product, you better make sure that you slow down. That is a really tough mistake to kind of unwind. It happens and it will happen, but that is a hard mistake to unwind. If it's a more junior role or if it's a role where you think like, hey, maybe there's three or four people, I don't quite know which one will make it will figure it out. I think it is much easier to unwind the decision that you've made as well.

Speaker D: A lot of things that Sandra, you mentioned is true. I mean I would love to say that we do this at lovable very well, but probably not true. Other things That I think are very important right now. I know this sounds very kind of like typical, but spikes. I think we're very clear about hiring folks who spike like hardcore into a dimension. And we're almost willing to compromise on other things in their profile if they spike really hard into one dimension. So I'll give you an example. I think given the speed of execution being so important, if you hire and find an engineer who can ship faster than most of the candidates that we talk to, it's very likely that we're going to make an offer to this candidate because they spike really into one dimension. Sandra mentioned reference and back channel. I know this is very controversial right now, but we do so much back channel and we heavily rely on backchannel. So much so that there are some very strong indicators and alleviates the risk that you take. You can do super thoughtful back channeling. And then in the age of AI, I know it's weird to say this, but human connections matter so much more. So actually we don't really do that many like we do, but it's maybe not 100% of the interviews are not the traditional interviews where you have like, hey, cross functional interview or like, hey, like, how is this product interview? Or what is your coding skills? We bring a candidate on a Friday night, we fly them, um, family included. They spend a day. They do like what we call a work session. It's a VIP experience where you come, you stay at a hotel in Stockholm. Um, and then we basically spend a whole day or sometimes two days working with you. I think this brings a lot better signal. And the chances of closing this candidate are actually much higher than like doing the typical interviews where they go through like one or two or three or four interviews that are like super defined in the books.

Speaker B: Yeah. Creating the time for that deeper connection. You want both sides to be as bought in. You want both sides to have the same level of conviction. If you don't take the time to do that at a deeper level, you're opening the chance for them to go elsewhere, I think, and I love that I guess we've got an audience here of number of founders, a number of people in operator roles. We'll have founders watching this back. We always like to talk about the harder parts of the job, the mistakes that can get made and how we can try and solve for those. So what are the common mistakes you've seen over your career that founders can make when it comes to hiring and hiring decisions? And what tips and advice can we give them that we haven't already I

Speaker D: mean I can share a few. I think doing one mistake that founders often do is they don't do a debrief post hire. Super important. Even if you make a good hire or like if it's a successful hire, you should do a debrief always. I mean the more senior that matters so much more, you always can get better. You always learn a lot. So that's really good. I think being decisive, being an operator and then working for a founder, one thing that you expect from a founder is to be decisive. Whether you're going to agree with them or not. One mistake that you can do is not knowing or not making a decision. I think we expect the founder to be super decisive, especially towards the end of a process so that we can move forward. And then if we make a mistake, we leave and we learn. But I think these are two common mistakes that I see when it comes to hiring is not debriefing and then not also be decisive enough.

Speaker A: I totally agree. I have so many more by the way, I include myself in that I have made pretty much any mistake you can make on hiring. So even when you know things theoretically, the practice of it I think is more an art than a science. I alluded to it a little bit earlier. The confounding scaling and linear growth that is gone. And I think traditionally on average 200k ARR per employee was like the metric that people were kind of going at. And that's how they had their forecast and their budget and they had count mid journey 11 people to 200 million ARR. So that's 18 million per employee. Lovable. I think we're 50 people at 100 million AR. And you said like you are now 130 people at almost 300 so you can do that cursor 20 people to 100 million ARR in 12 months. It is actually what we're finding is you have to have a mindset shift of not thinking about how many people will I have but how does that actually accelerate my growth and does that allow me to be getting more market share, winning and having the first movers advantage before everybody else moves in. Because competition is everywhere all of a sudden. Right? You need to think about this not using the references. I mean by this not action real references as a tool both to weed out who's a great storyteller and did they actually do what they said they did? Like would their boss agree and their peers and are they as well liked by their peers and people who worked with them on teams than they are or by the people they reported to, but also to really set it up. And as founders, I find a couple have told me, oh, I don't do references like my talent person, my people person does that. Huge mistake. It's like a competitive advantage for you for your onboarding and accelerating their onboarding. Right. Asking the question, if you were coaching me as a new manager, how do I recognize when they're not doing well? How do I best help them? What do they need from me so that they can be at their best? Like those I think are questions that most people don't ask and it will just help you when you're having the person. The question of AI, I think Shopify CEO has declared that he's no longer giving anybody headcount in the organization unless they can prove that AI can't do it better. And so you have to go through this exercise every regularly on um, technology is changing. Can you build agents that do part of the role and therefore you shift the headcount to a more value add role? Do people understand how to work with them? So you need to continue to train them. So there's a lot of shifts happening in the industry right now that from a company building perspective I think are going to be entirely different.

