$5B in Venture Deals: What Founders Need To Know with Nick Washburn of Intel Capital

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There's this really good recent investor, Charles Hudson. He's a friend of mine. He was on the board of the NBCA runs Precursor Ventures. Years ago at a Kaufman Fellows talk, he gave this he called it Wind to Intervene. This actually relates to being a director. His Wind intervene was a 2 by 2 where the x axis was the your certainty, like your functional experience in the role and the Y accidents was the consequence of the decision. So if you think about that lower left, like you're not an expert, it's not consequential. It's like I call that the who cares Zones upper right, like it is high consequence to the company and you're an expert, like definitely intervene. I think most of the time as investors and board members, you're actually the other two. And so when you have high expertise on something, but it's really low consequence to the company, I like to call it the learning zone where it's, you should just, even if it's human nature to want to intervene and help, but you just know it's not going to be the problem. And so that's where like founders and like all of us, even as board members like you, learn by doing. I need some traction. You need some traction.

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Hey, Traction fam. Excited today to welcome Nick Washburn, senior Managing director at Intel Capital. He's been investing in the next wave of innovation and fintech for a long time, I guess since 2014, and he's backing awesome companies in cloud infrastructure, AI and data. He's also on the board of the National Venture Capital association and is a Kaufman fellow. So we're going to dive deep into founder investor dynamics, how Intel Capital is navigating today's venture market and the rise of AI driven business models and how that is the next wave and reshaping SaaS. Nick, welcome to Tracktion. Thank you so much for making the time.

Oh Lord, it's a pleasure. Thanks for having me man. I really appreciate it. See we're also both going with sparkling water, which is. I'm addicted to this stuff. I am.

My wife buys boatloads of these from Costco and I got used to drinking these. I used to drink pure water. Three years ago I stopped drinking and so whenever I go to bars with friends, I just instruct the bartender or at events. Just give me sparkling water and throw a piece of lime in there.

Yeah.

So this is, this is stuck. So excited to get into your background. How did you get into venture capital?

I fell complet backwards into it is the short honest answer. I was like poli sci undergrad. I graduated college in the fall or sorry the spring of 2002. So fall semester 2001, 911 happened. So that had a lot of impact obviously on America, the world and like finance jobs.com crash was like in full swing. So I ended up going to. I kicked the can down the road a little bit to be honest, to law school. Even though I had no lawyers in my family. Got there and realized I don't want to be like a confrontational litigator type thing. So I started corporate law in New York and I was doing a lot of big company M and A work and I moved to the bay area in 2008 also another interesting time. So July 2008 and. But that's how I started getting exposed to technology. Worked with a bunch of startups, did a bunch of work for SilverLink and Big Technology focused private equity firms. Joined Intel Capital in 2014. So I went from being a revenue generator to a law firm to kind of cost center which is an interesting transition. Also went to being a people manager which is we can spend an hour and a half on that. And became our managing counsel and our chief operating officer. It's just like a bunch of random sequence of events that happened. But fast flash forward today. Like I'm not a practicing attorney, haven't been for years. Focused on early stage infrastructure software work with like very tech forward developers as founders. And why that space? It was when I made the final transition. There's like really three intersections one. That's where my network was. A lot of friends were rising engineering managers around the Bay Area hyperscalers. It was right around the first time the first kubecon happened. Cloud native infrastructure was just starting to come out of the hyperscalers. And lastly I think it was around the time the individual developer was becoming the conduit of technology adoption of companies. So I kind of looked at that Venn diagram and I was like I'm going to go spend all my time there. And I, I, I'm happy, I am because I really like that kind of fada Persona.

What's really interesting is your background in legal prior to being becoming a vc. What I'm seeing a lot is an off track probably here is a lot of companies are moving away from setting up Delaware Seas and Texas and Nevada. Why is that? I'm just curious.

I haven't really seen that as much to be honest. I think everyone goes in Delaware because it's just try to intrude in like the norm. So if you set up LLC versus a corporation and if you incorporate an estate to be honest just more questions you'll get from investors of like why not this way? And so you know I think it's once things become the way of doing it, that's why they're done. Why Delaware? I think historically it's very established kind of approach towards corporate law and like just what fiduciary duties are and how the court system there's like interpreted things every year. So it's, I would advise entrepreneurs not to reinvent the wheel and just form a C corp in Delaware frankly like we, we invest a lot in companies outside the US like in Israel for example. A lot of those companies even like incorporated Delaware for this very reason.

Yeah a lot of company, almost every company I know that's raised money has and even if they're international they have a Delaware C either as a main and put the foreign entity as a sub. Now as a follow up to this that you sit on a number of boards I'm looking for an interesting or maybe an out there scenario where your legal expertise helps save the day for a startup.

Well I gotta be careful because I'm not a practicing attorney like I don't go down that path and obviously always advise companies to engage with their counsel. I'm going to answer your question. This is not a deflection. There's this really good receipt investor Charles Hudson, he's a friend of mine, he was on the board of the nbca runs Precursor Ventures. Years ago at a Kaufman fellows talk he gave this, he called it when to intervene. But I like I like my old office at home. I actually had this thing literally printed on my wall. And this actually relates to being a director. His when to intervene was a 2 by 2 where the x axis was your certainty, like your functional experience in the role and the Y axis was the consequence of the decision. So if you think about that lower left, like you're not an expert and it's not consequential. It's like I call that the who cares? Zones upper right, like it is high consequence to the company and you're an expert, like definitely intervene now. I fortunately I haven't had anything like around the legal realm where a startup where I've seen oh gosh, you're about to do something like God forbid illegal or something where you would jump in. So I haven't had to deal that in practice. I think most of the time as investors and board members you're actually in the other two. And so when, when you have high expertise on something but it's really low consequence to the company, I like to call it the learning zone where it's, you should just, even if it's human nature to want to intervene and help, but you just know it's not going to be the problem. And so that's where like founders and like all of us even as board like you learn by doing. And so I've seen stuff Lloyd, where it's like they're going down a path like how they're going to handle like sales compensation plans. I just had sat in so many board meetings over the years. I know it's like that's not really going to work but I know it's not the end of the day. And so it's really the hardest thing is actually like knowing to just keep it quiet and not jump into trying to be like a savior. The other one which is like super consequential but like you're not functional expert. I call that the destruction zone. And honestly that I think is VC's advisor, executives, kind of everyone around a startup. There's not enough people who are just willing to say I don't know the answer to that and just be thick skinned and be like let's go find someone that does. And I think people will throw in opinions on things where they're not functional experts. And it's like inception, like that idea gets planned and it can just create into this cascading failure. And so given I'm not practicing anymore and sometimes it can be like close to consequential. A lot of times it's like hey, go and talk to company counsel about this. Like you should really think this through with them. So I think it's been, I seen more of that to your question of it's not the then obvious thing but it's like we maybe shouldn't be going down this path and like I suggest we go like talk to the experts on it in practice. Where has my prior career helped me the most with companies I work with? It's been around M and A like companies that are being acquired and stuff because I used to just do that for a long time, for decades. So I've seen it all. And I think working with founders, when someone approaches them to acquire their company, like helping them navigate not only like the process but even you know, there's this magical line of saying shift before closing a deal where all of a sudden if you think about the team and management at the end of the day has got new offers for the new employment, they have retention packages, all this kind of stuff where like they've kind of stepped across that line where they're like now on for all intents and purposes like on the buyer side and even knowing when that change happens because it's important as you guys like towards the end like you think through final issues and incentives and stuff definitely.

And I think that's a huge value add to a company. Also thinking about how do you structure for a potential M and A Because the legal transaction side of it is probably once you have a deal, super interested. But how do you even warm up potential buyers and build those relationships before the deal happened is an art in its own. And a lot of founders don't go and do that.

