The Exchanges

Q The teams that close the customers are off the deal when it closes?

A They keep it for a year, year and a half. We will continue to evolve that, but the set of people that get new accounts Are completely distinct from the set of people that are growing existing accounts. Honestly, it's a different skill. The person that is managing an account that's spending fifty million dollars a year, that person's a manager. They have 20 people. This is a big complicated beast where you have to learn. Often these folks, our folks know the architecture of their customer often better than the customer because they talk to everybody within the company. They know what the pain points are. They make business proposals for, hey, we can do this project over here. We can make your regulatory reporting a whole lot simpler, or we can do this other thing. And so they are on that cadence of how do you create value with the customer? Then we have a different team that's focused on, you know, us winning five, 600 new logos every week.

AI assessment note: “They keep it for a year, year and a half.”

Q And did you find, how did you, Get just in the early days, just that acquire brand new domain experience. We'll just go hanging out with fleets. Did you, was there a key hire you made to the team, like a COO or VP of ops or something? Was there anything special? Just good old fashioned founder learning?

A Just get out there. And it was, at the beginning it was show and tell. Like we basically built the simplest cloud connected sensor we can imagine, which is a temperature sensor. We took it into two industries, which is food and beverage and then pharma and biotech thinking that, Hey, they have like temperature sensitive assets that might Spoil if something happens. And we said, Hey, this is, let's see if we can go do something useful with this. Those initial beta testers were the ones who actually brought us into the fleet. They said, this is cool. Our big fridges don't actually break very much. What does break is the cold chain. Like when we try to move something from site to site, we had a customer, they were delivering this cowgirl creamery since you're here in the Bay area, right? Like they make fancy cheeses. They would lose like 10,000 dollars of cheese when they deliver to Whole Foods because someone would leave the doors open and all the heat would come in.

AI assessment note: “Just get out there. And it was, at the beginning it was show and tell.”

Q And they, uh, of 70, but do you, do you drove that process with a banker? How the hell did you talk to 70?

A So we did have a banker and that was the long list, right? We sit down with the banker and say, who do you want to mail a teaser to? And they started with their long list, filtered it to the long list they showed me. And that was like 60 or 70. I think those got teasers, very short brief. And then the ones who came back then got the confident and were willing to sign an NDA. They got the SIM, the confidential information memorandum that had considerable detail in the company. And then the next level of that filter is LOI. Okay. Who's really interested? Give us a letter of interest. And then the next level is going to exclusivity and selling.

AI assessment note: “So we did have a banker and that was the long list, right?”

Q the world is weird today. And I want to hear from each of you, starting with Arun, one to 10, just how is, how, how is SaaS doing? Look at public companies, look at the earnings for Okta and Salesforce and Zoom and your own portfolio. How's SaaS doing one to 10? And then how is SaaS investing one to 10? Like, where are you on the one to tens?

A I think, uh, if you look at some of the, and we might have some debate about this, but if you look at some of the recent company earnings and just looking at our portfolio, I'd say SaaS companies are doing probably about a five to six, but the trend line, especially over the last quarter or two, and what we can see over the next quarter or two is mixed to down. Uh, we have been super conservative on investing. And so we've made one growth investment this year. And so one this year, wow, one this year, and that's down from about 20 from last year. And so, uh, our investing pace has slowed significantly from the start of the year. And so I think our investing probably preceded some of the results that are coming out. And so, you know, from a investing perspective, I'd probably put it at a two to three right now.

AI assessment note: “from a investing perspective, I'd probably put it at a two to three right now.”

Q Was now HubSpot could mean a lot of things. Actually, I don't know what it means. Was this always the vision to be some sort of SMB business? What was this initial vision on? I'd actually don't know on day zero.

A Yeah. The only reason, well, not the, I mean, the primary reason we started the company is both of us had a, a passion for SMB. This is when we were both grad school students when we first kind of met as classmates. And partly the reason is we had both done enterprise software before in our prior lives. As it turns out, enterprise software sucks as a life. Um, you've got these extended sales cycles. It takes you so long to figure out product market fit because you don't get as many data points back. Um, the other end of the spectrum, you could do consumer applications, consumer companies, and those tend to be very kind of, uh, bimodal outcomes. Either you could come up with something great. It's the next Facebook and it's billion plus dollars and, or it's nothing because you, you know, you just don't know if you're going to break it through. So beauty of SMB is that you have the kind of old fashionedness of enterprise, which is you can charge money for software, but you have the scale of consumer where there's millions of them out there to be served. Yeah. And we were just excited about, and we thought it was an underserved market that, you know, there were, everybody ends up getting pulled up into the enterprise. Um, and we felt that if we could kind of have the courage of our conviction and stay in SMB, that that would be, that would work itself out. That was one of the found…

