This is a much warmer welcome than what we had coming into Y Combinator the first time. Legora's YC journey started with a rejection, but more on that story later.
In YC they teach you something and it's called the two sentence description. It is describe your company in two sentences. Legora is the agentic operating system for lawyers and it handles complex legal work from start to finish so lawyers can achieve more than ever before. And over 3% of all the world's lawyers are now active users of Legora. You will learn more about this when you get accepted into YC.
When we started looking at the legal industry, it felt like one of the biggest opportunities to apply large language models to solve real problems. And the software that we were up against looked like it had built in the '90s. As software engineers, we have been incredibly spoiled with great software because we love to build for each other and for ourselves. But in the legal industry, this is what the software used to look like and what we were up against when we started out.
Now, Legora has grown into a global brand, putting celebrities like Jude Law at the New York Wall Street. And still I feel like we are only getting started. My most favorite Slack channel in Legora is customer love. It is where our customers post things that they sort of truly feel like they couldn't have achieved without our system. And we mine many of our sales calls for quotes like these. And I wanted to share just a couple with you because I think at the end of the day, this is what it's all about.
A parent asked me at one of the tournaments how I juggle work and all of the golf travel. One word, Legora. Never has the path between an idea and execute been so short. Never, man. If Legora went away tomorrow, I just go back to coaching high school basketball.
When Legora went into YC, we were questioned about the idea of even selling and working in the legal industry. It is such a conservative business that had never been sort of lenient to software before. But from the time that we went into GA of October 2024 until the last end of quarter, we've grown from 1 to 100 million in ARR and starting from just three engineers in Sweden to a company of over 750 people all over the world. This is awesome. And the fact that we've gotten to do this starting from Europe, I think just adds another flare in that hat.
But the Legora story almost didn't happen and it actually didn't start with me. In fact, it started almost like the great beginning of a joke. And so a lawyer, a physicist, an engineer, and a psychologist back in 2020, before GPT, before AI was cool, started a company called Judelica. And what they observed was that law school students were going into their internships basically to summarize court cases. And with the early models from Google called BERT, they started to explore what this space could be and what was possible to build.
My story started in the Swedish archipelago at an island which looks something like this. And I met my two co-founders at a volleyball game. I think startup founder stories can come from many different places and this definitely wasn't one, you know, high odds of a place to start. But when I met August and Siga, they showed me a demo of the product they had built. And our group chat actually looked exactly like this. They gave me a demo of the project and with GPT 3.5 they had built a very simple product that could explain what a stock option agreement really meant. And so we started with that and I said this is a super cool demo, a super cool project and my co-founder Siga said I'm glad you want to help out. And I ended up helping out a little bit more than just that.
When GPT 3.5 came, that was the internet moment of our generation. I dropped out of college. I never finished my master thesis because the opportunity cost of not building had become too large. But when we started out, it wasn't obvious that we were going to be a success. And so to learn about what the legal industry was, what it meant, how lawyers actually worked, we came up with the ingenious plan of cold emailing lawyers on their emails that we could find on their websites and writing to them on LinkedIn asking for a lunch where we could learn more about their different practice areas. And we offered to pay their hourly fee to have lunch with us. And many of them took us up on that offer. But fortunately for us, many of them didn't make us pay for the hour and many of them even paid for the lunch.
And once we had gotten, you know, our feet under ourselves, we approached one of the largest law firms in the Nordics named Mannheimer Swartling. But just two years before that, their managing partner had gone on TV and said that AI back when they were starting to use it was really more artificial than intelligence. And so we had to work really hard to change the perception of what both technology and what AI could be in the area of law.
In law, you are not paid when things go right, you are punished when things go wrong. And many of the initial AI solutions in the space had required immense amount of training. You had to sort of bring a lot of use cases and examples just to get very very little results. And when GPT 3.5 came, that really changed the story. And so with Mannheimer Swartling, we ended up moving into their offices and moving and working really close with them.
And as I said in the beginning, the warm welcome here was quite different from the first time we interacted with YC. We applied in May of 2023 with a promise of being able to query all legal documents using large language models. And when we came to our interview, one of the first questions that we got asked was what type of lawyers are you serving? And you know, not very knowledgeable about the legal space yet. Our response was, "What do you mean? Are there different type of lawyers?" And that did not land very well with the YC partners at the time. And so I actually remember very painfully that Tom Bloomfield started laughing in the interview when we gave that response and we knew that we were cooked.
