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20:48One, you're going to generate way more code than anybody's ability to review that code. So starting with GitHub Copilot six years ago or whatever the date was five years ago, like that was just priced in, which is as soon as AI writes most of the code or and then like 90 % of the code and then 95 % of the code, then by volume, we're just going to produce this unbelievable amount of code. And any change in a system, you know, everybody kind of thinks about security as like, you know, is there a zero day where there was an unpatched component of your technology or somebody found a clever new package that you could kind of slip into?

21:23Every time you ship a new feature, you have a chance of a security vulnerability because the AI could have written in, oh, you know, we want to actually open up that port in the system because we need to do something. And maybe that was the wrong decision for the agent to go and do. So we're going to be living in this new world of cyber risk in the form of using agents more. And then on the other side, obviously, if you have the offensive side able to use AI, probably more in the form of open models and whatnot, then they can find more vulnerabilities because they can scan across the internet far faster than before.

21:55So you actually have two new forms of risk in the development process. And you only have one benefit, which is agents can also review the code and try and keep it secure. So it's going to be a very dynamic period. I think, you know, for better or worse, agents are the solution to the problem that agents have caused. And that's why there's going to be a lot of money made in agentic security as well.

22:16Harry Stebbings:You said agents are the solution to the problem that agents have caused. It almost reminded me of when Janssen went on TV and was like, oh, every engineer should be spending. I can't remember the amount. I think it was either 250 or 500 ,000. Yeah, or like half the salary, essentially. Yeah, and it's kind of like, you know, drug dealer, you should buy drugs. Well, OK, no shit. But again, you know, obviously, listen, we love Jensen for that level of grandiosity and charisma. So I actually I bet, you know, whether he's off by half or not, I mean, directionally, the idea is actually pretty salient, which is you're going to be spending more on compute per person in the future than than you ever thought.

22:54And that you certainly are today.

22:56Harry Stebbings:What percentage of salary are you going to spend on compute in box in five years? Great question. I don't think we've modeled that out in five years. and obviously the joy of being public. Well, this is your chance. No, no, totally. You know, I was told not to model long-term financial projections on podcasts. So yeah, it's a weird SEC financial thing. That's so boring. God. Don't ever go public if you don't want to model on podcasts. This is why the Collisons don't. Everything else is great. They just didn't podcast. Yeah, cheeky, piney, piney. I don't know if you'd be able to pin Patrick or John on the same question for their five-year view, but it'll be a larger number for sure than it is today.

23:35Harry Stebbings:I'll smash them with four tequilas and then ask them. You said one of your observations in your very viral tweet was about token maxing and kind of token allocations within enterprises. I'm really intrigued. How do you think about advising CIOs on token allocation, token maxing, what we should know that we don't know? How do you think about that? This one's tough. It's, you know, the general advice will end up sounding kind of like, you know, kind of generic by definition. You know, usually, I mean, it's going to have something to do with your tokens will have to correlate to where there is the most amount of, you know, value generated for your company.

24:09Like most bland statement of all time, but just obviously it has to be true. In the software industry, we're into token maxing because guess what? Like generally the value proposition of your company will correlate to how much software can you produce. And so if you're trying to drive a lot of change and you want to make sure everybody's shipping lots of software and you want to be able to teach the best practices faster, then token maxing and leaderboards are an interesting way to do that. It's not obvious that you're going to see that across every industry. We've seen a couple of interesting examples.

24:35One company had this sort of like Shark Tank pitch-a-thon type thing, which is teams have to show up and they have to go pitch for compute token budget. And then you kind of allocate it in some central fashion like a VC would. And then you sort of, you know, I don't know their exact interval, but I would imagine you review that three months, six months in being like, OK, did you get the upside that you thought on that token usage? So that's an interesting one. Another company had a kind of a view of like it's some kind of like natural stratification of 5 % of your users are doing the most valuable things.