AI assessment note: “the primary reason we started the company is both of us had a, a passion for SMB”

Q the coming months, is it okay to just ask nicely any change? It's hard to get the money for the round. Is it, is it okay? Is that, is that, I know Bessemer doesn't have any issues, but is it okay to ask? And should you, should you not ask with a nice smile and not be a jerk? Should you ask if there's any issues or not there yet?

A I think everything's on the table. Um, I think the more insightful questions though up front are fun size, fun timing, reserve models, and, um, and types of LPs. I think those will give you the health, um, status kind of sense up front. Every VC is going to say, of course, the money's there, so I'm not sure you're going to get a candid answer, but I think the data on those earlier questions will actually give you the probabilistic model, um, to, to, to figure it out yourself. Um, and if they're, you know, if they just closed a fund but haven't done a capital call on it, um, and our first time fund, like there's some risk there. If they're at the end of a fund and they were about to go out fundraising, then, um, then it really matters what the reserve models are because If they're off on that math, there may not be money available, and so I think those are the things to really push on.

AI assessment note: “I think everything's on the table. Um, I think the more insightful questions though”

Q we ever could, right? Um, and so, running this pension with these obscure financial regulations, with a pension broker who won't, who just yells at us and never explains any of the issues, we were stymied. We couldn't get help for years on how the hell this pension works. Um, but, 10 K, our, our AIVP revenue knows all the data, right? So you asked Claude to ask 10 K.

A Yes, I asked Claude. I was like, okay, since we have this new MCP, I'm going to hook all my apps up, which included a 10 K with all of our financials. And then I gave Claude all of our pension docs, right? Like the, the plan, um, how much it's vested, how it works, the minimums. Then I gave him, I actually didn't have to give him my emails because Claude has my emails where Replit doesn't, but Claude's already hooked up to my Gmail. So I said, hey, can you also look through my emails? Of all the emails about the pension between the brokers, the tax team, the two part-time people on our finance team, like, just look it all up so you have all the context and all the recent docs, because they're telling me I need to, like, fund, fund it right now, like, today, or something dire's gonna happen, and I just don't think that's true. And so between the two of them together, because Replit and TenK's agent has all of our financials, they could see what we already accrued into the pension. I gave that to Claude. Claude looked through all my emails, got all that data, and then right away understood something that we could never get help on in a minute.

AI assessment note: “Yes, I asked Claude. I was like, okay, since we have this new MCP”

Q Alex, how big is the team today and how big is engineering?

A So this is a good question. We have roughly half and half split. So, 80 people engineering. And engineering is now really broad. I need to acknowledge that. Software engineering, machine learning engineering are always kind of traditional professions, but the amount of people who do automation, prompt engineering also increasingly grows. And the rest of the team are, we have maybe around like, 70 people creative team. Who are not native prompt engineers. And this actually is very important for us. We learn by external signals and internal signals how to make those models actually usable. How to empower creatives to actually use them. And what we are seeing is that one creative director can now make ad end-to-end, like, let's say within a day. Like, before that, it would take weeks, it would require to assemble, like, physical production crew, rent a lot of equip, equipments, book a space, and so on. And now it's completely different. So for us, we believe that Like, one of the core unlocks for Higgs field is to having creative team and engineering team working together.

AI assessment note: “80 people engineering... maybe around like, 70 people creative team.”

Q Are there two, or are you, are they both running or only, you're only running? So you're not using any compaction from Claude?

A No, no, no, no. Just ours is better. And I think the thing about the primitives that the labs build, They tend to be very generic, and so I think every app will need to, uh, you could start with the generic firmatives, but for it to perform really well on your benchmark, on your users, every use case is going to be different, and so we care a lot about, like, you know, certain pieces of data around the architecture of the app. There are certain things that absolutely need to remember. Like, if it forgot that it has a database, like, that's catastrophic, right? So there are things that we really care about preserving, but then there are a lot of things that are like bugs and things that you solved. Actually, if you keep them in context, Asian performs worse because it is confused by, by the history of it. So you need to be very prudent about knowing what to delete and knowing what to, what to keep in the background. We have sort of a graph-like structure of understanding the different memories, and we do compaction on, um, actually there's like multiple layers. There's compaction, but there's also writing to long-term memory, and long-term memory today is marked down files. So repli.md, I'm sure you look at it sometimes. Repli.md is an example of that, but there are other files that the agent can write to, and you can also prompt it to write its own long-term memory. You can say…

AI assessment note: “No, no, no, no. Just ours is better.”

