Best Podcast Episodes About Hewlett Packard Enterprise
Everything podcasters are saying about Hewlett Packard Enterprise — curated from top podcasts
Updated: Apr 26, 2026 – 25 episodes
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Ridealong has curated the best and most interesting podcasts and clips about Hewlett Packard Enterprise.
Top Podcast Clips About Hewlett Packard Enterprise
“… san francisco it's like oh well slightly dirtier but still okay yeah um here's something i would like to share with everyone since you brought up Hewlett Packard. Great. I just want to underscore for all the young people out there, which is like everyone in chat, a lot of people don't remember because they were in diapers at this time. I just want to point this out. Just to underscore how much this industry changes in a relatively short period of time. If you were to say today, I've got a brand new CPU, brand new chip coming, get hyped everyone I've got a brand new chip coming from Hewlett …”
“… new jersey like because that's like i don't think anyone from san francisco wants to be told they live in new jersey yeah yeah they're offended by that for sure right it's like where is this team from it's like new jersey or something it's like no it's san francisco it's like oh well slightly dirtier but still okay yeah um here's something i would like to share with everyone since you brought up Hewlett Packard. Great. I just want to underscore for all the young people out there, which is like everyone in chat, a lot of people don't remember because they were in diapers at this time. I just want to point this out. Just to underscore how much this industry changes in a relatively short period of time. If you were to say today, I've got a brand new CPU, brand new chip coming, get hyped everyone I've got a brand new chip coming from Hewlett Packard literally nobody would be like oh wow, like I can't wait to see, or most people would just be like what? Like what are you talking about? They don't do, they're just like they're like Dell or something they make like printers or monitors, I don't even know what they make, doesn't matter right? Hewlett-Packard was actually the partner. Them and …”
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Ridealong summary
Hewlett-Packard was once a powerhouse in computing, but their ambitious Project Itanium failed to deliver, leading to their decline in relevance. Today, most people don't even remember HP as a major player in the CPU market. This illustrates how quickly the tech industry can change, leaving once-prominent companies forgotten.
“… it's amazing like how fast this stuff shifted because like, you know, Steve famously had this, you know, short period of time where he worked for Hewlett Packard. And I think, I don't know if it's true. The legend is that Jobs pitched his manager at Hewlett Packard. No, Wozniak pitched him. Was it Wozniak? Okay. Okay. Wozniak pitched. There was some other story where Jobs went into some meeting with some manager trying to pitch the thing. And the line from the manager was, absolutely not. This is the dumbest study I've ever heard. Get your feet off my desk and get out of here. You can just …”
“And then what happens is other founders look at that and they're like, oh, I could do that. Right. Which is exactly what Steve Jobs said when he saw Nolan Bushnell. Exactly. I can run my company. I can do that. Yeah, exactly. And by the way, you know, it's amazing like how fast this stuff shifted because like, you know, Steve famously had this, you know, short period of time where he worked for Hewlett Packard. And I think, I don't know if it's true. The legend is that Jobs pitched his manager at Hewlett Packard. No, Wozniak pitched him. Was it Wozniak? Okay. Okay. Wozniak pitched. There was some other story where Jobs went into some meeting with some manager trying to pitch the thing. And the line from the manager was, absolutely not. This is the dumbest study I've ever heard. Get your feet off my desk and get out of here. You can just imagine Steve with his – And they had to be bare feet at that time. My favorite Apple lore is that the first sale in Apple's history was made barefoot when he walked into the bite shop. He was barefoot. What's amazing about that is – so it was that for sure. or for Hewlett-Packard. Everything I'm describing was Hewlett-Packard in the 1950s and 1960s and …”
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Hewlett-Packard was the most influential company in Silicon Valley from 1940 to 1980, shaping the entrepreneurial landscape that followed. Founders like Steve Jobs and Intel's Bob Noyce drew inspiration from HP's model of founder-led management. This legacy reveals the crucial role of visionary leadership in tech innovation.
