Climb By VSC: Episode 39

Vijay Chattha: Everybody welcome to another episode of Climb by VSC Ventures. I'm really excited today to have a long-time buddy on the show. Ryan Gembala of Pathbreaker Ventures. I met Ryan, I want to say 10 years ago. Why don't we jump into it. Why did you start the fund, and tell us about what you're looking for in that thesis?

Ryan Gembala: Pathbreaker is the manifestation of a career span. Across the three pillars of the company building process, building funding and achieving liquidity. At Facebook, I worked on the liquidity side as a deal lead on the M&A team. So I was one of the handful of people at the time in 2014 and 15, helping to lead M&A strategy and deal execution and that was an era where Facebook was heavily investing in emerging areas of computer science, internal AI, computer vision, sensing technologies, etc. I saw the writing on the wall that these technologies would pervade every sector of our planet much like software had over the prior three decades, these emerging technologies would do so over the next three or four decades. And that's the thesis of Pathbreaker is investing in deep, deep technology and deep people that are driving these technologies across the industry. When I started my career as a founder and social entrepreneur, I learned capital allocation at the University of Chicago. academically and then did an adventure for five years from seed to Series B and then jumped into the portfolio to get closer to engineering and product after we invested which is the context in which I met you and your great firm BSc and then went to Facebook. I've been working across sort of these three areas and now we bring those experiences and relationships to bear for founders when we partner early with operators.

VC: : Okay, awesome. Let's talk about that journey. So leave Facebook, which is really a social media consumer company. And you're saying to yourself, Oh, I'm going to do deep tech now. So what was that? Like? How did you go from that to sourcing. How would you find? How did you build your network in the early days?

RG: Yeah, so I had been in the Valley for I guess five or six, maybe six years at that time. It doesn't take long to build a network in the valley. If you're active and you hustle, right? It's an area that awards if you have been in the valley both operating, investing and then doing m&a on a daily. So the network got big pretty quickly and then a lot of other people from from University Chicago Business School, you know, we're at large companies and, you know, if you're in the flow, you're meeting lots of people and people are starting new companies every day. So from the deep tech perspective, I would say, you know, in 2015, when we started we were one of the first deep tech firms in the Valley. And there were very few with the appetite to invest in hardware software systems. So Bill, the first investment I made out of property or fund one in January 2016 was a robotics company called Simbi robotics and bringing computer vision and mobile robots to grocery and data collection on the shelves. So when you're one of the few, people find you and I was having large, very well known venture funds send me AI deals in 2015 and 16 because they weren't investing in AI at the time, which was interesting.

VC: Amazing. And so well first of all, Cindy has gone on to some great things I just saw. Was that what I saw? Was it last week?

RG: Yeah. Cindy just raised the $28 million Series B which was led by our friends at Eclipse Ventures, which I like to say affectionately is like a heavyweight version of Prop breaker. They're 4 billion AUM and they like full stack hardware software systems just like we do and and so they're great partners and Simbi has publicly traded customers like BJs and SpartanNash to family owned you know, three to $20 billion privately on groceries that are fighting for every dollar and every dollar in groceries won or lost on the shelf. And so a robot with computer vision can tell you if something's out of stock in near real time relative to a human that wants to do that work but doesn't have the reach and scalability to do it as frequently as a robot and computer vision.

VC: Got it. So for every Cindy out there, my guess is there's probably at least three or four more that we're trying to be Simbi, maybe another X number in China. How much is it just a founder bet? Are you too early to even test the technology? Is it all about the referrals where that person is coming from and you know their pedigree is going to be they're going to be able to make this in scale, like walk me through that.