There's a famous repetitive statement of like companies are bought, not sold. And so like it's always hard because you're trying to build something standalone and very large venture investors because they have portfolios or the power law nature of the industry clearly are swinging for the fences on things. But maybe that doesn't make sense. And so you know, I had a company about two years ago. It's like the good example of it didn't have product, like we didn't have product market fit. We all kind of knew it and we were doing iterations of small pivots to try to find it and kind of couldn't get it to work and about honestly when there's still 18 months of Runway, I sat down with the founders and we started having a really good two way conversation of like this isn't working but we're kind of on A road. And you'd think, okay, we still have a year and a half of Runway, but practice, like, it takes a long time to build relationships, getting comprehens. So we could swing for the fences and pivot. Try ideas 9, 10, and 11. But like, the end result might be we just run out of money. Or we could take what we have, which had value. That's important. Go find the people who. It would be valuable to build those relationships. Try to do some partnerships in cross sell to try to get the company acquired and do it in a way where I think we came to a mutual conversation decision as a boarding the founding team too. That's actually what's going to be the best for the employee base because everyone will end up having jobs and like, what you've built will turn into something bigger. And the company ended up getting acquired. Like, the investor was like, we didn't make returns, but it was just the right outcome for the company. And. But it's really hard because you got to sit down and have a. A direct conversation where you're honest and transparent. Like, not caustic or anything, but, like, hey, we just need to make sure we're all seeing the play in the field the same way. And if we are, like, that's the first thing. Do we all agree, like, we don't have product market fit? Do we all agree, like, time is of the essence? Because someone might say 18 months, that's forever. But like, Fortune had a really good functioning board and good founding team. We all agreed and it ended up being a better outcome than I think it would have been.

Yeah. And a lot of, I guess venture investors have differing views on that. Right. Some folks view it as, like, how much Runway do you have and how far are you from achieving sort of product market fit or Lyft? And maybe you explore an M and A and others, like, run it to the wall and if you hit an inflection point, it's great, and then raise. And if you don't, then you shut down and it's a loss for us. It's a risk we took. What's your view on that? And how do you coach founders through that? That's really.

That's a great question. I've done both. Like, I've had been on boards where we've basically gone right to the end and hadn't shut down the company. Now, like, there is an important thing. You always got to make sure there's enough money to, like, obviously pay employees for, like, their accrued time and do a orderly shutdown, like you can't email the employee base. Like, we're out of money. Sorry. Be honest. That creates a lot of legal issues. It's just not the right thing to do. But we've, I've had been on boards in startups where there's a signal there and, and maybe we over indexed on the signal, but it was like there was enough of a signal where like looking at what was happening, we thought it made sense to keep going. And I've been on boards where when you look at it, it just feels like that signal is not strong enough or the team's tired or a lot of different reasons. So I don't think like there's a set playbook. I do think it's important they'll like, you know, usually lead series A's and sit on the board. In practice, like it's, it's complicated because you're a fiduciary to the company you invested in, frankly to the common stockholders, but you're also a fiduciary to your fund. And so there's a natural conflict there because what's in the interest of the fund power lot is this like swing for the fences. It's like the difference between 1 times and 0. Your money is like negligible when you're looking for huge outlier returns. As a board member, that's not in the company's interest necessarily, like at all. Not in the interest of the common doc holders, employees. So I tend to fund Italy and I think we do here. Like I take my duties to the company very seriously and that like guides me when I'm a director on the board. And maybe this is a little bit of like my original legal background where I'll do things. It's not to the detriment of our fun, but it's like being very conscious in the decision we're making to make sure. Like it actually isn't just like an option, but it's actually the right thing for the company to do.

And so what are some of those signals then? Because I guess one of them is growth or our customers loving the product. Like what are the indicators of product market fit here? But at what point do you tell them, hey, I think it's time you retrain the rest of the money and move on. I've been in some of these situations as a board member across a few companies or an angel investor, and it's really hard. Right. I think one of the signals I've used is have the founders lost the will? And if you've lost the will and the desire and the passion and you see no path forward, then just return the rest of the money. You're going to hit a wall regardless if you've lost the will.

Yes, I agree that I've not had to deal with that fortunately. But certainly it happens. As with all things, the extremes are obvious. Obvious pulp product market fit where it's just pull you can't sell quick enough as evidenced by I have a portfolio company, it's growing exceptionally well and effectively is breakeven. We almost feel like please spend more money to grow because they just have Sol solved a problem with people with budget where it's the number one problem and it's 30 clicks above number two and so there's just audience. So like that is obvious. Product market fit now the risk on those, and I'm sure you've seen this too in your own portfolio is just like that's product market fit now. But does that keep continuing scale? Like those are like the head fake ones which are really hard where there's really good growth and then something happens and it flatlines. Where do you go from there versus companies where it's just you spent 18 months, 24 months of a seed round and there's no usage, there's no users, it's just burn and there's just for whatever reason product packaging market like there is just nothing there that's obvious. The ones in the middle I think is what you're talking about. That's the hard one. Quite often I've actually if I'm honest with myself in my portfolio I've more often seen not the there was nothing there and we pivoted and it turned into something I've more seen there's a little something there and I've. I myself have overindexed them thinking like oh that that's we should go down that path. There's more to it than it is and there really isn't. And so it's like that's what I've seen more and there's some usage or growth but like not enough or there's growth but really what are we doing? Like we're spending eight bucks to earn a dollar. It's like you're kind of pushing that. That kind of stuff you fall trap into following and. And it turns out like it' not a lot of depth there. Yeah.

Because at your phase you're coming in. Intel Capital is coming in at series A. Right. Typically and beyond.

Yeah. So we tend to invest between seed A and B. So we'll do all three. I'd say our bread and butter is series A that's probably we do about 25 to 30 new investments a year lead 80% of those of the 25 to 30 new investments a year like not including all the follow ons and stuff at least 50% of them are Series A's maybe even more depending on the year we'll do some seed stuff and then we'll do some B. I tend to do a little bit more you could call it late seed early A they look the same and it's more like developer first companies. There might not necessarily even be revenue but it's just very thesis driven and I've validated the problem statement it's more of like is this the team and packaging to solve this problem now having said that I'm leading a series B right now and so like it just depends a little bit but usually we have something is built to get to your question there's a founding team that built something someone is using it now is that usage revenue? Is that usage just usage? It depends a little bit on the market and whether it's infrastructure software versus application layer or we do a bunch of semiconductor and silicon stuff that's companies that series A at that stage look very different. It's like design the silicon design is built but there's no tape out yet. So also depends on the sector but to answer your question like there is signal there but like how strong it is and how much the data is like radically depends on the sector and.

Stage given you're investing across seed A and B. I'll ask this a little tongue in cheek what's I want to invest look like when you come across a deal and what's runaway look like right because especially now in with the proliferation of AI and agentic and the models getting cheaper and cheaper there's so much noise in this market right. How do you like separate the wheat from the chaff And I guess the question makes sense is like how do you identify what's I want to invest at seed series A and B and what are those metrics and this doesn't quite look right. I'm my gut's off. Let me run away.

