Christina Cacioppo——AI时代如何打造一家历久弥新的软件公司——[Invest Like the Best，第496期]

So, Christina, I’ve been so excited to do this with you. I think it’s been 5 years since we last did it. A lot has happened.

A lifetime ago.

A lifetime ago. You’ve been very successful in the intervening 5 years, so I’m excited to catch up. Can you give us the 1-minute history of Vanta? I know we’ve done this before, but just to level-set for people: when you started it, why, what it did then, and how it’s evolved—

Yeah.

—what it does now. Quick overview.

Started Vanta about 8 years ago, which feels about—

Whoa.

—8,000. Yeah, exactly, or 17 centuries ago. The premise was: Can we help companies build and earn trust? That means starting security and compliance programs, or maturing them, and then getting credit with their customers through audits like SOC 2, ISO 2701, HIPAA, security questionnaires, trust centers, and so on. Basically, the idea was: Can we build a security company by helping companies implement security because it’s what their customers are asking for?

We were initially known for SOC 2 billboards. We do have a billboard on the 101, and I joke that we’re mostly known for making billboards. But it started very compliance- and audit-centric. The idea was always, “Hey, that’s just one way to get a company started on this.” Since then, we’ve gone into different areas of security and different ways of earning trust with your customers. Today, we have about 16,000 customers globally and about 5 products.

How did you win? This was a new category when you started, and I remember having to get SOC 2 compliant and certified at my old business in order to win certain accounts. It became an important thing in the software era. There were many companies—I could probably name a handful—that were trying to do what you were trying to do.

Yes.

You’ve emerged as the only major winner. What would you attribute that to? Since we last talked, how did you win?

Execution. Software is a blessing and a curse, and that’s even more true now than it was 5 years ago. You’re really only as good as the last thing you shipped. You can be first and start it, but that doesn’t really matter. It’s even more true now because someone can vibe-code your thing in a weekend. You’ve just got to constantly ship new products and features that make the experience better for customers, building on that differentiation.

There’s some feature-level differentiation. I think the other thing we really invested in when it got competitive, which was very good, was integrations—pulling in data from other tools. Now you can connect Vanta to 400 tools. We pull a ton of data out of those tools, and that’s what powers the automation, the agent, the AI, all of that. We call it our trust graph. It’s really just a security data lake, and it’s bigger and broader than any other provider’s, including some security providers’, because we touch areas they don’t. In retrospect, that data foundation has let us build new things faster, in software and with agents.

There’s that piece. Then I think on the go-to-market side, it’s just—

Good billboards.

—keep pushing. Good billboards. Shockingly good. “Compliance that doesn’t suck” got really popular on r/accounting, which none of us knew was a bucket-list item in our lives. When r/accounting likes your things, you’re like, “Okay, something worked.” The lived experience is that you feel like you’re going as fast as you can, and you should, in fact, lean in further and push harder.

What was the scariest moment?

The last 12 months. SaaSpocalypse. You’re like, “Okay, great job building a system of record. You’re now screwed.”

You’re now worthless.

Yeah, exactly. You’re worth, like, “Good job playing the game. Here’s some steak knives.” Parts of that are true, and parts of it aren’t. In the vein of “you’re only as good as the last thing you shipped,” you’re like, “Great, what is the agent?” You have all this data and a system of record. Fine. What the heck are you doing with it?

Say more about what that’s felt like. Roughly, Vanta is a business that’s growing very fast by historical standards, with very high margins—

Yes.

—which 4 years ago would have been considered the best business model ever. Nothing changed about that. I think you’re probably growing faster—

Yes.

—and the margins are still really high, and yet the market has decided that the multiple for a business like yours is a third or a quarter of what it used to be. What has it been like to live through that as one of those entrepreneurs?

Cognitive dissonance. You’ve got to hold 2 things in your head, right? One is, I think in the fullness of time, an 80% growth business with 80% margins will actually be better than a 160% growth business with 30% margins over the same time period, if you run it out long enough. One of these will return more cash in the fullness of time. But today, the latter is valued at 3X or 4X the multiple of the former. It’s 10X the multiple of the former, right?

There’s a part where you’re like, “Hey, guys, everyone’s being irrational here. This is a good business.” You have to keep doing the things that make business sense and the things customers want, which may or may not be token-pricing models that put you more in the latter category than the former profile.

Then there’s a very clear, game-on-the-field piece. If you need to be financed again, you’re looking at investors today, many of whom are AI maximalists. I’ve talked to firms that are like, “Yeah, we’ll invest in the labs, and we’ll basically invest in tractors in Iowa, nothing in between.” Robot tractors in Iowa and labs and everything else. You’re like, “Oh, interesting point of view.”

From a talent perspective, you hire ambitious people who want to do things, and if it feels like they’re not in the right boat, they’re going to change boats. The talent-war part is very real, too. You’ve just got to live with the fullness of time. I think this will all sort itself out, and you have to live for the fullness of time.

So there’s this funny fear that now Bending Spoons is the grim reaper in the hallway meme or whatever.

Yeah, yeah, yeah.

The grim reaper in the hallway—

Totally.

—you know, meme or whatever.

No one wants to be that spoon.

No one wants to be a bent spoon. Love Bending Spoons, by the way. I think it’s an interesting question. The siren song right now is selling tokens via agents—

Yeah.

—for security and compliance, I’m sure—

Yeah.

—or something like this.

Lots of thoughts on this.

I’m just so interested by companies like yours that were winners of this last era and now have to make a set of decisions. Look at the 10-year rate. The cost of capital’s going up because, for the time being, you can deploy lots of money at really high returns in AI stuff. Someone looking at your business is like, “Well, I want higher returns or the same returns, and I get that through agents or something.” Talk me through what it’s been like to make the decisions. What are you thinking today? Do you think of yourself as an AI business? What’s that like?