Q You got deleted. So, so for all seriousness, we've been doing this for a while. You built our whole AI VP of, of customer success. We built the saster annual.com together and Replit. What happened? Why were you deleted by your, your affirmatively intentionally deleted by the agent, your session. So what happened?

A Yeah, it's free sound. So we have an agent that powers our agenda, as Jason explained, and what happened was he just decided to be lazy because we started adding more and more sessions, right? We're closer to SASTR annual. We have more speakers coming in, confirming for SASTR in May. We had more speakers, so we added about like, 20 more just in like the last week. And the agent was lazy because he didn't update That he should look for all sessions that from the API, he just decided he would just stick to the core set that I gave him originally. And so when I added these new sessions, he, he decided he would just pull the first 50 instead of all of them. And so I got dropped, a bunch of others got dropped too, but this one was the most like visceral one because I just got dropped. But what was worse was the agent was lazy about it. He decided to blame the API integration. For why I got dropped.

AI assessment note: “he decided he would just pull the first 50 instead of all of them”

Q You got deleted. So, so for all seriousness, we've been doing this for a while. You built our whole AI VP of, of customer success. We built the saster annual.com together and Replit. What happened? Why were you deleted by your, your affirmatively intentionally deleted by the agent, your session. So what happened?

A Yeah, it's free sound. So we have an agent that powers our agenda, as Jason explained, and what happened was he just decided to be lazy because we started adding more and more sessions, right? We're closer to SASTR annual. We have more speakers coming in, confirming for SASTR in May. We had more speakers, so we added about like, 20 more just in like the last week. And the agent was lazy because he didn't update That he should look for all sessions that from the API, he just decided he would just stick to the core set that I gave him originally. And so when I added these new sessions, he, he decided he would just pull the first 50 instead of all of them. And so I got dropped, a bunch of others got dropped too, but this one was the most like visceral one because I just got dropped. But what was worse was the agent was lazy about it. He decided to blame the API integration. For why I got dropped.

AI assessment note: “he decided he would just pull the first 50 instead of all of them”

Q list, right? I mean, classic crappy copycat lists, uh, are a low effort thing like buying a purchase list, but if you do it, if you spend the time to do it right, you really target the ICP that works and then customize the copy. That's a hack to getting scale if you don't have it yet in the early days, right? Is do it, do the copycat really well.

A To your point, like, I think when I had Clay copycat it, It gave me, like, 2500 more CMOs, and I was like, that's probably too many. Like, so I went through, I went through it one by one. It took me a couple hours. I think it was Saturday. I went through it one by one while I was watching something on TV, and I deleted all the people I didn't want, because I was like, you know what? The list is pretty good, but there's, like, 2000 people here I probably don't want. So I deleted a bunch. I, like, hyper-pruned it to get it to the best quality, but then, you know, that's how I, Double their attendees for that particular thing in a week. So it can work really well, but

AI assessment note: “So it can work really well, but”

Q price, right? We almost lost everything. We almost lost everything. It's not going to happen, but so I'm picking three leaders that won't go under rather than a synapse, right? But if Brex, Mercury or Chime, which would not go under, if they did tomorrow with no notice, what would happen? We've got like three million at Brex. I don't know what at Mercury, what would happen to my money?

A In theory, and this is most likely what would happen, is Brex goes under, the bank still has it, and there are two banks, they're columned Fifth Third. Fifth Third's a big giant bank in the Midwest. The bank would say, we need a copy of everyone's balance. They need to know Lentkin balance or Sastra balance, right? And then they would say, oh, you got three million dollars. They would write you a check for three million dollars, and they, not a joke, would probably put it in the mail and send it to you and hope that eventually to get to you. Um, That's in theory what would happen. That's what was supposed to happen at Synapse and Evolve, but they went to the books that Synapse, the ledger, said everyone had, and no one, they said, you said it has three million dollars. It's not three million dollars here.