25:0620 % are doing the next tier of most valuable things. And then everybody else is sort of doing general productivity and making up their numbers. But the idea would then be like, well, for that five or 10%, give them the best models with unlimited capacity for the next 20 % have some limits. Maybe it's a little bit more efficient of a model. And for everybody else, it's sort of like we're going to just use the cheapest thing on the market. It's not going to be like the game changer of the employee productivity. And so I think everybody's kind of working their way through this. The part that back to Silicon Valley is again, kind of, you know, sometimes more, let's just say like, like positively naive view is, is like real world.

25:42They have like budgets and they have like annual budget planning cycles because they have EPS numbers. They commit to Wall Street. And so you don't get to just be like, oh, we're going to token max across the enterprise where everybody gets unlimited token budgets, because obviously then that company would just miss their earnings throughout the year. So you have to like wait for the budget cycle. You have to figure out what teams are most interested and have the best use cases. That's a natural journey. One fun about Mark that I think is well understood now at this point is the budget of tokens will have to move out of IT spend and into regular kind of OPEC spend.

26:15This can't be treated like, oh, I'm going to trade off between Salesforce licenses or compute tokens. Like it's going to more be, I'm going to trade off this next marketing campaign. And instead, I'm going to go and drive more automation in our marketing engine. Like it's going to be that kind of set of tradeoffs.

26:31Harry Stebbings:What happens to that token budget when it transitions to that different spend category? Well, first of all, it goes up because IT spend as a percentage of revenue of large enterprises is... But is this the same as the kind of classic VC blog post, which every firm has written, which is like AI, it's moving from software budgets to labor budgets. And every partner goes and likes the tweet and there's like no fucking shit. Like really? I mean, if you do it in that voice, it sounds kind of like, you know, simple, but like, yeah, that's just like a very big deal in technology. We've never had, there's never slash rarely been a technology that you could sell into an enterprise where you weren't capped by that company's corporate IT budget.

27:14And so now for the first time ever, you have a technology where you can go into the line of business and you can say, I can now offer you a new tool in the form of an agent that will augment a workflow that will make you 50 % or 100 % more productive. And so maybe I should be able to get 5 % of your OPEX budget this year to go and do that. That is a new budget to tap into. And I don't think it like 10X is the size of IT spend or technology spend globally, but it certainly doubles it.

27:41Harry Stebbings:I mean, current enterprise technology spend is estimated between 10 and 12%. To see that going to like 20%, as you said there, it's like, I think, relatively feasible. You said about kind of companies being like, based on earnings per share, and actually having budgets that they have to adhere to. Very strange not to have venture funded companies. Yeah, they don't have a limited VC to go and solve this. Can't we just go to our venture investor and ask for more money? The one thing that I worry about is we see this insane demand side pull. Every company in the world needs an AI story. Everyone wants to kick the tires with something.

28:11Harry Stebbings:And I think we project the same demand side pull and extrapolate it continuously. do you worry that we are in a momentary 18-month period on the demand side pull and that may not always be lasting? It's very possible I should be more sensitive to that, but I would take the opposite side of that particular wager at the moment, partly because I already saw one diffusion cycle with cloud and actually how long that ended up taking. And the kind of spiky early nature, you would have just been like, oh my God, this is on fire. And how could this last? And 20 years later, it lasted and got way bigger than we ever realized.

28:49If it works, the market's always larger than you ever think. The only part why 18 months is like not even a relevant window to me is I think diffusion is going to take longer than Silicon Valley thinks. And it's back to the very first kind of that new role idea. When you go to most companies, they can't yet just deploy an agent to do, you know, financial proposals for all of their clients without a human reviewing the thing. And because the SEC will just show up and be like, hey, you just gave this person bad financial advice and you're going to lose your license. Like that will just start to happen kind of across the board.

29:20And so that's why, you know, people take time. That's why there's a lot of regulatory controls and compliance teams. Security teams have to figure this out. That just takes time in the economy.

