The Exchanges

Q You also said in this stage, and I really want to double down on this because I didn't really get what it meant. You said that you shifted your technology teams toward thinking about the reusability and durability of systems. What does it mean, reusability and durability of systems, and how would you advise founders on that, given what you know now?

A When you're pre-product market fit, you know, it's, it's, um, it's very easy to, to, to try to build systems that, um, have extremely long shelf life, and I think you should only do that if, if they are Very high confidence, meaning like you , you know that this system is going to be alive for a very long time and very high risk, meaning, um, if this system doesn't work, um, we're screwed. The rest, I think you should just, um, understand that the shelf life is probably 12 to 18 months and be okay with it. Once you find that product market fit, um, Then your goal is basically scaling that as well as adding new products. And so as you go multi-product, you just need to ask yourself, what can I reuse from the first product in terms of the second product? Because you should typically go after a second product that has, um, you know, economies of scale in terms of systems you've already built. And so an example for that for us was our first product was cards. Our second product was expense management. It was a reimbursement. Now, when you think about a reimbursement, it's fairly simple. There's an employee identity, which we already have. There is a form and a request flow, which we already have. There's, uh, an approval system, which we already had, and there's a money movement system. We had a money movement system between the customer and ramp when they paid us back for the card…

AI assessment note: “what can I reuse from the first product in terms of the second product?”

Q they're about kind of less debate around the goals themselves and less on the metrics themselves that you care about, but they determine success. And I've seen you say before, I just care about how we're going to win same, but what is winning? Winning is dictated by setting a finish line and hitting that finish line. So do you not need to set them to know what winning is?

A I think winning can be derived. So there's, I think there's like leading and lagging metrics, right? And you want to, you want to win on your lagging metric, but you really want to focus on the, on the, on the leading metric. I think setting goals on lagging metrics like revenue, market share, NPS, that's, that is, um, that is not going to be clear to a team on how to actually change those metrics. I actually much rather focus on the leading metrics, which is like, how many customers did we get on this new product? How many, um, features did we ship in this specific segment? Um, how many logos did we close, um, with this specific strategy? Those are much more leading rather than the lagging ones, which is, which is revenue.

AI assessment note: “I think winning can be derived.”

Q What was a really strong hypothesis you had that turned out to be wrong?

A One of the hypotheses we had was that we can embed like a financial product directly in our, in our, in our, um, invoicing products, and it'll just like have massive take up. And, and the hypothesis there was that the person paying the bill had the authority To take a loan, to pay the bill. That was the wrong hypothesis in the sense that the person paying the bill, oftentimes it's a clerk. It's, it's a, it's a, it's an, it's a, it's an agent that just is more of an operator than necessarily like a big decision maker in terms of like your financial, um, your financial decisions. And so you actually need approval from a more of a CFO, a strategic finance person to understand like, should I pay an interest rate to actually extend that payment? And so we had the wrong hypothesis in terms of like, The actual target segment, which then made our product, we had to essentially shift our product to increase the, the take of that.

AI assessment note: “One of the hypotheses we had was that we can embed like a financial product”

Q Can I ask you, who makes you more nervous? Is it like incumbents or is it startups? Cause it's like your amateurs could actually integrate AI pretty well and play into the next generation of, especially like expense management. Well, I don't think Concur will, but amateurs I can see doing better, but I,

A So I, I think if we weren't in the B to B like fintech space, I would say incumbents, and you've seen that with like Microsoft teams and slack, right? It's like a, it's like a perfect play of like, I can build something that like is pretty much a copycat and I can distribute that way better than you can in this ecosystem. So that's, that's scary. That said, there isn't a incumbent B to B spend management company That is actually even close to like a Microsoft level of like innovation and velocity. So I'm not really scared of the incumbents at all. And like Amex is like, it does not know how to build software. It is an incredible company with an incredible brand and an incredible card and merchant product. Um, but they're a far cry away from, from being a SaaS company. So I would say, I would say, um, um, um, new entry, um, and, and specifically, um, folks that are going after, again, like a very pointed solution and find a new, a new entry in, in the finance, um, space. And so that's why we take a, we, we, we want, like, keep a very close eye on, on, on new players. We invest in new players. We acquire, uh, you know, aqua hire, uh, great talent. Um, and we actually use that as a testing bed to figure out, like, what's working, and we include that in our product strategy.