Yeah, I'll answer that first Lloyd with what are my biggest investment failures Because I think like that then informs what I try to now run away from. I think where I've gotten it wrong and lost all of our money on investments has been when I've been way too opportunistic and what I mean by that is I've met a great founding team. It's not in like a category I don't know at all. It's what's good. I invest in like infrastructure software, developer tools, data infrastructure. So I don't even really do much at the application layer and I do all the software so it's in that umbrella. But it'll be something an area that I haven't actually spent that much time in. And so I've made the investment on a thesis that hey, this is needed or this is a priority for this particular buyer Persona. In fact I'm completely wrong and usually it's been the same thing. It's been it's not a priority or if it's a priority it's 10 levels down what actually matters to that buyer. So it's hard to sell and it's really quickly easy to churn if like budgets get tight. So like it's constant and the only way I can avoid that mental trap is like having a prepared mind I suppose. Now what's the burden of like being thesis driven? I probably miss a ton. Like there's probably stuff I should be opportunistic on and I don't because I just like I'm not spending as much time in that sector. So for me like I try to be super non transactional as a result and I tend to know founders for quite some time and get to know them before I invest. So whether it's seed A or B, it's the same on that respect like the series B I'm leading now. I've been talking to the founders since 2021, 2025 and I've gotten to know them. It's a space I know spend time with before we even started talking about investing. I've built a network of buyer Personas and heads of platform engineering, heads of software development, heads of libraries, at frameworks, at very big enterprises, at mid sized enterprises and at startups. And I'm constantly talking to those practitioners of like what's a huge problem now? Have you thought about this space? And so I start to get crowdsourced theses from like actual practitioners of like with budget that would ultimately be customers. I then go trying to meet everyone in the category I'm looking at. So like last year I was looking a lot at like local first software and I talked to so many builders and it's builders are like companies aren't even builders, just people on random projects and open source libraries and stuff and start to like take the data I heard from the ecosystem and inform is there kind of something there. And then if I find a team I really like and I think it's solving a problem of like some customer I heard of, I kind of matchmake them and I'm like hey Sarah, you had mentioned this is a huge problem. You should go talk to Rachel. She's the founder of this company. I'm not an investor but see like really smart and by doing that I'm one kind of building rapport with my network but two like you're actually getting signal and diligence on it. So by the time I get enough signal I'm like I've seen enough, I'll just go and invest one of my startups just we just announced a series B that acre capital led in this company. MADA does mass code refactoring. I led the Series A in 2021 I met Jonathan the CEO like he hadn't even incorporated the company yet. I, I, I met him through like a, an acquaintance they had worked at Netflix is Nick, you should talk to Jonathan and like he built this really powerful tool. He had Netflix and we got to know each other over the course of years. At oldest co founder I introduced them a ton of customers and when we invested like there was zero revenue but I heard such strong demand from those people I'd introduced them to where there's a propensity to pay. There was a big budget, there was a clear roi. It was obvious to push our chips in and company is doing right now and has very large customers. And so that's for me how it is. And to answer your question, the earlier it goes like for a seed for me it's got to be very thesis driven. I've basically convinced myself there is this gap in the market. I need to go find the best team that can solve it versus as you get to A and B, I'm willing to take a little bit more leniency on the thesis and more on kind of the evidence I see if that makes sense.

So let's back it up all the way to the seed then. Because I think at the seed the thesis matters but I think core to that thesis should be the founders. Right. Because the idea may change. You may have a thesis that I want to automate services with AI given the space that's heating up right now. But ultimately the founders matter because you may pick okay I want to do I want to automate professional services in legal for finance or in legal with AI but that doesn't work. And then you switch to finance or Health care or something else. But ultimately the founders matter, right? So what are the key ingredients of the founders you look to look for that are core to your thesis?

At Seed, I tend to really, I index heavily towards a profile that's highly technical just because the space is in the DevTools infrastructure software. I like to have founders that have a strong learning mindset, meaning like they're really strong and spiky in one aspect, but are incredibly low eagle and humble and knowing what they don't know and are almost like sponges. Define expertise and ask people what's around them. Because I just think like a learning mindset is key and then I try to make, I try to ensure like their functional expertise applies to the problem statement. Meaning like back to I keep using this lame inception analogy. Like I'm not trying to give them the idea, like I want them to already, like have been thinking about it. So much of my deal flow is outbound. Like I'm trying to stress, like I do a lot of research and I just, I'm like pinging people, Twitter dms, reaching out to them. Like I'm in and I'm interested in this, the space you're building in or that you're thinking about building. Here's why. Or I'll give a concrete example around like there's a lot going on with the energetic workloads. I've actually been looking at things that I think are nichy seeming, but are underserved, but are huge time problems for engineering teams and actually have both a cost and a risk element to it. So one example is actually like the data pipeline. So if you think from ETL to like orchestration workloads of dag, basic airflow workloads to transforming, extracting, loading, then doing the transforming data and doing data modeling. This is like the cardiovascular lifeblood of large enterprise. It's like the plumbing that moves data around. And with large enterprise as well, they have to store all that data in super expensive cloud warehouses, data warehouses. And they have to like remodel it depending on the use case. So for like data engineers, they're doing tons of stuff like testing that pipeline. They're doing things like writing documentation of like, why is this data model what it is? They're taking like queries and rewriting them to data models. It's like super time intensive and if done incorrectly, it costs them a ton of money on storage. And if also done correctly, the data is not accurate, meaning there's like governance issues. And so that's the space where I've been thinking about it. I talked to a bunch of friends of mine that are pre seed investors that do all infrastructure stuff and I got introduced to teams. That's not actually it was quasi but I'm like I'm looking for this. I found a great team. I just read a great seed round. It's unannounced so I won't get in the company. But like when I met the founders, like they came out of the world CTOs like Data Engineer, worked in large company data engineering teams. ML practitioner really understood that stuff. CEO, product background, product management, originally a developer too. So like I'd understood this. Had worked in a variety of industries, security, observability, infrastructure, software, but was always a data consumer. And so like basically you have the person who builds the pipeline, the person who consumes and benefits or burdens if that pipeline's wrong and they really understood this problem statement. And both of them also had machine learning expertise because there's these or energetic workloads that are highly tailored. So that's a good example of like a prepared mind looking for something about what I'm looking for in the team. It's like you really understand this space and it's not just because it's hot, but it's like this is a problem you've had before.

Yeah, it's a problem you're obsessed about. It's a space that you know. And also I think the problem has to be like high sort of frequency. Can't be like I come to it once in a while, it's like a problem that's a high frequency problem. At series A and series B, what are the top two or three metrics you look at before you look at a deal? It's like the revenue growth rate NR@.

Series A for me it's if you came to me, Lord, and you're like, hey, Boost has a million dollars of revenue but it's two customers. Yeah, that's interesting. That's less interesting to me than you coming and Saying Boost has $200,000 revenue so like one fifth the revenue. But it's like 100 customers. Because what I'm looking for is really early signal of repeatability of there is a clear use case that's common across a bunch of like buyers and those buyers looked at and feel the same. They're at the same stage of a company, they have similar size teams where there's just early signal of okay, this is repetitive and I'm not going to over fit a decision off of a small sample size. So I tend to think more about usage and number of logos or users than the gross dollars involved, if that makes sense. And that's much more important to me. And then I'm extrapolating like how much many more of these folks that are along those lines and is enough to get them to series B. And then from there that's really what I'm underwriting is what do I think this company needs to look like and achieve to raise a series B and kind of reverse engineer from that of like, is the team right? Is it going to raise the amount right amount of money, but not too much? Are the hiring plans right? Do I see enough like in this signal where I think I can, like it could get them there, where they can unlock that other milestone. Series B, it becomes much more like that stuff's all table stakes. It's now at a level and scale where it's like clearly working, it's clearly repetitive. I start to get a little bit more into SaaS metrics, to be honest, at that point I'm looking at like burn ratios, magic number, rule of 40 payback period. Like a lot. Honestly, we're much more around like sales and marketing efficiency because I know by the time they raise a Series C that needs to be like very much locked and loaded because at that point people are funding scale. And so I'd say founder problem statement risk. At C. Series A is much more of like early signs of product market fit as evidenced by number of users or logos and like the commonality of them. Series B is like you got into revenue and like SaaS metrics where like it looks like you should pour a bunch of money on it.

I think at series A, a lot of the times what happens is you get trapped into this fake product market fit. And one thing is, with every technological shift in an industry, a company also falls out of product market fit. We can discuss that as a follow on topic. But fake product market fit is you think there's a lot of growth and there's a lot of users, but sometimes there's not. High intensity high frequency usage. And then what ends up happening is the lagging indicator of that inevitably after a year ends up being churned or dormant users versus somebody who's high intensity, high frequency using the product. And the leading indicator of usage is onboarding. So you get lots of signups that people don't go through the onboarding process. They don't activate, then they're not using it, but you've got revenue collected with no usage. And then churn becomes A problem. But the other side of that is you've got usage and then you're an enterprise and then you land and expand and you see this 140, 150 plus percent NRR and that's a good signal probably for a B.