But that also gave us the perseverance and the drive to continue. And so with a lot of let down, the day after we did not work but the day after that we got back to building and two months later we got accepted under a new name and with a different platform. We had done our homework. We had done the work and from Sweden the idea of getting accepted into Y Combinator felt like we were going to Mount Olympus. We were going to dine with the gods and we were going to, you know, get to work with other startup founders who came from all of the great tech companies that we knew of. And once we got to Y Combinator, we realized that we actually knew a lot more than we thought we did. And this is one of my favorite pictures. And it is the screenshot I took after we did the video call after our second YC interview when we knew that things had gone a lot better than the first time.
So after we got accepted into Y Combinator, we moved into this law firm I mentioned earlier. Mannheimer Swartling was the biggest law firm in the Nordics, but they had very sort of no real clue about how to work with software and how to work with technology. And we ended up getting a conference room with no real windows where the AC would turn off at about 5:00 p.m., but it was really close to the Coke fridge. And so at about 6 p.m. every day, one of the engineers would go up, grab the door, and start waving it back and forth to get more oxygen into the room. And those conference chairs still made an imprint on all of our backs. I think 3 years later and me in the car there with two more screens is when we make the move from the conference room of a law firm to our first real office.
And I think one of the key takeaways from this entire experience is that first off, we quickly learned not to take no for an answer. But also the power of simply reaching out and asking for help. I think one big lesson from these first three years of building Legora has been that it is very powerful to be a person and to be a company that others want to see succeed and that others want to help.
And so we came to San Francisco, we got a room at an Airbnb up in Bernal Heights and we started building. And during YC, we grew from zero to a million dollars in ARR. And we also learned the hard way that working across San Francisco and Europe took a big toll on the team. I couldn't find a picture of this, but I bought an influencer ring light that I put on my laptop. And the reason I had that ring light was because I was doing sales calls between 1:00 a.m. in the morning to 10:00 a.m. in the morning every single day in San Francisco to Europe because that was where our initial customer base was. And after a rocket trajectory during YC, which now two years later is slow compared to what some of the companies are doing, we set off to fundraise. And this was my first time fundraising.
I had no idea what to expect, but we had lined up 80 investor meetings in a week and a half. And we had European investors, American investors. And the main takeaway from that experience for me was that you need to become a really good storyteller in order to drive interest and to get people on your team. It was also a very different experience talking to some of the European investors versus some of the American investors. I feel like in the US we think more about what can go right rather than what could possibly go wrong. And we ended up working with a venture firm called Benchmark. This is a picture of Chathan, our partner, when we had signed the term sheet. And I remember negotiating that term sheet on his desk with a computer opened going on decimals in the Excel to determine the exact number of shares and they ended up investing $9.51 million.
Now, following that investment, Redpoint pre-letter series A just three weeks later, and we started to run into a challenge. We had about $35 million on the bank. We were 10 people in the team. And there was actually a month following that that we made more money from interest rates on those 35 million than we did from customers. And that is not a very good sign when you have become a bank. And going into our first board meeting, we had Chathan and we had Redpoint and it was me and my co-founders. And we made a very hard decision, which was to freeze our sales motion. Because when you work with lawyers, you only really get one chance to get it right. If you show up and the product doesn't work or if the lag in the system is too high or if the system goes down when there's too much traffic on your Azure instance you are toast. And after that six-month sales freeze was when we really started ripping. And that's where you see that curve from 1 million to 100 million really starting. And what happened at the start of that was, you know, turning from a small startup looking for PMF to really establishing what our business and what our product was going to be.
In the very very early days at Legora, so even pre-Legora, the way that we would decide what to build was by voting. We would make democratic votes in the entire team. And for anyone who has built software before, you know that if you have too many chefs in the kitchen, that typically does not make one very good dish. And that was exactly what was going on. We were working on too many features. We had to rebuild everything for the product launch that we were going to have after the summer, after the sales freeze. And we had to build a platform where it was adaptable to foundations that were constantly changing both with the underlying models but also with the frameworks that we were using to build agentic workflows like LangChain etc. And so in October of 2024, we wrote down what we would call the Legora product manifesto. This was basically gathering everything we had learned, putting it into one very simple document that we shared with the entire 25 strong person team back then and that we would rally the troops around.