AI assessment note: “In theory, and this is most likely what would happen, is Brex goes under”

Q on this post. Whenever you get into MA, this 10 point checklist and we'll keep updating it. I would like it to be a canonical piece of content to help founders this first one. So let's go through them. But this one is takes a while to understand buyer motivations, know what they're buying. Do a little bit more of a deep dive here in practice. What have you seen?

A Yeah. So I think. You really do have to understand, and it comes from listening and speaking and engaging with buyers. And hopefully what you've had the opportunity to do is have those conversations before the moment where you say my company's for sale. So you actually know what you're going to plug there. And I do think that if you have this luxury, you've got to tailor your pitch for those different buyers. An example, Could be Amazon PillPack, where really I think what Amazon was ultimately interested in was the software system. We thought that the packaging, the robotic packaging, and the delivery mechanism was like incredibly novel, and it was, but the reality was Amazon could replicate that and make it better in a heartbeat. That wasn't what they needed, but the spaghetti between the The providers and the insurers and the PBMs. So the pharmacy benefit managers actually making that system coherent and making it work with multiple stakeholders. That was a huge software effort. And it's, it is Amazon pharmacy today. It's literally based on that pill pack code. And we always look at that as this was just an enabler, right? Like the real business was like the, what the consumer saw in the consumer packaging and messaging. And we had to get that right, but that was what Amazon was interested in. So tailoring and understanding that makes a huge difference. In some cases, you nee…

AI assessment note: “An example, Could be Amazon PillPack, where really I think what Amazon was ultimately interested”

Q it gives me my best diagnosis for why my cholesterol is high or others, but that was my moment where it was pretty cool. For this one use case, it seemed like instant parodies. First Tomas, what's your take in general? And is this re it's only been a couple of days, right? Is this going to make B to B apps in order of magnitude cheaper? What's the impact?

A I think the impact is gross. Your gross margins are so much better than they used to be, right? Like the second biggest cost for AI enabled SaaS applications has been inference. And when we were looking like a typical software companies, probably at 75% gross margin. Yeah. AI software application companies are like a zero to 30%, and now their single biggest cost has been reduced by 95% overnight, and they didn't have to do a thing. So now they, now, now they have AI, and you, Jason, you and I both know this, like the growth rates of AI companies are much faster than, say, the classic SaaS businesses just because there's so much in them. And so now you have companies that are growing one to seven or some massive growth rate. Before they used to have Challenging gross margins. And now they'll probably look the same as SaaS companies, which means you have pretty significant multiple and valuation expansion.

AI assessment note: “I think the impact is gross. Your gross margins are so much better”

Q started from domain experts to I can sell anything. You literally worked at a spa and forced yourself in the door at Manglement as like the first sales, first business person in the company. Like you literally interned for free. Didn't you force yourself in the door and say, this Software is still great. I'll work here for free and are now the VP of sales. Is that the story?

A That is, that's the story in a nutshell. Yeah, absolutely. I owned a salon in San Diego. I knew we needed something better, something that had payment processing incorporated, which in 2017 wasn't very common. I called the phone number on the website, much to my surprise. Two days later when I was signing up, I found out that the AE was in fact Daniel, the CEO. I was probably the 27th customer. And I loved what I saw. A lot of the things that were true then are still true now, like world-class product, super fast. Smart automations. And at that point, I'm like, hey, how do we do this? How do we do this together? I don't know what SAS is. There's far too many acronyms for me, but I had spent 10 years selling 20 inch hair extensions, so I knew how to sell something and jumped right into SAS. Thanks to you, learned what that acronym stood for.

AI assessment note: “That is, that's the story in a nutshell. Yeah, absolutely.”

Q started from domain experts to I can sell anything. You literally worked at a spa and forced yourself in the door at Manglement as like the first sales, first business person in the company. Like you literally interned for free. Didn't you force yourself in the door and say, this Software is still great. I'll work here for free and are now the VP of sales. Is that the story?

A That is, that's the story in a nutshell. Yeah, absolutely. I owned a salon in San Diego. I knew we needed something better, something that had payment processing incorporated, which in 2017 wasn't very common. I called the phone number on the website, much to my surprise. Two days later when I was signing up, I found out that the AE was in fact Daniel, the CEO. I was probably the 27th customer. And I loved what I saw. A lot of the things that were true then are still true now, like world-class product, super fast. Smart automations. And at that point, I'm like, hey, how do we do this? How do we do this together? I don't know what SAS is. There's far too many acronyms for me, but I had spent 10 years selling 20 inch hair extensions, so I knew how to sell something and jumped right into SAS. Thanks to you, learned what that acronym stood for.

