Peter Walker

Show Notes

In this episode, Peter Walker, Head of Insights at Carta, discusses his journey in the startup world and the role of data in his career. He shares insights on the challenges and trends in implementing analytics at scale. He also provides an overview of the funding landscape and the impact of the pandemic on fundraising. The conversation explores the impact of changing interest rates on startup funding and the challenges faced by startups in the current market. It discusses the decline in seed funding compared to series D funding, the need for capital in late-stage rounds, and the shift in fundraising dynamics. The conversation also touches on the liquidity of equity for startup employees, the decrease in startup hiring, and the changes in startup compensation. The guest shares insights on leadership, success, and advice for emerging professionals.

Takeaways

...
• Startups can leverage data to make informed decisions and improve their operations.
• Data storytelling is a powerful tool for communicating insights and making data more accessible.
• The implementation of analytics at scale requires data cleaning, understanding the audience, and integrating different databases.
• The funding landscape for startups has been challenging, with a decline in fundraising in recent years.
• The impact of the pandemic has varied across different stages of a company's life cycle.
• Changing interest rates have had a significant impact on startup funding, with seed funding down compared to series D funding.
• Late-stage rounds require massive amounts of capital, and the decline in late-stage funding raises concerns about where the money will go.
• Startup employees are facing challenges in accessing liquidity for their equity, leading to a decrease in exercise rates.
• The startup job market has seen a decrease in hiring and an increase in shutdowns.
• Startup compensation has undergone significant changes, with equity compensation decreasing and salary compensation remaining relatively flat.
• Leadership can be demonstrated at any level within a company, and energy and consistency are important qualities for leaders.
• Startups should consider starting fundraising earlier than expected and focus on making every dollar last longer.
• The guest's goal is to make Carta data ubiquitous and be the single source of truth for startup data.

more  

Quotes

“Energy is contagious.”

“The funding winter is thawing, but is still rather chilly.”

“Things are a lot harder than they appear on the surface.”

“A lot of marketers do themselves a disservice by not understanding data as much as they should.”

“The cap table is a record of who owns what percentage of a company.”

“A lot of B2B companies can actually use this as a new form of marketing. It's data content that educates your audience about the world and the market that they're in.”

“Insight is a piece of information that's going to help you make a decision.”

“Always on I think is it sounds good real time, but it isn't always necessary.”

“Industry, time, location, these are all very clear and obvious filters to put into your data that kind of expose and kind of tease out differences between parts of your data set.”

“I come in usually with a question. But oftentimes, the data... leads me to things I wasn't really thinking about.”

“The closer you are to IPO, the more difficult the fundraising market has been… Seed funding on Carta is down something like 30 to 35% from peak, whereas series D funding is down something like 80% from peak.”

“There's maybe more liquidity needs to happen at earlier points in the company journey if companies aren't gonna go public for a decade plus.”

“The employee that's hired in January of 2024 receives about 36% less equity than the employee that was hired in November of 2022.”

“It is an employer friendly hiring market at the moment.”

“I think we will see more shutdowns through H124 than we've seen in a long time.”

“Leadership in your role doesn't have to come along with a title. So you can have influence without having authority.”

"As soon as you prove yourself competent, you get to do so many things that are not in the job description."

more  

Episode Summary

Coming soon...

Lightening Round

---------------------------------------------------------------------------------------

Episode Transcript

Rohit Agarwal:
Hey Peter, welcome to Strategy of Finance podcast.

Peter Walker:
Hey Rohit, thank you so much for having me. Pleasure to be here.

Rohit Agarwal:
Awesome. Why don't we start with answering the question, who is Peter Walker?

Peter Walker:
Well, I guess we could go with a long or a short answer to that. But at the moment, I am the Head of Insights at Carta. And it's been really wonderful over the last, I don't know, three years or so to sort of build this community of early stage founders and investors that Carta is obviously a cap table management software. So we serve these folks every day. But my role has been to sort of bring data to their jobs and maybe use the. the privileged position that we sit on top of all these cap tables to make their lives easier. So it's been an awesome, cool chapter in my career to watch all this excitement and love grow for all the data that we have. I honestly wasn't anticipating this sort of response when I got into the job.

Rohit Agarwal:
Super interesting. We'll certainly look to unpack more about Carta as well as what exactly do you do in terms of being head of insights. But why don't we first go through your journey. How did you get here? Can you take us through maybe the key milestones that have shaped your career so far?

Peter Walker:
I think probably the couple major touch points would be first, you know, starting a company in college with a couple of friends. To be honest, the primary reason that we started it is because we didn't want to do consulting summer internships. So we were looking to do anything else. But really found that I loved entrepreneurship and got into it really deeply and then joined a startup right out of school called Public Relay, which did media intelligence for the Fortune 500. And that was a wonderful mix. You know, when people come to me and ask about what joining a startup is like, I think I was employee number 10 or 11. Um, the amazing part was that as soon as you prove yourself competent, you get to do so many things that are not in the job description. So I ran data teams, I ran marketing teams, I dabbled in design. I, you know, I worked in sales for a while. Like you just kind of touch on all different parts of this business and get to see how these pieces fit together. And that led me directly into Carta in some ways. It's jumped around to some other early stage startups and had a whole COVID period that we can get into. But getting bitten by that entrepreneurship bug in college was, I think, maybe the key turning point.

Rohit Agarwal:
Was there any point prior to your college that you thought about technology as an area to get ...into or entrepreneurship or that was literally the first introduction?

Peter Walker:
No, I mean, that's a good point. It wasn't the first introduction. My dad is an entrepreneur and had founded a couple of businesses, not really in tech, but in packaging and shipping. So I was always kind of aware of it as a career path, but I didn't go into school thinking that was going to be my route. And then as people just sort of buckled down into finance or majors or other things like that, it... it kind of dawned on me that none of that was that interesting. And I wanted to work, I think the primary function was I wanted to work with a very small group of people that I really liked. And that was one of the biggest things that drew me to startups is that it's this tiny group of people that you become very, very close with. And, you know, the company that I started in college with a couple, there were two of my best friends and it was an amazing way to learn a bunch of things together.

Rohit Agarwal:
Make sense. Can you share some of the key takeaways that you have from that entrepreneurial experience?

