SFG 33: Ryan Glasgow on AI-powered product feedback

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In this episode of the Startup Field Guide podcast, Sandhya Hegde chats with Ryan Glasgow, CEO and founder of Sprig, an AI powered product feedback platform that helps teams run in-product surveys and session replays with AI native analysis to help them build better products.
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Be sure to check out more Startup Field Guide Podcast episodes on Spotify, Apple, and Youtube. Hosted by Unusual Ventures General Partner Sandhya Hegde (former EVP at Amplitude), the SFG podcast uncovers how the top unicorn founders of today really found product-market fit.

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If you are interested in learning more about some of the themes and ideas in this episode, please check out the Unusual Ventures Field Guides on identifying initial customers, working with design partners, and validating your early product hypothesis.

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Episode transcript

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Sprig's origin story

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Sandhya Hegde
Sprig is an AI powered product feedback platform. It helps teams run in-product surveys and session replays with AI native analysis to help them build better products. Last valued at $330M, Sprig has hundreds of the largest and fastest growing tech companies as customers, including Notion, Figma, PayPal, Webflow, and Dropbox. Joining us today is Ryan Glasgow, the CEO and founder of Sprig. Welcome to the field guide, Ryan.

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Ryan Glasgow

I'm excited to be here and excited to dig in today.

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Sandhya Hegde

Me too. First of all, congrats on surviving four years as a startup founder. I feel like it's been the most roller coaster ride of a four years in the world that any founder has had to go through. Going back to 2019, could you kick us off by just sharing the origin story of Sprig? How would you describe your founder moment of, “Yes, I need to start a company, I think this is what I'll work on.” Take us back.

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Ryan Glasgow
Yeah, it starts a little bit before 2019, so my background before Sprig has always been in product management. I joined four companies pre-product market fit, including companies like Extrabux and Vurb. And Extrabucks was acquired by Rakuten and Vurb was acquired by Snapchat, and Livefyre was acquired by Adobe. And when we're helping find Product Market Fit for those early companies, I was constantly looking at my analytics data. At the time it was Mixpanel, this was pre Amplitude, and we're looking at the Mixpanel data. And I was constantly having these questions about our users. I was emailing them little questions: Hey, you used our product, you didn't come back. Hey, you've come back five times. What's working or not working about our product? And that was so paramount and critical to our journey of finding product-market fit, is just bear hugging every single user that we got, usually 20 to 50 of these users pre launch MVP states of these products. And when I went on to Weebly, it was post-product-market fit. But I was still the first product manager and so I came in, really helped them grow and in their journey of hyperscale, in their growth journey to run 50 million accounts when I left and even from the first few months there, I quickly realized that old technique that I was using of shooting out short emails. By this time there were tens and thousands, hundreds of thousands of people, and there was a moment where we were really looking to narrow our focus at Weebly on e-commerce sellers and we got really specific and hyper targeted about some of the questions that we had for these sellers. And we looked at our conversion data and we saw the drop off with sellers, and we wanted to understand that ‘why’ question. Like many product teams today we have incredible granularity, thanks to companies like Amplitude —  I know you're there in a past life — and companies like Mixpanel, of exactly what our users are doing with our products, we have all this data about how much they're paying us and we have all these dashboards around the revenue data and it all goes into business intelligence tools, but it was really the ‘why’ questions that I was missing. And I expected more sophisticated tooling at a high growth company like Weebly. I assumed that there was something very focused on these high growth and at scale tech companies to understand the user sentiment, user experience data, just like we had for the behavioral analytical data and the revenue data. It was such a critical part of our journey scaling Weebly to understand our users. I ended up building a very homegrown, rudimentary in-product survey solution to understand the key questions around how to improve onboarding conversion, or how to reduce churn, or how to grow the high value segments of the business. I took some time off after the acquisition to Square, and I was traveling and I was thinking about some different things to work on. And the one that I kept coming back to was just not having the sophisticated tooling and the robust tooling that I was looking for as a product manager and the other product managers at Weebly are also looking for of deeply understanding that user experience data at scale. And so the founding premise from the very beginning at Sprig was how to really empower and support product teams quickly growing at scale tech companies, how they can systematically and scalably understand their user experience post-product-market fit. And I really took those five journeys of doing something handling those first four experiences to wanting to do something in a more automated, scalable fashion and not seeing that tooling. And Sprig ended up really being a culmination of my career across those five startup experiences.