29:29Harry Stebbings:I had, I think, Matt Fitzpatrick from Invisible, which is like a Turing or a McCall competitor. And he said you cannot sell into enterprise without an FDE model. It is impossible. I mean, it rounds to being true. Super interesting to hear that because we're seeing the rise of, oh, we go PLG and then we seep up into enterprise. Well, I don't think of those as mutually exclusive for what it's worth. I guess what I'm saying is when you think about adoption within the largest enterprises, are AI services companies the best positioned companies of the next five years? As in you're saying like traditional professional services?

30:05Harry Stebbings:Yeah, I'm saying Accenture's AI team that come into Bank of America. No, 100%. These spaces are going to be, again, both bigger and more sustainable and robust than people realize. We are always so, back to the myopic thing, we're so myopic, we're like, AI will replace all of this stuff because it just does it for you. And it's like, I'm trying to think of, you know, maybe my most recent experience with the best models in the world, I probably had to go and change 15 % of the thing that was the output. We're nowhere near eliminating the human from the workflow. And so in a world where you don't eliminate the human, then there's a lot of like real change management of like, where should the human enter that business process?

30:41How would you want to review that work output? How do you wire up your systems to make them effective for the agent and human collaboration? How do you connect all of these data sources together? One thing that we see is, you know, if you wanted an agent right now in a Fortune 500 company to go and give you an answer to where is the most risk you have in your upcoming renewals for your contracts, that agent might find 10 different systems that contain contracts in them. And half those systems will be like legacy technologies that don't work well with the agent. They're kind of low throughput, or maybe you can't even wire them up.

31:18They're on network file shares. They're in legacy document management systems. So first of all, half your data state is not even ready to work with the agent. The other half of the data state is probably fragmented because you have two decades of employees bringing in their own tools. And so the agent will just go and find the wrong document or the wrong contract or the wrong piece of data because you never really cared to have some kind of standardized system for your contracts because people could just always go and find what they were looking for. Agents can't do that. I mean, they'll find what they're looking for, but they'll just as often find the wrong thing as the right thing.

31:49So they have to be targeted. They have to have that information get curated. They need to understand the context of what is the process that they're doing. What I just described right now is 10 years of work for Accenture in every enterprise on the planet, or the next gen Accenture that does this in particular industries or workflows. Like we have to go upgrade your systems. We have to start to understand and organize your data in the right way. We have to start to describe these workflows to the agent itself. We have to figure out where the human is in the process. That is just real change management that every organization will have to go through.

32:20Harry Stebbings:We also have to have someone to blame. this is why a lot of these industries last which is like i have lawyers not because i can't necessarily write an nda it's because it's your freaking fault if anything goes wrong yes no literally and and we don't know like i promise you you're not going to be able to blame anthropic when something goes wrong and so if you can't blame anthropic when something goes wrong then at some point it doesn't really work to tell your customer well that sort of system that we set up, screwed up your data or automated something the wrong way or create a security vulnerability because the company will just say, well, I'm never working with you again.

32:55So then you have to have some accountability in your own organization for who is liable when something goes wrong. And the moment you have to have any liability, you have to have some amount of ownership and accountability and people have to have, they have to roll up to somebody who has more liability and more ownership and more accountability. Like this hasn't really changed the fundamental pattern of human behavior and contract law and the regulatory regimes that everybody's a part of. We've just sort of given our computers a machine gun to go generate way more information and work with all of our data.

33:27Harry Stebbings:You said before, when I've tried the latest model, it's got like 85 % of the way there. I speak to many of the best early stage and more mature West Coast based companies. And they say, hey, we use frontier models to set where we can be. And then we use open source Chinese models to get as close as we can to that frontier benchmark. Is Silicon Valley being funded by a generation of open CCP funded open models? I mean, that must be kind of empirically true. I don't have the same kind of like, oh, that's so scary, you know, kind of element. Now, obviously, again, holding out some element of risk of some backdoor weights that can get triggered at some moment or some parameters.

34:07But like, that's not how I'm perceiving it. But also that's I would say that's kind of orthogonal to my point about like the best frontier model still will go and do the wrong thing. And so thus I have to be in the workflow loop to make sure that I review its work.