Peter Walker:
So the company that we started was called State of Glow. It was kind of a, the idea here was that we were going to sell merchandise at music festivals and use that to build like a music festival brand that we could then leverage as a website or like a pitchfork, etc. for music festivals. It's kind of a vague idea. But what we ended up doing was we ended up selling merchandise at 26 or 28 festivals a summer. You know. people say, oh, wow, so you just spent your time going to music festivals, that must have been so much fun. To be honest, it was getting up at four, driving this suburban with a U-Haul attached to it with full of merchandise down to whatever festival it was, working the full day, packing everything up, sleeping in a Walmart parking lot, and then keep going on. So the number one lesson that I learned is that things are a lot harder than they appear on the surface. If you're trying to just go to a music festival every once in a while, working there is not the way to do it. The other thing that I learned was that there are so many minute aspects of entrepreneurship that kind of take you away from the thing that you wanted to do. So in my case, you know, we wanted to build this cool website around music. And what I ended up doing was spending my time figuring out how to, you know, satisfy sales tax in 26 states. Not exactly what my initial intent was to be. So it kind of opened the eyes that, oh, There's a lot of company building that is sort of drudgery and busy work and like all the stuff that isn't exactly trying to build for your core mission. You got to be prepared to handle it.

Rohit Agarwal:
Makes a ton of sense. You said you spent a good number of years in marketing, right? I believe that's a pretty data intensive function. Is that, would you say, where you really honed your analytics and storytelling chops?

Peter Walker:
Yeah.
I think the marketing can be very data centric. I think in some ways I had started my career at the smaller startup as a data analyst and then kind of moved up through running visualization and Tableau teams, et cetera. And then I used marketing as sort of a break from that data intensiveness to learn about design and brand and sort of expression of a lot of broader ideas. And so marrying those two things was kind of where the storytelling came from. I think actually, to be honest, I think a lot of marketers do themselves a disservice by not understanding data as much as they should. I think that there's a really, you know, they use data to justify ROI on campaigns and things like that, but they're not consuming data in the way that a business intelligence analyst would or a biz ops person. And I think that if marketing had a little bit more of that flavor, oftentimes they would be able to kind of recognize the connections between the parts of the business a little bit more easily. I know that's been really, really helpful in my career at least.

Rohit Agarwal:
And that happens as a result of the organizational structure, or is it more a function of just people being too busy with a bunch of different priorities that they're dealing with and that kind of doesn't really surface in your face?

Peter Walker:
Yeah.
That's a good question. I think it's probably a little bit of both. As a company grows, Carta is close to 2,000 people now, so the functions get more and more specialized. At the small startup, you have marketing, and marketing does all of the things. Here we have an email lifecycle person, and the jobs actually get much more tailored. There's always room for that person who wants to go and explore. hey, what's going on this other team? The major thing that I tell marketers, which when they wonder, hey, do I really need to learn SQL or like what's the value of having this data sort of background? The value to me is just speed. If I'm a marketer and I don't know SQL, I have to go file a ticket with the right team to go get this data that's gonna help me make a decision. Whereas if I do know these technical things, I can do it myself. And I just can move much, much more quickly than, than other folks who have to wait and be kind of at the back and call of another team schedule. So I always think that if you can organize those or, you know, collate those things within a single person, it's a lot easier.

Rohit Agarwal:
You talked about Carta being 2,000-odd people. Why don't you introduce Carta in a minute for our audience to better contextualize the quantum of data, maybe, that you are also parsing through. And we'll, of course, talk about a bunch of analysis that you do. It'll be a good level setting for them.

Peter Walker:
Absolutely. So Carta is the premier cap table management software in the US. We also have a lot of different businesses, but the core function is we provide the software where founders keep their cap tables. And the cap table is a record of who owns what percentage of a company. And you might think, oh, that seems pretty simple at the beginning. And indeed it is if you just have you and a couple of co-founders. But when you're adding advisors, investors, employees, everyone that you're giving out bit of ownership in the business, it can get complex really quickly. So we streamlined that process for founders. We have about 43,000 startups on our software today. We also manage the back office in a separate software suite for the CFO of a venture fund. So all the venture funds that invest into these startups, they have a lot of needs in terms of tax, audit, valuations, a lot of back office administrative stuff. And we run that. business as well. So that's about 2,500 or so venture funds. So that gives us company side about 40, 43,000 companies, fund side about 2,500 funds. And the combination of those data sets is kind of a wonderful view into what's going on in private markets, mostly in the States, although we do have a lot of companies in Europe and Singapore as well.

Rohit Agarwal:
All right, cool. That's quite a large representation. And I would imagine even if you talk about the 40 to 43 K startups, they would be across the size, right? It's not just early stage. They would be from the very get go, very early seed stage, maybe all the way to kind of IPO scale companies, right?

Peter Walker:
Exactly. Yeah. And we actually, I think there was a perception a couple of years ago that companies should get going, get started, build a little bit of a business and then maybe their seed or series A come and join Carta. But we launched a product in 2020 called Carta Launch, which is completely free cap table until you raise a million dollars. So we have, I think, close to 10,000 companies that are actually pre seed companies and are just starting their journeys with us. So we see the whole thing from idea stage all the way to IPO.

Rohit Agarwal:
Very interesting. And then again, you are head of analytics. Going through all of this data seems like a pretty unique role. How did your function really come about? Who conceptualized it? How did you end up at where you are?

Peter Walker:
So yeah, this head of insights role is, as you said, kind of a, I think a pretty unique one. It doesn't exist in too many different companies. Maybe I should take a step back. In 2020, at the beginning of the pandemic, I've been working at these startups, and then obviously COVID happens, everyone's at home, and I ended up joining this organization called the COVID Tracking Project out of the Atlantic Magazine. And I ran there, I was the head of data visualization there for a year. And that was a really eyeopening experience in producing visuals and analytics and narratives for a wide public at scale, you know, it's COVID everyone's super interested in the data. And our charts were everywhere across the internet for, for that year. And it really just kind of had me thinking, what are the other data sets? What are the other you know, organizations out there that have a dataset that needs to be explained to the world in the right ways. And I think a lot of B2B companies can actually use this as a new form of marketing. It's data content that educates your audience about the world and the market that they're in. So that's what I do at Carta. And it's, yes, there's a ton of data. You have, there's a lot of things to wade through, but at the core of it, the idea is instead of just running another marketing campaign, Why don't we teach our audience something that they're already asking us if you're an early stage founder or early stage investor? And then we can become the sort of first source of truth for data in our industry. And that's a wonderful place to be if you're always on people's minds for, you know, just an education or a helpful reason.

Rohit Agarwal:
I'm curious, do you sit within the COO org or the marketing CMO org?