You know what, what's interesting, Yes, I totally agree. What's interesting is like on. On my own practice I keep mentioning dev tools and infrastructure software. Those are like radically different things in the aperture you need to look at them needs to be very different. Where I also get it wrong is when I apply the wrong aperture to them. What I mean by that is a developer tool is almost like a consumer investment because you're very much looking at that you're looking at for an individual dev. How often are they using this? Are they using it every day? Do they like can effectively if this tool was taken away from them on their employer would they quit and go look for another job? So it becomes much more about usage and a lot of them sometimes it's not paid or they're swiping credit cards. So yes, they might work at American Express but it's not a sanctioned IT purchase. It's something they're just like swiping a credit card for. So like now you got to look at like almost like a consumer style infrastructure software. Very different. That's like a classic enterprise sales because to deploy hardcore infrastructure information infosec needs to look at it from a security perspective. Usually the owners of underlying primitives like compute databases, networking have to be involved. You gotta go get a line of business application team for a POC and so like that to me it's. I'm not looking at usage, I'm looking at like the sales cycle, like the buying what this sales process is like making sure like the land deal's big enough to warrant the amount of pain you have to go through as a super early stage startup selling to enterprise. Both of those are looking at to your point quality of usage or quality of revenue but which depends a little bit. I think that's the super interesting thing right now out there with all the energetic companies and companies building on top of generative 8 on foundation model APIs is there's crazy growth rates right now just like the craziest stuff you've seen you rebound on Twitter. But we don't yet know the quality of that growth and that revenue and like it's you know 1 to 20 in x amount of time. But like a lot of that's individuals buying that like might not have customer loyalty. They Might the next shiny thing that comes that's a little bit better or a little bit cheaper they could turn off. And so it's hard to know if those growth rates like ACE and Toad or there's ones that have been a bell curve and come back down. And I think that's because a lot of the generative AI budgets are very much still experimental. Like enterprise is still trying to figure out just basic table stakes, data governance to even be able to access that. So a lot of that growth might be head fake.

And what's really interesting is I think you and I have seen multiple technological waves, right? If you see probably up until 2008 or so it was like the on prem stuff. And then 2008 happened and all the on prem startups. I was in a startup back then and we went from 10 million to zero in revenue because we couldn't sign new contracts and the maintenance contracts weren't worth it. And then you go into SaaS and first it was like this enterprise SaaS and then came the product LED or self serve, they call it shadow it or whatever you want to call it, self service products. And then towards the latter half of the SaaS technological wave, you got anyone being able to launch a SaaS product, right? Solopreneurs and whatnot. And then you get into a situation where you throw it in a marketplace and anyone can just try it and there's no loyalty, it's commoditized. And now agentic workflows on top of LLMs and foundation models have exploded and everyone just want to try a single use AI agent. So we don't know yet if there's loyalty there. So as you look at the market today, I think the agentic workflows and the wrappers on top of foundation models are very interesting because it's something that a lot of people have been waiting for over a decade, right, for about a decade who've been playing around with AI tooling since 201213 and just waiting. And now these agentic wrappers on top of LLMs are so accurate that autonomous work is finally possible. And that's why agents, single use agents are exploding. You can even use off the shelf infrastructure without writing code to create an agent and launch it, right? Like a crew AI or a personal AI. So what do you see happening in this market here? What is very exciting to you? I think one side of it is there's a lot more opportunity for one person multimillion dollar businesses. I can use something off the shelf if I have a services business. I can automate a lot of it. On the other side of it though is a lot of stuff is commodity. Then if you have 10 people write the same agent to do the same workflow, then what is the moat? And that becomes a little harder to pick deals, right? Because you can't just pick deals at all. This thing exploded from zero to hundreds of thousands of users because it might not have that growth next year. Similar to the COVID boom, right? Like everyone needed to go online. So you saw the proliferation of SaaS just explode. Companies were raising at this unicorn porn valuations and then people who didn't need to go online anymore or everything, everyone went online. Like the Shopify, the Twilios, the Zooms. The growth started to flatline or fall and a lot of companies who raise at these unicorn valuations couldn't meet the targets. And then you get like a whole bunch of markdowns starting to happen and zombieland for unicorns. I think some of that will happen in these AI agent workflows as well. Because a lot of growth, a lot of people just signing up, right? So where do you see, how do you separate the wheat from the chaff as you pick deals right now?

So it's embarrassing to admit and this is going to be counterintuitive given I mentioned earlier to look at an Angenic thing, but I had looked at that because of the very specific data thesis. But it's embarrassing, man. I'm intentionally not spending a lot of time on AI stuff right now. Like by design now we have partners that we've been investing around AI for a long time, well before this kind of firm phase. And I have partners that are looking at it and we've done a bunch of investments around this space. Personally, I haven't for a couple reasons. Like one, I tend to shine away from like latest shiny object stuff just because if there's this pond over here and everyone's got a fishing pole in it, I'm like, I'd rather just go in this pond over here that's just as big. But there's one line, two, the point you're raising, there's just, it's really hard at early when all of a sudden I'll just pick, I'll pick on a category which to be candid, I'm not dove deep into AI SDRs. Like are you seeing this? There's probably 30 of those companies right now. And if you go see the movie Beautiful Mind about like John Nash and Princeton where he's talking about his marketplace theorem where they're all get the bar and they're like we're all going to cannibalize the opportunity we need to work together. That's when I look at that space too. It's like this category should probably have one or two but when there's 30 really early one it becomes impossible to pick. But two there like that many companies are going to the noise is just going to cause them almost all the falter but three like I try to think through and judge me in 10 years if I'm right on this like adjacencies where regardless of what happens in the category like all boats will rise. So I can't tell you on the co generation stuff if GitHub co pilot will win, if the purpose built foundation model companies magic poolside or others will win or if the no code builders link bolt and any sphere and cursor cursor from any sphere if those will win. But I do know or I believe if AI is generating more code at higher volume with more frequency than standard developers, there's going to be more security risk in that code. Why? Because one, there's always going to be security problems in code because it's when you build an application it's not just your code, it's dependencies on many other libraries and frameworks. And so there's just going to be more dependency sprawl with more upstream vulnerabilities and more stuff in the wild. So as a result I'm going to go look at a bunch of appsec stuff. It's just like looking for problems in code because I just know there's going to be more of it. Just similarly, it's been interesting. I've had debates with folks about these kind of natural language. You can go build a web app really quickly, frankly without even a dev background. All that stuff's gotta get hosted and deployed somewhere. It's not like you go use one of these builders and it just, it just magically appears like there's database necessities, there's more networking calls happening underneath the hood, CDN traffic like not all those apps built will amount to anything but a Shopify will come out of that. Like many big businesses will be created by probably solo entrepreneurs. But ultimately what does that mean? More infrastructure is needed. So I'm like looking a lot at the plain old picks and shovels because I just know more. It's like the more apps that are out there requires more infrastructure. So it's not even stuff directly in AI, it's just the things that I think will naturally grow because of this that I'm actually spending a ton of time in.

You know, the more houses come up, the more security systems you need, right? It's like you need these foundational things, you need doorknobs. It's a given you need it. And I think that's if you go.