34:21Harry Stebbings:You know, as a venture investor, I specialize at making bold statements with little substantive evidence. It's worked for the greats. So do you know what? I'm just following their lead. Jason Lemkin, my dear friend, says, why has no public company created any good agent product? everyone creates 60 % shit agents but he's like the one person who's done is Palantir and no other public company has created a sufficiently good agent product why is that I guess you know I don't know that I can fully endorse the point but I can give you the because I would argue our agent is sort of the best agent for working with content you know this is a very fast moving space and you have to be kind of wired in at a level that that I don't think you've ever had to be wired in in tech.

35:07And the information sources aren't the classic ones. It's not the roll-up review two weeks later from your traditional news publication that is going to give you any kind of alpha. It's the practitioner who's literally the engineer at the agent sandbox company and their long-form article on how they are handling memory and the harness. If you're not wired into that ecosystem, system it's very hard to then have your team be at the kind of forefront of all of what is happening and so it just is a it's a different pattern than what we've ever had to do like COVID was was pretty crazy like we all had to kind of like hunker down and be paying attention to daily news cycles on COVID stuff but it wasn't like a tech problem like it wasn't hard technologically but there's not been a moment before where the speed of change and responsiveness you have to have is quite literally on a multi multiple times a week cycle is your job harder than ever yes because of that speed of transience of superiority of technology yes you basically have this component of one there's a tsunami of change that you can just feel and so you're like okay we got to like run faster than ever before and then there's just like the pure technical underpinnings which some of it has business and strategy implications some of it has product implications some of it has partner or ecosystem implications because of that tsunami that you have to very quickly kind of wire up what you are doing about that shift and where the market is going.

36:35At the exact same time, you have to also be like, find a way to be a bridge for your customers that also don't wanna get crashed into by the tsunami and they wanna be able to have a bridge into the future. And so there's just, you're juggling a lot right now.

36:48Harry Stebbings:You said your agent product is the best product. Again, Jason and Rory said this and Rory might kill me for this because he gets a little bit more sensitive about when I quote him or misquote him more appropriately. But he basically says, and this is Jason again, if you can't charge way more for your agent product, Wall Street doesn't give a shit. You have to re-accelerate revenue with agent products. Can you charge significantly more for an agent product? The answer is yes, but there's a little bit of nuance, which is our business model is we have a new plan tier that we just introduced last year that basically houses our best workflow capabilities, our business automation, our application development capabilities.

37:27And then the agent is sort of central to that because it's going to help you automate the work that you're actually doing with your content. So it'll read a document and extract metadata from it. It'll process information inside of a workflow. So that is actually causing a reacceleration of our revenue growth. Last year, we saw an inflection in our revenue growth. And so it's already happening in our business. And so we are doing the thing that I think Rory is sort of probably saying is the new benchmark. Now, to be fair to what's happening, though, is I think Wall Street still is sort of saying, we kind of need to just step back and see where everybody lands in this because of how much change there is.

38:04So this is very much a year where if you're in software or infrastructure or building agents, it's a year of complete, unrelenting execution.

38:12Harry Stebbings:Do you look at the ticker? Yeah. Every day? Yeah. But I was like a day trader. I've never met a public company CEO who hasn't. The Navan CEO was on the other day, and he's like, multiple times a day. Multiple, multiple. Yeah, no, 100%. But, like, partly I just, I have, like, ADHD or something, and so I just need, like, I'm like, ah. Will we look back on this period and be like, what the fuck? Companies trading at three times cash flow. Way over-exaggerated or not? Well, three times cash flow is very much over-exaggerated. I would say that we're in a period right now where basically the market is being treated roughly as a kind of indiscriminately, you know, kind of bucketed sector.

38:54And the next year, two years or whatnot, you'll start to see some separation and parsing between the companies. Because as I noted in the beginning, agents will be really good for some parts of software and agents will put pressure on other parts of software. And it'll mean some companies have to fully pivot and some companies can just sort of ride their wave. And if they respond effectively, clearly 3x free cash flow, that seems like aggressively low territory. But I also think that at times in software, things have been aggressively overvalued beyond the realm of likely what the terminal value is of particular category or company as well.