Speaker B: So much that resonates. I guess you're talking about tooling. You can't move for AI tools hitting you left, right and center at the moment. And of course some are more powerful than others when it comes to the hiring process. So Charles would love your thoughts on this. And Sandra, from what you're seeing with a portfolio, we talked about the importance of the human connection. Ensuring that is still very much part of the hiring process. But what about the tools? What are the ones you leverage to good effect?

Speaker D: Yeah, it's funny because I work at an AI native company and, and this is the AI era and you would think that a lot of things that are recruiting could be automated. And I feel like for years I've heard that like a lot of the recruiting process will be automated. It's not really the case. Like honestly like I feel like we still use and the model is like still fairly the model that I'm used to having like five, 10 years ago. We still have a coordination team, we still have sourcers, we still have recruiters closing. We still like optimize on candidate experience and human connection. So in terms of like AI replacing what we've been doing for many, many years, I don't see this happening quite frankly where AI is helpful. I will say though that one recruiter can do so much more now than what it was like probably five years ago. That is 100% sure. Get reading. Sourcing the way that they can move is like much, much greater. I think a recruiter can be also full staff where like in the past probably you were labeled into like or put into a couple of boxes and you would be like stuck to like a specific vertical that you would do and then you would move on to the next one. I see recruiters being more agile but I will tell you though, like I think something that AI is not replacing and maybe I'm not answering your question but this is like my conviction is I think a recruiting team and recruiters that are going to do very well in this specific area are basically recruiters who are sharks and they want to close and they're like just obsessed over uh, closing. And this is what Sandra mentioned. I mean there's a competition everywhere and I see that lovable is that in my point of view you have two type of recruiters. You have the gatherer and then you have the hunter. I know this is kind of like generalizing. The gatherer is someone who's going to be a project manager, can do a very good job working cross, cross functionality, bringing people together and then you have the hunter, someone who is like absolutely obsessed about closing. An engineer. I think this kind of DNA of recruiter right now is more likely to succeed long term because at the end of the day it's like did you hire an engineer or not?

Speaker B: I also felt the collective sigh of relief from all the recruiters in the room when you said that we've still got a job, we still got a job and impact to have, which is great. Wanted to come on to talk about high performance. I would love to hear. It's obviously uh, words that are banded around all the time. We know how important it is to build high performing teams and cultures. What does it mean to you both and how can you test for high performance when it comes to interviewing talent in an interview process, I think it's

Speaker A: really important to contextualize what you mean but also make it stage appropriate. What's high performance In a uh, 10 person startup is not what's high performance in a thousand person organization that is on its path to ipo. So you need to make sure that you know what you're looking for at the time and define that. So in the beginning probably not about hitting quarterly okrs, it's about shipping, product iterating, learning, questioning all the time and kind of doing things and raising the Bar for everybody around you. As you evolve, uh, you do have to have processes. Things will break otherwise. Especially as you're going closer to ipo, people will pay attention to whom you hire much more on the senior level, people will pay attention to your processes, much more to your risk, your cybersecurity. So there's all of these things that happen and performance might look, look slightly different at different times in your scaling journey. For me, the most important is always like structure. Your interviews don't just go in. There are some fantastic storytellers, but you need to go in and figure out did they really do what they said they do and how do I find that out? I do a structured competency based interview and I keep asking questions, okay, what happened then? And tell me more. What did you learn? How did you apply that? Instead of just glossing over, going into storytelling and kind of going into a different direction, you do that early on. You get, um, the DNA, almost the essence of what you're looking for. You were talking about the hunter. That's what I want. And this is the shark. This is what I'm looking for. Once they're inside, figure out very quickly whether they can actually apply that to the context of your organization. So you have to have not a formal process. I don't think you want to too early implement those, but you have to have an understanding of how do you measure success? What does it look like? Is failure part of it? Is iteration part of it? How do you feed back back to people? And how do you make decisions both on hiring, salary, promotions that are linked back to the performance? And that's how you kind of start building the culture around it.

Speaker B: That's great. Thank you. Uh, Charles, anything to add or.

Speaker D: Yeah, I mean, I think performance cycles are a long time gone. Yes. Because you don't have to spend like 20 hours a week writing like PR feedback and um, going over. And I think now it's like mostly like uh, quick pulses, they're more frequent. But like you sort of have like one question that you would ask the manager and the manager would be, is this direct working or not working? And then what can be done? But it's very small touches now. There is not a formal performance cycle. I remember at Meta when I was there for almost four years, there was this whole thing called performance, uh, cycle, um, psc and essentially it would take maybe the whole first two weeks of January going through psc and it would be very time consuming. And this is long time gone. And I think Meta even got rid of it. As well. So that's something to be aware of. And I totally agree with Sandra that adaptability is what matters the most. So obviously in like very early stage startup and in a very fast growth, the only thing that can matter right now is how can you be adapting to the environment as an individual. And that's probably the number one thing that can spikes on the performance for folks.