The evolution of user insight platforms
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Sandhya Hegde

Nice. I'm curious. Obviously as investors, when we look at problems like this, often the question we try to answer is why now? Right? Okay, this is not a new problem. It's been a problem for a while in this form. And there are companies that do surveys, do in-app experiences, right? Maybe not focused on feedback. The tech kind of exists and the market kind of exists in some other form. Like why has no one solved this before? I'm curious, you must have asked that question as soon as you were at Weebly. Given like, Weebly is a bigger company, has a budget. In hindsight, now having worked on solving this problem, why do you think no one had taken this approach to it before?

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Ryan Glasgow

When you look at really the growth of the product team budget, we all know engineering and marketing and sales, very large budgets on the P&L statement, and those have typically been areas that investors have invested in. They look at companies like Salesforce and now Datadog and Atlassian, and they're under those three budgets. And ten years ago, it was very difficult for an investor to be excited about a product management or user research tool. And I think that Mixpanel and Amplitude actually helped grow that budget and helped really expand that addressable market and helped pique the appetite for investors to realize that this could be 100 million ARR plus business. It helped justify, I think, that product management should have a larger budget than it did. I think that was one area, the budget really started to grow for product teams because of the tools, or really proving that a larger budget had an outsized impact on the success of the business. No one's going to argue now with having Amplitude or Mixpanel as a part of a product team's budget. It's going to be a required tool of some sorts. The other one is that ten years ago, Amplitude and Mixpanel were just getting started and those were the first product analytics solutions. And what dawned on me about having so many questions about the analytical data only emerged until we had the analytical data. And so it was not my first year at Weebly, or even second year at Weebly, that we're able to get incredibly sophisticated tooling and data and dashboards around our behavioral data and exactly what users were doing with our product. And once we had that data in place, we had those dashboards in place, and I can go on Looker and do pivot tables about cohort retention that then introduced the questions that Sprig solves. And so it's almost like a second order type of data set where you look at your churn data, you drill in and see yoga studios are churning at a really high level. How do I figure out why these yoga studios are churning at a high level? That introduced the need and the problem that Sprig now introduced. So when the analytics solutions really started to mature and become more ubiquitous, that's where I think the experience data started to become much more critical because those ‘why’ questions started to emerge from that data.

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Sandhya Hegde

I guess they've always been critical, but now they're also like, which ‘why’ questions to prioritize, which are the more critical why questions? Because you can tie the critical ‘why’ questions to the critical metrics really clearly and the ROI of being able to answer the ‘why’ questions is starting to become well established. Right? Okay, yes, the product strategy is really driving the revenue strategy. It's not separate. I think that makes a lot of sense. And I think your point about where in the maturity curve this is also makes a ton of sense.

So, great, you have conviction, you have this insight, you are starting a company, you're a solo founder. What were the next few weeks and months like? How did you go about building your early team, putting your pitch together, what was easy and what was hard?

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Ryan Glasgow

Yeah, it was definitely, 2019 was very different than raising around right now and getting started and the capital was not nearly as flowing even I think in AI this year as it was then. And so I raised Angel Round from friends and family and as a solo founder, actually raised around close to a million to get started and then hired full time. so I hired some full time folks and the first person, I really broke the problem up into two different areas. I had a pretty big breakthrough starting Sprig and this is a book and concept that I recommend for anyone who's looking to really identify and start a company is called Outcome Driven Innovation. The entire premise of the concept or the book by Tony Ulwick so you can look it up and read the book and it's very formative in starting Sprig is that you want to talk to as many people as you can. And if you look at the Lenny Richisky series, you often get 100 design partners and you talk to 100 different potential customers, but what's interesting is that you look at the outcomes of what they're trying to solve and you look at the outcomes they're looking to solve where they're unsatisfied with the outcome of how the tool is solving the outcome today. And you look for high important, and so you want to solve outcomes that are really important but also one they're unsatisfied with. And at Sprig, what I realized, and to your point, there are a lot of tools out there, but there were no tools that was solving, collecting at scale, very large scale, thousands, tens of thousands of contextual survey responses, but also analyzing that survey data at a very large scale. And so the first hire to join me was a head of AI and he's still here as our AI architect leading our AI vision. And I broke the problem up into scalable survey data collection and scalable survey data analysis into two separate jobs to be done. I hired him to solve the second one, AI analysis at scale. I hired another engineer to solve the first one of collecting the data at scale. And those two were each solving the different problems with that precede round. And then we started to build around those two. But it was very much looking at what the user researchers are doing at Weebly of manually collecting the data with some very basic tooling, manually analyzing the data and seeing can we actually automate this lower level type of activity to free up these product teams from doing this very laborious manual data collection and data analysis. So answer your question head of AI and then a full stack engineer.