On the outskirts of Austin, Texas and there's like land and they need to go build homes, you need roads, you need schools, you need hospitals, like if there's a boom there, it's going to happen. And so I, I very much believe that on the pure play AI stuff. The other reasons I get challenged and frankly like we as a firm get challenged is the venture math on it. A lot of those companies there is still technical risk. To be blunt, if you think about the pure model layer, there are. Look what happened to Deep Seq, which is not funny. Like a lot of what kind of it was interesting, the timing of it blowing up because there have been papers back in November and December of prior models using the same art that if you read them was the same outcome. But it's just the timing of why things become the zeitgeist. If you could tell me that, you'd be interested to know. But that layer changes so much and so it's hard to think about. I'm going to go invest huge amounts of money for really low ownership with companies that have technical risk. I very much believe early stage ownership matters tremendously because the risk adjusted return profile. So I'm very curious to see how a lot of these big round, really early rounds work out in a lot of places.

It hasn't, right. If you look at inflection, which raised a billion, read Hoffman investment in that. And that was like I think infrastructure for creating chatbots and agents doesn't seem like they're doing well. Or adept where Microsoft acquired a lot of people in the race like quarter billion, right. Ultimately there's just a lot of noise in the space and sometimes as an entrepreneur you wonder leave the big guys and the ones with the funding to race to the bottom maybe on the foundational models and we'll just build around it. And there's a lot of money to be had building around it. Whether it's the infra you talk about or whether it's the application. The way I see it, right. Like you had these silicon chips that got commoditized but ultimately we remember the brands that were built that leverage them like Apple and Tesla and so on. Ultimately with the same with the models and the infrastructure they'll fight its way to normalcy and bring down the cost of the AI and the compute and the businesses, the biggest businesses that will still be built are the brands that leverage them, that deliver huge customer value.

Yeah. At the end of the day, particularly the application layer, really at any layer, the last mile matters tremendously. Packaging, experience, distribution.

That matters a lot.

The interesting thing if you think about the mobile transition, I won't even go back to like mainframe, new client server like mobile and then cloud. Yeah, large enterprises were laggards there. Look at meta, Facebook for a long time like lagged on mobile. The interesting thing now is the large enterprises are iterating and deploying generative AI functionality. Very quick look at Adobe, good Salesforce, look at Microsoft. Now we know they have enterprise distribution channels like the best in the world. They have relationships, they have big ELAs, they have the ability to push out features to huge install bases really quickly get a feedback. So that's a question I have too. Like once again I'm not a big I think that foundation miles will absolutely impact the world, will impact you. And I personally I think that there will be huge value creation capture and there will certainly be some startups built that are massive companies but a lot of it's going to go to incumbents and it kind of didn't necessarily happen in the last two waves. So it's interesting, an interesting time.

But if you look at these large incumbents and you play in the infrastructure space. So I'd love to get your feedback here or thoughts on this is AWS had a seven year head start on the market before anyone caught up. But nonetheless it was like infrastructure right? Is it cloud storage and cloud compute and LLM? Isn't it in their best interest to acquire the most phenomenal or build the most phenomenal horizontal agent infrastructure? Because if you look at agents are like arms and the LLMs are the brains, it's infrastructure to run a business anyway. Right. It feels like they would make acquisitions. I've seen them acquire companies or hire in the press. But it's logical for these infrastructure companies to then go from like compute to LLM to agent infrastructure and people just leverage them as an all in one to build companies on top. What is your take on that?

For the cloud service providers at the end of the day they must make most of money off their primitives. So like IaaS versus PAAS versus SaaS. Like AWS makes a lot of money off of just selling compute and like being able to manage that compute and selling databases and the like now I'm not an Andy Jassy or Matt's head by any means but I think if you look at Azure, look at gcp, look at AWS historically a lot of the how high they move up the stack, whether they build it themselves, partner with it or just let someone else do it ultimately is to pull more of that bottom layer. And so I think do they want to go all the way up into certain ingenic workloads? There'll probably some be sometimes where it makes sense because they have the breadth and depth with the customers and there's enough signal where they can make good margin there and they think it's going to pull through a lot. But also it's like the all boats rise. They're also incentivized to have a great ecosystem of other.

Yeah, makes sense.

Other providers because it just sells more of the bottom as well. And so I think there'll be a lot of partnering to be honest and like it gets back also like Lloyd to like it's like the classic innovators dilemma. Like companies get so big at the end of the day, like it's hard to innovate and so there's always a room for someone to come in quick and nimble and very fast and they do that. Or like new tech, open source technologies are created in that team goes. And it's why Confluence a huge company and why GitLab was a huge company and why MongoDB was a huge company. AWS has the equivalent kind of key value databases. MongoDB. MongoDB is a huge company. Frankly a lot of people run MongoDB on top of AWS compute. It's just sometimes it's like the team and the market opportunity and execution and the big folks just can't catch up in time.

Yeah. So what I'm hearing actually and even if you compare that to AWS and why it's been a market leader is I think in the AI space there's one more aspect.

Right.

A lot of people are building these agents infrastructure. I think longevity in this space also matters because the inference models get better and better based on interactions, multimodal interactions on proprietary data sets. And the more at bats you've been, the more accurate you are, the more efficient you are. Right. And so you see everyone's building the Nth AI SDR but someone that has 10 years of historical data that they can train it on probably win in that space in the long term. What's your take there?

Certainly like having proprietary data sets really matters and to your point on the SDRs is who's got the most sales data? Salesforce probably HubSpot next. I think there's also an interesting thing that you can decouple from the companies and the infrastructure and it just has to do the economic soup du jour of the time of buying cycles. You know what I mean by that is it's like the approved vendor list in big companies. Like that accordion. Is it get bigger or getting smaller? We had a period for like up to Zerp where it was like very much best in breed. Any stack like a large enterprise would be like I want the best of this, the best of this, the best of this. And the improved vendor list got very large 2022 up until now it's starting to contract. You know what, I'm willing to take 80% of the features if I can consolidate down to three banners. Security is like the, this is like I, I don't even do that much in security is the classic like the approved vendor list and security constantly. It's a bunch of point solutions and then the big behemoths like Palo Alto and others just put out that functionality and it tightens. So I think the timing of when people start companies and go to market and how it relates to what's going on with that buying cycle. Is it best in breeder platform also like quasi controls the destiny of a lot of these companies and it's completely outside their control. And it has to do with like broader economic macroeconomic trends and like even whether that P and L owner in a large enterprise is like a center of power at that time or not. Like as a CISOs, like right now CSOs are super important, like very important inside companies and risk is very important. There was years ago where they weren't. And so that depends too. And so that's why I think at least on the venture side, consistency of deployment, not like flexing up and flexing down. Because it's impossible I think to actually time this stuff. And she just needed to be investing consistent across time vintages.

But I think you bring up a good point here, right? You got these technological cycles like on prem and then SaaS and then within the SaaS there was like mobile cloud, fintech and then now it's AI and more agentic or autonomous. There's also buying cycles that people don't overlap. They just think about technological cycles.

Right.

And so the buying cycle is very important to the icp. You pick because you may say, oh it's this market's going to Explode, it's trillions of dollars. But the reality is if you don't overlap that with ease of access and propensity to pay, you're going to get nowhere. You'll just bang your head and go nowhere. So I think that's a great point you bring up is connect the technological cycle to the buying cycle when you get started on icp and if there is no propensity to pay, there's no ease of access particularly there could be huge propensity to pay. But if you are relegated to spending a year or more trying to get into that approved vendor list, you're screwed.

Yeah. And if it's a period where companies are contracting the amount of external providers they want to do and they're willing just to go with not best in class but like just lower level but a platform because they have a master services, you're like sol like at the end of the day, yeah, like we all have biases and like also whether explicit or implicit, whether known or just unknown and then also like we have what our appetite and flavors are for things. I guess I would just caution my comments are very much colored with I believe to once again steal a phrase from someone else, all roads lead to steak dinners. And what I mean by that is, is to build a really big company and what I do, you're going to have to sell the enterprise at some point like it is. That's just where it is. If you want to build really big business, you're going to be having to like in where I spend time. I believe you need to do that ultimately. Like not the first year, not the fifth year, maybe nine. Like it's the 10th year, you're going to have a lot of revenue concentration with like Fortune 1000 companies, Global 2000.