When we benchmark where we are from an agent and product perspective against, quote-unquote, “AI applications,” we have yet to find someone who’s further along. You could say we’re doing a bad job looking—that’s the obvious critique there. We’re constantly going to the set of names you imagine when you think of AI applications, and generally finding they’re not yet where we are, where an agent is doing most of the work.

It’s chat-based, but there are long-running agents. Our agent is auto-generating UI on the fly, because sometimes you want chat, and sometimes you want UI. We have an agent that’s building UI.

A user can do something, come back in the flow, and keep it going. It’s very much optimized around keeping the user going in the flow loops.

So, to make sure I understand: you’re like a watchdog that’s always on, watching the security and compliance programs?

We are definitely that, but in some ways you could do that in the past with just monitoring and alerting.

Uh-huh.

The Vanta product experience is now oriented around an agent that brings you things and often says, “Hey, I went and did this for you. Are you good with it? Then I’ll go do it.” Okay, great. The next thing I think I should go do is this.

What’s an example? Just ground that in an example.

Someone just left your company, and you didn’t get them out of all their accounts. I just wrote a custom agent for you that will go do that. Do you want me to turn this on? Great. Do you also want me to remove access from these 3 people? Great.

So it’s not just, “Here’s a red alert that someone didn’t meet the monitoring stack.”

Didn’t, right.

It’s like, “Do you want me to remedy this?”

It’s like, “Would you like me to go do this?” We’re taking a lot from the AI labs and their UI. It’s like, “You want me to do this once? You want me to do this always?” Great. The idea is that the agent will just be doing more of this work with the user’s permission. If they tell us to go do it, we’re just going to go.

In the course of that, we end up using a lot of tokens. We’ve talked to our customers a lot about token-based pricing, and what we’ve generally heard is that people are really smart. If you try to charge them based on tokens, they’re very quick to say, “Oh, you’ve just marked up a Cloud token 4X.”

Hmm.

“Are you 4X as good as Claude? I don’t know. Let me try it out.” You actually put yourselves in a competitive position against the models that probably no application really wants to be in. We’re going to talk about harnesses. You don’t want to get there.

What we’ve seen on token pricing is that if you’re trying to mark up at all, users are very smart, and you’ll lose on that comparison. You can not mark up, and this gets to the margin question, but anyone who is marking up Cloud tokens 4X and trying to pass that off to their users, I think, is just saying that.

So what are you doing?

We’re eating the token cost right now.

You’re just taking a lower margin.

We’re taking a lower margin and really concentrating on usage. That experience I just talked through, where the agent is going off and doing things, is something we fundamentally believe is a much better user experience. We’ve got 25% of all our customers in that sort of flow right now.

If we can get that to 75%, I think we’ll have much better retention and a much better customer experience. Then, if we need to sort out pricing later, we should sort out pricing later. This is a usage phase and a deployment phase for this technology. Just go nail that, and you can figure out commercialization after.

I’m also curious: you said marking up a Cloud token, but what about marking up a Kimi token or something that’s much cheaper? What’s it been like deciding what to use, what’s good enough, and what the cost is?

This was something we started concentrating on at the beginning of the year: basically, evals, task-specific or agent-specific evals. From a product perspective, we call it all the Vanta agent, and it’s one thing. Of course, behind the scenes, it’s hundreds of agents that all have specific tasks and use tools and have computers and that whole setup I think everyone’s converging on.

At the beginning of the year, we really invested in using our subject matter experts—the folks who ran security and compliance programs at other companies—to write the eval frameworks, evaluate their evals, and use tooling for that. When we think about model swapping, it’s mostly about quality, not cost.

I also think some of that is because we don’t use as many tokens as coding. Coding and coding agents use lots of tokens, maybe legal and document drafting next. When you get to more of the decision-action world, which is where we are, we just don’t use that many tokens relative to coding. That lets us optimize for quality rather than being as concerned about cost as some other companies.

When you talk to other founders, both from your era and this new era, what are they doing here? Are they also eating the cost and just charging a software fee? What do you think the end state’s going to be?

I think everyone wants to get to outcome pricing. Everyone wants to get to that. In another life, I was a microeconomics professor. I love this conceptually. You would get paid for outcomes, and the incentives would be aligned. Love it.

The hard part is: what are the outcomes? A support ticket closed makes a lot of sense. To that point, maybe I should differentiate outcome and output as I understand them. In support, the ticket closed is an output. The outcome is actually that my Sonos now works.

Even the ticket closed is relatively unobjectionable. I think a lot of companies, Vanta included, are trying to figure out what that neat unit of work is that we can all agree on. You can say it’s a document drafted, an alert closed, or an account offboarded. You can kind of do that, but then there’s so much cognitive overhead, because you’re like, “I just named 3 things. I could name another 47.”

Then our user has to be like, “Well, if I do this with the agent, I pay this, but if I do it on my own…” No one wants that. Everyone I talk to wants to get to outcome-output pricing, but it’s really not clear how you get there. Charging tokens puts you up against Claude. Some people try to obscure that by charging credits and having some credit-token exchange-rate-y thing. Again, users are smart, and they’re like, “I see what you’re doing, and I see you’ve obscured it. Fine.”

Are you similarly far along if you compare yourself, as you just did, to companies in how you’re building the product and the business using these tools? What are you doing that’s interesting there?

1. AI Inside Vanta

For an 8-year-old company with an 8-year-old code base, it’s so much easier to throw coding agents at a small code base than a large one. That’s a token-input thing, and they’re getting better and better.