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Ryan Glasgow on validating early hypotheses

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Sandhya Hegde

Makes sense. Now you obviously had a product vision that was deeply rooted in your own personal experience. How did you go about thinking through, okay, what is it you want to validate? The early product, was it largely based on your personal experience? Or did you still try to explore maybe different types of product leaders? Did you have any hypotheses you still needed to test before you built your minimum viable product? And if so, what were some of those questions that were on your mind?

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Ryan Glasgow
We did get some traction with small startups, so we had quite a few companies paying us small amounts of money. I was sending cold emails to Y Combinator companies for example, of various sizes. We also had some, what we call mid-market tech companies, so Codecademy was one of our first customers, and we also had some design partners that were what we call enterprise tech. And so Hotwire, Square, Robinhood all pre-launch. And what I did want to hone in was validate that assumption around that outcome driven innovation process is that the unmet need in the market and the problem that is not solved right now is actually around the high growth and at scale tech companies. The trend that I saw is that the larger the company and the larger the user base, the more they're interested in Sprig. And so someone like Hotwire, who I had no connection to, spent close to six months with for an hour every week helping shape and guide and build the Sprig product. Someone at the head of research at Robinhood invited me to the Robin Hood Menlo Park office and packed the room with 30 leaders across the entire product of analytics and research and design and the head of product and said, I think this is interesting. I think this is something that we should consider for our growth at Robinhood. This experience data can be critical for us to build a world class product experience. And when I noticed that, this contrast of these larger companies and people that I didn't know saying, let's set up another time next week, let's keep the conversation going. Here's my feedback, and I want to shape this product with you. It's not product-market fit, but you start to get a pull, and you get a pull from these businesses where the SMBs there was definitely interest, but because of the alternatives, because they can talk to customers one on one, candidly, there wasn't as strong of a need. And to your point, there are other solutions of the market type form or Google surveys that are low cost or free that might be an adequate solution for an early stage startup.

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Sandhya Hegde

They have less product area and fewer customers. Both vectors magnify the size of the problem itself. That makes a lot of sense.

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I'm curious, were there any surprises for you? You went into this kind of having a lot of clarity on having solved the problem yourself. Were there any surprises that were unexpected as you spent time with maybe even bigger companies than you had worked at, like Robinhood.

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Ryan Glasgow
In terms of surprises, I was going back to the last point of just their willingness to commit their time and started to realize that for a business, a person's time is more important than their money. And as a consumer and someone who primarily had worked in the consumer space and working with small businesses at Weebly, someone would gladly spend 8 hours building a website from scratch and not pay someone $300 to build that website for them.

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But if you look at these larger organizations, it's candidly not their money. It's a budget that they have, but they're also incredibly busy people, so for those that are looking to sell to mid-market enterprise and larger companies, I think SMB to an extent. But the signal to look for is that the people who are willing to continue to spend that time with you. I think the willingness to pay, as you probably saw at Amplitude, will easily grow and change if you're solving a real problem. But the leading indicator is someone is willing to have that next call with you, that next meeting, and you don't have a personal connection with them. That last part is really critical. Our friends and family and colleagues will spend all the time in the world helping us out, but that's not any indicator and potentially negative indicator that we're solving a real problem in the world.

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Sandhya Hegde
Makes sense. And what were parts of the pitch that you faced more concerns or questions or skepticism around? Like the pain was really clear. You have a lot of validation around the pain. They are giving you a very precious time bringing more people into the room. Perfect, right? What about the feedback on the solution that you were building?