RG: There's no one recipe that works every time. And there's no one right way to build a company. So I always tell founders Look at this. You know ever ever you've company is its own snowflake and what works for Cindy might not work for Bernbach you know, which is a robotics company that's preventing wildfires that we we've invested in and so, in the case of what I look for, I would say it starts with like highly specialized people. And in Sydney's case, you had two roboticists from Willow Garage, which was the early Google funded robotics thing. Take with Zod and not officially Google funding but early employees that had been really successful. They wanted to build robots, and then Brad the CEO was a Senior Product Manager at Silver Springs, which was a data business in the energy sector, traditional industry and Brad was a senior PM and ran a flagship product for them. And so I think of deep product experience and, sort of deep technical insight. That's an ideal combination where hopefully someone on the team has the ability to sell to early customers as well. And when you have that, that combination of salesmanship and deep engineering differentiation, or technical differentiation and the and having built products at scale before that's that gets me that gets me excited enough to spend time with the team and then it becomes around. For us at least, are they building in the direction that the world is going over the next at least one decade, ideally over the next three decades? And in the case of Simbi, getting hourly labor in some of these industries is really challenging. The turnovers can be, you know, 200% and there just isn't enough staff to do all the work that you would need to do in an operation like this so that those trends weren't improving. And then you know, people are consuming more than ever before. So, you know, we like the direction of grocery and the need for more tools that can turbocharge the work inside an environment like that. And then yeah, I drove out to Concord, California and saw a robot that was doing basic traversals in a grocery store. I called you know 10 People from business school that were at potential customers or existing customers and did a lot of work and I always say you know, we let founders take us into the industry is best suited for their their innovation. And we don't pretend to be experts in every industry. But we'll do work. We'll do a lot of work quickly to try to learn as much as we can and get conviction.

VC: Got it. And then so talk to me like first check in. Where are you guys investing now? What's the right time for the founder to come to you?

RG: Yeah, we invest in pre seed and seed stage investments and, and I try not to put too many parameters around what a company needs to look like for us. I think, by definition, we're investing in anomalies. And so we need to be prepared to be flexible to what those might look like and so we're happy to be the first check in and lead a pre seed round. We're happy to be the first check of a seed and help signal that we're excited about it and help the founder pull together the rest of the round, whether we're officially elite or not. So we don't need signals from other investors to get to invest. But we always invest with our friends and colleagues and in whether it's other funds or angels as we put rounds together.

VC: What are you? What are you advising founders now that we got interest rates higher. It feels like that's a knock on deep tech. I mean it is a little of anything that takes longer to get to revenue. Seems like it's having bigger challenges like are you a new check a new company comes in and do they get two years of runway? is it changed the strategy on burn like how are you advising founders?

RG: Yeah, that's a great question. So in the zero interest rate days of deep tech from let's say 2016 to 2022. You could, you could build and make modest commercial progress depending on your sector or a lot of commercial progress. It really depended and then you would get rewarded maybe for all of that or maybe just the technical piece. Or the commercial piece. And then there was money for deep tech projects that were just making engineering and technical improvements over time and building a really interesting system that would one day generate a lot of revenue. And while that's still a valid way to go about solving a really massive global problem, it's much harder to raise capital and an environment where interest rates are six and 7% for that type of business. So, you know, for us, the change that we that I've been talking to all of our founders or potential investments in is, is if you look at like the precede asset allocation or resource allocation in a in a plan, no longer can you get to a seed round just by making engineering progress with a ratio of, you know, 100 to one, maybe the CEO is spending some time signing otherwise or getting mo use or working a commercial that no longer really holds. Sometimes the founders can do the initial sales, but if they're not spending 50 to 75% on commercial activities, the engineering progress won't be rewarded by the time you need to go raise. So I would say whereas historically we would have been fine with a lack of commercial orientation on the founding team in this environment. It is a requirement for us now. And that might not be that might not be an individual like this. It's probably not like a business co founder, but it's it's at least someone on the founding team, usually the CEO that has maybe some sales background in addition to product or in addition to engineering or they're very comfortable in that role to you know, and without that it's really challenging to to show the kind of traction in this market that's going to that will allow a larger number of investors to consider investing in your pre seed or seed stage startup.

VC: Does it make sense? How about runway, like if you're on a new deal, are you thinking differently about how long they need to get to the next round? I don't know if you've thought differently about once you've cut the check how quickly you expect the next round to come together?

