The Wisdom Wall

“my underlying belief is early markets are actually pretty darn efficient, a lot more efficient than, than people realize.”

“I think in these times where you don't know the TAM and things are moving quickly, you definitely want to pick the best team. I don't think you should overthink the space, but like asking questions about like TAM or valuation or value makes a lot less sense because that's actually what's uncertain.”

“anybody listening who, who is a VC, you can take as many board as you want. The actual board work itself is not. The question is, can you still be available to founders and add value whether you're on the board or not?”

“there is no, as far as I can tell, as far as we can tell, there is no inherent endemic mode In the technology stack to AI, other than just overcoming the bootstrap problem.”

“if you look at these examples of quote unquote successful open source companies, in almost every case, they were going after and cannibalizing an existing market, which is way more difficult than actually doing new innovation, right?”

“GrokBot got really right is, no, how about if it's actually an employee? So now you have this thing that's an entity, and it doesn't have, like, special access to your keys or whatever. It has its own computer, and it has its own browser, and because these are the smartest models in the world, it can do whatever an…”

“today to build a frontier model costs, let's say, three to five billion dollars, right? So, and let's, you know, and, and that's to train it. And so the inference has to pay back at least that. Of course, right? You know, in order for any of this stuff to be viable, let's say two times that. So let's say that now…”

“it turns out that you don't speak to these models in code. You speak to these as humans in natural languages. Therefore, the, the model has to, like, understand, like, the, the breadth of human experience and language, right? And so, you know, that means in order to build a coding model, you're actually building, you…”

“Like if you really believe in the product, you would never do a plugin because then you're part of somebody else's product. If you really believed in the product, you wouldn't do enterprise early, you do it later, because the product itself is the kind of go-to-market motion”

“if I'm writing a program, I'll like, whatever, I'll use a cloud database, I'll use storage, I'll use networking, you know, whatever it is, but like correctness and logic for the program is under the programmer's control. Maybe I'll use a third party library. But again, like, I'm choosing the library. I know the inputs.…”

“And right now, if I give. 20 people a billion dollars, they can actually use it usefully. It's very, so it's like, it's like we've kind of moved the industry from like this engineering bound problem to a capital problem.”

“No, you're building the machinery. I'm saying in this case, if you're like, I want to exhaustively explore every protein combination. Right. We can just turn that into a money problem. Yeah, yeah. It's kind of very strange.”

“I sit in these boards too. So the board goes to the CEO. What does the board say? We need more AI. And what does the CEO said? Oh, okay. I'll get like a consultant to do more AI. And then they have some centralized project that nobody knows how it works. They haven't aligned their operations and those things will fail.”

“What we're seeing instead is instead of viewing AI as software, like just view it as a user. And so instead, like take your product Make it a CLI tool and then have the AI be an agent that actually uses this. You're not fusing the two. You're just making it more useful for AI. This is a very, very significant…”

“these models don't integrate well with software. Actually, I think it turns out and what we're learning as an industry is if you view them more like humans and you draft on the, um, mechanisms we put in place for humans, they are much easier to integrate.”

“You know, we've actually built in a lot of these permission systems. You have to treat it like a human. As a separate human, and then instead of like building another auth layer”

“And at the end of the day, like, it's the semantics that end up mattering a lot more, right? And so, like, the agents, in my recollection, or in my experience, are very, very good at picking the right Back end for whatever they're doing. So they don't, they're not like, oh, like the interface for this is very good. The…”

“So like, what do people, in my experience, the more senior folks actually use AI for code? It's like documentation, writing, testing. I mean, it's a lot of the other stuff that may not actually like increase like the shipping schedule, but like you get a lot more robust code, a lot more maintainable code, a much better…”

“Honestly, last quick point on this is, like, for the first time in a very long time, we're seeing brand effects with an early technology, and what I mean by that is, if you look at, like, whatever, the major model providers, you know, how much better are they from each other? Like, you know, maybe, you know, a little…”

“you shouldn't be looking for good deals with respect to other investors. You should be looking for good companies and price shouldn't sway you from that.”

“most companies fail from indigestion, not starvation, which is they just raise too much money too easily. They don't listen to the actual market, which is, you know, the customer base. And as a result, they just have a bunch of bad practices and end up running out of money.”