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Ryan Glasgow
Going back to the Hotwire example, the main challenge I was facing is that we had this incredible pull from these more mature companies. But we were an early stage startup with, at the time, four or five people and at the time, just under a million raised. And it was actually how do we cross that bridge? Do we perhaps change our ICP down market to help and then move up market in the future? Which, going back to what we discussed earlier, there is more competition down market and so how much progress can you make? Can that be a distraction to your roadmap? And so I think it was getting not only customers to have that patience to help shape that product until they were willing to make that investment and try Sprig, but also getting and finding investors who were also willing to have that patience and say, “We want to be committed to your vision and your founding premise and founding thesis for Sprig.” So, very fortunate to bring on Bill Trenchard from First Round Capital, who led our seed round 2019, and also someone who had worked with companies like Looker to their exit to Google, he was a seed investor there, so he had seen that path and that journey.

I think that's why we both felt like it'd be a really good investor-founder fit because I wanted someone who had a journey similar to Looker and he had already seen and I think just they're about to be acquired, doing very well, or had just recently been acquired and had already seen that strong success and was willing to make that bet again.

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Sandhya Hegde
Makes sense. Could you walk us through the timeline for when you went from prototyping to having, okay, this could work in production for a hot while. How long did it take you to get to that? Okay, this product could actually be deployed for your ideal customer profile, as opposed to the small startups that are not great customers, but give you love when you most need it.

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Ryan Glasgow
So the first customer that we did go live with, and it was critical that I didn't have any personal connections to the people that we worked with, was Square. But again, no one that I had any connection with that was buying and paying us for the pilot, which I want to emphasize is critical for anyone who's not just selling to people that you've worked with and have a personal connection to. And they're willing to install Sprig in the product offering and run some surveys. And they did a paid pilot with us, and they had already spent several months up into the paid pilot. We got the paid pilot. We ran a paid pilot. It was phenomenally successful. And they're really one of the first true target companies in that mid-market enterprise. P that said, we'll try this out. We'll do a paid pilot, we'll see how it goes. And because our goal was to build a more sophisticated at scale product offering for these more sophisticated businesses, we had to look at what's the smallest it's almost the MVP of what cannot be done manually ourselves, right? And so the only piece that we couldn't do ourselves is that SDK that had to go into our customers' product. But designing the surveys, the questions, adding the questions, configuring all the questions, the dashboard itself, the AI analysis, 90% of the product offering or how it appeared to them was all manual. We presented all the information in slide decks, we did all the analysis manually. We built all the surveys directly in the database. There's no way to build those in a self-serve manner.

When you're building for these larger companies, you have to look at what's the MVP that we can't do ourselves? And we just focus on that SDK and the ability to control the SDK manually. I think the biggest learning lesson there, I think also really relevant for founders, is that doing things that — everyone knows the rule of doing things that don't scale in terms of sales and marketing and hiring and other processes, but also the more that you can do things that don't scale with your product is such an amazing learning opportunity that helped shape our v1 because we were doing so much else manually and we knew exactly what to build when it came time. We had the resources, the conviction, the capital, the headcount to go build but it was so clear on that product spec for the areas that we were doing ourselves for months and sometimes up to a year.

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Sandhya Hegde
And how old was Sprig when you did your paid pilot with Square?

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Ryan Glasgow
The pilot with Square was — we signed the official contract right at our seed round in the fall of 2019, yeah.

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Sandhya Hegde

Got it. And you were UserLeap at the time.

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Ryan Glasgow

We were UserLeap at the time and so when I started the company, you go to your domain provider, you type in — I was looking at combining two words which is the most common way to get those domain names and it was available and started with UserLeap. So that was our first name.

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Ryan Glasgow on founder selling

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Sandhya Hegde
And maybe it's a good point to transition to adding more customers, right? Like you have a very clear product spec, you are able to work with customers as big as Square and these larger design partners. How and when did you make the transition to okay, I'm now going to focus a little less on the product development process and really go prospecting? You closed all of the early customers yourself. What was your approach as a first time seller really? And how did you teach yourself how to go about doing founder selling?