AI assessment note: “So I would say, I would say, um, um, um, new entry”

Q in terms of internals, you said before that you worked in two-week sprints. And I remember I was running, it was really annoying. I was running around Hyde Park in London, and I was like, great, that sounds awesome. How do you structure a two-week sprint? Like, what does that actually mean in reality? So can you explain, how do you plan these sprints, and how is it broken up?

A So I've iterated a lot in terms of just product development processes, and this is the process that I've, I've come to love. I'll be super tactical. So you have, you have a Monday leads meeting where you talk about, What is the actual plan for the next two weeks? And you alternate between tactical and strategic there. So one week, it's like the tactical two weeks, and then the week in between, it's the strategic around the next, like, couple months. That's just the leads. So you align with the leads, product engineering design leads, as to what you need to achieve. On the Tuesday morning, you have a team-wide, like, scrum meeting that basically is your five to 10 people, 10 max, where you're actually saying, we've decided this is what we're going to do, and that the decision has been made, and it's all about Um, people signing up for work. So don't assign, but, but have people sign up. Hey, Joe, uh, here are our goals. What do you want to achieve and help us achieve in the next two weeks? And out of that meeting, you basically come back with, um, uh, the clear assignment of roles and responsibilities, and then any, uh, additional like deep dives that people need to have in terms of specs or designs or decisions, et cetera. There are no other meetings that are recurring. In the, in the, in the entire product development process. Those are the only two one hour meetings that happ…

AI assessment note: “you have a Monday leads meeting... On the Tuesday morning, you have a team-wide”

Q You also said in this stage, and I really want to double down on this because I didn't really get what it meant. You said that you shifted your technology teams toward thinking about the reusability and durability of systems. What does it mean, reusability and durability of systems, and how would you advise founders on that, given what you know now?

A When you're pre-product market fit, you know, it's, it's, um, it's very easy to, to, to try to build systems that, um, have extremely long shelf life, and I think you should only do that if, if they are Very high confidence, meaning like you , you know that this system is going to be alive for a very long time and very high risk, meaning, um, if this system doesn't work, um, we're screwed. The rest, I think you should just, um, understand that the shelf life is probably 12 to 18 months and be okay with it. Once you find that product market fit, um, Then your goal is basically scaling that as well as adding new products. And so as you go multi-product, you just need to ask yourself, what can I reuse from the first product in terms of the second product? Because you should typically go after a second product that has, um, you know, economies of scale in terms of systems you've already built. And so an example for that for us was our first product was cards. Our second product was expense management. It was a reimbursement. Now, when you think about a reimbursement, it's fairly simple. There's an employee identity, which we already have. There is a form and a request flow, which we already have. There's, uh, an approval system, which we already had, and there's a money movement system. We had a money movement system between the customer and ramp when they paid us back for the card…

AI assessment note: “as you go multi-product, you just need to ask yourself, what can I reuse”

Q they're about kind of less debate around the goals themselves and less on the metrics themselves that you care about, but they determine success. And I've seen you say before, I just care about how we're going to win same, but what is winning? Winning is dictated by setting a finish line and hitting that finish line. So do you not need to set them to know what winning is?

A I think winning can be derived. So there's, I think there's like leading and lagging metrics, right? And you want to, you want to win on your lagging metric, but you really want to focus on the, on the, on the leading metric. I think setting goals on lagging metrics like revenue, market share, NPS, that's, that is, um, that is not going to be clear to a team on how to actually change those metrics. I actually much rather focus on the leading metrics, which is like, how many customers did we get on this new product? How many, um, features did we ship in this specific segment? Um, how many logos did we close, um, with this specific strategy? Those are much more leading rather than the lagging ones, which is, which is revenue.

AI assessment note: “I think winning can be derived. So there's... leading and lagging metrics”

Q I clearly just quote prior guests who I think are smarter than me, but Glenn Coates, who's VP of product at Shopify said, the day the founder relinquishes the title of head of product or CPO is the day the company dies. Do you agree with that statement?