Peter Walker:
So I report to the CMO. Yeah, so I'm a marketer here at Carta by definition. I do play sort of a bridge role between data and marketing a lot of the times. I can be helpful there, but at the core I'm a marketer.

Rohit Agarwal:
Got it, makes sense. And so thereby I would imagine most of these insights analytics that you are doing, they are more external facing, not necessarily internal facing around the operations of the company.

Peter Walker:
Right, exactly. So we wouldn't say, although we've done some special projects on my team that are kind of internal facing, the vast majority of our work is built to be shared with external audiences. The only point that I'd have to that though is, once you start building an insights function, you're producing things on a regular basis for external folks. What you quickly realize is that a lot of these things can be equally helpful to internal people as well. So... You can use them to educate your sales force, your customer success managers. You can use them on calls across, you know, for instance, we have a lot of ecosystem partners that help Carta succeed and we in turn help them grow as well, people like lawyers, accelerators, et cetera. Um, and they can be very, very interested in the kind of data that we have as well. So it's, it kind of, it's, yeah, we build it for external folks, but it can be equally useful to a lot of internal cartons as well.

Rohit Agarwal:
Do you have a framework in terms of how should other companies think about having such a function? Is there a size element to it? Is there a density of data that you think would make sense and after which only companies should think about such kind of a data intensive marketing? You know, for what kind of companies and what stage does it make really good sense?

Peter Walker:
It certainly helps to have a sort of above a threshold of density of data. I don't think that, so I wouldn't recommend that, you know, your average call it seed stage startup, for instance, might build this function but I would also say you don't have to be the market leader in order to have enough data to be starting with. So probably what you want to be is a place within your market, within your industry, where you are, you have enough of a flywheel that you're growing and you have customers to be talking about. And then of course, all of this data is aggregated and anonymized, so you need to have a data science function or at least the data team of some way, shape or form that can do that aggregation and anonymization for you. After that, it's really up to the market. I think a lot of people, when I speak about this insights function, they get excited about it and then they fall back to this question of statistical significance. Is this statistically significant enough to be talking about or are we just putting stuff out that doesn't mean anything? I think that's a valid question, but my pushback is always, what is the market that you're working in? If you are working in a market where there's tons of data and everybody, a lot of this is already public then yes, you're going to need more information in order to make an impact in that world. If you're working in a place like, say, early stage startups, where a lot of the information is opaque, it's kind of tough to find, and then any data is better than no data in most cases. So it really just depends on the kind of audience that you're speaking to.

Rohit Agarwal:
Interesting. As you think about, you said again, your analysis is more external facing. There are many companies which have analytics team, if not fully blown function, that are predominantly built to be able to look at the business side of data, right? The business operations data. It could be around product, could be around marketing, sales, finance, HR, whatever. I would imagine the analytics part of it, perhaps even tools, as well as the storytelling part of it, are quite fungible between these two external facing as well as internal facing analysis that one needs to do. Of course, there are two different data sets, perhaps. But the core idea remains the same. Is there an argument to be made in having both of these internal as well as external analytics team under one umbrella, or you think it makes sense for them to be separate?

Peter Walker:
I think you can make the argument that they should be combined. You're right. When most people hear the word insights, they think internal product data, internal business operations data, how do we improve our sales cycle? How do we use product feedback to make the right adjustments to the app, et cetera. I think that those can be useful portions of an insights function, and they're actually probably the core of what most people think. The other thing that comes into play there, a thing like surveys. So surveying customers, making sure that you're in touch with customer needs, et cetera. I think the skills are very fungible. You can build a lot with the same tech stack. You can build a lot with the same people. The valence is a little different. The emphasis is a little different. You don't do quite as much storytelling internally as you would externally. But I think that more companies should explore having those two functions either housed together or at least in close contact with one another. Again, I just don't think that the insights, the external insights portion is that common outside of one report a year maybe from a company that spends a lot of time and effort, maybe even outsources it to an agency, things like that.

Rohit Agarwal:
You used two words, insights and data storytelling. Can you unpack each one of them? Why don't we start with maybe what are insights?

Peter Walker:
Insights are pieces of information that have utility. So you can have a data set that has reams and reams of numbers and it's complex and difficult to parse. And an insight is the sort of aggregated result of those numbers that tells you to take an action or not take an action. It helps you make a decision of some kind. An example, on Carta, we have many, many companies that are always raising fundraising rounds. You know, so from that we can publish an aggregated version of a median valuation for say a series A startup. So that you as a series A founder can look at that and go, okay, I have a sense of where the market is headed in terms of valuations that helps me when I go into that next negotiation with the VC. So that's an insight. I think that insights can be instantiated. They can be created in a lot of different ways. They can be written down in docs, they can be graphed in charts, they can be spoken on podcasts. But the insight itself is a piece of information that's going to help you make a decision. Whereas data storytelling is more about transforming maybe these slightly more boring spreadsheets into charts, graphs, visually insightful graphics that give you a bit of a sense of how the data is trending. And storytelling in this case, I think a lot of times the people who are building the data, who are building the analytics, lack some storytelling nuance. And the people who are good at storytelling maybe lack some of the data nuance. So merging those two things together, I think you can tell a really fantastic story with charts and graphs. And I think it's an underrated part of marketing that is probably going to get much bigger in the next couple of years.

Rohit Agarwal:
I would imagine you need to have good understanding of the business itself to be able to then take a data and render it on a chart, right? Like anyone can create a bar chart, a column chart, you know, maybe a column or a line chart. Like that's easy with Excel or other tools, right? But unless you have an understanding of the business in terms of saying, okay, what story do I want to tell? I would imagine it becomes hard to substantiate it with using any chart.

Peter Walker:
Yep. Ahem.
Exactly. I think that's a great point. There's any there is and now with Gen AI charts, etc. There's going to be an explosion of people who can just make graphics. But the key is, do you understand your business? And maybe even more importantly, do you understand your audience? Do you understand what an early stage founder actually needs out of that data set? And are you going to build something that gives them an answer that they can then take and use in their in their daily lives? That's the real It always comes back to like, how well do you understand the audience that you're building?

Rohit Agarwal:
Is there a good versus a bad insight? I can imagine there could be a bad storytelling, but could an insight be also good versus bad?

Peter Walker:
But certainly an insight could be negative or positive. You can discover something is going wrong in the business. You can discover founders in one area of the country are lagging behind founders in another area, things like that. I don't know if the insight itself could be morally good or bad. I think it's more just how are you going to use that information? And as you mentioned, storytelling, there's a reason why people say lies, damn lies, and statistics. because you can build data and charts and graphs to make a point that maybe you're being a little disingenuous about.