“… companies where when they pass a major milestone like that, you know, see that's OK. Well, gosh, CNBC decided to do it's the it's the anniversary of Hewlett Packard and he and they found some person who pitched a story about the anniversary. And so there's going to be something on the website or maybe they found a half an hour on CNBC on the cable channel to do it for. Can you think of any other tech company that has that kind of impact where this seems like not just something to celebrate for the fandom, but something that this feels like a moment, a time to look back and not just think about …”
“… are around to know that person or could give their testimonies, you need to know the perspective or else these are just incidents that just sort of abut each other chronologically. But the most interesting thing is that there aren't a whole lot of companies where when they pass a major milestone like that, you know, see that's OK. Well, gosh, CNBC decided to do it's the it's the anniversary of Hewlett Packard and he and they found some person who pitched a story about the anniversary. And so there's going to be something on the website or maybe they found a half an hour on CNBC on the cable channel to do it for. Can you think of any other tech company that has that kind of impact where this seems like not just something to celebrate for the fandom, but something that this feels like a moment, a time to look back and not just think about Apple, but think about the relationship of technology. Exactly. In the industry. Even IBM. Yeah. I can't think of another company that's made such an impact. Chris, you're watching Mac Break Weekly, so that makes sense. Right. I mean, even like last year, Microsoft had their 50th anniversary and they did a lot of stuff. And I think that there's a lot …”
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Ridealong summary
Apple's impact on technology is unparalleled, making its 50th anniversary a moment to reflect on its history and influence. Unlike other tech giants, Apple evokes deep emotional connections and discussions about the evolution of the industry. This perspective is crucial for understanding the company's significance beyond just its products.
“… a thought experiment anymore. It's a live dashboard with weekly metrics. All right, folks, quick pause. Here's the uncomfortable truth. If your enterprise AI strategy is we bought some tools, you don't actually have a strategy. KPMG took the harder route and became their own client zero. They embedded AI and agents across the enterprise, how work gets done, how teams collaborate, how decisions move, not as a tech initiative, but as a total operating model shift. And here's the real unlock. That shift raised the ceiling on what people could do. Humans stayed firmly at the center while AI reduced …”
“the zero-employee company isn't a thought experiment anymore. It's a live dashboard with weekly metrics. All right, folks, quick pause. Here's the uncomfortable truth. If your enterprise AI strategy is we bought some tools, you don't actually have a strategy. KPMG took the harder route and became their own client zero. They embedded AI and agents across the enterprise, how work gets done, how teams collaborate, how decisions move, not as a tech initiative, but as a total operating model shift. And here's the real unlock. That shift raised the ceiling on what people could do. Humans stayed firmly at the center while AI reduced friction, surfaced insight, and accelerated momentum. The outcome was a more capable, more empowered workforce. If you want to understand what that actually looks like in the real world, go to www.kpmg.us slash AI. That's www.kpmg.us slash AI. With the emergence of AI code generation in 2022, NVIDIA master inventor and Harvard engineer Sid Paresci …”
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Ridealong summary
If your enterprise AI strategy is just about buying tools, you’re missing the mark. KPMG transformed their operations by embedding AI into their entire model, empowering their workforce and accelerating productivity. This shift reveals that successful AI adoption is about integration and culture, not just technology.
“and was really interesting because that was the first time that I realized that large companies, enterprises, institutions want to leverage crypto and they want to leverage at scale. The problem is that not all of these companies are set up to integrate those brand new rails, this brand new technology in a way that is regulated and compliant and not just in the US, but across all jurisdictions, right? Like crypto makes everything global from day one. The problem is that regulations have a lot of fragmentation. It's not the same frameworks. And so …”
“and was really interesting because that was the first time that I realized that large companies, enterprises, institutions want to leverage crypto and they want to leverage at scale. The problem is that not all of these companies are set up to integrate those brand new rails, this brand new technology in a way that is regulated and compliant and not just in the US, but across all jurisdictions, right? Like crypto makes everything global from day one. The problem is that regulations have a lot of fragmentation. It's not the same frameworks. And so really interesting problems to solve there. I was kind of helping build a lot of the core infrastructure for the custody and the on and off ramp and then core infrastructure for the issuance of the Libra currency. And this is the first time that I realized that something like Bastion was needed, some type of partner that would help with the …”
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Ridealong summary
In 2023, the need for a partner to help enterprises navigate the complex world of blockchain and crypto led to the creation of Bastion. This was sparked by the realization that many large companies struggle with regulatory compliance and technology integration in a fragmented global landscape. With a background from Anchorage and Meta's Libra project, the founder saw firsthand the problems faced by institutions and decided to take action.