A Yeah. I listened to that and I love that. Um, I, I don't agree. And again, this is the Shopify, you know, obviously, you know, Toby's like very involved in the product surface area at ramp. I think we, we have, um, Slightly different approach. I think that the, our founder Eric is very focused on our vision, very focused on our brand, very focused on our marketing and our story and our positioning in the market. Um, and it has a very strong sense of, of what we want to be as a company and a very, very high bar for who we want at the company, how we get there. I don't think that it's necessarily super important for the, the founder to, um, to have the strongest opinion. I think that they need to shepherd Uh, the culture to get there. They need to hold the teams accountable for high velocity. They need to be able to opine on what looks good and what it doesn't. What is a good decision, a bad decision, but you need to have an empowered, uh, product team and tech team that actually calls the shots in terms of the sequencing. We've done well with, with kind of our CTO cream, uh, wearing more of that, that product hat. Um, and I think it's, it's, um, um, yeah, I think it's worked well for us so far.

AI assessment note: “I don't agree. And again, this is the Shopify”

Q at odds because you're welcoming discussion and debate and leaving comments on my product specs and everyone being able to say anything about each other's work with What was your core strength? Which is speed, speed, speed. Yeah, cute, you've got an opinion, but fuck off and let me do my work is kind of what I'm thinking. How do you retain velocity while welcoming everyone's opinion on your work?

A You can, you empower the decision maker. So I actually think that like more data does not slow you down. I'm inundated with, with data. I mean, I, we have, I'll tell you, we have Slack channels with every single negative feedback we get from customers. Every time we lose a deal, there's a, there's a, there's a Slack, like, why did we lose a deal? Who did we lose it to? Um, and why, you know, was it a product feature? Was it a timing feature? Was it a pricing feature? Whatever it is. There's so much data that's, that's happening. Um, and in specs, there's so many comments. I think that that makes you Better at making the decision. I think what you need to do, though, is you need to empower the person to make the decision, and when the decision is made, you need to commit, even if you disagree, and you need to align on the outcomes. If a PM gets 16,000 different, like, comments on the doc, and you read all of them, you say, I'm still going with this decision, then you commit, you hold that PM accountable to that outcome, and then if the outcome works, you can reflect back on those comments, and you can change your mind. Or if the outcome didn't work, the PM should reflect back on the feedback that we're given and we'll have a post-mortem on it. So I don't think more data slows you down as long as people are again aligned. The culture can't be like, I just want to share my opinion…

AI assessment note: “you empower the decision maker. So I actually think that like more data does not slow you down.”

Q Now I would love to start. I always like some context. So first, how did you make your way into the world of product? Let's start there as an entry point.

A I've always been like very short term focused in my career. So I just follow a lot of the energy and I think that's going to be a theme throughout this, this chat. The first like energy was management consulting out of college. So Um, is all the hype around just, um, how to think, how to structure, how to sell. Then I got kind of bored of PowerPoint presentations. So I, I wanted to get close to the metal in terms of big data. Uh, and I joined a big data analytics company and that's where I got my first foray into product. And I think that the way I did that was getting super close to the customer and understanding the customer pain points, and then, um, having great relationship with the, with the tech team and understanding, like, how do we build technology to solve those pain points? And I think the product team kind of came running for there.

AI assessment note: “joined a big data analytics company and that's where I got my first foray into product”

Q In terms of learning from your hypotheses there, postmortems are a crucial part of any product team. What have been your biggest lessons in terms of how to do postmortems well as a product leader?

A A lot of documentation, um, blame, like no blame. Um, I think it's actually like you need to have curiosity. You need to engage with, with questions. You need to have a fairly cross-functional team that everyone that's effective be present so that you build trust. Um, with those teams, oftentimes, you know, when you screw up, it's not the engineering team that, that is affected. It's the customer service team. It's the account manager that had to apologize to the customer. And so, uh, bring those teams together, share the data, be upfront with the facts, um, then open up discussions around, like, what could we do better? What are some of the ideas or hypotheses for what we could do better? And then take action items that are very clear, um, and timely, Uh, to address those things so that the post-mortem doesn't happen again. I think that's the most important thing is, like, screwing up once, it will happen. We will screw up all over the place, and we have. Screwing up twice on the same problem cannot happen.

AI assessment note: “bring those teams together, share the data, be upfront with the facts”

Q Final one for you, Jeff, when you think about company product strategies that you see, which one are you most impressed by?