Rohit Agarwal:
Makes sense. Can you talk about some effective data storytelling techniques that you have used in your career?

Peter Walker:
I think, so a couple of things, if you're coming from a data-centric background and you're trying to explain the numbers that you look at every day to an audience that maybe has never seen them before, the first thing that we tend to do is we overcomplicate things. We try to tell them all of the interesting data points that we have about this data set and we confuse them right off the bat. So the number one thing that I would tell aspiring data storytellers is simplify whenever possible. If you're going to make three points in a single chart, consider making three separate charts that make one point each. So simplifying and clarifying your work, I think, is one of the easiest ways to get going. The second point that I'll make is that a lot of the times people fail to use text and written words alongside the charts in the way that they should. And this comes up, the most common data storytelling is actually probably going to be you building a PowerPoint or a Google Slides deck to show to a boss or someone else in your company. The thing that you can do that will make your chart stand out is actually nothing about the chart itself. It's in the headline of what you're writing. Don't use that headline space to tell them what the chart is. Use the headline space to tell them what they should be taking away. So for instance, don't write in the headline, number of new deals per quarter. That's obvious. You can write that in the subhead. You just have that somewhere else in the chart. Write in the headline - Q4 deals declined because X. Give them the actual takeaway, and then you're guaranteeing that even if you don't get to make this presentation, the key point that you want to tell them is going to carry with them no matter who gets to talk to the executives in the end. So that would be the two points that I would have is use text well and then simplify your charts whenever possible.

Rohit Agarwal:
Makes sense. Yeah, I think quite simple and yet very powerful. Is there a framework that helps us understand if certain analytics or insights should be one-off thing, versus maybe periodic in nature, versus even be available real time at all time?

Peter Walker:
This is actually a pretty deep question. So one of the things that I think people get wrong about building insights to put out into public is there's this tendency when you get started that what you're going to do is you're going to build a big report and you're gonna put it out every quarter or every month, or you're gonna commit to some sort of periodic recreation of this data without actually first establishing through social or other channels that this is information that your audience actually wants. So you shouldn't a priori decide that these are the exact right graphics and exact right data points. Go out to your audience, build one thing, put it out there, see if you get feedback, keep building that way. And then once you have a corpus of information, you can build a fuller report. In terms of the periodic nature of some things, you know... Some things seem to be pretty obviously useful on a quarterly or monthly or yearly basis. Change in valuation, for instance. People love to compare this quarter to the last quarter, this quarter to a year ago, etc. Most of the time, though, I think that there's less of a need to be always on. There's only really a few, I mean, it depends on your industry, but there's only really a few things that deserve a... constantly refreshed data set. For instance, at Carta, we have this product called Carta Total Compensation, which helps founders and investors, or excuse me, founders, to understand what they're gonna pay an employee in salary and equity. And that database is built off of thousands and thousands of startups who, we have their equity values, we know what they're paying in salary to various positions, et cetera. Some people come to us and they say, well, we would love this to update every day, but... If you go and talk to HR teams, they don't want it to update every day. They're not making a huge change to their compensation plan every day. That would be incredibly disruptive to the business. So they actually want it to change maybe once a quarter where they can actually digest the changes and see if they're going to make corresponding decisions. So always on I think is it sounds good real time, but it isn't always necessary.

Rohit Agarwal:
Makes sense. Can we talk about some key steps in the analytics process from maybe data collection to all the way to insights generation? And I don't know, maybe even decision making is kind of really the end goal of it.

Peter Walker:
Yeah, absolutely. So I think there's a couple key points before you get to any sort of visualization or dancing through the analytics and the data. The place where you have to start is, of course, cleaning and prepping your data sets. If you have a wonderful data science team, as I do, a lot of that work is gonna be done in models before I even touch the data. So removing outliers, understanding where maybe there are errors or things are a little bit off. That's always the first line in any sort of data project. Then secondly, you're going to use that cleaned data set and you're going to try to take whatever key information you can from it. There's a lot of different ways to do this. Some people like to do this in Python. Some people like to do this in SQL. Some people like to do this in business intelligence tools. I'm a pretty visual person, so I tend to... you know, do data discovery through charts in Tableau or other business intelligence programs. So that's your one is cleaning and prepping to his data discovery. And then three is the creation of a finalized graphic or insight. And that's where the storytelling comes in. That's where you write the narrative. That's where you explain any outliers. That's where you make it clear to your audience what you're talking about. And then you can distribute it in any number of ways.

Rohit Agarwal:
Are you always testing a hypothesis or one can even go on a complete exploration path that hey, here's the data, let me just see what the chart is going to throw and maybe then I'll try to suss something out of it.

Peter Walker:
You do both, for sure. I think at the beginning, it's good to come in with a strong hypothesis and say, I'd like to either prove or disprove this idea. But as you get into it, the data oftentimes will sort of reveal within it an interesting part that you hadn't considered. Maybe this is where you get into the idea of cross references and filters. So perhaps your data set is pretty standard if you're just looking at it overall, but if you segment it by industry. you see that one industry has had major changes while the rest of them have sort of trundled along and been the same. And you wouldn't have known that to come in with, you just, you put that filter on your data and it showed, it exposed itself that way. Industry, time, location, these are all very clear and obvious filters to put into your data that kind of expose and kind of tease out differences between parts of your data set. So I come in usually with a question. But that question, oftentimes, the data leads me to things I wasn't really thinking about.

Rohit Agarwal:
Do you have a suggested way to formulate a good problem statement or hypothesis that you want to test?

Peter Walker:
The best way is to answer a question that you've already been getting. So, you know, people ask all the time, how do you think about coming up with new insights? Or like, what is your process for generating that? These days, I would say more than half of the questions that we answer come directly from the audience. They are comments left on our posts. They are questions on a webinar. There are things that people are clearly thinking about that we can then go back and answer. So. Listen again, listen to your customers. If they're asking questions repeatedly, those are the questions that you want to go and answer for them. But if you have to come up with it yourself, I think maybe two guiding principles. One is, am I asking a question that has the potential for a non-obvious answer? So if I'm just asking a question and it always is gonna come back with the common wisdom, it usually isn't going to be that interesting to folks. And then two, am I asking a question that has the potential for significant change? So even if it's not obvious, is it likely to have changed over a period of time? Time is probably the easiest parameter to think about here. And it allows you to build things that add to our earlier discussion. You can then save that and refresh it a quarter later and have a new answer. And those are really nice to fall back on as you're building sort of a standard set of analytics that you report on.