“I really believe the best companies themselves are non-consensus to customers. I just think that the investing market is, is, is, is different than that. Like they kind of understand that and therefore a comment on investors being consensus is very different than a product or being consensus.”

“venture capital uses like the same. Model that you'd use for like a dentist office or something, like a partnership where everybody's equal, right? Like that makes sense for a small service organization, but you can never scale that.”

“So if the use case is the model is creating content, And that content is whatever. It could be language. It could be image that clearly works, right? So, okay, if the model is automating something a human being would do, and we conflate these two things all the time, that's totally different, right? So if I'm like…”

“The only sin is picking the wrong company in a certain space because because that conflict thing, because you're conflicted out of the winner, like investing in a space that doesn't work is fine. I mean, like, there's no way you can actually predict whether a space is gonna work or not.”

“for the first time I can recall, programs are abdicating logic to a third party. Like, we've always abdicated resources.”

“GPT wrapper was this, like, derogatory term. Like, we've kind of come to the conclusion, like, that's not even a thing. Like, when someone writes software on, like, whatever the cloud, you don't call it a cloud wrapper.”

“Conflicts really matter in this space, and so if you're too aggressive early and you don't really think through things, it can really keep you from investing in the one that's winning.”

“we've kind of come to the opinion that there is no AI. There's like a bunch of subspaces that are totally different that all require their own strategy.”

“like, like anybody that likes decried, oh, defensibility isn't going to work has been wrong. Um, anybody that's decried, like, it's all going to aggregate has been wrong. So zero sum thinking has been wrong.”

“AI actually solves that problem. It just solves the bootstrap problem. It's like, these models are so magical. So, like, You know, you wrap one of these models, uh, you know, you make it available, and people think it's amazing they show up. But what's also clear is, like, that doesn't solve your retention problem if…”

“open weights is not the ability to produce the weights. But open software is the ability to produce the software. Like if, if you give me open software, I can compile it, I can modify it, whatever, but giving open weights, you don't have it. You don't have the data pipeline, you know, when you're talking about open…”

“It turns out that model was trained on everything humans have ever gathered. So is, like, the incremental experiment gonna update that? Maybe. Information theoretically says probably not.”

“But as soon as you're doing RL, where you're training it in a specific domain with a specific verifier, you're likely losing, you know, other areas. So you make it really, really good at playing chess. It's going to be less good at, you know, something else like that, you know, like, you know, writing general scores or…”

“So the internet actually introduced the notion of asymmetry, which is the more that you rely on it, the more vulnerable you are. So to wit, the United States is more vulnerable than, like, you know, random, you know, you know, random federal country.”

“Software was always the disruptor. One of the most exciting thing about the AI wave is, like, software's being disrupted.”

“I don't remember ever in, like, the history of computer science where we've, like, from an application standpoint, we've abdicated logic. Like, actual, like, like, like, like, application. Like, in the past, we've abdicated resources. Like, you were like, give me compute. Give me swords. Like, you know, these…”

“Infra creates TAM.”

“The thing is, is all the other models catch up very quickly, because they distill so well, so like, that's, that's not defensible, in a way. And so the companies that are defensible, that I've seen, is they'll put out a model that's very compelling, And then once the users engage in the model, they find ways to build…”

“even if the weights and biases are open source, I don't know how much you can modify it. Right? So it almost feels like we're going back to this old mainframe day where, like, it's great to have it, and you can operationalize it, but you're not going to have the same level of flexibility as, you know, you have with,…”

“market transformations aren't created when the economics get 10 times better. They get created when they're 10,000 times better.”

“the behavior that's developed around these things is iterative, and so that human in the loop that used to be in a central company is now the user, so it's not a variable cost to the business anymore.”

“So, there are solutions to pretty much every one of these techs that's very simple to use, so much so, if you don't use them, like, I kind of view you a bit of an anti-vaxxer. And the reason is, is like, you are the attack service for your company, and they're gonna help you with the company assets. But if you don't…”

“Where if you have a sales person selling something, you actually benefit by more knobs because it'll demonstrate more value. I mean, I hear often people say, why does IBM or SAP make such complicated products? Don't they know how to build products? That's actually missing the point. The point is, is I want something as…”

“it's hard to give something away. It's much, much easier to sell it, especially if you want to have impact afterwards.”