39:27So I think there's just a pendulum that needs to kind of find its equilibrium right now. And that'll play out over the next year.

39:34Harry Stebbings:Do you think this generation of CEOs that you have around you, though, is equipped for the AI transformation that is ahead? Because I don't. Like, I think I'm not blowing smoke up your ass. You are. You're so versed in this. You're so fluid. But a lot are like, and one said to me the other day, no, we don't have the AI chops in house. We might need to bring it in. This one's hard. I think you still have a lot of kind of founder led or tech, you know, forward, whether they were an engineer or just they're just very technical category of folks that are pretty dialed in. And like I have Slack channels and WhatsApp groups where people on the weekend are just like working with Cloud Code or Codex building stuff and they're public company CEOs.

40:14So they are clearly wired in, tapped in. They can feel the technology and they are not going to let their company lose. you know assuming that that as a as a category they're in a spot where there's a lot of upside so yeah but like every every technology wave there's winners and losers i don't know that the this won't be any different you just have to be super dialed in and work through it

40:33Harry Stebbings:a hard one before we do a quick fire okay who has the world turned their back on who you think should be much more appreciated oh boy um you know i'll give maybe a shout out to like atlassian as an example. I think that feels like oversold territory. You think 78 % is a bit harsh? I think possibly. And it's in the category of they've been fighting this narrative, engineering gets commoditized. And so where in the stack was their engineering revenue generation? And again, with my headset, I'm like, no, there's going to be more engineers. And so now, does that mean that Atlassian's product set will look exactly like it does today?

41:11No. Obviously, it's got to evolve and whatnot. But I think if you're like a company selling infrastructure for engineering to be more automated, that seems like a good spot to be in. And you look at what Linear is doing and it's fantastic and it's awesome to watch. But I think there'll be multiple plays in that space, just given how big the market is. I think right now, this is a moment where you need to be deep in the workflow and you need to have data. You have to have data in your platform and you have to be the best place for that data to go. and you have to be the best place where agents want to work with that data.

41:41That's like the mandate right now is if you are not the best place that an agent would intentionally choose for working with data of that particular category or automating the workflow in that particular area, that's a tough spot to be in. And that's the job for all of us if you're building software.

41:58Harry Stebbings:And the best place where agents want to work is defined by great API. Great APIs, great pricing models, the surrounding features to the API. So if you were to say, hey, I want to be able to wire up a workflow where, this is the box sales pitch, I want to be able to wire up a workflow where an agent is interacting with FINRA compliant documents. You know, FINRA compliant document means the things that gets generated or seen or shared with the customer, and it can't ever be deleted and removed for a certain amount of time. Then on one hand, the APIs have to be super clean for the agent. On the other hand, you have to have a bunch of surrounding capabilities to ensure that that company can go to their regulator or auditor and say, yeah, we are complying with FINRA.

42:37So that combination is what makes it so you would build that kind of agent on something like Box. And that persists across a variety of industries.

42:44Harry Stebbings:I'm going to do a quick fire round with you. You have to go and be a public company CEO, I know. So what have you changed your mind on in the last 12 months most significantly? I do think that I've become more convinced that software is headless in the past year than I was maybe three years ago. And it's because of the level of agentic capabilities on tool calling and searching across systems and the accuracy of that. And that has happened faster than I would have perceived. So two to three years ago, if you were to kind of wire up an agent and tell it, hey, go work inside of Box and find a document to work with and do some process, it would basically almost always find the wrong document and it wouldn't be able to handle actually like cracking open the file and reading through it.

43:30And so thus, you know, going headless wasn't sort of the most urgent priority from an agentic standpoint. And in the past year, those capabilities have just absolutely accelerated to the point where I'm fully convinced that you have to be, you know, headless first as a software platform.

43:45Harry Stebbings:What acquisition did you not make that you wish you had made over the box journey? Jensen said in the show, oh, I wish we'd invest in frontier models. That was my big mistake. What acquisition did you not make that you wish you had done? I honestly don't, I don't think I have any M &A regrets. I actually, it's the deals that I wanted to do that we ended up not doing that I don't regret is probably more the situation. Which one is that? I'm not going to tell you those, but there are somewhere left in my own devices I would have done. And I look back and I'm like, oh, thank God that there was more rational logic in the process.