One thing we’ve spent a lot of time investing in over the last year, and I know Notion has spent a bunch of time on—they’re about 9 months ahead of us on—is modularizing parts of the code base so the agent can understand smaller parts of it fully and then be really effective. If you chuck it at an 8-year-old code base sight unseen, it just doesn’t have the context window to understand everything and will do silly things. Then you need a high-context engineer to babysit it, which is helpful but sort of invalidates some of the point.

Companies have always had this problem. They’ve just talked about it as, “When we onboard a new engineer, it takes them a while to figure out the code base.” Agents have made it, “Well, great, now we want to onboard 9,000 new engineers tomorrow.” It’s heightened that problem. I’d give ourselves a lower grade on that. We’re in the process of using agents and people to make the code base easier to understand, too.

If you had to grade yourself from 1 to 10 on “Wow, this changes everything. Building this company from this point forward is going to be totally different,” is it a 10?

Oh, yeah. Nine. Yeah.

You’re a nine?

Eight or nine. The principles are still the same. Everything is hard. People matter. All the tropes are still the tropes, but the way you do stuff should be quite different.

Do you feel like there’s a separation happening? Again, if I took your cohort of successful companies from a year ago, do you feel there’s a bifurcation where some have gotten the memo and are doing really well—

Yes.

—and some are just going—

Yeah.

—belly up?

Kind of. I think there are structural parts of some markets, and I think that makes me very good at identifying them, where you can put any entrepreneur in the world into that structure. This is kind of the “Does the market or founder win?” Andreessen Horowitz thing, and you’re like, “The market wins.” I think that’s still true, and I think this AI technology shift has made some markets that used to look really good look really bad.

The best person in the world can run into that and will still run into a brick wall. I think there’s also a founder motivation piece: you’ve got to be in it and push in this era. If you don’t want to do that, totally fine, but the rest of the company will not self-organize to do so.

So given that you’ve been at the edge, what’s the AI adoption 101 if you’re back to being a professor? What have been the most important things that have been hard to do but have proven fruitful?

Just getting people to use it, which sounds obvious, but definitely use it yourself. Build for your company personally; it doesn’t matter what. Understand where the models are, where they’re good, where they’re bad, and what a harness means. Do that at least every 2 weeks because it changes so quickly. You have to have a visceral understanding of what works and what doesn’t, so that when somebody comes and says, “We’re going to fire all of our SDRs because I built one agent,” you can be like, “Did you now? Where is that true, and where is that false?” So there’s a “be in the muck” aspect to it. You want to get as many other people into that as possible.

Broadly generalized, it’s very black and white. Some people just go do that, and some people don’t. If you’d asked me a year ago, I’d have said, “Oh, well, there’s some intrinsic motivation, and the people who aren’t doing it have separate problems. Go deal with them.” I think I’m slightly more empathetic now, in that we’ve seen very strong people not dive in, and you have to nudge them more. Try to figure out what’s blocking them. Something can be blocking them, and you can get people into the muck even if they don’t dive in initially.

If you’re a small company starting out on Vanta, great. We’ve got this set of controls for you. You adopt them, maybe mess with them on the edges, and you’re off to the races. If you’re a larger company, you clearly run a security and compliance program, and you come to Vanta because you want that visualized. You want the automation, the monitoring, and the real-time dashboards. You don’t want the Jira ticket thing. Fine. The hard part is that you’ve got to get all that existing stuff—the controls, the risks, the data, the policies, the procedures—into Vanta.

Classically, the way you’d do that as a SaaS company is you’d say, “Oh, we’re going to make an onboarding wizard. It has 4 steps and a progress bar, and we’ll give you confetti.” You’re going to do that whole thing. We were setting out to build better onboarding this year, and in the first couple of product reviews, the team kept bringing onboarding wizards. I kept saying, “Stop with the onboarding. No, go use an LLM. Stop.” But they kept bringing onboarding wizards, and this was a motivated team of talented people. They cared, and they kept bringing them.

We finally have the experience now. They shipped it, and it’s working. It’s basically Claude: a big canvas. Drag all your messy files in, drag in all your screenshots. We’ll make sense of it, ask you questions, and then you’re set up and off to the races. It works really well. Why were these smart, motivated people building onboarding wizards? When I finally went out and asked, they said, “Well, we don’t know if we can get the ‘drag your files’ thing to work. It might not work, and we know the onboarding wizard will work because we’ve built those before. We basically don’t think we’re allowed to fail on this project.”

“Oh, that’s the thing? Great. We’re just going to bet that the LLM flow is going to work, and we’ll make it work. We’ll hill-climb all we need to, but burn the boats and just make this thing work.” Then they were like, “Oh, okay, great. Do you want a product review tomorrow?” It was this funny thing where I thought, “I would not have guessed that was their blocker.” And you saw that, and they were going.

You mentioned the talent war thing before. There’s this big trend, the low-margin, high-growth thing, where, from an investor’s perspective, the funny example you gave of a lab or a tractor: everyone wants something that can be that thing. Tell me about how you’re going to be a $100 billion business or a trillion-dollar business. Somehow, now every business needs to be that big. What’s that like to face down where—

Oh, it’s so bizarre.

—you may not be building a business that should be a $100 billion business. There are, like, 100 of those in the world. There aren’t that many.

Yeah, and it’s not to say Vanta won’t be. For me, it’s like, “Oh, should I adjust the pitch and be like, ‘Well, inevitably, the baseline here is Vanta’s $50 billion. The real question you should be considering if you join: can you take us on a journey to, like, $250 billion?’” Should I just start saying that? Probably not, but the answer is not definitely not.

You’ve thought about it.

Totally, because you’re like, “Well, that is the pitch that people who work at Vanta are getting from other companies.” The market is saying that so much, you do seem unambitious.

So what do you do?