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Ryan Glasgow
So I'd never worked at a company that had a salesperson and so it was starting from zero on learning sales. I was fortunate that I come from a lineage of salespeople and so I'd like to think there's a little bit of a head start, but I'd never actually seen it myself at a company that I worked at being in the B to C and B to SMB space. We were fortunate to have First Round that was really helping build our pipeline. And what they were doing is they had someone at the firm that was providing intros to the First Round community network. One of those was Codecademy for example and Dan, the product really connected with Dan Layfield, who’s our director of Growth at the time. And so if you have an investor who can help make those connections, that's a great way. Those investor ‘asks’ at the end of your investor update, making sure you're getting those warm intros to people in the investor network can go a long way. And if that's not something that is a possibility, I do think that either doing the SDR efforts yourself or having an SDR who can automate that outbound email process on your behalf so you can give them a script, you can give them your LinkedIn login, you can give them an ICP. And the goal that you want to look for is, can you get three to five meetings per week? And each meeting is a learning opportunity. Now we have Gong, you can record the calls. Back then, we didn't have that. And so it was taking notes and looking at the patterns at the end of every week of what was working and not working. And so the first thing was just getting those meetings on the calendar, different ways to do that. And then the sales process and the sales book, that was super impactful for me. And I'm a reader. We'll get to the resources, I think, at the end, and I'll share some resources and books. But the sales book, that was most helpful for me, and it's quite dated, so if anyone reads it, it might feel a little dated. But the concepts are very helpful. And it's called you can't teach a kid to ride a bike at a seminar. A bit of a mouthful, but you can't teach a kid to ride a bike at a seminar. And it's by Sandler, and so he is considered one of the classic minds in the sales field. And it really helped break down sales into a process of decisions. And one of the key lessons that I learned in sales that pass on to any founder listening is that every meeting is a decision. And you want to start every meeting saying, this is the decision we hope to make at the end of the meeting. And getting to a signed contract is if it's SMB, it could be two to five meetings and two to five. Yeses. For an enterprise contract, it could be 20 to 30, potentially 15. Yeses. But just focus on each meeting as: start the first call, looking to understand whether we should book a full demo with other people at your team. End the call. Hey, we just wrapped up. Want to check in as the question that we started with. Based on what I'm hearing from you, I would recommend we schedule that wider demo with your team and then at the demo, starting with that prompt, ending that meeting with whatever that decision was. And if you can break down your sales process into a set of repeatable decisions for each meeting. It really took off the stress for me because I knew exactly where I stood with each product prospect, but it also broke down a lot of the stress for the prospect because they understood exactly where they were and what decision they had to make during that call.

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Why Sprig bet on generative AI

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Sandhya Hegde
Makes sense. I love how methodical you are. I think one of the qualities you really need as a founder is the ability to learn, because every six months you need to reinvent yourself as the company leader, as your company is growing fast, and that's the best case scenario is that you're painfully evolving with your company because it needs you to evolve. And you're clearly a learner. And I love how you separated out even the methodology for how you validate your product idea versus how you build pipeline. And we actually also work very closely with the founders we invest in to help them build pipeline, but we love to say, “Before you have clarity on what to build, cold outreach is actually your best friend.” Because if we do warm introductions before you have clarity on what to build, you won't get the brutal feedback you need. You'll get a lot of nice feedback, people who don't want to hurt your feelings, people who don't want to weaken their relationship with the VC who invested in you and introduced you. So you get sort of mixed feedback, which is much worse than a clear ‘no’. Until you know what to build, I think cold outreach is your best friend. If your messaging isn't working immediately, if you're not able to get time with strangers immediately that you're not solving a problem they care about — that's the wrong time to ask for warm intros. The right time is, “Okay, we have a very clear thesis,” you're building in this direction, “now, I just need to meet a lot of people who fit this profile,” and that's when you use your network. You lean on your investors, and it's very important to get the timing right when you shift into that mode. I love that you already knew that coming in.

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And I think maybe switching gears a little bit to the fact that you had an early thesis around AI. So you started the company, this was pre-GPT 3.5, which I think in 2020 was a huge turning point in the world of what you can do with unstructured data, especially when it comes to language. I'm curious, how did you think about your AI strategy before 2020 when you started the company versus once the LLM out of the box APIs were available? And potentially the cost of developing an AI native product might look extremely different when you have industry grade APIs and models available. I'm curious what that switch looked like for you.