A Maybe surprising for me to say, but I think Apple continues to crush it. Um, uh, from a product strategy perspective. And what I mean by that is, you know, they have a level of craftsmanship, a level of, of, of delight and brand that just has incredible loyalty to their customers. And they've also just had this compounding effect of, of the ecosystem that they've been building that continues to just drive so much revenue. I mean, when you think about like the iOS ecosystem and the monetization on, on applications, when you think about Apple pay and the Apple card and the Apple wallet, Um, it just continues to compound and you see that in the public market. So, um, I'm super impressed with, with that company and their ability to continue to innovate even at that scale. And honestly, they've, they've rarely missed and they're still absolutely, um, winning the market today. And so I, I hope that Ram continues to have that level of brand loyalty and, and that compounding effects of the ecosystem that we're building today.

AI assessment note: “I think Apple continues to crush it. Um, uh, from a product strategy perspective.”

Q What have been your biggest lessons in how to truly understand customer pain points? Because a lot of people go through customer discovery, but I think we'll both agree many do it badly. What is the best way to really understand customer pain?

A I think you kind of have to walk in their shoes for, for a full day. Like what do they listen to? Go listen to that. What conferences do they go to? Go to that conference. What are their, uh, pain? What are their aspirations? Um, what does success look like in their role? What, what is their degree? What do they learn? What, what, um, what is the, their habits? And so I, I spend a lot of time with, with, with customers. Um, and then it's all about just like asking the right questions. Oftentimes like product managers, they have an idea and they, They ask the question to validate their idea and it's actually the wrong idea. And so just ask them like, what does success look like here? What is the worst part of your job? What, um, what takes a lot of your time? Um, and just continue digging in and digging in and digging in. And then lastly, like when you do have a product, like sit down next to them or have them share their screen and just watch them do work in your product. And you will see how painful your product is and how many different ways you can improve that product. Oftentimes just PM spend way too much time In the office, and I think that, um, that's, that's just a huge downside for your team.

AI assessment note: “walk in their shoes for, for a full day. Like what do they listen to?”

Q Would you rather, I'm, I'm going off piece, but I'm enjoying this, like, peppering of questions. Would you rather have someone who's worked in the same category before, Or someone who's worked at the same stage of company that you are before?

A Stage. Um, anytime. I, I think the, the, the category Is not that relevant. You know, I come from more consumer than, than B to B. And I think that's actually an advantage because you're focusing on metrics. You're focusing on conversion. You're focusing on models like lead scoring and lead routing, all the things that like B to B companies have done really poor job on. So I think the stage is actually much more important. Oftentimes if you hire someone from a larger company, they come in and they, they just get shocked. Like, where's, where are all my resources? Like I have, I've never been used to doing the work myself. Like, what do you mean? I don't have like, People just like supporting this one thing. And so I would much rather actually hire people who, who are coming from, um, uh, companies that are a bit more scrappy in terms of resources that have gotten their hands dirty, even if they come from a different, different space. It's not rocket science. B to B SaaS is not rocket science.

AI assessment note: “Stage. Um, anytime. I, I think the, the, the category Is not that relevant.”

Q I said that kind of what would you advise others when you think about advising yourself? You know, you've had an incredible spell at RAMP, and it's an incredible journey to date. What do you know now that you wish you'd known on day one at ramp?

A Oh man, so many things. Um, I think that one of the, we, we did a lot of things right at ramp. I think the things that we got wrong were always around hiring and hiring is probably the hardest thing to, to get right. But it's especially hard when you don't know what you actually need. Um, and the biggest, the biggest mistakes were probably on, on, uh, on, on go to market earlier on, you know, we, we hired people who, who had seen success in growth. And, and it's hard to disambiguate, like, what was your role in that growth, um, versus the company? And also what was the go to market motion of that company compared to the go to market motion that we, we, we strive for. And so, um, you know, growth means a lot of different things. Is it, is it lead gen? Um, is it, is it performance marketing? Um, is it brand? Is it sales? Is it outbound? Is it customer success? Is it account management? Um, is it product led growth? There's a lot of different combinations. And so, you know, people hire their first go to market leaders, and I'm sure you have another growth podcast that we can, we can chat through. They often make a lot of mistakes there. And it took us a while to figure out the right combination, especially because, you know, ramp is, is both sales driven and product driven and marketing driven. And we have like, you know, what we call product less sales. Um, and so there's, there'…

AI assessment note: “be super clear on the strategy, hire and hire more Um, more IC level people”

Q like, go sponsor another event, and a lot of marketing is, like, ah, kind of intimidated by product, especially if it's kind of engineering heavy product teams, and there's a chasm often. How do you encourage synchronicity between the two, where they can work together effectively in that way, whether it's messaging for landing pages, whether it's telling press the right story and messaging, How do you create that alignment?