There’s a Vanta principle of “do what it says on the tin.” Do what you say you’re going to do. Look, you can put ambitious things on a tin. It’s not that. Don’t overpromise and underdeliver. What we do is give some of the context—“Here’s what we do as a company, good, bad, indifferent”—and then talk about the business metrics. We’ll generally just show a candidate everything. It’s fine. The metrics are good. We don’t really want them to leak, but if they leak, it’s not the worst. We walk them through that and what we’re doing and how it grows over time. We try to root it in all of the facts and all of the data. In some ways, it’s countering the vibes with data and trustworthy vibes versus YOLO vibes.

So what is it like in those talent wars? If the most talented people are being told this thing’s going to a trillion, basically every other company that’s trying to hire them—

Well, the better one is, “Well, we’re $6 billion today, but Sequoia’s going to do a $10 billion check in a month, and then somebody’s going to write it up to $25 billion next year. But we can get you in at $6 billion today.” That’s a good one. That one’s tough.

So you’re faced with that. What do you do? Do you not want those people? Maybe it’s a filter.

Sometimes. I think if you go to the person and ask, “What are you optimizing for? Why did you entertain this?”—but not in a pokey way. Just, “What’s annoying you at Vanta?” One of these specifically was a very strong leader, still at Vanta. This person felt like they couldn’t make decisions that would put Vanta on a similar trajectory, and that would be their preference. But they were like, “Oh, but this new place is promising me full decision-making authority on this trajectory.” Totally fair feedback. “What do you need to feel like you can make these decisions? Just go make these decisions. Go.”

There’s a money part and a FOMO part, for sure. We’ve definitely gone up on comp, and comp bands are kind of a joke now. The comp band is whatever; the data you have is wrong. It’s what’s being offered to these people in the market.

How much more do you pay the top person at Vanta than you did, as a multiple?

Oh, I think we should have way more comp dispersion than we do.

So that’s interesting, but if I go 5 years back and that person made X dollars, what multiple of X does the person make now?

Total comp. It’s probably a factor of 10.

Wow.

I think it actually should be higher. My comp philosophy is that you never pay the top people—

Enough.

—enough. You should always try, and you will never hit it. And there are a bunch of people you pay much more than their contribution.

Say a bit more about what those top people are doing that’s so valuable, typically.

High agency, get shit done. That sounds so milquetoast, and that’s worth millions of dollars. But yes, actually, it is. A high-context person who understands the company, the customers, and the domain, making generally reasonable decisions and sometimes bad ones, then iterating on their bad ones and just moving, is so valuable.

Do you think it’ll be 10X again in 5 more years, or is that starting to get too crazy? Is the rate at which the most valuable people are getting more valuable staying the same, or accelerating?

Accelerating. The counterforce is: at what point will investors get more concerned about dilution and stock-based comp? They weren’t throughout the 2010s, the late 2010s. We had more of a stock-based comp conversation as an industry in 2020, 2022, and 2023. Now we’re definitely not talking about it. That’s the counter side. Without that push on dilution, I think people just get paid more and more. That’s what they probably should.

How much do you care about your valuation and multiple and the engineering of those things?

I’ve historically not cared, and sometimes even done things to demonstrate my not caring.

I care about ARR and ARR growth. I pay a ton of attention to those; those are the metrics. I think I've now been through enough valuation environments—the 2010s, 2021, 2022—and seen the multiple roller coaster that I just don't put a bunch of stock in that. Or I used not to.

I think the thing I care a bunch about, which would then get me to care about these multiples, is the sentiment of people who work at Vanta. Do they feel like they're at a company that is growing, and growing both in general and relative to their other opportunities in the market? There's a part of the market that's raising money every 6 months at 5 times the prior valuation, and that's a real talent competitor.

And what about things like tenders? Have you done this historically?

We have not done them historically, but the game on the field is that you're doing a tender every time, and you gotta do them.

Does this feel unhealthy?

Totally. My opinions about it don't matter. I can have all the feelings I want in whatever direction about tenders. They are normalized, and people expect them as part of their comp. If you're not giving it to them, you gotta give them a bunch of other stuff to make it up.

How does all of this affect your exit ambitions—to go public, to be sold, or realize some endgame for Vanta? Not at all?

Not really, which is, again, a very founder-privileged statement. The endgame is: How long can we keep this going for? Ninety-nine percent of the big independent software companies in the United States are public. Yes, an IPO in that sense. I don't have it as a bucket-list item myself. It's more of a means to an end. Lots of people join companies and want the bucket-list item, so, founder-privilege caveat here again. But the goal is a big, independent, standalone company.

On all this stuff—tools for building, ways of building, all these kinds of things I'm asking about—what do you think is overhyped and underhyped?

2. What AI Hype Misses

Underhyped is knowing the company and the customers, relative to knowing the skill set. It's still really hard to hire, train, onboard, and make people who join a company effective. The company can make this better and easier and put information at people's fingertips, but there's still totally something to be said about someone who's been at a company, knows how to navigate it, knows the customers, all of that.

I'm at a phase right now where we value that skill set more than the functional skill set of, “You're good at sales” or “You're good at customer success.” We'd take a worse salesperson on sales skill who knows the Vanta pieces more. There's something in that. Especially as a lot of the labs and fast-growing AI companies are building out go-to-market teams, I think they're very much valuing that you're a good salesperson. That's slightly off. As we think about building agents for all of this, the company-context piece and the customer-context piece are probably being relatively undervalued compared to “You're a good salesperson.” I think that skill is slightly less valuable today than it was 4 years ago.

What about overhyped?

Token-based pricing, low margins for the sake of having low margins, and custom training models for the marketing value.

Being able to say, “We post-trained a model on our stuff.”

Exactly.

Explain why.