44:21Harry Stebbings:Who is going to win the enterprise race, OpenAI or Anthropic? Oh God, that's impossible. Back to the cloud piece. I think it's totally fair to think about it as a race. And certainly if you're in either of those companies, you have to treat it like a race because you obviously want 80 % market share, not 55 % market share. So you have to treat this as a, we got to dominate. That's exactly how they should be executing that way. Everything is going according to plan. If you compare it to other areas of compute, and I ran this analysis recently in 2010, not maybe you were 12, but the rest of us, we were just in companies doing things.

44:57In 2010, AWS made$500 million in revenue. Azure had just launched and GCP was called Google App Engine. And it had a little like a turbine logo with like wings or something. So that was the state of cloud. Fast forward to this year and it's a couple hundred billion dollar a year revenue ecosystem. So in 15 years, right? So, and we were in that moment being like, who's going to win? AWS or Azure or GCP? How is this all going to play out? And it just turns out the market was so large. Obviously, it was due to their execution that they kept it going and kept it large and the competition kept up, but it just didn't really matter.

45:32Everybody kind of won. And so I sort of think of AI in a similar fashion, which is I can't predict if it's going to be open AI 60 % and Anthropic 40%, or it gets flipped, or I'm off by another 10 % here or there. But no matter what, these markets are just fantastically large. Companies are going to adopt multiple of these systems. They don't want to have a single vendor in this stack. One service goes down or one changes its APIs or one has a new commercial model. It's going to be a multi-vendor, multi-AI world. And so that's why it's very hard to kind of call it at this stage.

46:05Harry Stebbings:What does everyone think they know about enterprise adoption with AI that they get totally wrong? What they think is that the outcomes that you're seeing in AI coding will quickly come for other areas of knowledge work. And that is a slight misread on the other areas of knowledge work. And some of it is the idiosyncrasies of coding. And some of it is the broad kind of just elements of the rest of work and how it happens. If you were a venture investor today, which category would you be most excited to invest in? Obviously, I'm just hypothetically speaking. God, I think I would still be probably loading up on all of the frontier rounds.

46:43It's like these numbers could continue to get much larger.

46:46Harry Stebbings:Could they get, I mean, much larger? I mean, this is where at$850 billion, you've got like a three X to like a$2.1 trillion style. You know, I always think it's hard because I kind of have said that on the way up of many companies. Like, you know, just like. I did it with crypto. Like, how much further can it go? It's like. Yeah. Well, that one I'm going to put in a different category because that can just sort of be memed to life. I actually think to the point on Atlassian and you and your whole category is the casinoization of the stock markets, which is like if you're a momentum trader today, you still buy Palantir because the market's a casino right now.

47:27Yeah. Well, to be a little bit more fair, I think you have some one off companies that have done an amazing job capturing the zeitgeist on that. I think the broad story right now is the sector rotation story. hey, this AI thing's happening. Right now I can get a higher return if I get closer to the semi-stack and the kind of where the workloads are going and where the data center build out is happening. And I get less of a return if I'm in software with kind of pure licensing. And so I think that is probably more of the color of what we're seeing. Now, some of the data center and infra names maybe have been memefied also.

48:03And so that's kind of helping the case, but it's just a really weird time overall that's hard to think through.

48:09Harry Stebbings:So you would not buy Allbirds as an AI company? I mean, maybe you would because of that exact point. So I think that will be in the kind of one-off category. So Newbird AI or whatever it's called. But I think, no, this is a generic statement. There will still be a lot of money to be made in the companies that can take the innovation that we're seeing in Silicon Valley and in the labs and apply it to the real world work that happens inside of enterprises. And whether that looks like vertical AI, whether that looks like the new kinds of tooling that companies will need, there's a company and a new category merging on agent observability and evaluations.