Rohit Agarwal:
I'm curious what you put out in public. Do you have a different version of that within your product that your customers are consuming or customers are also consuming what you put out in the public only?

Peter Walker:
No, both for sure. The public stuff is consumed by everyone, customers, prospects, anyone honestly in public who has social media. But there are also analytics tabs within our product that allow our customers to either dig more deeply into something themselves, or it just places the data right when it's needed. So one of these things that I think people misunderstand about information like the ones that we put out at Carta is that this data is useful, but it's most useful in a specific moment of time. So if we take an example, if you're a founder and you're about to fundraise using a SAFE, a simple agreement for future equity, the moment that you start to create that SAFE on Carta is the moment where you would love to have market data about SAFEs. You know, you don't want to go to the blog and look it up or go to somebody's LinkedIn and look it up. You want that data right there at your fingertips when you're creating the instrument. So we can have a light box pop up that says, Hey, I see you're creating a SAFE. Here are the latest market trends for SAFEs. So founders can have the information right when they need it. And so that temporality of data, I think is really important. And it also means people sometimes think, well, you've put the data out in public, so it's not useful to your customers anymore. That's totally not true. Most of them didn't see it the first time and most of them won't remember what it was even if they did see it. So putting it into the product and infusing it in a native way can be very, very helpful.

Rohit Agarwal:
That makes a ton of sense. Yeah, quite powerful to have it in context.

Peter Walker:
Exactly.

Rohit Agarwal:
What are the biggest challenges organizations face in implementing analytics at scale? I mean, you're talking about 43,000 startups, 2,500 odd funds, completely different product I would imagine attached to the hip, but still very different interfaces and so on. What do you need to do?

Peter Walker:
Yeah, I mean the core problem as usual, which we'll be familiar to, I'm sure a lot of the audience when it comes to data sets across the company is just having these databases talk to each other in a way that makes sense. As you mentioned, Carta has three or four major businesses. Those businesses began at different times, so they may be using different analytics stacks in some cases and having them all talk to each other and having the data clean and easy to analyze is... is always a big challenge. It's not something that is ever done. It's always a consistent project that you're working on because things change. So that's number one. Number two is, as you mentioned, you wanna have someone who has a good context on what analytics are actually going to be useful to produce, because you can sit and waste a lot of time in building things that nobody really cares about too much if you're not... tapped into the customer viewpoint or customer thought process. So those would be the two trap points, I think, that kind of come up a lot. And there's something that we had to do at Carta. I've been enrolled for three years now. Probably the first, I don't know, three or six months was spent cleaning data, figuring out the questions to ask, etc. It wasn't like we were just putting this out immediately.

Rohit Agarwal:
make sense. Are there some emerging trends that you are seeing around analytics that professionals should keep an eye on?

Peter Walker:
I think the number one is the use of GenAI in chart creation and insight creation. A lot of companies right now are trying to do natural language to SQL. So you can write your questions in English. The idea being that if you empower everyone in the company to ask questions of their own data, they'll be better able to answer customer questions and better able to use data in their day-to-day role. I think that's a cool and interesting viewpoint. I think that's overrated in some ways. I think there's actually a lot of people who won't ask too many questions of their data because they don't trust the answers. So that's a difficult one, like the hallucinations in the gen AI space. The moment that it gets one answer wrong, like you really lose trust in it. So that's a difficult thing. But I love the innovation that's coming with chart creation in particular. I think the visual... Taking data from a data set and creating visuals through natural language is going to radically increase the number of charts online, and it's going to be really interesting to see how people use that. So if you're in the analytics space, you definitely have to stay up with the latest on Gen.ai stuff.

Rohit Agarwal:
All right. Well, why don't we now move on and dig into the state of the union and really understand certain specific insights that you generate that could be useful to our listeners? Let's start with answering the question. I think it's at everyone's top of mind. Is the funding winter over?

Peter Walker:
Perhaps we could say the funding winter is thawing, but is still rather chilly. So if we just look at Carta data for the last, call it four years or so, obviously everyone knows venture capital fundraising went through this gigantic boom in 2021 and early 2022. At Carta, that looks like in the last, or in, excuse me, in 2021 as a whole. companies on Carta raised about $220 billion, which is the most they've ever raised in a single year. In 2023, that total was down to about $66, $67 billion. So a really sharp decline. We are starting to see a little bit of green shoots in 2024 so far. Q1 was decent, I think a little bit higher than Q4, but not like a jump. you know, not a massive change. So things are getting a little bit better every quarter, but it has been a difficult fundraising environment for most founders for the last year or so.

Rohit Agarwal:
Are there any specific nuances across the different stages of a company's life cycle, whether they are seed versus, you know, A, B, or maybe more growth oriented, or is it pretty much same across the board?

Peter Walker:
It's down everywhere, but I think the nuances are really important. So the closer you are to IPO, the more difficult the fundraising market has been. Series D, Series E, Series F, you know, late stage companies, the fundraising has dried up most severely for those companies, whereas Series Seed or Pre-Seed or Series A, funding number of rounds and total capital invested is down, but it's not down nearly as much as it is in the late stage. So to give you a sense of it, I would say that, you know, seed funding on Carta is down something like 30 to 35% from peak, whereas series D funding is down something like 80% from peak. So it's a, it is a difficult picture. The further along you were in that journey when interest rates changed in 2022 and kind of the venture capital world really, really shifted.

Rohit Agarwal:
And we are also talking about big dollars because certainly series D, series E, those funding grounds are gigantic in nature.

Peter Walker:
massive, massive dollars. I think that's one of those hidden things that most people aren't considering when we talk about dry powder and look at all the capital that VCs have raised from LPs. Doesn't it have to come back into the system at some point? Maybe that's true. Maybe it isn't, but it doesn't all come to the early stage. That's for sure. Some of it has to go to these late stage rounds. You know, hundred million dollar rounds on Carta were pretty common. in 2021 and they're just incredibly rare now. So where is all that money going to go if late stage doesn't pop back up? So hopefully we knock on wood and there'll be more IPOs like Reddits that are coming soon. And maybe we get back to a little bit more of a healthy fundraising environment for the pre-IPO kind of companies.