“… be better than MCP. And hooks, I think, are really good if you are the type of person that loves to make their tool like super custom. But from enterprises, what we've seen is that enterprises will have like a couple of people focus in on making skills, MCPs, tools for their whole organization or for big teams in their org. And because factory is the only offering that lets you actually from an enterprise perspective, manage who has what customizations from the user team and enterprise level. I think that a lot of power users end up getting converted over to factory because it's just easy to get …”
“… them. And obviously, we have a registry for things like linear, notion, axiom, Datadog, Sentry, etc. My view is that skills might be just a better way to manage like integrations context. And so if you can get a skill for a given capability, that might be better than MCP. And hooks, I think, are really good if you are the type of person that loves to make their tool like super custom. But from enterprises, what we've seen is that enterprises will have like a couple of people focus in on making skills, MCPs, tools for their whole organization or for big teams in their org. And because factory is the only offering that lets you actually from an enterprise perspective, manage who has what customizations from the user team and enterprise level. I think that a lot of power users end up getting converted over to factory because it's just easy to get everyone in your 10,000 person company outfitted with a skill that meaningfully changes their dev productivity on a daily basis. So there's like a permission system or something? Yeah, permissions and also just shared access to a ton of different skills, tools, MCP at the enterprise level. And you can tell me now on this, but can you actually show …”
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Ridealong summary
Managing skills in enterprises can significantly boost productivity, as seen with the Factory platform. By integrating shared skills and permissions, companies can easily equip thousands of employees with tools that enhance their daily tasks. This innovative approach transforms the way teams collaborate and achieve their goals.
“… issue, especially where a lot of the solutions, as in the ones you just mentioned, tend to come from the center and be very centralized within the enterprise? Yeah, I think setting clear AI policies, like what data can we use, what outputs require review, and who's accountable. It's very important when you're working with multiple data partners. I have seen it's like setting house rules for a teenage AI. Don't let it roam around, whatever it wants to do. So I think setting clear AI policy, what data could be used for, where it's coming from, what the intent for it, it's very imperative. Yeah, you …”
“… before the problem of working with partners, that that data is being shared. It's getting very messy through these systems that jumble them all up, especially on the generative side. Just any advice for working with different data partners on this issue, especially where a lot of the solutions, as in the ones you just mentioned, tend to come from the center and be very centralized within the enterprise? Yeah, I think setting clear AI policies, like what data can we use, what outputs require review, and who's accountable. It's very important when you're working with multiple data partners. I have seen it's like setting house rules for a teenage AI. Don't let it roam around, whatever it wants to do. So I think setting clear AI policy, what data could be used for, where it's coming from, what the intent for it, it's very imperative. Yeah, you say teenage AI, but I think teenagerdom especially really describes this moment of adoption where this is not the stuff that came out of the womb, so to speak, back in 2022. This has advanced very far in three years. In another three years, we could really see it start to be, generally speaking, old man AI, have a lot of authority, even carry a lot …”
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Ridealong summary
To avoid legal chaos, companies must implement clear AI governance policies, including transparent data tracking and human oversight. As AI evolves, it resembles a 'teenager' that needs guidance to prevent copyright issues and ensure compliance. Enterprise leaders must start addressing these challenges now, or risk falling behind as regulations tighten.
“… I think there was some MIT paper that came out. This is not a faulty MIT. This is somebody who published the paper. It's like, oh, you know, most enterprise deployments really, really aren't working in terms of AI. We're seeing the exact opposite of two things. So there's a company called RAMP and they are kind of credit card expense management products. And you see this giant tick up in January of 2025, which is, you know, when did enterprises and these are much more like who uses RAMP. This is not necessarily a startup, but it's a more forward thinking company. It's not necessarily GE. It's a …”
“… here is just remarkable. And the important thing is just the opportunity set that it unlocks. So whenever you have a bull market and very, very exciting tech, there's always somebody saying it's a bubble or it doesn't work or it's all overhyped. And I think there was some MIT paper that came out. This is not a faulty MIT. This is somebody who published the paper. It's like, oh, you know, most enterprise deployments really, really aren't working in terms of AI. We're seeing the exact opposite of two things. So there's a company called RAMP and they are kind of credit card expense management products. And you see this giant tick up in January of 2025, which is, you know, when did enterprises and these are much more like who uses RAMP. This is not necessarily a startup, but it's a more forward thinking company. It's not necessarily GE. It's a company with thousands of employees, maybe in the Bay Area or New York that wants to be more tech forward. And they've just realized like, wow, this stuff, Jen, to your point, like GPT 3.5, pretty good for I was like, wow, it's pretty amazing. I can write a new episode of Seinfeld with it, like amazing things that I could do almost to kind of wow my …”
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The podcast emphasizes the transformative potential of AI in enterprise settings, suggesting that companies like Emergent are not just riding a trend but are fundamentally changing how businesses operate and generate revenue.