A We have a culture at RAMP where even if you're not in the team, you can, you, you can Advise and leave comments and suggestions to other teams. And we build in the open. And so what I, what I mean by that is like, if you're a salesperson, you can go into my product spec and leave a comment on my product spec with your opinion. That is welcome. And same, same thing. If a product marketer is designing a great landing page, you can have an engineer comment on that landing page and be like, this, this value prop doesn't make sense to me. And what, what, what that does is it gives everyone visibility and what everyone is working on. So there's trust because oftentimes trust gets decreases when you don't know what the other person is doing. It also just lets people be empowered in terms of, of, of, of giving feedback and, um, that slows some things down or it's like a bit harder to manage. Uh, but long-term I think it like leads to like much better craft. And so yeah, the engineers understand end to end how to launch the product as well as the product marketer. Product marketers have full access to all the decisions we're making on the product. They're, they sit down with us in terms of user research, and that's important so that they can actually craft the good market motion. So there's always going to be a tension, um, but that tension is like greatly mitigated. If you have shared …

AI assessment note: “gives everyone visibility and what everyone is working on. So there's trust”

Q Can I ask you on number two, it's hypothesis. What was ramps hypothesis and how did it change?

A So our hypothesis from the start was that finance teams were equipped with tools that did not work for them and then incentivize them to spend much more time. And, uh, spend too much money. Because of that, their employees suffered by having to jump through hoops for expense reports and having to understand accounting speak to even like submit those. And everything was just backwards. It was backwards in terms of control. It was backwards in terms of incentives. Um, and so our hypothesis was how do we give a product and a solution to finance teams that helped them spend much less time managing expenses and made the right decisions for their business in terms of spending less. That hypothesis You know, was, was kind of a positioning statement around like the card that helps companies spend less, uh, which was a great anti positioning against the status quo. I think that over time, you know, we, we fine tune those hypotheses. So for example, for, for the first version of our product, it was all about like receipt hygiene, like finance teams chasing people down for receipts. And so we just doubled down on just that hypothesis. What if ramp became the bad guy? What if ramp, um, automated the receipt collection Process. And the finance team was actually the good guy. Just point to RAM saying this is RAM's fault. It's not me. I'm trying to be the good guy. Um, and that hypothesis wor…

AI assessment note: “I think that over time, you know, we, we fine tune those hypotheses.”

Q I clearly just quote prior guests who I think are smarter than me, but Glenn Coates, who's VP of product at Shopify said, the day the founder relinquishes the title of head of product or CPO is the day the company dies. Do you agree with that statement?

A Yeah. I listened to that and I love that. Um, I, I don't agree. And again, this is the Shopify, you know, obviously, you know, Toby's like very involved in the product surface area at ramp. I think we, we have, um, Slightly different approach. I think that the, our founder Eric is very focused on our vision, very focused on our brand, very focused on our marketing and our story and our positioning in the market. Um, and it has a very strong sense of, of what we want to be as a company and a very, very high bar for who we want at the company, how we get there. I don't think that it's necessarily super important for the, the founder to, um, to have the strongest opinion. I think that they need to shepherd Uh, the culture to get there. They need to hold the teams accountable for high velocity. They need to be able to opine on what looks good and what it doesn't. What is a good decision, a bad decision, but you need to have an empowered, uh, product team and tech team that actually calls the shots in terms of the sequencing. We've done well with, with kind of our CTO cream, uh, wearing more of that, that product hat. Um, and I think it's, it's, um, um, yeah, I think it's worked well for us so far.

AI assessment note: “I don't agree. And again, this is the Shopify”

Q we think about the process now, you said number one before, did you have impact background and go in depth? Totally agree. Number two, second round. Do you put in the work take-home exercise? What's included in the take-home exercise? What do you want to see? Is it on your company? Is it on their old company? Is it on a different company? Can you help me on that one?