48:46I'll give a shout out to BrainTrust as an example, not an investor, where I can just kind of sit back and be like, shit, like we thought that agent builders were going to need evals. So that's like a Silicon Valley TAM. And then I'm like, oh, actually everybody on the entire planet, if you're putting agents into an enterprise workflow, needs evals because you need to know if all of a sudden your agent just stopped producing, you know, loan origination documents the right way. And so that's a category where it's probably not going to be owned by one of the labs. You kind of want it to work across all the labs.

49:17It's a very relevant kind of new form of infrastructure for an agentic enterprise. I think you're going to see a dozen, two dozen, five dozen of things like that, that start to emerge.

49:28Harry Stebbings:I've known you for a while now and you put up with me for multiple different sessions. So I want to finish on something a bit off script, but you're a phenomenal CEO. You're a public company CEO. The pressure that you have on you is intense. You're also married and have a great relationship. Biggest advice on marriage, when it's super stressful, it's hard. And you also have to show up and be a great husband. What's the advice on marriage? It feels dangerous if I I actually acknowledge the great husband piece and other other parts that were embedded in that. That feels like you need a full 360 eval.

49:59I will I'll just say from my perspective, and I'm very lucky to have an amazing wife and family. And, you know, you are you're in a grind in one of these roles. And so obviously having a strong support base, you know, helps a ton. We try and make time, you know, for for the fun side of life as much as possible. But obviously that gets constrained in the kind of window that we're in. But I've been with my wife for 15 years or so, 16 years. And so she's seen the whole grind all the way. And she has her own set of grind in her business. And so it's just lots of fun.

50:36Harry Stebbings:Dude, you're my hero. I want to be you when I grow up. Thank you for being so great. I really appreciate it. And I was 14 in 2010. Okay, all right, all right. So I almost called it. I almost called it. But before we leave you today, Did you know the industry average for booking a business trip is 45 minutes? That's a massive waste of your team's time. Well, with Navan, your employees can book a trip in just seven on average. Navan is the AI-powered travel and expense platform designed for companies that value efficiency. It drives real business impact through high employee adoption and automated policy control.

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51:46Harry Stebbings:Airwallex simplifies the spend behind it. Founders, let's get real about the growth tax. You've raised VC funding and you're scaling globally and it's no longer about shipping product. It's about orchestrating operations across continents. But suddenly, your payments and finance stack is choking your growth. You're logging into lots of different banking portals, waiting days for transfers, and reporting across entities. It's operational drag and it's at your scale. It's costing millions. That's why I'm so excited to partner with Airwallex. Airwallex are more than just a banking alternative to HSBC or Citi.

52:17Harry Stebbings:Airwallex brings you an intelligent financial operating system that powers how global businesses operate and grow, allowing you to manage and automate banking, treasury, payments, and spend. The most exciting part for me, they're heavily investing in agentic finance. If you're scaling globally, you need a banking and finance platform that's borderless, real-time, and intelligent. Check out Airwallex today and see how they're helping thousands of businesses like Canva, McLaren, and Deal. Scale at airwallex.com forward slash 20VC. Terms and conditions apply. Your monies are safeguarded, not FSCS protected.

52:52Harry Stebbings:See airwallex.com for more details. While Airwallex helps your money move globally, Vanta helps your security keep up. Security and compliance done wrong is a giant headache. Security and compliance done right, though? Well, that's Vanta. Vanta helps you earn trust and speed up growth. No spreadsheets required. For startups low on time and resources, Vanta becomes your first security hire, using AI and automation to get you compliant, fast, and unblock really big deals. And if you're big enterprises, Vanta is your AI-powered hub for compliance and risk, bringing together data from across your business and automating workflows so you can prove trust at any moment.

53:30Harry Stebbings:Vanta scales with you at every stage. That's why top companies from startups like Cursor to enterprises like Snowflake choose Vanta. Do security and compliance right. My listeners can get$1 ,000 off Vanta by going to vanta.com forward slash 20VC. That's vanta.com forward slash 20VC for$1 ,000 off Vanta.