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Ryan Glasgow

 It was certainly a very early bet. At the time, the largest companies in our category — Qualtrics, Medallia — they were using word clouds and it had to be a literal string matching of, I say price and you say price, and we'll do a bubble on the screen for price, but I say cost and you say price and you're in the cost category and someone else is in the price category. So we were very early to what I think is now just emerging as something that's becoming more common and going back to the outcome generation innovation framework around the outcomes that were important to the high growth and at scale companies, one of the really critical outcomes was the ability to analyze that data at scale. And the other thing that validated that is that when we were manually doing, we only built the SDK to start 5% of the product. We only just focused all of our efforts there. And then when Kevin, head of AI, I wanted to validate before he joined that there is value in grouping responses into themes, even if there are no overlapping words or phrases. And so you say it's too expensive, and you say, I say I can't afford this price. Grouping those into the same theme is something that has never been done before.

When we were building out those decks for companies like Square, they found incredible value in not just the feedback and the data that was collected from the surveys, but quantifying the data and saying 12% of the people in this survey cited price as a concern. 33% of people said adding a product is very difficult or cumbersome. And it was really in the analytics around their survey data where we had the big breakthroughs with those early pilot customers. When Kevin came on board, it was just, this hasn't been done before and you're the first one who's going to have to do it. We're this seed stage company and we're going to have to see what we can do. So we started with the open source Google models, at the time it was Bert, and we started to build our own in-house tooling. We tested different human loop processes around how to really check the data and see whether the AI was accurate or not. And we started probably around 50% efficacy. And so there's a little bit of work on our research team behind the scenes and the dashboard reviewing and checking and tweaking all the AI analysis. But there was so much skepticism at the time around AI is that we actually had to guarantee our customers that we will review every single response that was collected by an expert user research team. And we had to build a whole set of administrative capabilities behind the scenes for researchers who we brought on to review and check all the data to review and check all the data very fast and ways to automate and just multi-select and quickly move and break themes up and combine themes very quickly. And so to your point, it was a fairly large investment, but it was something that allowed us to bring in these customers and something that was very unique compared to the other analysis technologies available. For us to really solve the, complete the vision, at least paint the picture of what we want to do long term, we felt it was really critical to use AI in that way that had never been done before.

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How Sprig's product has evolved since the launch of GPT 4

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Sandhya Hegde
And how has that changed? How has it been pre and post chat GPT launching?

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Ryan Glasgow
It's exciting for us because our goal at Sprig is to always be at the forefront of what you can do with AI in the field of product experience and more broadly, sentiment and how people perceive product experiences. At the very beginning, we were considered the leader with the text analysis that we had done. but there were so many other things that we wanted to do, but these models could only do very specific tasks with huge amounts of training data. And so when these new models started to emerge, we actually at the beginning of this year, switched over to GPT 4, so we're now using the learnings we had for the past three years. We migrated GPT 4. We're still reviewing a little bit, but it's more ad hoc and more passively. But what's exciting for us is that it's all — nearly all — real time, very in the moment. It's far more accurate. We can get descriptions and summaries of the data, but the biggest thing for us is it's opened up the possibilities of what you can do with AI. Just a few months ago, we launched the ability to where the entire survey data is ingested into GPT 4 and you can actually ask questions about your data, correlations, trends, and so the possibilities, all the things that we had to put on the shelf in 2019, 2020, 2021, 2022, we're now immediately jumping on. We're immediately implementing or immediately executing on. We see it very much as this race implementing these different ideas that we've always wanted to do, that we always wanted to expand beyond that original version of the AI implementation.

‍Sandhya Hegde
Got it, I would assume your buyers are a lot less skeptical than they were maybe as of September 2022 versus now. Very different right now, seeing is believing. Awesome.

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Ryan Glasgow's evolution as a CEO

Sandhya Hegde
I'm curious, how have you approached learning and growing as a CEO? Especially, I think, since you're clearly being so intentional about it and you are a solo founder, I think it's kudos, first of all, and you have gone through a very challenging four years for any startup founder. Right? There's been a pandemic. There's a huge market bull run, followed by an immediate big crash and software budgets getting slashed everywhere. And now there's like World War Three on the horizon. How have you approached growing as a CEO and also learning what is it that your team needs to feel a sense of stability and momentum over time?