RG: Yeah, it really depends on the company. I mean, I hate super prescriptive adventures. I think that it can lead you astray and allow you to say no to things that don't fit your box when you should do them. So I really let founders educate me and I try to maintain an open mind as to what the right plan is. Now if I see if I have some thoughts on maybe risk mitigation or opportunities for now. I will of course share them but I want founders to filter any advice they hear from me relative to what they know that I don't and I'm really comfortable with that information as symmetry. So all that to save Ajay, I'm not super prescriptive. 18 months, 24 months, nine months, depending on the founders, you know, 12 months might be the right answer for another founding team. It might be three years depending on what they're trying to do.

VC: And when you look at robotics now. Right? So and you've probably looked at a lot of companies, where do you see the opportunities like what gets you most excited in this space right now? Like, are there certain verticals where you're like, Hey, that's a lot of progress. Like maybe it's retail or something semi-like looks like there? There's things happening here. Maybe there's not the need for 20 more companies to be funded in this space. Here are the Greenfield opportunities, or what do you think of like, what's your thesis like in 2023?

RG: Yeah, absolutely. I think robotics is arguably the most interesting place to be investing right now. 75% of fat breakers investments touch hardware. It's really hard to solve globally important generational problems with software alone, I would argue, and so if that's your goal, and venture is to invest into generational businesses that are 1020 30 years old, I think there's a whole sorry, 1020 30 plus billion dollar companies. I think there's a whole field of hardware oriented businesses that, you know, eventually might have monopoly style potential or just without a monopoly just would capture so much value being full stack. And robotics to me represents an opportunity to build those kinds of full stack value capture businesses across industry. So we're investors in a company called hyphen, which builds robotic may clients for the restaurant industry. Burn bot, which builds robotic systems for wildfire prevention. Inevitable which builds clean propagation systems for global ag both field and indoor presa which builds clothing care robots, that will dramatically reduce the carbon footprint. So right there that's agriculture, laundry, wildfire and restaurants. And I'm not an expert in any of those industries. But you know, I'll tell you what those founders are. And I like following them into those industries that might be overlooked, might be traditional, and historically don't have the same kinds of balance sheets as a tech company. Would like to make investments in these areas. So often, we end up competing with very few people for a long time. You know, I think robotics is while it's challenging, it's certainly challenging, and it requires more capital upfront. Over the long term. I don't think as much I would argue it can be more capital efficient than a software business. And we've invested in 30 robotics companies, and only one software company for robots. So I think that's the other thing people like to dabble and venture off in software investment horizontally across robots. We've invested in an incredible team that's doing that called foxglove. With Adrian McNeil who was at cruise and built their infrastructure for visualization for many years and that's a really it's a, I think, a lot more challenging to invest in software for robots than it is to go take a full stack problem in an industry.

VC: Wow. Got it. And as you see, like the last four years have been crazy, right? We've had a pandemic. We've had the markets provide too much cash and too little. You've had people staying at home and not going back to work due to the pandemic or possibly stimulus depending on who you ask. That drove a labor supply shortage, which sounds like it is getting filled a bit in the last year hospitality and some areas maybe not fully. Where does this fit in terms of the era of robotics is like what are what are the tailwinds here, and like, I just want to kind of have you like, reflect a bit on where we are. If you're like, look back, you're gonna write a book on this one day, and what will this era look like? And what will sort of move the needle?