“whether or not a company is going to do well is, Somewhat independent of technology often, and somewhat independent of the approach they take, and it's more like, you know, do they become the popular one that they use?”

“some of the most fundamental research contributions are actually happening in industry today, and not only that, that, you know, the academic system has actually moved towards short-termism, especially in incremental publishing.”

“does it still make sense to build a direct sales force? As in, will it increase the unit economics if you do? I think our experience here with Slack and with GitHub and with many companies is, It's definitely yes, right? Yeah, the answer is yes. Because that's how you maximize ACV per customer, because there is a…”

“But even those aren't something that you can really protect because somebody could walk into a T-Mobile store in Idaho, and they could show a fake ID from our team. They could port my phone number to their phone, and then they could use that to reset all of my passwords.”

“And the thing is they don't have the sales force to carry pre chasm products. They're good at distributing things where there's a known budget, but if you're doing something. Fundamentally new, there's no way that a VAR can actually pitch, educate the customer and so forth. And so normally you have to create a pull…”

“The biggest jump in operational complexity a startup will ever do is when it goes from one product to two products.”

“A natural response of startups to not having product market fit is building another product, which I think is probably the worst thing you can do.”

“there's no other single number that like ties to the valuation, the price point. Because basically that's ACV.”

“don't discuss pricing until after you've got them to technical close.”

“it's quite possible to get a ton of engagement, and a ton of money, and do pox, and pilots, and everything else. And still, it's not actually moving. Like, you can even get license revenue, and it still remains shelfware. But if someone puts it in production, they want to use it.”

“Once you actually start to see a repeatable sale from a non-expert, then I think you now have good signal. So for example, anybody that can push the deal through without actually having the original founder, I think then you're kind of getting close to product market fit.”

“for example, if I look across AI startups, the ones that tend to be getting the most traction have taken AI and applied it to a vertical problem. They have access to a Priority data set, or they've done a specific sort of optimization, and now there's a vertical focus towards something, as opposed to I've got this very…”

“once you're talking about something as a service, questions around open source kind of diminish. Because they're not actually dealing with the code itself, they're dealing with the service.”

“if you've originated a project and you're bringing that to market, you should retain the ability to be the sole supplier, if only to set pricing and brand awareness in the market. Companies live or die by this type of thing.”

“in direct enterprise software sales, it seems to be this valley of death between like, say, 30 K and a 150. If you're 20 K or below, you know, it, it, you can call somebody up and they can pay for it. And let's say if you're 200 K and above, then you have a hopes of supporting a direct sales force and still have good…”

“So, so, so open source becomes very viable marketing.”

“Like Silicon Valley loves software companies because you get a repeatable product to market with a really high margin and high multiples. But if you start looking around a lot of the open source business models, it looks a little bit like a PSO company, which is lower margins and harder.”

“If you're having a hard time selling something, it's almost never priced early on. It's the market's not ready, or you actually don't have product market fit, or you don't have the right sales model.”

“If you identify, listen, we have to do direct sales because, you know, this is only applicable to the Fortune 2000, and this is a market category creation situation, so we have to have, like, kind of the deep conversation and it has to be evangelical sale. If your ACV isn't actually probably higher than that, 150,000,…”

“In my experience, feet on the street, whether it's you, it's your sales teams or somebody talking to customers is the primary channel for dissemination in early markets. Like you can write articles. They very rarely create concepts in people's brains and they very rarely create value.”

“In general, when we have seen companies come in that have open source strategies that create large top of funnels with developers, you get nice, super linear, Revenue ramps to a hundred million plus once they build direct sales.”

“until we get to about, say, two to three times OTE, you've hit a mature market.”

“in the early days, actually doing Cash-based comp isn't always the best thing because they'll find a way to get it, and that's not always the best way to get market signaling and market feedback.”

“something honestly that's worse than having no sales team and no numbers is a sales team that's starting for Oxygen, just because they can be so disruptive, not only to morale, but to internals of the organization.”

“If at all possible, don't talk about pricing until here in, in early market. And the reason is, is there's no way they can actually value your solution because they've never thought about before until you get to technical close.”