AI assessment note: “That is, that's the story in a nutshell. Yeah, absolutely.”

Q thought about this a lot, two elements to it, but I don't think it's obvious who wins are Cummins in startups. It's obvious there's a thousand startups, there's a thousand flowers, but what's your nuanced learning from HubSpot plus Sequoia on who wins in B to B? Who wins in AI? Who benefits the most? Or who benefits the most is maybe a better way to put the question, right?

A I think that the age of old, it's the startups are innovating and they're racing to get distribution and the bigger companies have distribution and they're racing to innovate. The twit this time Is that the data is very hard to acquire for a start. So it's not just the innovation, but you need a proprietary set of data to do something cool with AI. And I think of HubSpot, for example, We've got the Zoom data. We've got the calling data. We've got the email data. We've got a lot of the unstructured stuff. And then we have all the structured stuff too. And if you're a startup breaking in and you want to do some amazing AI work, it's tricky with all that. And so I think it buys Salesforce HubSpot, the bigger companies, a little ton. The other thing I think is a little bit different about this than other platform shifts is it feels like everyone has read and learned the lessons of Clay Christensen and The Innovator's Dilemma. And the incumbents seem to be moving very quickly, whether it's Microsoft or HubSpot or Salesforce, you name it, no one seems to be sitting on their hands in this one. So I like, as I play both sides of this, but I, but in this particular case, I think the incumbents have a little bit more advantage than in most platform shifts.

AI assessment note: “in this particular case, I think the incumbents have a little bit more advantage”

Q the sales reps actually hate doing this. They hate helping for deployment. All they want to do is get the customer onboard and immediately go on to the next deal. So your, does your sales team not hate it? Or what are the learn? How do you get your sales team, especially these days when sales wants to do the least possible, how do you get them to do more?

A Well, I think it's how you set up the incentive structure, right? Um, if you pay your sales rep, uh, commission the day the deal closes and then there's no clawback or none of that stuff, then of course that's what they're gonna do, right? But we've worked really hard to have a incentive structure that, that makes it attractive for sales reps to be invested in the success, right? But we pay well on expansion over time as well. And we, and expansion is a good one too, right? Like we have three, four products now that someone can buy. Payroll is the latest one. We don't actually want you to buy payroll on day one. Like we will actively discourage you. We incentivize our sales reps to keep the deal sizes lower at the time it closes because the chance of success is that much higher. And we know that, hey, once they are successfully activated, now they trust us. They had a great experience. It's so much easier to talk to them about like product two, three, and four.

AI assessment note: “I think it's how you set up the incentive structure, right?”

Q Are there enough Americans, are there enough Americans to do the work for all of, for all of us six-figure knowledge workers? Are there enough people to do the actual work so we can live our remote lives?

A Yeah. I think you hit the nail on the head, right? Like it's not necessarily just a cost of labor, although that is a big issue as well, where those like front desk workers, uh, you know, you think about a spa with 10, 15 providers, they would normally have three, four providers that is before COVID and each of them get paid like 13, 14 bucks an hour. Now that same business has to make it work with like one or two providers. So half of them and those People make 20 to 23 dollars an hour. So cost of labor is up. Supply of labor is down and retention is really low as well. So there's this natural demand for these small businesses to invest more in technology. And I think that's also driving a lot of the growth that you see in vertical SAS right now that.

AI assessment note: “Supply of labor is down and retention is really low as well.”

Q on it on YouTube, but, you know, HubSpot's NRR was like less than 80% up until 25 or thirty million in ARR, right? So you're at one 10 NRR, uh, which from SMBs, right? Which is a gift. So what's the learning? Is it being multi-product? Besides having great software, uh, but a lot of us, what, how did, how did you get to a 110% NRR? What's the learning?