Rohit Agarwal:
I'm curious, what was the steady eddy state before COVID? What were the funding, total funding that your customers were raising if you have a similar kind of benchmark?

Peter Walker:
Yeah, so it's, I mean, if you just look at on an annualized basis, it was something like $50 billion or so a year in 2019. The caveat there is Carta was serving far fewer customers at that point than we are now. So, you know, we have, again, 43,000 or so startups on the platform today in 2019. No, I'm maybe 15,000 startups, something like that. So much fewer, many fewer startups, but the funding was robust for those companies. Some people might actually say that the boom times was, was any time where there was essentially zero interest rates over the last decade or so startups have grown up in this one environment. And then since early 2022, when the interest rates changed, that's when the real shift happened. And now we're in this, you know, before and after sort of.

Rohit Agarwal:
Given the, literally the vast amount of data that you have, have you ever looked at what is the right sort of balance of funding that startups on your platform at any given point in time, let's say today, if you talk about these 43,000 startups, would really require in a year? I don't know, is it, as you said, they're right now around 66, 67 billion. It's 100 billion right sort of steady number, like, you know.

Peter Walker:
That's a good question. I don't know if there's a quote unquote right number. I think, you know, if you asked some venture capitalists what is the right level of funding, some of them probably privately in 2021 would have told you this is too much. You know, we know it's too much, but we're caught up in this market dynamic and we're just investing and supply and demand is off right now. I think we've maybe undershot it from the correction from the boom time. So perhaps something like 80 to 100 billion for those 40,000 startups makes sense. But the difficult, the confounding factor in that analysis is companies today are actively trying to use less capital per unit of revenue or per unit of headcount than they did before. So if a company can get to profitability with $5 million raised instead of $25 million raised, they're trying to at the moment. And that will change their capital needs moving forward. So it really is always a balance between what is the ongoing desire from entrepreneurs in terms of how much capital they think they need to raise to get to the outcomes that they wanna get to.

Rohit Agarwal:
Makes sense. Having the benefit of hindsight now, are there any leading indicators that you could foretell a funding winter? Or is it only after the fact that we would find out about such kind of dramatic events?

Peter Walker:
I think it's spoken about all the time, but perhaps even so is still underrated, the vast impact of interest rates on startup investing. So when money is cheap, risky assets like startups become more desirable. When money is dear or costly, and you can make 5% to 6% in a savings account, you really you see less risk taking behavior and there's really no more risky investment than early stage startups. That is the number one sort of harbinger of where the market might go most of the time. The other point that I'll make is that when you looked across the lines in terms of valuations and round funding, the late stage started to falter before the early stage did. So if you're looking at the canary in the coal mine, it was those late stage deals not happening was kind of the first inkling in maybe even late 2021 before the rest of the market had shifted, that something was going, something different was happening.

Rohit Agarwal:
Got it, makes sense. Do you have any data, maybe over the last, let's go beyond the COVID time, maybe over the last six years on how much money in aggregate went into ultimately the employee bank accounts, whether it was through a share buyback or an M&A or an IPO, some kind of an actual monetization event happened. And that then eventually led to kind of employees getting tangible cash in hand.

Peter Walker:
Yeah, that's a good question. I don't have an exact figure for you in terms of how much equity has actually become liquid across those various formats. As you can imagine, the periods at which equity becomes liquid, really just three, IPO, M&A, or secondary sale of some kind. Secondaries were very, very popular in 2021 as people were taking some money off the table, as valuations rose. They've become far less frequent in the last two years. But IPOs is really where most of the liquidity to an ecosystem comes back into play. And IPOs have been shut since really the beginning of 2023. We've only had one or two big ones since then, Klaviyo and Reddit are essentially the standard bearers at the moment. So the other dynamic within employee liquidity in particular is that companies are just staying private much, much longer than they used to. So it used to be that, you know, eight years, maybe 10 years, but now it's more like 12 or 14 years, in some cases, before companies go public. So early employees and startups are having to make decisions about holding that unrealized equity for quite a lot longer than they used to. And that reduces the amount of capital can be recycled back into the ecosystem through angel investing and all those kinds of things. It's a difficult kind of balance there. There's maybe more liquidity needs to happen at earlier points in the company journey if companies aren't gonna go public for a decade plus.

Rohit Agarwal:
Are you seeing, you know, one is of course, it takes longer for employees to get the liquidity. Two is of course the valuation market has just completely tanked, right? So thereby even the perceived value of that paper stock has come down dramatically. I'm sure that has some kind of a direct impact on how people think about their compensation on an yearly basis.

Peter Walker:
It definitely does. Yeah, I think you can see that most clearly in the exercise rate as a statistic. So background, of course, most startup employees across Carta and early stage startups receive ISOs, incentive stock options, when they join the company. Those incentive stock options come with two criteria in order to become real stock. One is the vesting times. You have to stay at the company for a specific number of years. And then, of course, you have to exercise that. that equity, you have to pay to take possession, essentially, of those shares. And a lot of employees, when they come up, when they leave the company, they have this 90-day period to choose whether or not they're gonna exercise that equity. Something like 75% of them right now are saying, no, thank you, and they're just letting the equity go back to the company. So they've had no impact from the company except for their salary and bonus. Those are the only two components of the compensation that actually became liquid. That's a bearish signal, obviously. That's a signal that startup employees are not valuing their equity nearly as dearly as they used to.

Rohit Agarwal:
That is a huge number. And someone could have worked any number of years, one, two, five, 10, if they have not exercised it so far and you are in this period, it does become pretty hard for you to go and make that happen. Wow.

Peter Walker:
It's such an acute moment for most startup employees. Obviously you can exercise it beforehand, but when you're working there, there's really no impetus to do so. So a lot of employees make that decision about exercise or not exercise in that 90 day window. And it can be a really, it can be a challenging financial moment. You have the cash on hand to exercise. That's when you have to make a bet on the future value of this company. Essentially you are acting as an investor. You are saying I would like to buy shares of this company. And it's a stressful moment.

Rohit Agarwal:
And even I would imagine some of the, you know, newer financing models that were upcoming over the last three, four, five years, even they perhaps are not as supportive because the companies that they would have gotten into, their valuations have tanked. So I'm sure, you know, these funding vehicles, their funding has sort of stopped or... certainly reduced to a dramatic extent.