“The channel, a reseller, an OEM, a VAR reseller will only work in a poll-based market. Like if you're in a pre-market situation, they just can't do it. It requires too much evangelism.”

“And so if I think if you stand back and you take a high level heat map of the security industry, I don't think it's like building another mechanism or another point product. That's the problem now. We've actually got to a point that we can't really consume the technologies that are being created just because the sheer…”

“Developers influence budget. They often don't control a lot of budget. And so you can almost think of attracting the developer and getting them to use your product almost like a replacement for product marketing. It's like the top of the funnel. So you can get them excited. You can get them engaged. You get account…”

“And like, what's crazy is AI, A, solves the distribution problem. It just solves the demand problem. And B, these companies are able to raise so much money that they're actually on competitive footing with like the Microsofts and the medicine and the Microsofts. And so I think we're in a very new territory when it…”

“when you code, um, with AI, Your code kind of gets worse over time pretty materially, and so it's almost like you're introducing as many problems as you are solutions”

“Because the models are so hard to abstract away. Like, they're just, they're just unruly, right? If you try to, like, have traditional software drive them, they just don't kind of manage very well. So part of me thinks that it's almost like this, like, anti-disintermediation technology that you kind of have to expose…”

“I will say incumbents are very bad when new user behaviors and buy behaviors show up. Like, in particular, they don't know how to cater to it. AI is definitely a new user behavior and a new buying behavior, and so this is very much an advantage of startups, just because, you know, to change a, a large company around a…”

“being blinkered to how VCs view companies is, is actually quite dangerous because you're so dependent on follow on capital.”

“Markets are actually quite efficient. If the market's efficient and it's a good company, the price is going to be high.”

“if you're in a large public company, uh, like I was, you realize that the public markets really care about predictability over innovation for sure. I mean, and so innovation is stifled so much. And in fact, it, it kind of, It kind of causes large companies to protect themselves through kind of incumbency and…”

“if you have a message they wanna get out, they kind of have to go direct because I mean, if it's your own platform, it doesn't hate you.”

“what normally happens is somebody does something close source. It turns out to Create a market and then somebody releases open source and it like stops a monopoly from forming and enables everybody else, you know, and then it kind of, you know, keeps the, the people that are close to us to continue to be innovators,…”

“this is as big as software and the strategies need to vary as much.”

“Nuclear weapons are not dual use. Nuclear energy is dual use, right? An F-sixteed is, is not dual use. Like, a jet engine is dual use.”

“There was, there was always this prevailing view, which has turned out to be so wrong from really well-intentioned people, which was like, it's going to be regulated anyways. If it looks like we're self-policing, we can dictate, you know, how that happens. Um, and unfortunately that just turned out not to be true…”

“So one thing I've seen fail consistently, again, like you guys are way more expert than I am, but is this kind of notion of, You know, if a engineer spends one day a week experimenting, then maybe they'll come up with a great idea that changes the company. It just feels like that tends to not have enough momentum…”

“The distinction is it could have been the human being, the human mind that looked at the world, did the reasoning and created the world model. And that is cached in language.”

“One thing you definitely learn is that there is a skill to prompting like it, like this idea that like it, it allows everybody to be like creative is like not quite right. It just turns out that like some people know what they want and they have vision and they actually know the language of these models and they create…”

“Yeah, like the previous base models, you know, like the, the GPT lineage seemed to have asymptoted around GPT-IV.”

“it turns out that that chain of thought, if you have access to that, it allows you to train smaller models very quickly and very cheaply, and that's called distilling. So like the, the general, Term of distilling in LLM world means you have a teacher model, train a student model who's much smaller, and so it turns out…”

“It could be that the apps actually require you to own the model. And in that case, DeepSeek is less relevant because they're not building apps. And then, you know, this means that the impact to the opening AIs or Anthropics are, are not as great, right?”

“if it generates anything out of distribution. Like, and by the way, out of distribution means it's not commonly represented in the training set. Then that error is going to accrue and it tends to accrue exponentially provably, right?”

“It's exactly economic dislocations that create new startups, not just new technology.”

“So it's pretty clear if you just take the fundamental economic analysis that these large models bring the marginal cost of creation to zero, like creating that image, and language understanding, like reasoning over those documents.”