At the time, we were doing about $1.3 million in annual reoccurring revenue, and many of our competitors were doing 10 times that with products that only had one of these features. And I also think that's a function of having started in Sweden. The market is not big enough to house a real unicorn or a decacorn or something even bigger than that. And so one of the earliest questions we got from YC was when will you move to the United States? When will you make the jump? And it was off the back of this product refocus that we were able to not only compete out the competition on product but build enough momentum to make the jump over to the US and start to compete for the biggest logos in our markets. And I think as engineers and as tech people, we often overemphasize the reliance on product and on the tech. But if there's anything I've learned in these past three years, it's that it's all about the people. And building product is one thing, but building a company is a very different thing. And we made many early mistakes around this.
One of the hiring patterns that we had to unlearn was looking for fancy logos on resumes or what we like to call y-intercept. If you think about somebody's skill curve, it might start out really high, but if they don't have a good trajectory upwards, they are going to have a really hard time working in a company that is scaling exponentially. And so instead, we started to look for people like us who wanted to work insanely hard with a very high growth potential. And we doubled down on that talent over and over again. Our top seller today is 23 years old and he sold over more than $10 million worth of Legora. And he had no sales background. He jumped out of university and by continuously doubling down on that type of talent, I think we have built a very unique culture at Legora. And one of those things has been about bringing and building cultural fit.
Up until the point where we were around 500 people, I interviewed every single candidate outside of engineering. Now I interview every director and upwards. But what we have done is we have set the cultural foundation in the business where it self-selects for itself. We have three values at Legora. Lean in, fight for excellence, and grow together. And together they make LFG. Let's go. That also sends a signal to leaders and others who join the company who are coming from more perhaps established backgrounds where joining a company where the values includes profanity quickly sort of tells them what this is about.
Another very complex cultural thing starting a company in Scandinavia is something called Jantelagen or the law of Jante. This is very foreign to our American friends. But in Swedish culture this basically means that you should not think that you are somebody or you are not more important than anybody else. And your ideas are not better than anybody else's. And I think a part of this humility is good and it supports a culture where the best ideas win and where people earlier in their careers feel empowered to speak up. But it's very hard to build one of the fastest growing enterprise companies in the world if you think that you aren't somebody or if you don't think that you are better than anybody else. And so we have had to really create a nice cocktail of US, European and Asian culture all in one to create a global company that is Legora today. And so I really think that building a strong company culture is the best guarantee to attract and keep the best people.
Another way that company culture gets expressed at Legora is through articles like this one that ended up in Sifted. For us there is only winning. Everything else is losing in a winner takes all market or winner takes most market and the company has to run like there is no place for number two. I think it actually would be fair to say that when Legora was founded, it really had no reason to exist. We were one of many legal AI companies. But because of this mentality and because of not feeling like we're safe even though we have achieved extraordinary numbers by any normal measures, we continue acting like professional swimmers who are looking down in our lane while the competition is looking sideways at what we're doing. And at Legora we have had to build a culture to really support that ambition.
So starting years behind some of our biggest competition and having to build this intensity in a country where most people want to go for fika at 3:00 p.m. which means having a cinnamon bun and a coffee or you know go home at 5. One of the ways that that has been done is to create cultural values and cultural moments that really distinguish us from many others. And so in Swedish there is a saying, you can wake up with a taste of blood because you're so excited about something. And I was doing an article in Swedish and I used that saying and I didn't know that the interviewer was going to release that article in English and so when this came out it got lots of fun reactions. One of them was is Legora made up of vampires. The second one was you guys need to floss better. Many good ideas, but this has now turned into the word blodsmak internally, which means that and we just keep going at it. And I think part of having our HQ in Stockholm has worked to help us keep this. Everybody globally from the company makes their onboarding in Stockholm, which is a lot nicer in summer than in the winter. But that has created the same vibe in any Legora office regardless of where you walk in all over the world.
And I think one great example of this was we had a very big law firm in the US that our competition was working with. But that law firm had a specific problem around being able to draft certain types of documents based on incoming term sheets. And our competition had promised that they were going to solve that problem for them. And they hadn't. And so one of our US-based engineers, legal engineers, lawyers, learned about this use case, got on a flight to Stockholm, spent a week with our engineers, solved the problem in Sweden, and then went back to the US and delivered it to the customer. And I think that Swedish base has become one of Legora's real superpowers.