Peter Walker:
Definitely. Yeah. There's a ripple effect from fundraising dries up, valuations decline. Maybe a company takes on a down round. And imagine you as an employee are at this company that just took on a down round and you're going to leave to go to another company. Do you exercise your equity at that point? The market signal was maybe this company isn't doing as well as we thought. It's just a really... It's a tricky moment for a lot of startup employees, let alone the idea that you were laid off from this company. And then you also have to make the decision about buying equity in the company that just laid you off, which is a whole other thing.

Rohit Agarwal:
I would imagine this is going to have an impact on the ESOP pool that people would not have to create as we go into the future, right? Because they would have a lot of these, a lot of this untapped sort of pool that will come back into the broader pool.

Peter Walker:
Yes, so that dynamic is an interesting one. There's certainly the hidden benefits cynically to founders of employees not exercising is that equity returns to the pool and it can be reissued to other employees, of course. We didn't see option pools really decline very much in the boom times or through 2023. They've remained fairly robust. One note for founders though, it is you know, sometimes you hear this common wisdom across startups that you should reserve 20% of your company equity for employees. That is true if you're close to, that's basically the median if you're close to a billion dollars. But as an early stage startup, you should actually probably reserve less, you know, 10% start at about 10%. And then as you fundraise, you can expand that pool with your investors over time. But you don't necessarily have to start at 20. That option pool. You know, a lot of the dynamics that we're seeing in the compensation market come from two things. Well, one, there's just a lot less hiring happening, so they're giving out less of that pool to new hires. And two, because they haven't fundraised in a while, most companies didn't expand the pool as they thought they would. So each individual employee is getting a little bit of a smaller slice. And that's... It's just, again, the compensation market is responsive to all the fundraising dynamics that are happening.

Rohit Agarwal:
Has the layoff versus hiring that kind of market tilted towards hiring or is it still more layoff heavy?

Peter Walker:
not has not tilted back towards hiring. So what remains to be seen what happens in the first half of this year, but as context in 2022, companies on Carta hired about half a million employees. And in 2023, they hired about 260,000. So cut in half. And actually, for the first time ever on our platform, at least more people left startups on Carta then join them in 2023. So that's layoffs plus people leaving by choice, but total departures was actually higher than total new hires. So that's a difficult job market in some ways.

Rohit Agarwal:
But in some ways these guys are then getting a job somewhere else. Presumably larger companies if they are leaving by choice.

Peter Walker:
You would hope so. Yeah. Yep. Yeah. I don't know whether or not they're, you know, they're leaving by choice for another startup or they're leaving by choice for big tech or they're out of tech entirely. It's tough for us to see that.

Rohit Agarwal:
You do have some compensation data as well, right? Are there any specific trends that you can share in terms of how that has been trending and are those trends really differ by maybe functions or levels of seniority across an organization?

Peter Walker:
Absolutely. So our compensation data again comes from our Carta total compensation product. And we help founders figure out what to pay employees and salary and equity. When you look at the trends across those two parts of compensation, we'll leave bonuses to one side for the moment. On the salary side, on average, the startup salary for a new employee is basically flat, maybe half a percent higher. than it was in November of 2022. It really hasn't changed very much. But of course, inflation has been going on over that time period. So startup salaries have not kept pace with inflation. But they also haven't dropped very much. They're basically flat. A little bit better changes there for engineers, especially AI ML engineers, as you might imagine, and for VPs and above, but in general, the picture is mostly the same across the board. The equity side is the really challenging part for a lot of employees these days. So according to our benchmarks, the employee that's hired in January of 2024 receives about 36% less equity than the employee that was hired in November of 2022. And that's not because the company's valuation is lower. That's the number of the literal number of shares is down about 36%. So that is a big, big change. It's more impactful for early managers as the biggest people that were hit, whereas VPs and above a little bit more insulated from that change. But the equity comp has been the biggest shift in startup compensation over the last year, year and a half.

Rohit Agarwal:
That's a bit counterintuitive to think about, right? Your valuations are down and you are giving less percentage points of your company in some ways. So thereby the total equity that you're giving is kind of have a double whammy in some ways. And it's a tough job market, right? So in some ways, maybe putting it another way, companies are just using the bargaining power that they have to be able to attract you know, best or the better of the talents at much cheaper equity compensations.

Peter Walker:
That's exactly it. You know, when 2021 was going on and you wanted to hire an engineer, it's likely that engineer had three, four, five offers and you would have to really compete on comp in order to bring them in. These days, you may be the only offer that they have. And so you don't need to go above your stated ranges. You don't need to be at the outlier ends of your comp ranges at all to get them in house. So it is an employer friendly hiring market at the moment.

Rohit Agarwal:
Got it. How should companies think about fundraising in the current market?

Peter Walker:
start earlier than you expect, for sure. If you think it's going to take six months, it's going to take longer than that. The general gist, you know, what a lot of founders are hearing from everyone in the ecosystem these days is, try to make every dollar last a lot longer than it would in if you had raised two years ago. So is there a way for you to get to profitability is the key question. It's not always possible for an early stage startup to be profitable and that's okay. You don't have to be profitable out of the box from day one. There's a lot of founders who are making the choice about Do I bootstrap a new company or do I try to take VC money? The advantage of bootstrapping obviously is you can grow at different rates and you kind of have more control but if you want VC money, you still need to grow pretty quickly So not all those growth rockets are going to be profitable from day one. But if you're fundraising generally speaking this is a you know This is broad level. The metrics that you are going, the traction that you're going to need to have to show VCs in order to raise, say, a series A round is probably anywhere from two to three times more than you would have had to show two years ago. So more ARR, more customers, higher retention rates, more growth, et cetera. It's just, it's a very competitive fundraising market and VCs are being much more choosy about who they choose to invest in.

Rohit Agarwal:
Do you analyze or track mortality rates of startups as well?

Peter Walker:
We do track startup shutdowns. I wouldn't phrase it as a mortality rate or a failure rate. The difficulty with getting a failure rate is our denominator is always changing. So more companies are joining Carta, but even more than that, a large portion of the database that we're working with is with pre-seed startups, they fail at higher rates than startups in series C, series D, et cetera. So we don't produce one failure rate across startups. What we can say is that more companies are shutting down and shut down in 2023 than in any year on Carta. And the worst month for company shutdowns in Carta history was January of 2024. So it definitely is rising. Whether you express it as a rate or just absolute numbers, more startups are shutting down lately.

Rohit Agarwal:
And do you see that number plateauing, or do you see there's still more pain in the ecosystem that we will run through?