Go talk to the inference providers, and sometimes, depending on the provider, give them your CRM. They'll say, “Look, the reason to post-train a model is cost.” Some businesses have that need, but there's not a quality reason to do it. There's kind of a marketing reason to do it right now, and I think there's a lot of post-training for marketing reasons—for investors and for customers. Mostly for investors, actually.

If one of those people were pitching the other side of this—the value of post-training—what's the pitch to you?

Yeah.

One of these companies comes to you and is like, “We'll do XYZ for you.” What are they saying, and what do they say the benefits are?

“You are putting a stake in the ground of being a real AI company. Customers will notice.” I think that's the primary one. I do think there's a secondary one in some use cases, a form-factor thing. Especially with large enterprises, you want to deploy this piece of software wall to wall, and that requires integrations and 17 people to sign off. Oof. That's a whole thing. Why don't you just give them a model specific to them for this use case? I think that's semi-reasonable.

So if I was one of these people and I came into Vanta, what does post-training literally mean? What would it mean in your context? What are you doing? What are the steps that you would go through?

We would need a bunch of data from that specific customer, then go write a bunch of evals and change model weights based on that customer's specific data.

The process would be: they're trying to achieve something, they've got some data, you tune a model to achieve the thing—

Exactly. Yeah.

—increase the eval. And then sell them that—

Exactly. Yes.

—on an ongoing basis. And your point is that that's overrated because it doesn't actually improve their—

It can. I think I'm skeptical in a couple of ways. Does everyone really want to be handed a model? There's so much around that from a user-experience perspective, from a deployment perspective, and from a form-factor perspective. It feels a little like—you know on social media, with our mobile apps, when we hadn't figured out pull to refresh yet? There's something here. I don't think anyone actually wants to be handed a model, the same way it's like hitting a refresh button. I don't know, that sounds silly, but that's what we did in 2011. There's some version of that here. We haven't figured out how this actually works, and handing models, I think, is not the right solution. It's a reasonable iteration, but not the right solution.

Is there anything else in the popular discourse that you think is crazy?

Yeah, FDEs.

FDEs?

I kind of think FDEs are crazy. I think it's a great talent arbitrage, the same way a chief of staff is. What an FDE often is is professional services, but I think if you call it a professional services role, that's a very different talent profile than FDE in the current discourse. I don't think you're gonna get the Harvard CS grad who's high-agency and wants to go do things and learn how to build a business to sign up to be a pro serve person number 4 or number 12 at a company.

I think there's a real job there, but I think this FDE wrapper around it probably isn't going to stay. The company that we all think does this well is Palantir, which I think they probably do. They have eight-figure contracts. There are some companies that have eight-figure contracts. I think we're using FDEs at a place where there are five- and six-figure contracts, and those economics are probably upside down. We're in, again, an era of 30% growth, margin better, and so that sort of works. That doesn't feel sustainable.

When you're at a dinner in San Francisco with other founders, what are you talking about? Are you talking about models and which ones to use? What are the actual topics of conversation between founders right now?

There's definitely the talent-war pieces. There was a time—this is more 9 months ago—but it was a joy to go around the table and complain about Cursor, their taking of everyone. There's definitely that piece. There's a bit of an FDE conversation: “Do you actually do this? Is it working? Where are you on this right now?” Personal agents: which ones do you have, and what are actually useful?

When you think about the open-source stuff, Chinese models, this, that, and the other—

Yeah.

—what have you learned talking to people around the world who are grappling with these same questions?

I was with our customers in France a couple of weeks ago, which was lovely. One of the things I was very surprised to learn is that a lot of the French software companies in Paris are using Chinese models predominantly. I initially thought it was nationalism, maybe anti-America, just something there, and stupidly suggested that. Someone very quickly corrected me and said, “Absolutely not. We basically all switched to Chinese models when Trump closed Fable[?] off to non-Americans, and we just kind of realized there's a huge business continuity risk. We can't trust that if we build a business on one of these American models, it'll always be available, so we stopped doing that.”

If you dream the most about where the business could go over the next several years, what's the version of Vanta that could look like?

3. Vanta’s Security Expansion

We think of Vanta as a security company. We started with compliance. The best version of compliance is proving the security you have. You've got to have good security. We think we can, and are, moving into a bunch of security domains as sort of a platform pitch: Look, we've already got the data. We've already got the intelligence via the agent. We can start stacking products on top of that, more security-focused products.

As we understand the security of all these companies, the pressure on them to go prove they're legitimate and industrial-grade is just gonna go up. That's one of the founding theses of Vanta 8 years ago, but it feels even more true now. Whether they're working with enterprises, governments, regulators, or lawmakers, you just have to prove your software is industrial-grade in lots of ways. That will happen more and more, in more and more ways, in the future, and Vanta is the thing that connects both sides of that marketplace.

So what’s the direction of security? This is, of course, an incredibly interesting topic. In the early internet, everything broke; everything got hacked. This will probably be that times 10 or 100. Does security mean you compete with CrowdStrike and places like that? What does security mean, and what’s its trajectory in this crazy era?

These models are just so much more persistent than people. They’ll try nine quadrillion things, where a person would give up after 9,000. In the course of that, they find things and chain things together. A lot of the discourse is around zero-days, and there’s definitely some of that: these models are finding things we didn’t find before, or didn’t publicly find before.

I think what’s happening more is that these models are able to chain 17 benign-ish—or benign on their own—things together and then really find something. If you watch the OpenAI talk at RSA about Hugging Face, it’s basically that: persistence, putting together things that people on their own would’ve said, “That’s low severity. I’ll fix it in 90 days.”