And so to round things off before we jump into the Q&A, I'm sharing this stage this weekend with people who have built things at a scale that I haven't yet gotten close to. And so I will leave many of the big lessons for them. But what I can tell you is that three years in is a little bit smaller than that. Most of what actually mattered in the company and in Legora so far did not revolve around signing a big client or closing a new round of financing or open a new big office in Manhattan. It happened in, you know, a windowless room without much oxygen or on a call on our way to the airport, a Slack channel at 2:00 a.m. trying to fix a bug before a big presentation on Monday. And nobody puts that in a pitch deck, but that is what makes the company. And you shouldn't wait around for those big moments. You have to love the hustle.
And I think if I can leave you with anything, it's that even though we started in a small law firm in Sweden, I was born in the Swedish archipelago with a class of 10 other people, I thought I had a big plan for my life and I was going to go to McKinsey after school. But when GPT 3.5 dropped in our knees, we truly made that into our thing and we captured what I believe to be our generation's internet moment. And so you can just do things. Legora and myself is living proof of that. So with that, we're going to jump to Q&A and I want to invite a very good friend, our partner from Y Combinator, Gustav Alström.
We're really becoming professionals at this now. This is not the first time we're doing this.
You, too. It's good to see you.
Um, thanks for the talk. That was awesome.
Thank you. And always thank you for coming back and speaking to YC and to founders here at Startup School.
I want to ask the first question which is one that I've gotten from a lot of founders who ask about you, which is you guys are three founders or were three founders who were not lawyers.
And you started the best legal AI company in the world. Does domain expertise not matter that much anymore?
So there's actually a story of a Swedish VC who was very bullish on doing the pre-seed of Legora.
But they ended up not doing it because we did not have any lawyers in the team and I met them at the airport. I met one of the partners from there at the airport quite recently and they were very very bitter and Legora turned out to be the lesson for them that perhaps domain expertise is not what you need to succeed. I think that you need a willingness to learn about the market which we did very very early by you know exposing ourselves and spending lots of time with lawyers like as much as we possibly could.
Yeah. But I don't think you need domain expertise. It probably you know dependent on the market that you're going after. Like maybe if you're building in quantum computing or in fusion that's a good idea but legal was easy enough for us to pick up as we went along.
I spoke to some founders yesterday and we spoke about sort of like the next categories where the LLMs are not sufficiently good yet but they will be. And it made me think of what you just said when you were toying around with Bard in the early days. What gave you the confidence to build a legal AI product on a model that wasn't good enough? It was like good but not good enough. And there's many other founders probably in this audience who are thinking about the same problem but in a different domain maybe like I don't know mechanical design or some other part of somewhere where the models are just not good enough.
So I think the sort of tribal knowledge when we got started was that you have to fine-tune a model.
Right. In 2023, 2022 that was really like the name of the game. I even remember I think it was Bloomberg who spent you know millions and millions and millions of dollars building like a Bloomberg law model. Our view was partly because we didn't have enough money and partly because we truly believe that to be right, you know, the models will keep improving right like I'm sure Sam is going to come up on stage and say that later today.
And so by just betting that the models will keep improving and what you should be focused on is how can you deliver the value that the models generate to your market. That was the crux for us. Even with the first generation of ChatGPT that was unusable in law partly because the model wasn't good enough but partly because it actually didn't support you know private conversations European data hosting. I remember the first sales I ever did we basically said we are like ChatGPT but we are compliant in Europe like that was the pitch. That was not a very strong pitch. And you know, clearly ChatGPT would figure out how to do that later on, but at the time it was good enough. And so I think we recognized that you don't have to build for the world over here like you need to build for the world today and maybe like one step ahead.
And it's kind of like this ladder where you should maximize the opportunity now. Make sure that you get really good relationships with your customers and so that you can also have that conversation with them because if everybody's betting on this you know exponential uplift in model capability the Legora platform will continue delivering more and more value.
I think that we have built 1% of all the software that we will build over the company's history and probably the product will look very different from what it does today a few years down the line.
Yeah. A lot of news on models this week or last two weeks.
It's going to be like a great episode for whoever makes the documentary.