RG: So I think robotics so far as being two eras, from the applied side, so I'm going to start my era when app rager got going in 2015 from 2015 until COVID robots were relegated to the innovation groups and nothing wrong with innovation groups. At large fortune 500 companies, but that's where these products sell. And in the history of our planet and species. You couldn't have value. If you were a VP or an executive at a large grocery store or Procter and Gamble or John Deere, you couldn't evaluate a robot to solve your problem prior to maybe 2013 1415. So now you have this opportunity to solve your issue, solve whatever problem you're facing with a robotic solution or a deep tech solution. But no one in your organization knew how to evaluate that, how to procure it and or how to support it. So the innovation teams were era one in robotics, and that was 2015 to 2020. Okay, then COVID God smacks. All of us punch ourselves in the face, and we're left with massive shortages. You know, labor will stay at home and then at the same time we are facing a recession with pressure to still grow companies. With all these factors in place it really provided an ideal two things happen: one you had to consider automation solutions to survive. You have to consider digital solutions, remote solutions, automation solutions to survive as a company. And then you were forced to say all right, the past five years we've been looking at robots and our innovation group looks like they work. Now we no longer have the luxury to keep evaluating and getting data. If they work, they work and let's deploy that. So we've seen now the space to is a move from the innovation groups to the C suite and evaluating robotic solutions at the C suite level to then with much less data over much shorter periods of time decide to scale on to reach chain wide deployments within a robotic startup. And we've seen that you know in this year with Cindy announcing a 237 chain wide expansion with a customer called BJs Wholesale Club which is in the category of Sam's and Costco and BJs. And BJs has a $9 billion market cap publicly traded company and the executives were really supportive and blown away by the data and said yeah, absolutely. This works at 15 stores. It's going to work. It took him 37 stores and so time to roll it out. So that's I think phase two now is as C suites are being forced to grow revenue and evaluate those constraints they're facing with labor and supply chain. Robotics, as in automation, are our solutions for that. And the data supports that these robots can work at scale.

VC: Yeah, totally makes sense. And we're seeing it every day. Like you go to SFO airport, you see Cafe X, the robot coffee maker, and I feel like it's, you know, you're gonna start seeing more of that in retail stores at Walmart or wherever we're, you see, it's just interesting. Like, it seems like the visual moment and so at least on the enterprise side, consumer sides are coming in more. How are the companies that you work with thinking about selling? When, in some ways, these jobs are, these are going to replace some human jobs in some cases, right? And labor supply shortage is one way in some cases, it's there going to be humans that used to do this job and now it's not how do they have challenges with their with their with their, the message to the customer or is it just like the shortage is so bad that it doesn't even matter anymore? Because if you remember, like 2016 It was like right after Trump got elected I don't know if it's coincidental or not, but like, all of a sudden everybody's worried about robots taking jobs. I'm gonna remember this is like the same thing.

RG: I remember this vividly. We lived there in 2015 and 16. This was the fear frankly, this was a fear of mine and I wouldn't invest in a startup whose value proposition was solely labor replacement. Going from three employees with our robot you gotta want I want to invest in those types of companies, for fear of a that'd be really hard to deliver on and be, you know, that's not the kind of company necessarily that I want. To go bill. What's happened instead, is that the challenge has really been meeting demand or getting the work done that needs to be done. And so companies are buying robotic solutions not to replace labor, but to meet production that otherwise is throttled because they don't have enough labor. So in the case of gray matter robotics, they build an autonomous sanding and spraying and finishing solution for US manufacturing and they have a customer that makes a very popular consumer product that said, you know, we've got demand to make three times what we're able to per week, because we can't get enough labor in the production lines to do these dirty, dangerous sort of dull road jobs. And with gray matter, they can now meet demand. So that's been really interesting, I think, robotic solutions that just perform one task over and over again. Well, one that's missing an opportunity to capture a dataset that can then be generated that can then be sold to that potential customer versus someone else. So I think there's what when you have hardware in a customer's location, it opens up myriad opportunities for future products and opportunities to monetize and if that hardware robot performs and matches expectations, it's rare that it gets removed because the relationship between the customer in that in that startup ends up becoming so strong. And there's so much trust there because there've been a lot of people that have tried to deploy robots and hardware in environments that haven't worked when you find a team that can perform and build a product that doesn't fail, man, they just have continuous opportunities to solve problems for their customers.

VC: Yeah, it makes sense. And like So robotics is the core of what you're doing. But like there are some crossovers with other areas like climate. So can you tell me a little bit about some of the companies that you're working with and that space and what's your hunt if you have any particular other additional pieces ideas there, but love to hear more?