It's funny because you look at some of these at least in the B2B space at some point they build a sales team, right? Even Slack did it. Everyone's anti sales team and their PLG and adoption and network effect and virality. But eventually they end up building a sales team. But there's something to be said about network effects companies, right? I think if you look at tech, 60, 70% of all value has been created by these self perpetuating network effect companies. You look at a Shopify, not sure if they sell enterprise, that they do have an enterprise team now finally. But it started with small, right? And so why is that thesis there? Can't you build and why can't you build a massive company empowering the little guys versus eventually having to sell to the big guys.

I think on consumer stuff, absolutely. It's what you just described. I think on SMB mid market stuff as well. I think for infrastructure software specifically you have to sell the big guys. I just think it has to do with the infra layer application layer. You could totally build network effect companies at various cycles. Like the canonical example of this in infrastructure software which is didn't have a sales team was Atlassian. Atlassian is a very big company. Jira Tickets, Confluence, BitBucket. For the longest time there was this narrative that they didn't have salespeople. It was all product led growth for a time. But like Atlassian now is the powerhouse. Oh they have a salespeople, they have a CRO and a massive sales organization because to be selling seven figure, eight figure deals to very large enterprises, they're not swiping a credit card like a JP Morgan Chase is not Atlassian customer at whatever X dollars a year without involving very deep conversations at the C level and sales and like very long things. And so now Atlassian didn't start that way but they end that way. So I think in infrastructure software it's very hard to build a very big business that doesn't end up having. It's like the long tail logos will be very long. Revenue concentration will be very tight. Big enterprises. Yeah.

And I think especially now in the space we're heading into, in the autonomous work AI agent space, there's a real opportunity for infrastructure to land and expand. Right. If it's an easy to buy, easy to try, easy to use, you can proliferate within an organization on the credit card and then eventually end up in the CFO or CIO's budget but nonetheless it ultimately hits there. That's a very interesting point you bring up. It's just that a lot of startups want to immediately target enterprise. They don't have the skill set and then they waste a lot of time and they get nowhere and then they peter out, run out of money. How do you advise companies? Because you, you meet like say 20% of them are seed companies let's say right this solid infra people tech focused. How do you tell them, advise them to approach the market and the GTM and route to A and, and B.

There's no, no playbook answer. Like if I'm being totally honest, it so depends on the product and I want to distinguish between the user profile and the champion slash budget holder because those are necessarily the same people. So I, I've seen both. I led the series a At a company called Fly I.O. which was raised a B from Andreessen, a C from like EQT and company's growing great. When I first met Kurt was very much a bottoms up. Developers show up, use this, swipe their credit card and what they were playing into at the time was the ability to run full stack applications really close to end users with like basically just it was like magic. You could just take a Docker image, upload to their platform and all of a sudden if you had a user in Des Moines, you would be firing up that application logic in the data center as close as possible that user. Because as users we expect like instantaneous response times. So it was almost like a magical modern day Heroku for lack of a better term. But so it's very much bottoms up but underneath the hood. The reason why we really liked partnering the team is they weren't just built and tossed up in aws. They ran their own metal like they run data centers. And it's optimized for really low level infrastructure which we know is, we believe is very important.

For that business.

For the longest time it's not about going to sell an enterprise like enterprises are interested, it's almost hey, let's not talk to them. Like we have all of this growth within these full stack communities. We just need to see for developers, we need to ensure they have a delightful experience because they could go spin up a bunch of stuff on aws. Now it's not going to be as performant because it's not as geo distributed, but it's a known entity. It's like you don't get fired for buying IBM, you don't get fired for buying aws. And so more we wanted to have an abundance of workloads to see, to understand like why are people using, what are the architectural patterns, why they use Fly IO, what other features and products should be built in their abstraction. How higher or lower should we go? So like that was very much like the bottoms up motion. We kept it that way for a long time. Other companies like the mass code restructuring enterprise like out of the gate because we knew at the end of the day to maintain huge code bases for vulnerabilities, aging frameworks, library immigrations. The biggest pain point was with really big code bases and Elwood has bigger code bases. Think huge Java code bases that are aging and have been there for 20 years with so many dependencies but mission critical applications are on top of them. No one has that pattern other than very large enterprise like I. It's just that's what very large enterprise is. You go look at the code base of. I didn't go to Home Depot last night. Home Depot like their infrastructure probably code bases for all their operations and in store stuff and websites probably been built over 20 years and is highly complex. And to be clear, I'm not saying it's bad. I'm just saying this is what happens when 90% of your code base is other people's code. That's hard to maintain. It's very laborious. It creates like security risks. And so I just know that problem statement everyone's got it. The biggest pain points right now are in enterprise. So for that business enterprise sales makes sense.

Now as you work with founders like this founder VC relationship is so crucial. How does intel capital and you specifically help your founders? You guys have great market access probably, but give us some.

Yeah. So as a firm we like we. We're very thematically focused. We invest in what we call the future of compute which is really for domains. It's like cloud software so heavily infrastructure cyber security, applied machine learning, silicon as you could expect process packaging, interconnects like semiconductors, what we call frontier. It's really applied computer vision, robotics. So think like figure the humanoid revives company and then devices which for us is really like mobile technologies but the infrastructure side. So like we stay in our lanes and are pretty like thematically focused and then we help our portfolio companies that same two ways. One's like you already touched upon always go to market. We've leveraged intel and frankly our relationship of like really deep inroads into very large enterprise. And I don't mean just like the innovation groups. It's just like buying centers like the CISOs, the head of AppSecs, the head of running the security operations center group like very much down the line to like individual GMs and product owners. And we just basically give our portfolio companies what I would call is like very highly qualified SQLs. Like we've met with it the buyer, we've already interviewed them. We know the problem statement, we know what they're looking for. We match. We do this sometimes one on one. We have thematically focused events. We call them like customer connect days. Like we did one for all the Wall street banks back in the fall like on the Ford Nicee but then it's just very much matchmaking. And then similarly like we do something called embedded expert program. And so we will go to an example is like the CTO of one of our startups and say what's something like 912 months out on the roadmap that you need to do that's like more lower level infra or like scales your product that you like won't necessarily hire for right now but would like to get ahead of and they kind of write a user Persona and like a job description and then when we go on our network including within intel itself because intel has like a 20% program like Google, if we find the person that actually has that background matchmakes they do an interview. If the CTO is good on it, we basically sign standard consulting paperwork and that person goes works from the start for free for one day a week to get that job done. So we're basically giving our startups very senior very targeted engineering help for free. And so those are two ways we like I think like functionally like help help our startups for like me personally honestly Lloyd, like I think I try to strike the right balance and I hope hopefully I'm good at this but I try to get feedback from my founders of back to like knowing when to intervene, when to not to I I view my role just to like remove roadblocks to building a successful company. Certainly not be value destructive and know when to like lean in and maybe offer some help and know when to stay out of the middle. So like if one of my founders just texted me last night about a bunch of like pricing stuff, I'm not a pricing expert. Like I'm not I like I shouldn't even be opining on this. Like I just basically I don't have an opinion. I think we should go find someone who's like smarter in this area. I don't mind saying that like I just me upon even be worthless advice without context is like the most dangerous stuff. So I just look for ways I can help. I try to help a lot on customer stuff. I've done enough and seen enough like go to market scaling where I can pattern match there a little bit because quite often the reason there's a path through the forest is because it's just the way I'm doing it and then otherwise I just think it's really important to be try to be very responsive. My job is easy. Your job as the founder is ludicrously hard, like way harder than mine. And so I try to be very responsive. I try to always be incredibly honest, like not sugarcoat things but also try to do it with some deep empathy because the entrepreneurial endeavor is really hard. It's hard on you personally, hard on your family, hard on your friends. It's got many ups and downs. So even though I might disagree, like I try to do my best to say in a way where it's just index to listening first is what I would say.