I'm hoping that someone is making a documentary right now about everything that's going on. I'm not sure if someone is, but I hope they are. Open Weight Small is very much the topic right now. And when we spoke on stage a couple months ago, you talked about that you're not attached to one specific model. You can work with many different models. Have you updated your view based on this week? But like how do you think about so like I'm sure there was a moment like a year and a half ago when it seemed like there was just one or two models that were really sufficient to power Legora and now there seemed like a lot more.
Yes. Which I think will be great. And I mean you know clearly there will be applications of different
Models in different use cases, and so if you take customer support, you're optimizing for speed of turnaround, latency to the customer, and cost on solving a particular ticket. I think Finn used to charge like $1 per solved customer ticket. In law, you actually want the most amount of intelligence quite often because the fraction of token spend or software spend compared to human expertise applied to the problem is really tiny.
If you're solving complex litigation, you're going to want to throw the most brain that you can on that problem. And so we have really sort of two different camps. Like one group of our users are asking for the ability to loop really complex models to work on problems for a long period of time, racking up big LLM costs, and another group of our users are saying, can we get access to open source that is going to be cheaper on our consumption? And I think the answer is like somewhere in between.
I think ultimately one of the core IPs and muscles that I encourage as many of you as possible to build is the ability to evaluate use cases because that is the superpower that then allows you to route things effectively.
We did a lot of that early on because we hired a lot of lawyers into Legora and we made part of their job customer-facing, but part of their job was also to build out use cases that we would throw our evals on. And the frontier of cost, intelligence, and where that sort of frontier lies, yet to be seen. I think there's also a compute problem where when we lock in big contracts with the labs and with our compute providers, that is actually a huge thing. We cannot have our system go down when a number of percentage points of all the lawyers in the world are working with it and their clients rely on it.
And are there specific benchmarks you look at for how... I'm sure you are basically...
Well, we look at the Legora Bench. So we actually announced and released that on Friday last week, and that has been work for the past 3 years, and we've kept that internal up until Friday. And the reason for that was it was basically OpenAI or the Anthropic models, and so it wasn't that interesting to publish benchmarks on.
And we would only make those two models available in our system, and the user could pick. Now the smorgasbord of available options is a lot larger, and actually we found to our surprise that SpaceX and Grok was one of the best performant models, especially given the cost on our benchmarks.
And we don't even have them on our data processing agreement, and so we actually can't yet offer them to our customers, but now we will start to.
And do you see your customers having strong opinions about which models they want to use, or is it sort of like they just want the best, whatever is the best?
Some of them have strong opinions, especially like banks, big law firms have a... they don't want Chinese models.
Yeah. Makes sense.
So I want to go back to just a little bit earlier, like when you decided you want to build a startup. A lot of people in the audience here, I've had two dinners in the last two days with attendees at Startup School. We talked about when should you start a startup? People are working at DeepMind, people working at internships or jobs right now. Often you're one or two years into it. What would you say was the trigger for you to say I'm just going to do this and not do McKinsey or the other options that you had?
So my dad had two companies during the dot-com boom, both of which went to zero after raising too much venture capital. So maybe some...
Has he been a good mentor for you?
How often do you speak about...
Oh, we speak probably every day or every other day.
Great. Yeah, about lots of stuff.
I used to, now I'm like too tired to walk home often. So I would like take the train or like take a cab, but I used to walk home then I would call him and that would be a lot of fun. And sometimes we call him senior adviser. We have actually one of our biggest customer pitches, we were stretched for resources. So he came in and did the PowerPoint for that client.
He knew everything at this point.
Yeah. Yeah. He knows most of it. So he had two companies and both went to zero and then he had a boat business in the archipelago when I grew up. And so, I've always been surrounded by entrepreneurship and I always felt like I wanted to prove myself in that arena. I'm very competitive. I used to play video games. I used to play Dota 2, like more than I went to school. And then I think building a company is like the optimal, it's the biggest arena that you can enter and you'll either leave victorious or you'll leave defeated or you'll be okay.
And I was very decided in that I want, I should probably learn more about the world, which I thought McKinsey was going to be a great place to start at, which I still think it is. I think it really teaches you how to work, you learn work ethic there, but I did an internship and so I think I got a bit of that even during my studies.
And then we had this pivotal moment with GPT and so we were talking about this, like you weren't as excited about investing a few years back like pre-GPT because there wasn't a lot of...