RG: Yeah, absolutely. I mean, that when you're talking about technologies, by definition, they're horizontal across use cases in industries. And so we've made probably nine investments that could be considered climate investments. We lead the preceding round of running tide, which has been using automation solutions to grow carbon-sequestering moisturizer as well as kelp to sequester carbon in the open ocean. They work with Microsoft Shopify stripe Chan Zuckerberg Initiative, and as raised 70 plus million dollars from lower carbon and Founder Collective and others and we had the pleasure of writing leading or precede, you know, you couldn't saw you can't sequester carbon with droves of people out in the open ocean you need automation and machine vision, AI, and automation solutions to do that. Tree. Swift is an example of a company out of the UPenn grasp Lab, which a team of three PhDs had realized that you could use drones and sensors deployed below canopy in a forest and generate a dataset of every tree on the planet. Its health Size value, relative to the state of the art today, which is crews of people that literally walk for us with tape measures and clipboards and so if you're trying to value a timber plot for a timber owner or for removing carbon, we can do that at a scale and speed that's just unprecedented. Today, all the way to a company called Burn bot which I mentioned earlier, burn bots based in San Francisco and the CEO has lived in Tahoe for the last 10 or so years. He was assessed the successful entrepreneur Uber entrepreneur prior today that if you want to prevent a wildfire, you have to use a crew of people with torches that after clearing brush manually walks align with a drip torch and prays that gusts of wind and weather conditions stays such that the fire doesn't escape and explode and dramatically you know, torture millions of acres. With that technology drip torches and prayer you can't burn preventatively if a forest is near a school or a neighborhood or power lines, so burn bots built a robotic system that lays these charred burn lines and eliminates fire fuel. They sort of paint a field with these lines and then a drum comes in and drops and it's an incendiary vol that burns the middle. And about a month ago we announced a partnership with PG and E where pge is using Bernbach to use preventative fire next to power lines and highways and schools. At smokeless we extinguish the fire immediately in the system. So there's no embers there, it's near smokeless and you can burn your round. That's a phenomenal use of automation robotic computer vision hardware technologies, we're going to be able to potentially save millions of millions of acres. We have 20 million acres that should be burned today. And today we only do 10,000 A year that does those types of technologies get me fired up. When did you take deep tech and now you're using it to literally save the planet?

VC: That's amazing. And sort of let's talk a little bit about this process now. That these startups are going into fundraising. So it was like what from your Is there any specific metrics you could say hey, this is generally where we see series A milestones changing are companies in the portfolio raising the series B right now? Are they waiting? Like I think founders are very curious about like we hear it all the time. Like what are the milestones in today's funding environment, see the fair amount of capital at seed not that every company funded but but the A and B and c's are totally different stories?

RG: 100% I mean, we like it. I think many of us have companies raise hundreds of millions of dollars, almost a billion dollars in 2021 and series A, B, C, D, capital was prevalent. 2020 to 2023. The B, C, D capital is dry, and A's are really tough. And valuations are back to the 2015,2016, 2017 era. So creates a bit of a challenge for pre seed and seed should you be paying if with capital and competition for deals should you be paying series A prices for precede risk or seed stage risk? I don't think that's healthy for anyone. What metrics does the startup need right now to raise a Series A, I think to get the conversation going, you need close to a million arr. That's not going to get your round done, but it's going to get the conversation started with a great venture fund. That metric needs to probably have been achieved over the past 12 to 18 months. And the market needs to be really interesting and aligned with where the world is going both from a macro and micro economic perspective. In my view, if that holds a great series he gets a term sheet in six weeks, a couple years ago it was one to two weeks. So it's taking longer, it's probably taking three to three to five times longer if it's going well. And if you're if you're raising while you're approaching a million but you're not quite there you might be it might be three to six months. It's just tough. You know, I'd say the only way anyone fails in our world is if people give up. So if you have conviction if your existing investors are going to support you, you know, don't give up and frankly like a flat round is the new to ax up round. And unless you're growing really quickly, let's talk about the series. B and C right now. Most of those rounds are being led by insiders full stop. Most of those rounds are being led by insiders and it's if you don't have insider support, that's really tricky. This dynamic where the insider support takes the shape of a smaller price round or a convertible note, we're seeing lots of structures, so tranches happening where you know, 10% of the ideal round size gets put together now. And then if one or two salient milestones are achieved, there's a big slug that you know 20 to 40 million comes later. The other thing I'm seeing man is you know, I don't know if you've seen this VGA but at the series even a plus but certainly the BC is the fangs come out with the later stage investors and there's a people are trying to buy 20 to 40% ownership of companies because they have the font sizes to write the check now at a valuation where those percentages are possible. This is a new dynamic, where they're taking a lot more time to do a deal. Okay, so instead of diligence happening in a week or two series B is taking three months. Now after they've done three months of work they have a ton of conviction. Maybe they're the only firm that's done that kind of work. And so with all that conviction, and a big font size, they're dropping, you know, a large check and wanting to do it all.