A Yeah, well, it's interesting, right? Because when you think about NRR with most enterprise software, a lot of it comes from seat expansion where you just get more folks to use your tool. Uh, we don't have that, right? Like there's, there's none of that going on. So the expansion can only come from selling them new products that you didn't have before. So you definitely need to make sure that you're investing in like, in a products that people can even buy. Otherwise there is no chance for expansion. Um, so I think that's just the mechanical piece, but the thing that's really important to, um, get that is to have trust and, uh, people forget how, uh, much our customers depend on our software. Like literally it's their operating system. If management doesn't work, these businesses can, can close. There's nothing they can do. They don't know who their clients are. They can't access the medical records. They can't take notes. They can't take payments. Like they might as well close. And so we invest a crazy amount, almost like a bank in making sure that our systems don't go down. And so reliability and quality of product is so important, but once you have it, you get the trust from customers and that is the trust that you need. So that when you show up and say, Hey, guess what? We just launched marketing automation. Let's say you get a really high adoption rate on that one, because …

AI assessment note: “expansion can only come from selling them new products that you didn't have before”

Q a minute. How do you get to these two K customers? I was brought in. Obviously I knew Bill from you, but as a customer, I came in through our outsource controller, right? Who brought us in. Is that a big channel for you as a channel, a big way you get these little two K customers? Cause the direct marketing and sales is tough at two K, isn't it?

A Yes and no. There is plenty word of mouth. There's plenty self-service that kind of drives customers in. They might still talk to somebody in the sales team, but it can be pretty quick. So, you know, ultimately the three-pronged approach on the ecosystem has worked for us, right? So it's the go direct, obviously optimize digital marketing the best that you can, leverage the word of mouth that you can, the driveries, and then go to accountants, and then obviously go to the strategic partners. So the accounting firms do represent a big bulk of client base. And it, it is because it is like your advisor, they might have 10, 20 clients that they're like, hey, Everybody's going to use this because it's going to enable me to support you better. And that happens. Those are the firms that actually do the, I would say the best with bill.com and they make a business out of it, but they actually change the model around. And sometimes they will say, Hey Jason, you're going to pay me 5000 dollars a month to do all your bookkeeping, but you have to use bill.

AI assessment note: “So the accounting firms do represent a big bulk of client base.”

Q Sure, thanks, Taylor. So, Jason, my question is about the, I guess you could call it a subcategory of SaaS solutions that are pre-built or pre-tailored by vertical industry. We have such an app that's been pre-tailored for two industries. I just want to get your two cents. Do you think that customers are ready to buy into enterprise-level apps that are pre-tailored?

A Look, I actually think it's nothing new. I mean, check out the story of Service Titan, SaaS for technicians and HVAC maintenance. As vertical software is nothing new. There has been a niche piece of software for bookkeepers, for dentist office, for doctor's offices. We think these are like new categories. They're not. Walk into any of the oldest. There are multiple categories of SaaS for veterinarians. Okay. I don't know if anyone will have a ten billion dollar outcome, but people have been writing DOS programs and windows programs for years. So it's, it's not new. And it's certainly the case. Look at toast. Let's just do it for restaurants. Toast is essentially taking a combination of square, right? Plus other systems say we're going to do square for restaurants. Square had a little bit of point of sale, right? It had its readers and actually a significant chunk of square's business is to restaurants, right? To small restaurants. Toast said, Hey, we're going to just do one thing, right? And so there's lots of stories. Klaviyo, which was the only IPO of this year is marketing just for e-commerce. In fact, Klaviyo really is just marketing only for Shopify customers. 70% of Klaviyo's almost one billion in revenue only not only comes from e-commerce, it only comes from Shopify, but e-commerce, but, but emails for e-commerce are much more valuable than normal emails, right? Because…

AI assessment note: “Look, I actually think it's nothing new. I mean, check out the story of Service Titan”

Q years, not 20, but part of the challenge is obviously what are we going to do with this unstructured, slightly structured data, tagged, but massive, ingesting mass amounts of data that has a little bit of light structure to it, it has titles and search, and now you, it's remaking the company probably in some ways, right, where you can finally do more than text-based search across this data, right?

A Yeah, that's right. So we, we, we just, we, we lucked out. We have, we've been building a product for about three years. We just announced it called Box Hubs. And what, what Box Hubs does is, you know, traditionally you have your content organized in folders and you share those folders with people that you want to work with. Hubs creates a presentation layer where I can say, I want content from all these different folders to sort of be presented in this way to some audience. So Your sales team will have a sales portal. Your employees will have an HR portal. Your, your marketing, you know, all your employees will have access to brand assets via marketing portal. So that's hubs. We, we've been building that for three years and all of a sudden, you know, a year ago, you know, the LLM explosion happened and we said, wait a second, this is sort of the perfect scenario now where the, the, the customer is telling us what is their most authoritative set of content by topic. In a hub and you bring an LLM to that and now all of a sudden you can actually start to do more kind of question answer based, you know, like working through your data where you go to the sales portal and you say, what's the price of this product? And it's going to give you an answer instead of saying, here's the file that might contain the answer. So we think that's, that's a pretty big breakthrough in knowledge ma…