A We do cases that basically are, like, lateral things about RAMP, so they're about something that we would never do, so that we never really, like, steal people's work, but something that is, like, somewhat relevant to RAMP, so that the person can actually start thinking about RAMP, and, and, and oftentimes they get excited about the problem And they're like, oh my God, I really want to work at this company. And so it helps them just start understanding a little bit of our space. Um, but typically it's about, you know, a new product that is working or not working and what they would do about it. What I look for there is just like, did the person put in the work? Are they super clear? And are they able to like influence a team? Cause largely what a product team really does with the engineering design team is like, they're the ones advocating for something and influencing teams. And so if you can't influence me, that this is a good idea. Um, you're not gonna be able to influence the team.

AI assessment note: “We do cases that basically are, like, lateral things about RAMP”

Q How do you advise them on how to let go?

A I think the moment that they join, um, be very clear with them. Like for the first month, I'm going to micromanage you and I'm, and you're going to shadow me for everything that I do. And then the moment that you know that they got it, you need to step away and empower them and let them make mistakes. Oftentimes they either like give everything and then, but they don't let go. And so the person's super disempowered or the person actually doesn't have any of the context to make the decisions. So be a super micromanager the first month and then signpost that with your hire and then step off and step out and be very clear on the outcomes you're trying to drive.

AI assessment note: “be a super micromanager the first month and then signpost that with your hire”

Q You said that you kind of followed the energy and didn't really know where your passions lay in the first instance. It's the same for many people. Knowing what you know now and where you are now, what would you advise people who maybe don't know where they should spend their time and their energies?

A Figure out, like, what gets you excited? Um, I mean, you do, you do have energy throughout the day. Like, what, what is that, right? And for me, it was, it was all about Building great products and seeing metrics move and winning. Like, I think, I think I'm a very competitive person. Um, and so figure out like, uh, the right industries for me. Like when I think about ramp, for example, it's like probably the most competitive space. Um, it is extremely metrics driven. I mean, everything is metrics to the point of whether, you know, it's our risk or fraud losses or, or, or conversion or, or net retention or interchange margins. And find the industry that, that will take that, that box for you. Um, also just note like what lowers your energy throughout the day. Like what really bothers you? You know, is it like large meetings? Is it bureaucracy? That was for me for sure. And so find the, the industries of the companies that don't like meetings, that don't like bureaucracy. Um, I think at the very least you can actually cut down a lot of things and, and, and that makes this, the selection process a bit easier.

AI assessment note: “Figure out, like, what gets you excited?”

Q Can I ask you on number two, it's hypothesis. What was ramps hypothesis and how did it change?

A So our hypothesis from the start was that finance teams were equipped with tools that did not work for them and then incentivize them to spend much more time. And, uh, spend too much money. Because of that, their employees suffered by having to jump through hoops for expense reports and having to understand accounting speak to even like submit those. And everything was just backwards. It was backwards in terms of control. It was backwards in terms of incentives. Um, and so our hypothesis was how do we give a product and a solution to finance teams that helped them spend much less time managing expenses and made the right decisions for their business in terms of spending less. That hypothesis You know, was, was kind of a positioning statement around like the card that helps companies spend less, uh, which was a great anti positioning against the status quo. I think that over time, you know, we, we fine tune those hypotheses. So for example, for, for the first version of our product, it was all about like receipt hygiene, like finance teams chasing people down for receipts. And so we just doubled down on just that hypothesis. What if ramp became the bad guy? What if ramp, um, automated the receipt collection Process. And the finance team was actually the good guy. Just point to RAM saying this is RAM's fault. It's not me. I'm trying to be the good guy. Um, and that hypothesis wor…

AI assessment note: “our hypothesis from the start was that finance teams were equipped with tools”

Q When we think about, like, hypotheses in product, so much of it, for me, comes down to this kind of age-old question of, like, art or science in product. When you reflect on the, is it an art, is it a science? We mentioned that, kind of, when do you pull a product? Again, slightly art, slightly science. How do you reflect on, is product more art or more science?