Speaker A: I find one thing that has stayed true. So we did this big, we put out a book called Getting Through Chaos about a year and a half ago where we looked at by then the 210 most successful tech businesses and who were their first thousand employees and looked at the data of what really happened with those first thousand employees who got promoted, how many stayed, what kind of functions, when was the VP layer introduced and all of those things and then matched it up with, we have almost 30 years worth of founder journeys and questions that come back and somehow similar questions come back throughout the journey like when do I transition from having a co founder as a CTO to maybe hiring a CTO and bringing them in from the outside? When do I start having more sales than engineering leaders? And all of those things. And one of the things that really came out is where founders are spending their time. 50% of your time is spent on people issues. 50% of your time. Now most people will see this and go like, yeah, in the beginning because I'm just hiring and then I'm going to move on. No, it's like throughout what that 50% is shifts. But you have to like your people are your product. This is the most important thing. And even in a world where you might not need a thousand people or more, even in a world where you can reach reach the 200 million AR with 11 people, your people is the most important. And so you need to spend time with them and on them on also modeling that performance culture and going after it.

Speaker B: Very well said. I'm very conscious of time. There's so much we could cover and there's so many questions I have, but maybe ask one more. AI has transformed everything and it will continue to. You're seeing it firsthand. So what are your predictions for 2026 and beyond when it comes to how AI will continue to impact the trends we're seeing when it comes to building high performing teams, attracting talent and retention as well.

Speaker D: One prediction is maybe there will be chief Talent Officer. I think it's becoming such a key part of the company's success in how to build and it's such a strategic function now maybe this is stupid. But I feel like maybe Chief Talent Officer, I mean you could get a C level in talent. Another thing is I kind of alluded to it is the fractional exec thing where it could be very possible that an exec comes as a resident almost and does like a mission and then moves on from the mission. This could be a prediction for 2026 and then not a prediction but awareness that there is a wave. Right now, I don't want to call it a bubble, but it's clearly a wave of AI and so you have to stay humble. And I tell this to my team all the time. Like I think we are an AI native company. Things are going well. We've got like great brand but like chill a little bit. Like it's fine. Like we're not reinventing the wheel, we're not better than anyone else. Things have been done for many, many years before for a reason. I'd love to predict that 2026 will show that like people who are like not thinking that they have it down just because right now there's a huge wave of AI, it's like they're right. I do think like the fundamentals in people are still there and 2026 will show that that.

Speaker B: Very well said. And the fractional piece is super interesting. It's probably the fastest growing part of JVM and we've had our busiest quarter so far with companies reaching out about fractional execs across all different functions and areas. So let's see where that trend goes. But it's super exciting. What about you Sandra?

Speaker A: I agree with what we said earlier. I don't believe AI is going to replace talent recruitment or any of this. I do believe that understanding how not to treat it as a tool but treating as almost like an organizational philosophy philosophy will create a wider gap between recruiters and companies who know how to hire and those who are going to stay behind. And I'll uh, give you an example. I had one of our founders last week within 24 hours build an AI agent that can do the work of a Ah, Junior sourcer. And it's an intelligent agent, it communicates with you if you start engaging in a conversation and it also creates the outreach mechanism and the probability of which Whether it's a WhatsApp, is it email, is it LinkedIn in 24 hours? Right. Because for them everything they do in the organization is AI native. So interacting with agents and building them all the time is a part of it. And I think they will gain significantly speed in the getting to yes, we want to interview this person, but the other thing that they're doing is they're really relying on human judgment and the nuance that comes with that. And so they are really intentional that the decisions, the core decisions that get made are made by people and continue to be made by people. And for me, that is the other big prediction for this year as well, that it will not happen, that those big, really important decisions will get taken over. I do believe that their nuance and being able to feel is going to be something that distinguishes us even more.

Speaker B: Super interesting and very reassuring. Actually, I can't thank you both enough. You're two of the busiest people I know. So to, uh, take the time out to talk to us today and share your incredible insights, it's, it's hugely appreciated. So I just want to say a big thank you. And yeah, I'm sure our audience would like to do the same.

Speaker D: Thank you.

Speaker B: Thank you so much for listening to this 40 minute mentor episode. I really hope you enjoyed it as much as I enjoyed recording it, and that there were loads of insights and lessons that you can take away for your own scaling journey. If you did enjoy the episode or have any feedback for us, please consider leaving us a review on either Spotify or Apple podcasts. I always love reading what stood out to you from our various conversations. If you'd also like to stay up to date with the latest 40 minute Mentor episodes and insights, then please make sure you hit the subscribe button Wherever you're listening today, sign up to our mailing list through the link in the show notes and follow JBM or myself, James Mitra, on LinkedIn. That's everything for now, but I hope to see you again very soon for our next dose of pocket size mentorship.