I think that update is tough, and we have to fight with machines, because it takes what was, “Oh, that’s important, but low severity. I’ll get to it in 90 days. I’m going to fix this other stuff first,” and turns the prioritization on its head. Saying it makes everything critical isn’t helpful, because then you’re like, “Well, what do you do?” I think what that ends up looking like is that you’ve just got to fix stuff as fast as you find it, and some of the prioritization does need to go out the window. But if you’re fixing things at machine speed, you don’t have to prioritize. That’s where I think we’re going to get to, but I think it’ll be rocky as we get there.

So, as I visualize that, what it feels like to me is a constant penetration test—

Yes. Yeah.

—where an agent is trying to break in, like a white-hat hacker agent—

Yep.

—all the time.

Yep.

And then every time they find something, it’s got a buddy agent that’s a patch—

Goes fix it, yeah.

Is that the ultimate product vision, then?

For some parts of Vanta, yes. I think we can do that in very compelling ways for the bulk of our customers. I think CrowdStrike will do it better for an enterprise. This is where choosing where you play and what market segment is most important.

Is there a firm that’s doing something now that you start to encroach on, among the traditional security firms?

It’s a different market segment. Take an ongoing penetration tester and remediator, a fixer. We think we can do that for the cloud providers, like AWS or Azure—misconfigurations there. Classically, Wiz does that. Wiz will do it for its customers. Wiz’s customer base starts at a multi-thousand-person company, and its price point starts at a multi-thousand-person company.

We’re thinking about the platform in terms of where we’re already embedded with customers. Where are they unlikely to pay $150,000 for Wiz, but very well could pay 40 or 50 for something suited to them? We’re thinking through where we’re already strong and where the competitors are focused elsewhere, probably on a more upmarket segment.

How has your personal motivation changed? You set out to build this thing. I remember talking to you the first time about this very charming way you built the original product, building it in Excel first.

Yeah.

It seems very old school. Looking back on it, there’s always the “dog that caught the car” thing where—

Yeah.

—all right, you built this huge software business.

Yeah.

Amazing. How has your own motivation evolved or changed through all this? Why keep going?

It’s interesting and challenging, and it changes all the time. I really like my job. Sometimes I feel like I’m good at it. Often, I feel like I’m bad at it. That’s fine. In some ways, that’s not the point.

It changes, and it’s different. When I feel like I’ve gotten good at it, usually something happens, and then I feel bad at it again. I really like that dynamic. In the beginning, I had a lot more of a feeling of, “People think I can’t do this. I think I can, and I’m going to show them.” I still have that. We even did the, “You don’t think Vanta’s going to be $250 billion? Let me show you.” I still have it, but, as you can probably tell, there’s less of a dark edge to it. Still a little dark edge, but less of it.

It’s, “Oh, cool. We got here. Now we’re just going to see how far we can run,” in a way that feels a little more fun and joyful. My day-to-day is not always joyful. I don’t mean that. But it feels more like, “Oh, cool. Let’s see how far we can go with this.” I think we can go pretty damn far. Whereas in the beginning, I think it was more like, “You don’t think I can get off the starting line? Let me show you.”

How surprised would the 8-year-old version of you be at some specific skill that you’ve developed?

Oh, probably pretty surprised. Yeah.

What’s the most surprising one that you’re now good at that old you would’ve said, “No way”?

I like go-to-market more than I ever would’ve guessed. You get to talk to personable, friendly people all the time, and I was a terrible public speaker. I would get the most nervous in front of my own team because I cared the most about what they thought. I was like, “Oh my God, I’m representing you. I want to do this so well.”

Exposure therapy was helpful on that one. You just do it, and you do get better at it. But I think the thought of being at kickoff or an all-company get-together, in front of 1,000 people on a stage, would’ve made me think, “Oh, shit. I’m going to be bad at that.” I think the people around me would’ve been like, “Yeah, yeah, she’ll be bad at that. How much coaching can she get?” But it’s like anything else. If you work hard at developing a skill, you tend to get better at it. You just have to put in the work.

In that one in particular, I’m very interested in that. It always seems high leverage. What matters? You’ve given however many hundreds of these things. What makes one good?

The trope that no one remembers what you say, but they remember how you felt, is so annoying, but it is so true. I do have to believe in the content. If I just get up and feel like it’s contentless, I’ll also feel that way, and it’ll be obvious to everyone.

You kind of have to figure out your version of it. For me, I try to put real content in and also hold in my head, “No one’s going to remember any of these facts.”

So heart—

That’s not the point.

—matters more than mind.

So much more, yeah.

And the key to good heart is what?

Believing in it yourself. Authenticity. One-on-one or on a stage, people are pretty good at reading one another. When you feel like the person you’re talking to is going through the motions, doesn’t really feel like it, or is misleading you—maybe they’re also misleading themselves—people can tell. They can’t entirely articulate what’s happening. Something seems off. Versus someone who’s authentically into it, even if they’re into something kooky, that just comes off.

What are the big trade-offs that you struggle with right now? You can’t do everything. You’ve got to make decisions. The stakes are higher than ever. It’s easier to build than ever. It seems like a cool time to be doing what you’re doing, but there must be big trade-offs that you struggle with. What are those for Vanta?

One conversation we’ve had and have is that we’ve tried over the last year to build in such an agent-forward way.

What does agent mean?

I don’t know. You get 2 extra revenue multiples if you say “agent.” It’s like 3× if you say “harness.” I have to… I could say “harness” more. “Prompt file,” like, minus 3×, you know?

We’ve tried to build such a great harness for our customers, but actually not build a bunch of SaaS UI. You want reporting? We’ll have our agent go make charts for you on demand based on all of our data. We’re not going to put Tableau inside of Vanta, which is probably what we would’ve done in 2021 or 2022 if we had been building it then.