There wasn't a lot going on, like the last year or two before COVID, it was not a lot of new ideas.
Right, and I remember sitting down pre-GPT, like here are all the startup ideas I can think of, most of them were pretty boring. I don't think most of them would have worked out.
And then small companies got a really big advantage versus big companies.
And I mean I think you saw this in just like the way that Microsoft would build co-pilots. Like it didn't work for a really long time. Yeah.
And I remember when that came out and we were like, 'Oh my god, like we're so screwed.' You know, every lawyer already works in Word and Outlook and now they're just going to use Copilot. It turns out like it didn't work and the ability for us then to still build a lot of value was huge.
I think now reflecting back on that, you learn so much by having to figure it out, and I really think that the amount of things you learn is a function of the amount of discomfort that you are willing to endure.
Yeah. When we started Legora, I was like super introverted. I, you know, really didn't feel comfortable talking to customers. I wanted to code as much as possible. You know, when you have to go separate ways with an employee for the first time, like all of this is so hard, but you realize that startups is one of the places where you can learn the most in a short amount of time. I think, you know, if I were to build a company again or join a company, I still feel like I learned a lot working at other startups. I actually worked at startups before starting my own.
And then I would say you should think really deeply about who you started with and the problem space. And I think we picked a space more than we picked a problem, which I think is like two different ways of going about it. It was completely obvious that legal and AI was going to be a thing.
How it was going to be a thing was like very uncertain and so we just said let's march in this general direction and then we'll figure it out. That's one way of doing it. I guess the other way of doing it is like you find a specific problem, you solve that very clearly, you generate ROI and then you expand from that.
Yeah. You mentioned earlier, well I know that you are extremely competitive. How is that expressed inside Legora? Like how does a Legora employee know that Max is a very competitive CEO?
I think everybody at Legora is like that, self-selects.
How is it expressed? Is it like a Friday meeting? Here's our goals and like...
Well, yes. So we do, everybody knows every monthly goal. I think setting quarterly goals is like a little bit tricky.
Is that how it was from the very beginning with just three of you guys?
No, then it was no goals. Then it was just like every day you like try to maximize the outcome.
And then we got, you know, when you're 750 people you need to plan a little bit better and like have some better internal communication.
Actually communication is like the thing that really breaks when you scale. Yes.
I think a lot of people have talked about that already. But no, you really feel this drive from engineering that they want to build the best product and the best feature, and if you compare our tabular review versus the other alternatives in the market, like it's really sort of you stack rank it.
And we have lots of people on vacation now in Stockholm because it's July. And most of the engineers who are on vacation are like more productive than they have ever been because they're like taking a bit of time off, but then they also get to code now on problems that they like want to beat and they want to win.
It's a team sport. And I think you can be competitive but be it in a team way. And so you really need to solidify this like winning or losing together strategy I think, and when we get a big win, that is really celebrated, and when we have a loss we really like mourn it together.
And then we immediately make a plan of like how can we flip it or like how can we make a land and like turn it around, and I feel like people are in solution mode rather than like blame mode. And I think that has been a big momentum driver for us, but also we've been in like chasing, right? Like there were other legal AI companies that were bigger than us when we started, and so we always felt at least in the beginning like we were chasing. Now we are much bigger and...
Let's say you were the biggest one at some point very soon.
Is that going to impact your motivation or your...
I think at that time, so that's interesting. I thought a lot about like what happens at that moment.
I think we need to either pick out another enemy and go like, okay we have to be bigger than them now, or we have to like really find this way of being better than ourselves yesterday. And I think that having competitors is a good thing. You should not be overly focused on what they're doing, but it's definitely like a carrot, I think. And it's an easy thing to like rally around because what you don't want is you don't want a lot of side questing.
You want everybody focused on the same thing.
So, one question I got from the audience is how do you become more ambitious? And when I ask this question, I'm thinking of a company I'm working with right now who's like, 'Oh, we want to do this country in Europe and then we're going to do this other country in Europe and then maybe next year we'll do US.' You guys did a lot of countries in Europe just you're in the batch and then like...
And now we're at like 50 countries.
And now you're everywhere and you scale up really quickly. And is that ambition or is that the product was working or is...
No, it's definitely ambition. I mean I think it's like...
How does someone learn that or how does someone become more ambitious? Is that possible?