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Ryan Glasgow 

I've always took it. And a lot of people ask, as a solo founder, how do you do it emotionally? How do you do it mentally? A lot of people tell me I could never do it as a solo founder. And I think for me, it's just taking it week by week, month by month, and just focusing on what's in front of you. I'll enjoy that moment when I can think long term and think about next year, next quarter. But I think day to day it's just looking at what you want to tackle that day, what you want to tackle tomorrow and next week, and really look at it as, from looking at hindsight, probably three different evolutions. I think the first one was really as a manager. And so for any founder who has extensive management experience, you're off to a great start. I had very little management experience before starting Sprig, and so I had to learn how to manage at first a team of four and a team of ten. And then it was like maybe twelve direct reports at one time in the early days. And then you start to get to a certain size where you can't manage everybody and you have managers and you have managers and that's where at now. And you have to really grow as a leader and you have to think about how to inspire people and motivate people. And as a manager, you're managing managers who are managing other people. And so you have to think about how to work through managers. And so it's more advanced in the management concepts. And then I think more recently in the past twelve months, it has been about learning about how to be a CEO and even thinking about some of the, even the racism that we experienced that was very prevalent a couple of years ago. That's a moment as a CEO where you have to step up, you have to provide that leadership. When we had to look at a very volatile past twelve months as a company, we came out of a period and someone on my team said, hey, you really stepped up leadership of the capital L. The team needed a CEO to really be that strong voice, that strong person in the room. And hit me that, oh, that got through that. And the team really respected that and it stepped in as a CEO and.

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Sandhya Hegde

That it made a difference. For you to even just have a voice, even if these are like massive systemic issues, I think it's easy to say we are not going to be able to solve the root problem. So let's just not talk about it. That then creates this vacuum which gets filled with anxiety.

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Ryan Glasgow
Right? Exactly. And so I think anyone who's running a company right now over the past twelve months is probably where you learn the most as a manager or leader or CEO, whatever position you're in. And so it's certainly been a moment where I've learned to embrace the constraints of efficiency, embrace the challenges that we're all enduring right now and just some of the resources just to break it down and maybe this is helpful for others is the two again. I read a lot of books and I'll just cherry pick the few that have been most impactful is the author. Jim Collins is a Stanford professor and he deeply studies what a successful company the traits of successful companies over a hundred year periods, very long periods of time, and looks at periods of hypergrowth versus comparison companies that don't do as well. And his books have probably had the biggest impact on my growth as a CEO. And the two in particular are Beyond Entrepreneurship 2.0 and Good to Great. But he has a whole series of other books as well and he really unpacks something like a vision and how to craft a mission statement and how to craft goals and how to inspire and motivate people. And so his series is one that I've read several times to really deeply understand how to build an iconic company like Walmart or IBM or he talks a lot about Sony, for example, and what their formative years or periods of hypergrowth look like. And so that's definitely two books that I recommend for any entrepreneur and founder. And even back to the earliest days, the values, for example, and digging into Nordstrom, they have such strong value system that someone who doesn't fit their values often will quit within three months and they see that as a positive sign of having a strong culture. And you start to learn how to build a distinct culture that it's almost like a new hire is like an organ. Now, are they accepted or are they rejected and really leaning into that and realizing not everyone is going to be a fit for your culture. And that goes back to just some of the CEO learnings that I've had of developing a culture, developing people, and most recently has been really understanding and digging into the learnings of Frank Slootman. So the legendary growth stage CEO in Silicon Valley with Data domain ServiceNow and now Snowflake and his focus on execution has been so interesting for me to follow. I consider myself more of a Michael Porter strategy, strategic memo type person in the early years of Sprig and pre Sprig, but I've really shifted over the past one to two years, and very recently because of the frank Slootman's writings of focusing so much on execution and seeing my role as CEO, as really chief execution officer. And how can we move faster? How can we narrow focus? How can we amp it up here at sprig?

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Sandhya Hegde

Awesome. What an absolutely wonderful note to end on. Ryan, thank you so much for joining us. This was really valuable and I love what an amazing journey you have taken Sprig on. Kudos on all the progress and I'm sure a lot of listeners will be trying Sprig as well. Thank you so much for joining us today.

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