We believe in this in the short-term customer-outcome sense, but also in the medium- to long-term sense: this is what software will look like, and no one is going to be putting Tableau inside their products.

So there’s an aspect of this diffusion thing that’s just scary: maybe the tractor company takes 10 years, and in the meantime, you were right, but early, and therefore wrong.

And therefore wrong. You’re kind of betting on the time horizon there. The other version of this is big enterprises. We’re working with a U.S. enterprise, trying to close them, and they were basically like, “Hey, maybe we want your AI features, maybe we won’t, but can you turn them off for now?” And I’m like, “Ugh, why?” The answer is, it’s way easier to get a non-AI tool through procurement, and we want your tool.

Turn it on after we’re in.

Right? We don’t really have an off switch on it. You’re like, “Oh, can we go build that?” But you’re also like, “Gross. We don’t want to build that. We’d so much rather take that time and effort and build something actually useful.” Anyway, we’re not going to build this off switch, but it’s just one of those trade-offs.

If you were an investor, which you used to be, where would you be focused right now?

Oof. I do not envy the job at all right now.

Why? Why don’t you envy it?

As much as I can critique and make fun of some of these businesses on the company side, and say, “Oh, I think people are thinking about them in a very short-term way,” I think the FOMO and the question of “What are your returns?” are more acute on the investor side than the company side. I saw this tweet: “If you haven’t invested in a lab or an inference provider in the last 4 years, you should just shut down your firm, because what are you doing?” It feels more acute on the investor side than the company side. However hard I think my life is, my life’s not hard, to be clear. Whatever trade-offs we’re facing, it feels more echo-chamber-y, more judged on incremental returns and paper returns on the VC side than on the company side.

So what would you do? Where would you hunt?

The labs and the inference providers, apparently. No, those feel a little… Well, we can debate whether they’re played out, but they have high entry prices. The discourse and the certainty around the open-source model providers, and then the tooling and companies around them, feel sort of disconnected. It’s, “Oh, we’ve all decided the open-source model will be very real,” and then the ecosystem around them is so much less built out than the big labs. That just feels off to me. You probably have a better diagnosis of that.

What do you mean by the ecosystem around them?

If you think that a lab—or is it Longlight[?]? Is that what it’s called?—like, these are basically going to go deploy this technology—

Put AI on it, basically.

—and put AI in these businesses. Can you build one of those around the open-source providers? Of course, yes. But can you really grab one of those models the way OpenAI is grabbing its own stuff and just replicate that playbook? A bunch of the lab playbooks seem like they should apply to the open-source models.

And it’s just less mature, so there’s more to do there.

Exactly.

Yeah.

What am I missing on that?

I think it’s just a pace thing. Anything where these things can go… It’s kind of like, ironically, private equity or something—what private equity promised to do, which was to shape businesses up. Now they can do that much more easily, so probably everything will get way more efficient if it can, and the return will come from higher margins, more efficient operations, whatever. That’s an efficiency thing, not a generative thing. I guess what I’m more curious about, as you watch your peers and people around you, is where the green shoots are on the generative side.

A bunch of people are starting cybersecurity companies, both because of the environment and because I see proportionally more of those than other things. A bunch of people are attacking rev tech, like go-to-market technology, which I think makes a ton of sense. Some of the old SaaS rev tech providers should be building all this stuff, but it doesn’t seem like they are. Instead, they’re running more PE-bent, sponsor-sort-of playbooks, which is, again, a choice. It may be a reasonable choice. Robotics is probably underplayed, though it’s somewhat hot and hypey. That’s not a novel area, but it’s still definitely underweighted compared to all the software stuff. The models are also getting real damn good there, to state the obvious, so I’d probably spend time there.

What else do you feel like you know because of your unique path that others don’t yet fully appreciate?

Over the past couple of years, Vanta has spent more time with government, at the federal, state, and local levels inside the U.S., and outside the U.S. There’s an appetite for modernization. It’s a big stated priority of the current U.S. administration, but it exists outside of the U.S. too. The AI piece has created more FOMO among government officials. They may have always known they didn’t have modern processes or modern software, but it feels more imperative now than it used to.

Here’s a broader answer: all of the conversation around AI and the technology has changed the priority and increased the priority of a lot of modernization. Sometimes it’s within governments, sometimes it’s within enterprises. You see this with a lot of the cyber stuff and the CISOs we talk to. Their jobs are changing because of AI, and they’re saying, “Given AI and the risks from the agents, I’d like to overhaul my enterprise risk program, and I’d like budget for that.” If they’d said, “I want budget for my enterprise risk program,” 3 years ago, people would’ve been like, “Eh, we’ll talk about an ALP. Maybe.” Because it’s attached to AI, they’re much more likely to get that budget today, so there’s more of a buying motion.

What would be your big pitch to come work at Vanta right now?

Oh, it’s a fun stage. You get 16,000 customers using a product, using agents. When you ship things, they’re in use by real people, getting real feedback instantly. It has product-market fit. You’re just going and experimenting with fast iteration loops.

But early enough that you could still—

You can move, yeah.

—be a part of—

We will let you move.

Yeah.

Yes.

Because it’s such an amazing Silicon Valley microcosm, can you tell the most detailed version of the billboard war story that you’ve ever told?

I was always very much a billboard skeptic because it seemed like, who knows if they work? The tracking’s terrible. Founder ego is why someone would do a billboard, because they feel cool having a billboard for their company. So I was always very anti-billboard.

In mid-summer 2021, at the SaaStr Conference, which felt like a big deal at the time—thank God we’re almost beyond that—our marketing team decided to try out-of-home advertising. I was super skeptical, but I was like, “Fine, whatever. Try it.” We were going to put something on the billboard, and Sarah, who was our PMM at the time, came up with “Compliance that doesn’t talk too much.” She pitched it to our head of marketing, who didn’t like it because they thought we were negging our users. They were basically like, “No, don’t. Think harder.” Much nicer, but, like, think harder.