“And as a result, the investment community has kind of come up with this ethos around investing in consumer, which is basically, the graph is smarter than whatever theory we have about the market.”

“having a high price tag on it actually really helped with the commitment to do that, just because it was so material. So I don't know if this is a totally self-serving world way to think about it, but I'd like to argue that, like, high valuations are actually pretty good in this.”

“Well, the thing with software is if someone gets in the software at all, any piece of it, then basically they control the laws of physics.”

“A lot of people, they view sales as, I'm going to give, you know, one slide deck to somebody, you know, to a salesperson. They'll take that slide deck, and then they'll be successful in selling. No, like, actually, you're developing an algorithm that they need to follow that has a lot of if-else statements and things…”

“And the reason that we're seeing this rise in open source companies is not endemic to open source. It's the fact that we're seeing actually a transformation around developers and their aesthetic and the technologies.”

“I mean, I think that if I were to do it today, I would build one product that can Can be on-prem or off-prem, and it'd be as much as possible, the same product, which is going to require some gives on the on-prem side.”

“the developers are influencers. The developers have control and a large lateral voice on budget. Um, but in my experience, they aren't explicitly the buying center.”

“A community manager is not going to drive adoption like the best engineer on the planet actually building something good.”

“most material on go to market that you'll find in the general literature is around mature markets where you do things like market research and you know, how to do pricing and you know, how to do comparative analysis and all of this other stuff. And none of that applies in market category creating scenarios because…”

“So it turns out, at least in the enterprise space, pretty much all of the value of a company comes down to go to market. And this is very non-intuitive to me to begin with, but go to market is at least as important as technology.”

“I didn't understand until much, much later how true this is, that there's no single decision At least in enterprise, there's no single decision you'll make that is more important than pricing with respect to your valuation, not a single one.”

“What I've come to appreciate is, um, A, marketing is incredibly technical, and it's becoming exceptionally technical as developers become a buying center. It's actually also one of the best modes you can build around your company, so I think it's something to really invest in.”

“Every time you have a disaggregation, the market tends to grow by, say, a factor of 10.”

“almost all attacks have a human in the loop, an attack in the loop, was intelligent, it's dedicated, and is patient.”

“the second thing that happens in every time that you have one of these epochs is the existing incumbents from a previous era very rarely make it to the new one, right?”

“So developers having control or influence over budget changes all of this. And I think this is probably of all of the things that I'm speaking of the most significant and the most significant shift”

“these secular trends, like the internet was like this actually start with individuals and big companies tend to make decisions centrally.”

“Describing the game logic in English just doesn't work, actually, if you try and do it. And then, and then, like, actually scripting the output doesn't work either if you needed to use it in a game context.”

“they reduce a very, very complex multidimensional space into Basically a, a geometric manifold that's a reduced state space. So it's reduced degrees of freedom, but you can actually predict where in the manifold the reasoning can move to.”

“we as humans do the same thing as we take this very complex, heavy tailed, stochastic universe, and we reduce it to kind of this geometric manifold, and then When we reason, we just move along that manifold.”

“Even companies that seem like they're competing end up in totally different places just because so much white space is being created, but they're all competing, like totally different companies and spaces are competing with the same talent. So the first time I can remember where the actual talent competition is like…”

“Now, you know, someone can have an entire career investing in databases alone, right? And so as the market grows, clearly you have to specialize.”

“it's a lot more powerful that founders know that I've been a founder. Uh, and I know this is a such a cliche thing to say, but I, I, I do feel that resonates much more than like, I got a PhD in computer science or I know infrastructure.”

“Most companies with great brands did not do it through a VC firm. Right. And like, it's not like, you know, we somehow can single-handedly make great brands, but we are an accelerant.”

“So I, I think there's actually a very kind of technical question here of to what extent we can make these things have independent agency, but we can make them long run pretty easily.”

“every time we have a super cycle, it tends to start, you know, in these prosumer ways, right? The internet did this, right? Like, remember when Sun outlawed the, the browser, right? This is like Sun Microsystems, right? But they didn't really know how to consume it. So the enterprise doesn't know how to consume these…”

“companies go through three stages. They go through the product stage, the sales stage, and the operations. And there's actually leaders for each one of these stages.”