VC: I mean, we're seeing all kinds of things. We're seeing a lot of much more pressure on the founder's leadership change than ever before and maybe in 10 years, because milestones are so much more critical. And saying what the promising what you said you're going to do at the fundraise to where you get to much more tightly manage the trucks thing is interesting because that's like old school 2011 stuff this right now or 92,004 stuff, recovery stuff, right, tranche because that's how much the market is getting nervous, right, the investor that say, to make sure things are happening and also like let's be honest, like we read a lot of articles about people misusing money, so it's, yeah, there's probably someone out there too on the LP saying, hey, like, you know, before you cut that 100 million dollar check, right, like, let's make sure thanks. So yeah, of course you're seeing down rounds too, right? Like that's not such a deep tech is happening

RG: In some ways, deep Tech was insulated more from the down round than SaaS, I would argue because SaaS got so inflated in 2020, 2021 and 2022. Deep tech didn't really see that we saw appreciation and value of companies but not to the extent that the SaaS multiples exploded, and so this the compression has been severe in SaaS, I would argue but not as much and deep jackets come down a little bit not not quite as severe.

VC: Yeah, again, it's company by company and who raised how much at what valuation right in the last ghostwriters, but, but that makes sense. And that's helpful, I think, to the founders that watch our podcast or hear it. Let's get into a couple of things like maybe a hot take here. I think that's super helpful for the audience. Like, what are you not investing in right now? And I think you'd mentioned it was probably one of the more popular trends

RG: We were investing in AI applied AI from 2015 to 2022 pretty aggressively. And if that strategy made sense when AI was scarce, I would argue at the application layer. So we've had three AI exits already, McDonald's acquired a prince which was using conversational AI and the drive through Reddit acquired spike trap, which was using AI for sentiment analysis and real time conversations. And then relativity acquired text IQ, which was using AI for privileged review, classification and in legal matters. And so we've as a firm Pat burgers made money in AI. But it was predicated on this idea of scarcity where you needed PhDs that represented maybe a handful of people in the world that that had worked in their particular field of AI research that then could get access to training data, whether it's through a customer or some other means that then could sell an enterprise solution to solve that problem with that, those three components. Well, what open AI has done is made the PhDs and the training data available via an API call essentially. So you sort of have a PhD in your pocket. If you want to use a large amount you want to use AI to solve a problem. So you no longer are burdened by your being able to recruit from Stanford or Google to find the PhDs that can do work to build or buy that solution from a startup. So I think generative AI right now, at the application layer, at least is a minefield, it's very hard to find teams that are actually doing something novel. And instead it's like, you know, it reminds me a little bit of like, webs, Amazon Web Services, or Google Cloud, like that was innovative at the time, if you 20 years ago, you know how to put together a data center. That was the strategic advantage now it's not you just make it you just use AWS for storage and compute. No startups are differentiated for using AWS anymore, so I don't think startups are going to be differentiated for using large language models, unless there's something else that's scarce in their system. So yeah, we're not really investing in generative AI applications. That said I made one exception with an incredible team out of AppDynamics called an app edge that's getting access to disparate data sources and, and giving customers what they want, which is really the answer. So they've trademarked the answer GPT and they're building an answer solution. And these were engineering and product leaders from AppDynamics, which Cisco acquired for $4 billion. And, they're specialists experts in their field, but absent that sort of unique unicorn style of ingredients, it's really it's, it's not super differentiated, in my view to be investing in generative AI.