Sarah kind of believed in it, so she went to me, which she usually doesn’t do. She’s not someone who goes around her boss, but she really believed in “Compliance that doesn’t talk too much,” so she took it to me. I read it and immediately laughed. I texted Andrew Reid, our investor, and asked, “What do you think? You have good internet meme taste.” He loved it, so I was like, “Okay. Let’s try it. Let’s run it.” What’s the worst that’s going to happen? People will think we’re obnoxious and then probably forget in 6 months.

We put the billboard up somewhere near Burning Man. It went over so well. We tweeted it, and the tweet went viral. It kept circulating over the next couple of months and ended up on r/accounting and all these places. You’re like, “Oh, this is a gem.” I think it really worked because it was our brand and our marketing at their best. Our attribute is a wink: we take our work seriously, but we don’t always take ourselves seriously. I think there was something about that that resonated. It was a little obscure, but sufficiently obscure that if you got it, you felt like you got a secret. Anyway, “Compliance that doesn’t talk too much” just worked.

In 2022, the market crashed. It turned out there was a lot of billboard inventory available on 101. We got this great spot where 101 and 280 intersect, and it was a great spot for not that much money, especially in retrospect. We joked, “Oh yeah, we’ve locked it up for years.” We were known for that billboard in that spot. I think I even said on podcasts that the contract was locked up for years. It was not locked up for years. But that billboard got famous, and people would contact us and Sarah all the time and ask, “How do you do billboards? How do you do your billboard?” We’d say, “Oh, we work with this agency. We work with this guy.” We referred this guy all this business, and he’d be like, “It’s him, it’s him, it’s him.” Millions of dollars of business. Great.

It turns out we did not have a multi-year contract in the background, which I should’ve known, certainly if I was going to say that on a podcast. It didn’t really do what it said on the tin. The contract was basically, “You’ve put the billboard up.” That’s it. This was not a contract at all.

Multiple years go by. Sarah’s having dinner with one of her friends, who works at a startup, and her friend says, “Oh, it’s so sad you guys gave up that billboard spot. Why’d you do that?” Sarah says, “Pardon?” Her friend says, “Oh yeah, we just signed for your spot.”

Sarah says, “What?” We go back and look at the contract. The contract’s written in crayon. There’s no contract, basically. It’s a placement order. We call the guy, and he says, “Yeah, you know, it was a placement order. They paid more.” So he swapped it out from under us.

I go to the founder of said company and say, “Hello. How much can I pay you?” I’m an extremely inelastic buyer here. What can I pay you for this spot? He says, “Nothing.” I say, “How about I double?” I think he was paying about $1.5 million. I say, “How about I give you $3 million just to get this spot?” And he says, “We’re actually cash flow positive.” So, literally, I’m an inelastic seller. And we lost the spot.

Good punchline.

Things that made me think, “Oh no, Vanta’s screwed.” Honestly, losing that billboard, I thought we probably just lost a bit of market cap.

Bad, bad, bad omen.

Yeah, yeah. You’re both bad omens. There’s some 5% market cap decrease that just happened here. Yes.

Is there anything I’ve missed that has your curiosity, your attention, that you think is really important right now?

You see it in the data center conversations, and to some extent in the personal agent stuff. We just don’t trust software companies and tech companies the way we used to, and that’s getting worse year over year. It’s kind of hard to imagine that inflecting back up and getting to the useful optimism of 15 years ago.

In that environment, companies showing that they’re trustworthy, industrial-grade, and secure through lots of metrics and actual definitions is more important than ever, and will just get more and more important. And again, to a host of customers, regulators, lawmakers, auditors, et cetera, Vanta at $250 billion is in the center of all of those transactions. We help companies meet those high bars, or wherever those bars are set, and then convey that, helping them go convey that and accelerate their businesses.

Is there a way of saying that AI has ushered in this extremely high-excitement-but-low-trust—

Yeah, that’s good.

—era?

Yes.

And Vanta’s job is—

Rebuild some of that trust.

—preserve the excitement, but increase—

And, yeah, increase the trust. Legitimately so, not just on vibes.

What will satisfy the market to trust again?

In a B2B context, with businesses, I do think there’s the vibes piece, but there’s a very real data piece. I’d like to see specific things or specific improvement curves, or make promises with maybe contracts behind them. That one’s, quote-unquote, logical and rational, the way enterprise markets often are.

On the consumer side, it is vibes. That one seems very hard to turn. I do not envy that.

Do you trust them to use Instinct, et cetera?

Big companies? No.

Why not?

It’s not that there’s anything particularly interesting in my email or chats or whatever. My life’s not that interesting. But I would rather just Google or just Apple or just insert company here have that information.

What’s security like five years from now? If you wrap it up with, “Okay, here’s where we’re going, and we want to be the person at the center of this,” describe that state for us.

Security five years from now is faster, even more intense, more offensive. Hopefully, yes, we’ll have more attacks, but I think you need more white hats pushing back on all of that, and at a speed that we haven’t had before.

I think you’ve got to get humans to that speed. You’ve got to get some amount of the human decision-making out, where humans are architecting systems and writing rules, but not making every single decision. It’s like falling from that. Writing emails, maybe that’s all we’re doing in the future. We’ll all write emails all day long.

If you had to define what the next five years of Vanta will be in one word, what word do you pick?

Expansive. I think we have this incredible base of customers, of data, and now we get to go build things on top of that. Eight years to get here. We could go just build stuff on top of it for the next five or eight.

It’s so cool that we did this five years ago. Here we are again. Thanks so much for your time.

Thanks.