“We've been doing computer simulation forever. We totally know the limits of simulating physical phenomenon. Particularly chaotic systems. We have actually very far bounds on these. It's, by the way, it's not just like the, the limits on, on the size of like a, like a computer word or an integer or something like that.…”

“Um, so one thing that is, to me, was non-intuitive, but remarkable about these models is how Easy they are to distill. Which is as soon as someone creates a leader, everybody uses that leader and kind of sucks the life out of it. And then all the models kind of converge on it very quickly.”

“So one of them is often when you bring the marginal cost of something down, like with compute, you know, we did it for computation and for the internet, we did it with distribution. It, it, it increases the TAM a whole bunch. So, so for one, you almost always see this massive TAM expansion. And part of that tends to be…”

“early in super cycles, it's very hard to distinguish between an infra company and, like, the application companies, and the reason is because the TAM is so small and so new, the new technology becomes the app, right?”

“it's a super, super horizontal piece that takes basically a computer with a single view in the world, or maybe multiple views in the world, and creates a full three D representation that that computer then can act on. And so you can see that that's a very, like, Concrete, pivotal thing from everything from like…”

“to solve this problem, you need experts both in AI, and that's like the data and the models, like the actual model architecture, um, and graphics, which is like, how do you actually represent these things in memory, in a computer, and then on the screen?”

“the AI learnings of the last couple of decades is not that the technology can't be built, or even that we can't monetize it, we're actually good at all of that, is that this is very hard for startups to build businesses around.”

“Many of the traditional use cases of AI require correctness in the tail of the solution space, and that's a very hard thing for a startup to do for a couple of reasons.”

“You are a conduit to every organization that you're connected to, and so many attacks will start with you in your personal life and then move to the company.”

“So consumer companies are typically marketing-led, and that drives everything else about the company. Why is it marketing-led? Because if your customer's a consumer, there's no way you're gonna pay a sales force to go talk to every one of them. There's just no way. And so, the way that you get out to consumers is you…”

“It's very rare that you've got some sort of crazy technical moat in a consumer company, but some are just good at making products that users like, and they end up becoming winners.”

“And then you build a sales engine behind that to monetize that user base, and you have sales efficiencies that are far better than we've ever seen before in B to B.”

“buying a company when you're running a large business is, like, one of the few decisions you really have to live with. Like, a lot of the other ones, like, you kind of work your way out of in some way or another.”

“What you learn about starting a company is it's actually the opposite, which is almost every solution is dealing with the heavy tail of complexity, and it's a bunch of patches and the real world and everything else, and so mentally you've got to go from, I'm going to look at a problem space and extract elegance to, you…”

“Some companies like, you know, listen, we're just going to do organic growth. And they don't actually do sales. And in our experience, these tend not to be kind of hyper growth on the revenue side, right? So they'll continue to kind of grow customers, but it's hard for them to actually get these nice hyper linear…”

“as soon as it's publicly available for free, everybody knows about it, and it's very difficult then to kind of retract that. So you have to be very thoughtful about pricing and packaging up front because any experiment basically is reality now.”

“if you're doing bottoms up growth, I think you have to expect a lower ACV, which is a different way to build a sales team. And so you just have to be more comfortable with either inside, inside, outside models, and then you have to be more comfortable with focusing in on expansion rather than upfront ACV.”

“so much about enterprise dynamics come from renewals. Expansions and upsells. Often hyperlinearity, um, in growth comes from expansions.”

“doing one thing is really hard and doing two things I think is more than twice as hard often. And, you know, if you have to both have a sales team to bring on enterprise and a marketing team to bring on customers, these are like two fairly independent tasks and both of them are difficult.”

“Like over time, R and D pencils out as almost a fixed cost, or at least like super sublinear, right? You know, you've got a number of engineers, but sales scales linearly with a number of, of people on the ground.”

“there really is no single point in the company that better encompasses the ability to sell something in a repeated fashion than in product marketing.”

“I find the inclination is you're criticizing sales when often like the salespeople are doing the best that they can. They just haven't gotten the tools.”

“So often in category creation, you're actually competing with the status quo.”

“most of the products we see in this space have to position both to IT and to the line of business.”