A lot of what you do as a helper, right, a VC is be the broker of resources. If you're the call at 2am or 2pm for the founder because the founder knows you'll listen and you know somebody, I think that's a good win. I'm, I'm going to listen and, and, and listen to understand and hey, Nick knows somebody who knows somebody. Nick's going to connect me. I think those are really important traits in terms of founder investor relationship. What are the key elements you think have contributed to your most successful founder relationships?

Two way honesty, like just being very honest. Two way humility, like being both sides basically able to say, I don't know, I don't have a clue. I'm like way out of my element or I'm scared. God, it really doesn't feel like this is going to work out or gosh, I'm, I'm excited about this but I'm not totally sure. So it's just really like honesty and humility to be able to like just be upfront. Like it's no, no egos. Like no one, Lloyd, no one knows everything. Like I, I don't know, I don't know anything. Like you know on like a lot of stuff. And so just being able to do that and be upfront and honest and I also think I've got the, when I've had the best relationships, it's like where there's like a two way mutual respect where you know that I know when you're showing up, Lloyd, and you're telling me something I might disagree with. I know you're coming informed and you're raising it for the right reason. And I think it takes time to build. That's why I said I spent a lot of time trying to build like not transactional relationships. That's one of the things that was a shame, at least from my perspective. In 2020, 2021, a lot of founders went and raised money like really quickly. Like just very much optimized for like round size. And you can't divorce a VC once you like they're on the boardroom. I've been on some dysfunctional boards and it's not, it can create our company. And so if I had like one word of caution to founders, it's just take your time and back channel a ton who you're Taking money from and when you back channel them, don't go talk to the winners, go talk to the companies they shut down. It didn't work out because I think when things don't go well, like success has many fathers failures and orphan that phrase, go talk to the companies and it will work out and talk to those founders and see how that person was, were they patient, were they measured, et cetera.

Very few stand by the founders in bad times and it's really hard. And you're right. I love this phrase, success has many fathers, failure is an orphan. That's great advice. Talk to founders they back that actually failed and see how they behaved. I think another thing is investors seem to have this wealth of knowledge but it comes from pattern matching versus playing in the field. They sometimes try to over index on that and or they're they've executed a time that wasn't relevant to today and they over index on that. And sometimes ego comes into play and a lot of people forget that it's important to be vulnerable and if you're not, then everyone around the table is just not going to speak their mind and passively commit. And then when the train wreck happens, they say I told you so. I like this two way humility, two way honesty and two way respect from your experience. What maybe and you don't have to name names but was there a founder relationship that went south and some lessons you learned from it?

I had a founder where it was the honesty wasn't there. Now I don't, I'm not saying like fraud or like anything even close to that, but it was just like you would find out about bad stuff. I think that they were, their heart was in the right place because they genuinely thought they were going to turn the corner on things. But it was like very delayed and so I think I would find out about stuff like once it was like a fate completely like there was no way coming back from it. And I don't think finding out four would have changed the outcome. That's the irony of this. I don't think that we could have workshopped the way out of like not having great traction of product market fit was just more of okay, I clearly for whatever reason you don't feel comfortable telling me bad news until the last possible time. And I, I don't even fault the founder. I fault like our mutual relationship. There was probably aspects that I did too where like I made them think that I don't know what mutually happened where they felt like they couldn't tell me something that was bad. And like that was sad to be honest, because it's right. That's not what you want. Like I'll say very specifically, the VC board member founder dynamic is so complex when you really think about it. Wood, like the power dynamic is very unusual. It's like lopsided. Yeah, you're building a company, but I gave you money. And so like theoretically, like I have you access to more money as a board member. Like what's one of the jobs of a board member? Like hiring and firing the CEO. So there's that aspect of it to. So it's just this like very. But then the VCs got partners, they have to deal with their own limited partners. They're fun. But then those duty. The whole thing is super complicated. And that's why I think just coming at it from our first principles, like honesty, responsiveness, empathy, like it goes a long way. And I don't know, sadly it's like the exception, not the norm in the industry, which is my traditional waste.

I think that is so crucial. Right. And a lot of people, especially first time founders, they think it's important to be perfect than be transparent. I think transparency saves the day because ultimately everything is an experiment. You're worse for holding money on a failing ship, on a sinking ship and then sink everyone. With you, you'd rather be transparent and be like, here's the money back and maybe you work on the next thing together. I think.

Yeah.

Even from a founder perspective, yes. One of the key things is to ensure that the company has capital. But you also need to ensure the company is growing. Right. Are people happy? Are customers happy? There's money in the bank and you gotta be honest. If employees are not happy, customers are not happy. You gotta be honest with the board because they can help you. Right. But if you keep lying or keep hiding the truth and kick the can six months down the road and there's a blow up, then why don't you tell me? Right. And that creates this mistrust.

It's interesting you as a founder too took that aspect of talking about the things that a founder could do that caused the problem. I'll take the counter. As a VC, the things that VCs do that cause a problem, which happens all the time. We already talked about this notion that you have to opine on everything. Yeah. Like golly, there's a power in saying silent. Like some of the best board members I've seen are like, they don't say a thing, but when they say something, it's like super Relevant and on point. You're like, geez, where'd that come from? Like, you're right. That's like the power of staying quiet. It's like underappreciated. Like I really think, and I think that like I said this before, like advice without context is so dangerous if you think as a board member, like I don't have context on so much in a company because I'm not in it it every day. And so like you just got to be very careful. The whole pattern matching thing, like, gosh, we could do another episode of that. If venture capital is a game of outliers, how can a pattern apply?

You know, without context and with the best context that Chat GPT has, it still hallucinates. Right? So you're just human, you're just human then. And I think the best way to build that relationship is all parties be vulnerable if it's in the best incentive of the investor and the board member. If the founder can be transparent and then not cause an adversarial discussion, but be an open and honest discussion. And ultimately it's like, are we doing what's best for the company? And what's best for the company doesn't necessarily mean leave the money in the company in many times, right? The company is what its customers, its investors, its employees, its shareholders. And so if the company is bleeding for cash and they have, they're losing customers and there's no line of sight to get to product market fit, do you run this company till you bleed it through or do you return the money? I think, listen, it's a very interesting dynamic and being transparent and like you said, two way humility, two way respect and two way honesty is key. And I say honesty is important, but I think transparency is even more important. It's your, your VC is probably you spend more time with your company than with your spouse. It's like another co founder, right? You have to be transparent. A lot of founders, I feel like they forget that the sales job ended when the term sheet, when the money was wired. After that you got to be honest. And if you keep the sales job up at board meeting one, probably that ends with some metrics a couple board meetings later and then you have this, hey, why didn't you tell me? Why did you exaggerate? And a lot of founders miss this. And, and I don't blame the founders, I blame the culture, the founder of VC culture. Because a lot of what's informed startup culture is what we do in Silicon Valley is the pitch competitions and the advisors who probably 90% of them haven't built a company. It's all about polishing the pitch to earn the. There's not a lot of conversation around how do you present and build a relationship for long term sustainability. And so everyone goes in this mindset that I'm always selling, I'm always selling, I'm always selling. You're selling until you're not and then the relationship is broken.

Yeah. The truth Lloyd is most board meetings are massively ineffective. Massively. Massively. It's like I, I had a conversation with young undergrad who was a friend of a friend. I was like looking to get into potentially tech. It was, it was, it was very interesting because he had asked me like what makes for a good board member and I gave him this like answer I think I call like the four P's. Like when I said it I could see him taking it back because he thought it was going to be like this. The best board members are up on the mountain and just piling all this coffee. I think it was like punctual beyond time present actually listen, don't be looking at your phone or devices. Like management spent a lot of time do this punctual prepared. Read the materials before you show up. So we're not just talking about something that you like. I would already have the context on. And then the fourth it was having the. Have the power to be quiet and it's like really? I'm like if you do those things you're like 90 90th percentile as a board director because it's just, it's a lot of wasted time.