AI assessment note: “you bring an LLM to that and now all of a sudden you can actually start”

Q next metric because we do have a lot to cover and, and I want to talk about, uh, ARR, which, which kind of started out as a It was a well-defined metric, you know, and then it became something pretty fluid between companies. So I wanted to hear, Jason, your perspective on, you know, should all companies, should all SaaS companies measure ARR? What changed since we started using it?

A Well, look, I think the most, I think, I think we could probably all agree that, and this happens, this has happened even with terms like cloud or SAS, it's gotten corrupted over the years, right? And so ARR used to stand for annualized recurring revenue, um, and then fintech exploded. And, uh, and, and so they all wanted to claim they had ARR, even if a lot of fintech revenue is not recurring, right? Not all Stripe payments are recurring. Um, bank banking as a service is not recurring, but they still all claim they had ARR, right? So we had that issue and then it, it wasn't nowhere in that ARR was the word SAS or software, but it should have been because the other thing that happened is hybrid models, models that are services and software models that are hardware and software all started to claim it was ARR, right? And, um, I wrote up today on the Sastra blog, if folks want to look Matterport, I don't know if you ever use Matterport. It's like that cool three D software where you can walk through houses and buildings. It's like super cool, but half their revenue is from services and cameras, so their gross margins are in the forties, right? I think Monday approaches 80, right? Or, you know, this, there's, there's some loose definitions of gross margin, but that's dramatically different margins than Monday, which is a software company to 80 Matterport, which is super cool, righ…

AI assessment note: “ARR used to stand for annualized recurring revenue, um, and then fintech exploded.”

Q the iconic perspective? How are you guys thinking? We, we, Doug and I talked right when things went We're starting to get tight. We did it. We did one of the first interviews that things were somewhat bullish, right? I think you were anything sub 500 was still a good valuation X months ago. Is that where we're at today? Where, where, where are we on both one to tens?

A Yeah, I think it's tough. Um, I agree with Alex long, long term. Uh, I, I'm still very bullish, but I think you're asking about today. And I think it's, I think it's really tough. I mean, it's hard to be bullish when the very best companies, the very best, In the public markets are down 60 to 80%. Um, that's painful, but I think you're asking more about how are the companies actually doing. And in that respect, I'd still go closer to Arun with a five or a six because of how it's deteriorating. We look at all the data and we have data on lots of companies. 2021 was like the best year ever in my career. Almost every company hit a hundred percent of their plan for net new ARR. Those numbers were deteriorating fast. Q one, the medium was 99% hit their plan. I've never, uh, Q two, yeah, 87%, Q three, median, 69%. And so companies are starting to really miss their plans, both public and private. You're seeing much fewer public companies raise their guidance now dramatically down Q one, Q two. We don't know all of the Q threes, but there's very few raises in the public market for full year guidance now, which is a huge change. From before, and those companies, as you know, have significant buffer built, and so we are seeing in the private and public a significant deterioration in their attainment versus plan. You want to talk about growth rates. The median growth rate was about 83% la…

AI assessment note: “I'd still go closer to Arun with a five or a six”

Q Okay. And so what, what, as much as you can tell us about, I think some of it's public, but how, how did it happen? Did you get a random email or a DM or how did, how does this process happen for twelve billion? How do they get started?

A We had been through sort of an, a little bit of an informal round with another couple of potential buyers. Uh, and you know, it, it, it didn't end with a, a good, a good deal. So we walked away from it and I was, I had sworn I would never listen to another offer again. I was done with it. I was going to move on and just run my company for the rest of my life, and then, you know, maybe within a couple of days, I got a call, uh, from Catalyst, actually. I'd been working with them for many years, and they said, just take one more call. You're going to like this one. Oh, interesting. So I took a call with Alex Chris, uh, my, my new boss, and, uh, I mean, we hit it off immediately. He's a small business entrepreneur. Uh, he'd been with Intuit for 17 years by then, but Uh, he had run a business, got acquired, and he knew the passion required to manage small business companies, and he knew the pain that they suffered from, and he knew what drove us at Mailchimp, and we just got along really well, but they are, they're also a very careful company. They care about, ah, culture fit, and they did a lot of culture diligence, and, ah, that all, which I loved. I loved that they cared that much, and, but, but that did mean one year of, ah, kind of wooing each other.