“Like, every use case of AI requires specific tweaking in a massive, massive way.”

“with disruptive technologies is like the disruption happens first and then all the day two ops happen second.”

“if you're going to be doing tiering based on features, you've got to understand this really early on, and it has to be part of the product development cycle. You've got to make it actually part of the iterative cycle. Like, you have to think about it every time you do it.”

“open source needs to be independently complete and functional, like useful for a purpose, totally independently, maybe not all purposes, but if you just, Put it out there, and it doesn't really work, or it doesn't really work for something to get a job done. I think that you're gonna cause, like, issues with the…”

“initial outreach, initial branding, initial touch point, top of the funnel, like that can be aided with freemium and open source, but all of the sables Enablement, all of the partner enablement, and the customer certification, and the analyst relationships, certainly this is something that the marketing functional head…”

“I think the failure modes are if you're Very aggressive about reaching as many people as possible or as many customers as possible, and as a result, you set your pricing too low. I think that's hard to recover from.”

“You see budget shifting towards the profit center and trying to contract on the cost center. Behavior always follows business.”

“And I think actually one of the biggest logical fallacies that technical founders do is the following is they think that if you create a widget, it has intrinsic value and anybody that runs across that widget will be able to not only Understand how cool it is, but like the dollar value attached to it. The reality is…”

“in most market category creation situations, in most of them, you have to have a warm body in the customer selling, just because the customer doesn't even know how to think about it. So you, in most of cases, you have a direct sales model,”

“that direct sales is going to by far dwarf your cost, it becomes all of your variable cost, and that will become your margin, and that will set your valuation.”

“Market category creation is the customers don't even understand the technical concepts. They don't understand the approach. In many cases, they don't even know they have a problem.”

“So if, for example, early on you set your price too low, you'll basically cannibalize your entire future market and it's very difficult to raise price.”

“Like when you're dealing with like the early adopters, like the first adopters, they don't really listen to analysts because they're often like kind of wild west and they'll engage with you directly. But as soon as you go down market, like Gartner is really important.”

“Early market sales is very, very different than mature market sales. And the people that do well in early market sales are often very, very different than people that do well in mature market sales.”

“R and D really does pencil out as, as a fixed cost.”

“as markets grow, The unit for which you can create a viable company shrinks, right?”

“what we're seeing is we're seeing a next level of expansion where the app itself is being disaggregated into a set of APIs.”

“So if you compare that with today, today there's an API for everything. I mean, here's an example of a few thousand APIs everywhere from getting a random quote from Chuck Norris to identifying images, uh, in a picture to searching your email inbox. Right. And so what that means is if you are a domain expert, not…”

“Every time you have these, these disaggregations, you have to retool the infrastructure because the abstractions change.”

“the final one is whenever you have new disaggregations, you have on top of them, the emergence of new aggregation layers, like marketplaces that help you kind of sift through the chaos.”

“If there's a function that's sufficiently complex, um, that's being used by a large enough number of applications, it's a good candidate to become an API company.”

“The arms race says, I have one new weapon, and that will change from a symmetric to an asymmetric battlefield. And this says, you have these massive changes in the battlefield, and that requires both sides to entirely retool.”

“Unfortunately, the most difficult thing with starting a company in the enterprise space is actually bringing whatever you're building to market. And the reason is, is the incumbents have pretty much the entire go to market side locked up all aspects of it.”

“Now, professional services isn't the type of business any vendor wants to be in. It's just very low margin, right? For every dollar that, you know, the customer buys, you've got to put a body there and you've got to pay for that body.”

“so much of building an early enterprise company and changing the way the world works is understanding how people view the environment, mapping yourself to that, and then incrementally changing it to understand the value of your solution, which is a multi-step process.”

“in the case of the data center, if I'm a server, I should really only have to talk to other servers, um, that I need to talk to and nothing else, but the reality is, is, you know, if I'm able to compromise a server, I can talk to anything that I want, and so we need to move infrastructure to this principle of least…”

“the application has evolved into a network. I really believe that. So an application used to be like, I'm running Pac-Man, but that's no longer the case now. Like, think about like, think about like one query to Google, man. Like, you're literally touching hundreds of compute nodes, you know, databases, load balancers,…”