I think that relationship, especially with your VC or lead investor. The vc, your lead investor needs to know what's happening before the board meeting. Like you have a strong dynamic especially at the earlier stages. Seed series A, series B. What I find is a lot of board meetings get sucked into this. Let's present the deck.

Yes.

And it's extremely frustrating. Spend show up all the time doing a beauty pageant of the exact team presenting and polishing their department to show it in the best possible light. Again, that is a culture that starts from let's pitch, let's pitch, let's pitch. Everyone's in pitch mode and I would much rather see a notion dog personally or present in a notion doc where all the numbers are there for each department. You know what good looks like. You know what the leading indicator is. Why don't we just talk about the top two North Star metrics in a lot of companies it's probably NR and Gross margin and growth rate or some. And what are your top initiatives for the quarter that's driving that? And who's the one neck to catch? But you get through this financial gymnastics and I'm starting to actually realize that you need more product people in on a board or people who have a passion for product because that's what you're selling, than finance people. Because finance people make everything transactional or.

Have a tendency to.

And product people actually inject love if, if, if they. Because they care about the product.

Yeah. Yeah. For what it's worth, I tend to tell the companies I work with we need to keep board meetings two hours max. Like max everyone. The expectation. This is just on the CEO. It's on each of us board members to hold other board members accountable. Two hours max. Absolutely. Everyone needs to have pre read everything. We're not discussing anything that's in the pre read. If you have a question about stuff you've read, you could take it offline with the relevant functional hashtag. And those two hours are going to be spent on two to three strategic topics that all. That's all we're talking about. Like the most critical three things relate to the next phase of the business. One might be product. One might be do we not have product market fit? One might be like how much risk do I want to take on hiring? It's not like the flipping the deck slides. Amen, Lloyd. That's what I mean by ineffective. And it's just like it invites tangential questions that are not relevant to the trajectory of the company. And sadly like that's how most board meetings are.

I would love to see notion or something just kill the PowerPoint because then people will not be incentivized to, to design these beautiful decks and logos and everything. Just like it's a memo. I, I like what Parker Conrad did with rippling is like popularize the memo. Just okay, this is the facts in. In marketing for example, or gtm. Right? What do you care about? Let's look at marketing for example. You care about like leads by channel by payback period. Right. Channel efficiency. Why do you need to know what campaign they ran and how awesome it was and all the other things and all the effort. Who cares? Like channel leads, close ratio efficiency, payback period. Every department has four columns on that. They can put in a notion doc and then talk about strategy. But we get wrapped up so much in the emotion of it. And I think it, it makes board meetings so ineffective and frustrating. I'm on a couple of boards and, and and so I'm like probably sharing very recent frustration.

My only caveat on my statement is just for the meeting, which isn't even Q4, like for the annual planning meeting for next year, I usually want to have a little bit more detail. But once again this like slides are word doc. It's usually like very high level and all I really want to know is what are the assumptions behind all the numbers? What are we assuming and like where is risk versus not? Then I say just send me the whole Excel. I'll look through the model myself and I'll. If I have questions, I'll send you. Not in a board meeting, but I want to talk about the, the inputs to it, not the outputs because it's the outputs. I'm like trying to understand what's the thought process and like where are we taking risk? Is it appropriate or not? Basically like that's annual planning. It's like how much do you want to lean into risk and why.

Yeah, that makes complete sense. Now intel, as we close this off, intel raised a lot of capital and spun off this new entity. How big is this? Is, is it a new entity and a new fund or, or. Tell me about the spin off.

Yeah, so we're like super excited. It got announced, it's not yet done. So believe it or not, Intel Capital, we're in our 34th year of existing. So right now we have about $5 billion invested in north of 200 companies. But we're going to be spinning off as an independent venture fund like traditional. The intention is to look and act and operate, just have the flexibility and autonomy like one of the Sandhill Road funds with the ability to access additional capital beyond Intel. Like to be clear, intel is going to be a very large anchor LP and we have a great relationship there. And a lot of the programs they talked about are through intel, but we just want the flexibility and autonomy and intel wants to provide it where we can diversify our LP base and, and I think for our founders like there really is no change still myself and my other partners that are investing, we're working. All of our companies are coming with us. So we're super excited. Don't yet know what the new name's gonna be. I'll let the branding experts figure that out. Not myself, but very like we're very excited. So it should be done by towards the second half of the year and.

You know, it should get you a lot more deal flow as well. I think SAP did that successfully with Sapphire a while ago. Maybe it's 10 years into that, it should get you a lot of deal flow because sometimes people see intel as this big company with a venture arm and they just make up these notions in their head about working with the navigation of it, the help, the support. And you might be seen more founder friendly. At least me looking at it from a founder like, ah, do I approach Intel Capital? It seems like a bunch of corporates running the fund versus a standalone thing which might be seen more collaborative.

Like we've had the benefit because we've been around for a long time in a really good portfolio. We've invested like $13 billion into like thousands of startups. I mean since actually this is an amazing stat I heard from someone on our team in the past 10 years, investments of ours that have gone public are now worth north of $100 billion market cap.

Wow.

So like we've had north of 700M and AS and IPOs, we have 30 unicorns in our portfolio right now. And so I think like the way we've gone around that, Lloyd, to be honest, it's like founders talking to founders. Like whenever I'm looking at an early stage startup, they're like, hey, we like you. What's it like working with Intel? I'd basically just say, look, I'll walk you through it, but you should just go talk to founders in our portfolio because that's the best way to have a very frank conversation of what it's like. And I think what people do, they realize we like look at and feel a lot more like the already like what we're going to structure into. Like we just are operating that way to begin with, but we're like very excited.

What do you see as the top opportunity coming out of this for you? In addition to all the autonomy and so on?

It's hard to forecast that, to be honest. Venture is always changing, to be honest, Lloyd, and we're like trying to not be dogmatic and think through things and change. We've always adding to our team. We've brought in some great partners the past couple years and we'll always continue to do that. And this is like silly to say, but it's the truth. What's our North Star like? I want to go find the next five Intels and like from the very early stage and go help build huge iconic companies. Intel created Silicon Valley. Like it's. That firm exists because of intel. And so like that's like our mission and I think the opportunity honestly is to go do it.

As we brace for the autonomous future, couple pieces of Parting advice for founders you'd like to leave with.

Don't be transactional. Take your time getting to know investors. No one knows everything. Discount everything you hear. Don't over index some stuff. And always give your co founders, your employees, your VCs and ask the same of your VCs the benefit of the doubt. Like I think if you show up, you give someone the benefit of the doubt and have that mindset when you first talk to them. Puts you in a learning, listening mindset. And I think that causes you as an individual to grow faster.

I think that's what the sort of legal system was built on. Innocent until proven guilty. But oftentimes we come with this preconceived notion and it just destroys relationships.

Right?

Guilty until proven innocent. And then you don't talk for days. And then time. I think there's an old saying in sales, time kills all deals. If you don't give people the benefit of the doubt and then you let time pass between conversations, it just makes the relationship erode and potentially explode. This has been a great conversation. I rarely go over an hour and I think we're like an hour and a half into this. Nick, thank you. Thank you so much for spending the time with me. I dropped two companies for you in the chat that could be infrastructure and interesting. I'll give them a plug to Personal AI. Personal AI, which is AI infrastructure for enterprise company I'm advising and another friend's company, Polygraph, which is with a prolification of AI, content, security, governance. The need for that has gotten huge, so they do that.

Awesome. Lloyd, it is a pleasure. I appreciate you. Sorry for running you so long.

No, I enjoyed the conversation. I forgot about everything. Luckily I had the time block. So thank you so much and we'll push this online in the next couple of weeks.

Awesome, Lloyd, take care.

Have a good one. Bye bye.

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