AI assessment note: “I got a call, uh, from Catalyst... So I took a call with Alex”

Q And how did, what did you learn from that? What did you learn? I mean, you made, you made it pretty far without a CS team with small businesses. What did you learn from that?

A I mean, we, we started to, I mean, we, we just did so well with, with smaller businesses, and then we noticed as they grew, And, uh, you know, maybe they would hire VPs of sales or VPs of marketing, and they would start to use MailChimp. Their needs changed. Suddenly, it wasn't the founder who loved our unique and kooky small business brand. It was a new person, uh, and they were, they, they treated us differently. And so I would go out and visit some of them, and, you know, I would say, what do you think of our brand? Uh, where, where does our brand, you know, rest in your brain with other brands? Are we next to Nike? Are we next to Apple? And I remember one, one marketer told me, uh, uh, no, your brand lies next to my microwave oven. And I, you know, it kind of broke my heart a little bit. And I said, well, what do you mean your microwave oven? And he said, you know, my founder liked you and he loved the brand, but I've got to grow this business and I need you to be reliable. And if it doesn't cook my food in a minute, I want someone to call and answer my questions and just get it running again. I don't want to have to read KB articles, blah, blah, blah, blah. So, you know, that told me, gosh, we've got to, like, spool up a customer success team of some sort, and it was, it's been a long journey. Uh, we've got some great new executive leaders that are, and Intuit's got a lot …

AI assessment note: “that told me, gosh, we've got to, like, spool up a customer success team”

Q Whatever. Have you noticed a pattern among, I don't know, the ones that end up on this stage? Where they go one way or...

A I think I noticed a pattern, um, and I wrote it up a couple years ago and refreshed it, um, And then I'll add a new anecdote. Um, you know, I wrote this years ago and then I've updated it of like the three plans you need to make as a founder, and I call them, no one's really ever copied this nomenclature, but I call them C-ten, C-sixty, and C-ninety, and C is the confidence factor. And C-ten is the big plan that there's a 10%, like a two percent chance you're going to hit it, like, talk about that with your co-founder over beers or Rosé, there's no point, right? 10%, there's a chance. So talk about what, if we plan, if we think we could do nine million next year, but look, if the Stars aligned. We did a Google sheet. It's possible to do 12. That's, that's your 10%. The 60 is probably where your core plan should be. We have a 60% chance thinking we can do it. More likely than not, but barely. That's how you build your core model. Your core model's for sales, for marketing spend, for hiring and engineering and product. And then with your finance person, or yourself, or your outsource person, you build a C-Ninety plan, which is one, we're 90% sure, even if sales slow, we're gonna hit this plan. And the advantage, you don't, in my experience, the 10 becomes your stretch plan, the 60 becomes your base, and the 90 is the quiet plan you use to not run out of money. That's how you mana…

AI assessment note: “I think I noticed a pattern... the three plans you need to make as a founder”

Q Yeah. So number six, thinking you're getting away with under investing in management, upskilling in HR. We might've touched on this one too, on the hiring of the people, but what was this real mistake? Where did you, we all under invest, but what was that? What was, where are the painful memories here from under investment?

A I have this, I had this, I had this really, um, valuable experience in that when we acquired zoom info, it was a company that was in our space doing something similar. Um, But doing it in a completely different motion. And so it's as though like all of the things you thought you might do along the way, you got like an open book case study to your competitor doing. And in this, in this way, like we, we under invested in middle management along the way, especially in our go to market motion. And instead of investing in managers, people to like manage a group of people and get them motivated and keep them focused on metrics. We invested in a bunch of automation. And so instead of like investing in a manager to manage sales folks, we built a lot of automation. So our sales team would never miss a follow up would always, you would always see what's going on in their accounts would be alerted if their account like logged into a trial and took a bunch of action. We basically automated managerial functions. And that made for a, for a, you know, a high margin business, but then we acquired zoom info. And what you saw was a very opposite approach. Instead of investing a bunch of automation, they invested a bunch of managers in that go to market motion. And you saw that when you invested in great managers, the outcome wasn't a lot of places much greater than just investing in automation a…

AI assessment note: “we under invested in middle management along the way, especially in our go to market”