A It's funny. Like I, I, so I, I have a standard scientific process for product development that I've like tried to apply across the entire teams and yet like different teams perform in very different ways. And so that kind of shows you that like, it is more art than science. And I think art is a big part of, of what we do at ramp when we, our biggest advantage is actually, um, it is velocity, but it's also the, the design experience of our product and how, how, Um, delightful it is to, to finally work in a solution that is much more consumery in terms of its design than typical B to B SaaS. And that takes a lot of creativity. And so I would say, you know, I spend a lot more time on, on the art part of product, which is, uh, which is almost like painting on a canvas in terms of, of, of prototypes and designs and, and, and flows. And I think that's, that's a, that's how you build great products is really spending a lot of time with an empowered design team, testing and iterating with our, with the customers.

AI assessment note: “that kind of shows you that like, it is more art than science.”

Q How do you advise them on how to let go?

A I think the moment that they join, um, be very clear with them. Like for the first month, I'm going to micromanage you and I'm, and you're going to shadow me for everything that I do. And then the moment that you know that they got it, you need to step away and empower them and let them make mistakes. Oftentimes they either like give everything and then, but they don't let go. And so the person's super disempowered or the person actually doesn't have any of the context to make the decisions. So be a super micromanager the first month and then signpost that with your hire and then step off and step out and be very clear on the outcomes you're trying to drive.

AI assessment note: “step away and empower them and let them make mistakes”

Q Would you rather, I'm, I'm going off piece, but I'm enjoying this, like, peppering of questions. Would you rather have someone who's worked in the same category before, Or someone who's worked at the same stage of company that you are before?

A Stage. Um, anytime. I, I think the, the, the category Is not that relevant. You know, I come from more consumer than, than B to B. And I think that's actually an advantage because you're focusing on metrics. You're focusing on conversion. You're focusing on models like lead scoring and lead routing, all the things that like B to B companies have done really poor job on. So I think the stage is actually much more important. Oftentimes if you hire someone from a larger company, they come in and they, they just get shocked. Like, where's, where are all my resources? Like I have, I've never been used to doing the work myself. Like, what do you mean? I don't have like, People just like supporting this one thing. And so I would much rather actually hire people who, who are coming from, um, uh, companies that are a bit more scrappy in terms of resources that have gotten their hands dirty, even if they come from a different, different space. It's not rocket science. B to B SaaS is not rocket science.

AI assessment note: “Stage. Um, anytime. I, I think the, the, the category Is not that relevant.”

Q Having done many of these now, when you look back, What are the biggest mistakes you think you made? And I guess if you were to advise other founders on doing two-week sprints, what would you advise them knowing what you do?

A I think that people tend to put too much emphasis on like the task, the system, um, the meetings and not enough on just like, what do you need to achieve those goals? Um, and so, and product managers Oftentimes become project managers where they'll like do the work on behalf of the engineers that just like simply don't want to do the, the, some of the work that we're putting them on, on them. What I mean by that is, um, don't write tickets on behalf of people, like let them write their own tickets and give them the goal, not necessarily the task, have them manage up. Like if you, if you, if you're constantly asking them for updates or you're constantly asking them like what's blocking them, you're, you're disempowering them and you're, you're, you're emphasizing a culture of, Of, of, of you project managing their work. Instead, like every single person at RAMP owns their work and manages their own project and they're managing up. This is the risk that I have. This is the question that I have. This is the key decision that I need you to make. Um, and that just creates a culture of just empowerment and velocity. And so don't treat your employees, uh, like babies, um, because they will become babies or you will hire babies or you will meet, retain babies. Instead, like treat them like founders themselves.

AI assessment note: “give them the goal, not necessarily the task, have them manage up”

Q at odds because you're welcoming discussion and debate and leaving comments on my product specs and everyone being able to say anything about each other's work with What was your core strength? Which is speed, speed, speed. Yeah, cute, you've got an opinion, but fuck off and let me do my work is kind of what I'm thinking. How do you retain velocity while welcoming everyone's opinion on your work?

A You can, you empower the decision maker. So I actually think that like more data does not slow you down. I'm inundated with, with data. I mean, I, we have, I'll tell you, we have Slack channels with every single negative feedback we get from customers. Every time we lose a deal, there's a, there's a, there's a Slack, like, why did we lose a deal? Who did we lose it to? Um, and why, you know, was it a product feature? Was it a timing feature? Was it a pricing feature? Whatever it is. There's so much data that's, that's happening. Um, and in specs, there's so many comments. I think that that makes you Better at making the decision. I think what you need to do, though, is you need to empower the person to make the decision, and when the decision is made, you need to commit, even if you disagree, and you need to align on the outcomes. If a PM gets 16,000 different, like, comments on the doc, and you read all of them, you say, I'm still going with this decision, then you commit, you hold that PM accountable to that outcome, and then if the outcome works, you can reflect back on those comments, and you can change your mind. Or if the outcome didn't work, the PM should reflect back on the feedback that we're given and we'll have a post-mortem on it. So I don't think more data slows you down as long as people are again aligned. The culture can't be like, I just want to share my opinion…

AI assessment note: “You can, you empower the decision maker. So I actually think that like more data does not slow you down.”