VC: And then how about I mean, there's a lot of money that's been raised for AI funds. Seems like a lot of people are doing the plot like the picks and shovels businesses, some, some infrastructure companies, like how many of those are going to become I mean, how many of them are there need to exist?

RG: I think the most interesting places for pop breaker to be investing in AI is, is on the harbor side of AI. So we're invested in a company called Phantom Radiant, which has been working in AI hardware for a long time, six, seven years. The constraints AI right now is NVIDIA GPUs and GPUs. So for a team that's building novel AI, hardware architecture, that's, that's really interesting. And so as a firm that spends 75% of our dollars investing in hardware, we're a great partner for big AI hardware swings,

VC: Very interesting and I think kind of just to cap it off, like as you're thinking about your career, you've been building this from investor to operator to investor you know, what have you what are some of the like, I guess personal lessons now they can get to that part of the discussion. Like what are some of the maybe I just helped with sort of inspiration is tough time right now and be a founder. It's tough. Maybe as you build your career so far, best advice you are given?

RG: I think my advice to founders to really simplify it is to trust yourself. You're going to have a lot of people in your ear as you build a company. Investors will have access to your ear. Sometimes they'll have influence, but you know your business better than anyone else around you. You have more data about the customer, whisper the competitive concern, interpersonal dynamics amongst your management team that might prevent some product idea that you've heard from an investor or an advisor. You're in the best position to make these operational decisions. I always tell founders, I'll ask a lot of questions I'll share from my experience. But if you end up implementing 0% of an idea that I've shared, I'm going to assume that's the right answer because you have the data. I don't feel like founders need to follow venture capitalist advice. I feel like founders need to listen, they need to sample and then they need to make the decision and sometimes they follow the advice because they know that's the right answer. And other times they don't because they also know that's the right answer. I'm very comfortable with that, that level of trust. If I've done my job and backed the right founders, they're going to do well in this area. And I think founders should just trust themselves and trust their gut on people. And at the end of the day, you know, I think a venture capitalist's job is to help founders realize their full potential. We should help clear paths, you know, kapow breaker wants to back founders in pursuit of generational impact, they'll go off path to do so. And if we make a contribution, we're helping to clear paths through bringing more capital into the company through introducing a customer, introducing a great hire, and sometimes, you know, sometimes working across the cap table to rally behind the founder or bring in additional investment or be supportive of the founding team. So I think my message to founders is they're in the best position to know what the company needs. Seek input, but at the end of the day, it's your company, and we have to trust you. So trust yourself.

VC: Yeah. That's a great piece of feedback. So Ryan, again, thanks for the time today. You know, just to end it up. Who else should we get? On the client podcast? For some folks and inspire you in this work

RG: In climate you should have Steven Chen from Tree Swift on Steven has a background as options trader and ag and then a PhD. in computer vision at UPenn grasp lab. And what they're doing in forestry is completely novel under the radar. Lots of interest from investors and what they're doing but most importantly for customers and they've grown 25x year over year, and are solving really hard technical problems in pursuit of generating this dataset of forestry for both timber and carbon. And then I would say on the robotic side, you've got to have Brad will Gulia from Simbi on, Brad has deployed and built more robots in service robotics. Then I think anyone where robots are operating during store hours around customers, as well as working with employees and generating a novel dataset. Cindy as robots operating right now as you and I are speaking on four continents and across half the United States and that kind of scale up delivering a full stack robotic solution with AI and mobile robotics is really hard to do and so he'd be a great person to challenge.

VC: Amazing. Ryan, thank you so much for the time today. This is great. Everybody checks out pathbreaker ventures through building an awesome company and robotics. He's the man looking forward to doing more deals together and appreciating your time today.