Peter Walker:
Unfortunately, my prediction is that number will continue to increase at least for the first half of this year. There was a lot of companies that took on bridge or extension financing last year, tried to get any money they could in the door to keep things going. And my sense is that 2024 will be a year where some of those bridges and extensions sort of stop and... VC spend more time funding new companies instead of trying to prop up the ones that they've already funded. That's a bit of a prediction, but I think we will see more shutdowns through H124 than we've seen in a long time.

Rohit Agarwal:
Got it. Peter, this has been super interesting to dig into. Let's move tracks a little bit. Let's learn a little bit more about you again. So tell us, how do you define success?

Peter Walker:
The way that we talk about it internally is the tagline is make Carta data ubiquitous. So my goal is to have any conversation that's between a founder and an investor or a group of founders on a WhatsApp thread, for instance. We want Carta data to be part of that conversation. Interestingly, my success metrics are not really driven by net new leads or new customers, although those obviously... We track those and those are great outcomes. It's much earlier than that. It's about building affinity and love for Carta in the ecosystem. And that allows me, if I'm not being held to a specific lead number, for instance, it allows me to act in different ways and to be more generous with the things that we're doing. So the success for me is making Carta the single source of truth for startup data.

Rohit Agarwal:
Very cool. What is your approach to leadership?

Peter Walker:
Well, I've managed a number of teams in my career. At Carta currently I'm a team of one, although I'm hiring, or I just made a hire, knock on wood. I'm excited for him to start very soon. One of the things, you know, I'll speak a moment about leadership from my CMO, Jane Alexander, who just left, who brought me into Carta. One of the things that I learned from her that I think... more leaders, especially in bigger organizations, can take from smaller ones is that energy is contagious. So at a small startup, because there's so few of you and you're working together so closely, you can very clearly see the energy, the activity, the excitement when it comes from the founder or the CEO and it kind of ripples out to the organization. But I think sometimes leaders lose that as they get to bigger and bigger companies. And they don't realize that a lot of the energy and excitement amongst a team comes from their leader. And so if you can show up every day excited and energetic about the problems that you get to solve, it can act as this sort of external motivating factor to a lot of people. So I think that was one of the biggest things I learned from Jane, is that energy is really important.

Rohit Agarwal:
Makes a lot of sense. If you can change one thing about your career, what would that be?

Peter Walker:
That's a wonderful question.
I think, if I'm being honest, I think I would move to San Francisco earlier than I did.
I had a wonderful experience working for startups in DC and I learned a lot, but there is something different about... I'm assuming it's the same as if you're an actor living in Hollywood or if you're in finance living in New York. There's something different about constantly being surrounded by people who are interested in the same sort of problems that you are. So I've found San Francisco to be... If you're in startups, there's really no place like San Francisco.

Rohit Agarwal:
No doubt. What advice would you have for emerging professionals who aspire to be leaders?

Peter Walker:
I think young people that are just getting started, leadership in your role doesn't have to come along with a title. So you can have influence without having authority. And that is something that kind of builds the foundation for leadership later on in formal ways. The best way to do that, the easiest way to stand out at a company is to do excellent work at your core job. And once it's excellent, just start asking to be put on things beyond that. And then people will look at you as someone who is reliable, can get things done. But there's no need for you to have a title in order to influence decisions and to be a leader amongst your peers. So don't wait for the promotion to get started on being a leader, be a leader now, you know, offer advice, be a listener to your fellow colleagues, et cetera. You can, you can lead from a peer level before you ever get to the titles that you.

Rohit Agarwal:
That's awesome. Let's move to our final round, the lightning round. Should be quite fun. All it takes is I'm going to ask you some simple questions, and I need immediate responses. OK, let's start with some warm up. Sweet or Savory?

Peter Walker:
Savory.

Rohit Agarwal:
Books or Podcasts.

Peter Walker:
Podcast.

Rohit Agarwal:
Thinker or Doer.

Peter Walker:
Doer

Rohit Agarwal:
Introvert or Extrovert.

Peter Walker:
Extrovert.

Rohit Agarwal:
Scotch or whiskey.

Peter Walker:
Scotch.

Rohit Agarwal:
How does someone impress you?

Peter Walker:
Being incredibly consistent and reliable.

Rohit Agarwal:
If not into analytics or insights, what would you be?

Peter Walker:
Maybe an improv actor.

Rohit Agarwal:
Uh-huh, interesting. If you can do what you do at any other company, which company would you choose and buy?

Peter Walker:
Spotify because I think that they have an unbelievable data set. And I think that their wrapped campaign is the classic textbook example of building insights that people care about.

Rohit Agarwal:
All right, cool. What is your ideal place to retire?

Peter Walker:
Santa Barbara, probably, but maybe home to Denver. Those would be the two options.

Rohit Agarwal:
Okay? If you could teleport yourself right now, anywhere, where would you go?

Peter Walker:
Tokyo because I have had it on my list to go to Japan for so many years and every time we try to plan a trip something goes wrong. So it would be great to just go, finally.

Rohit Agarwal:
All right. It seems like my next question was, what is number one item on your bucket list? I would imagine it's Tokyo. Cool. If you could un-invent something, what would it be?

Peter Walker:
That's it. That's it, yeah, for sure.

Peter Walker:
Uninvent something, probably Twitter. I'm sort of addicted to it, and I think it's probably bad for my mental health, but I love it, so maybe not. It'll be an idea.

Rohit Agarwal:
Who is your role model personally or professionally?

Peter Walker:
Lots of role models. I think, I mean, Jane, my CMO, that I, I'm sorry, has been a really strong influence and role model on me. And I also really deeply respect my little brother, who is just finishing up his residency as a doctor and is gonna be a general surgeon. And I compare, sometimes compare my day-to-day life to his day-to-day life. And I realize what I'm doing is not that hard. And I should be probably pretty grateful.

Rohit Agarwal:
makes a lot of sense. Penultimate question. One thing that can make you 10 times more productive.

Peter Walker:
Coffee helps for sure, but also apps that kill my internet access. So I have to do analysis without having, you know, I can just be in the tableau or whatever the workbook is, you know, cutting down on those digital distractions has been really helpful.

Rohit Agarwal:
The last one, describe yourself in three words.

Peter Walker:
Energetic, Curious, Nerdy.

Rohit Agarwal:
Very cool. Well, Peter, this has been a tremendous show. Thank you so much for sharing all the insights and taking us through this beautiful journey. Appreciate it.

Peter Walker:
Absolutely. Yeah, this has been really fun, Rohit. Let's do it again.

Rohit Agarwal:
Certainly. Thank you.

more