Q In terms of learning from your hypotheses there, postmortems are a crucial part of any product team. What have been your biggest lessons in terms of how to do postmortems well as a product leader?

A A lot of documentation, um, blame, like no blame. Um, I think it's actually like you need to have curiosity. You need to engage with, with questions. You need to have a fairly cross-functional team that everyone that's effective be present so that you build trust. Um, with those teams, oftentimes, you know, when you screw up, it's not the engineering team that, that is affected. It's the customer service team. It's the account manager that had to apologize to the customer. And so, uh, bring those teams together, share the data, be upfront with the facts, um, then open up discussions around, like, what could we do better? What are some of the ideas or hypotheses for what we could do better? And then take action items that are very clear, um, and timely, Uh, to address those things so that the post-mortem doesn't happen again. I think that's the most important thing is, like, screwing up once, it will happen. We will screw up all over the place, and we have. Screwing up twice on the same problem cannot happen.

AI assessment note: “bring those teams together, share the data, be upfront with the facts”

Q got our goal. We've got our hypothesis and the third was right to win. Why are we uniquely positioned to do this? And the honest truth is like, is anyone really uniquely positioned to do something when you think like, Google, Facebook, in this case, Stripe, anyone could allocate a insane amount of resources and come and take your lunch. No? Am I wrong? How do you think about that?

A The reality is that it's very hard for large companies to, to actually innovate. Um, and you can see this with like, when you're launching a second product in your, in your company, it's, it's, it's hard and you're And still hard. I mean, think about like, if you have a huge company and a huge go to market engine, and you're trying to launch a new product, like it becomes exponentially harder. And why is that? You have, um, you have board expectations, which are very short term focused. You have, um, a go to market team, which is incentivized with one business model. You have an understanding of one specific customer profile. And then you have like one core DNA of, of, of engineers that are all like incentivized to, to, to build organizations under them. And so it's hard to just like break all that. You need to break sometimes the, the, the actual business model. You need to break the go to market motion and focus on a new customer. You need to break an engineering and product and design, uh, work structure to create new teams. And that's really, really hard. And so you've, you've seen that, you know, um, uh, how, how has Amazon actually been able to launch financial products? Um, it's, it's been hard. How has Salesforce actually been able to make, um, their acquisitions super successful? It's hard because they do seed based, um, uh, incentives. Whether it's like Facebook tryin…

AI assessment note: “The reality is that it's very hard for large companies to, to actually innovate.”

Q thinking process, number six was risks, which is why would we fail? When you think about that, talk to me about how do you know when to give up on a product and when it's a fail, and how do you think about That core segment of why we fail in the product strategy session. I love the statement here, double down or pivot is hard. What does that mean?

A At RAMP, we've, we've shipped a lot of things and I don't think we've been like particularly good at like taking things down. Um, and the framework that I have around, you know, do you actually like sunset the feature or the product or do you keep it is one of like, what is the cost of keeping that up? And I think until, until very recently, we were able to hide the complexity of, of new features and we only open it up for certain segments, um, of, of, of customers. I think if you get to a place where you're, you're cluttering your application or you're adding a lot of complexity and that like reduces the stability, then you should really think about like sunsetting these features. And so for me, I would much rather have a lot of features that we can turn on and off based on the segment and based on the needs and continue testing rather than, than, um, deprecating. I think in terms of like doubling down, you know, we, we should, we should be very clear around how confident are we that the next hypothesis that we have Will pan out and how, how much effort will it be to test that new hypothesis? And oftentimes, You know, the first hypothesis was, was your, your, your main one, and you might not have a second one that's that strong. And if that's the case, then like, don't double down.

AI assessment note: “the framework that I have around, you know, do you actually like sunset the feature”