“And I think that you're going to see the shift from enterprises. Now the CEO saying, Hey guys, time out, quit like, you know, like trying to DIY this stuff and vibe code this stuff and go out in the market and let's find the best enterprise grade AI application for the problem we're trying to solve. And I think that we're going to move into this new period of, um, SAS, right? So if, you know, cloud, you know, gave birth to this whole new type of company, you know, Salesforce, HubSpot, right. Um, these …”
“And I think that you're going to see the shift from enterprises. Now the CEO saying, Hey guys, time out, quit like, you know, like trying to DIY this stuff and vibe code this stuff and go out in the market and let's find the best enterprise grade AI application for the problem we're trying to solve. And I think that we're going to move into this new period of, um, SAS, right? So if, you know, cloud, you know, gave birth to this whole new type of company, you know, Salesforce, HubSpot, right. Um, these incredible SAS applications, we're now beginning to move into a period. We're going to see these, this incredible emergence of AI applications, right. New or some SAS companies will be able to cross that chasm themselves and create, uh, really powerful AI enabled applications from there. So do you think that some of those SAS, like Salesforce or, or …”
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Ridealong summary
We're on the brink of a massive shift in AI implementation, where enterprises are moving away from DIY solutions to seeking robust, enterprise-grade AI applications. This evolution mirrors the rise of SaaS companies in the early 2000s, with some companies set to dominate while others may fail. As enterprises aggressively evaluate new AI solutions, the landscape is primed for both innovation and disruption.
“… that much better. We've asymptoted to, we can call it AGI Actually, Olly Godsey talks about this. We're already at AGI for a lot of functions in the enterprise. For those tasks, you probably could build very specific companies that focus on just getting as much value out of that task that isn't coming from the model itself. There's probably a rich enterprise business to be built there. I mean, could be wrong on that. But there's a lot of interesting examples if you're looking at the legal profession or whatnot. And maybe that's not a great one because the models are getting better on that front too. …”
“… I think there's also just a possibility that the capital markets will just give them the ammunition to just go after everybody on top of them. I do wonder though, to your point, if there's a certain task that getting marginally better isn't actually that much better. We've asymptoted to, we can call it AGI Actually, Olly Godsey talks about this. We're already at AGI for a lot of functions in the enterprise. For those tasks, you probably could build very specific companies that focus on just getting as much value out of that task that isn't coming from the model itself. There's probably a rich enterprise business to be built there. I mean, could be wrong on that. But there's a lot of interesting examples if you're looking at the legal profession or whatnot. And maybe that's not a great one because the models are getting better on that front too. Then the value comes from services. It comes from implementation. It comes from all these things that actually make it useful”
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Ridealong summary
Many experts believe we're closer to AGI than we think, especially for specific enterprise tasks. With open-source models rapidly evolving and capital markets backing aggressive growth, companies may soon leverage AGI capabilities to dominate their sectors. This shift could redefine how businesses operate, focusing on extracting value from these models rather than just the models themselves.
“And I see that as a little bit of a bellwether because I think as Salesforce goes, so does a lot of enterprise software. And I think a lot of people are going to try and have to figure out what is the new business model in this headless world. You know, do you do you charge a little bit of a small just API tax? Is there a seat for the agent? So there's obviously some work to do with that. And Stephen, I saw one of your tweets on some of the complications there. But I think as a moment, it's a big deal because I think it's a recognition that software …”
“And I see that as a little bit of a bellwether because I think as Salesforce goes, so does a lot of enterprise software. And I think a lot of people are going to try and have to figure out what is the new business model in this headless world. You know, do you do you charge a little bit of a small just API tax? Is there a seat for the agent? So there's obviously some work to do with that. And Stephen, I saw one of your tweets on some of the complications there. But I think as a moment, it's a big deal because I think it's a recognition that software will be running in the background. It always has for machine users and applications. And now it is for these sort of probabilistic machine users or non-deterministic machine users. And what's cool and where I think this gets pretty exciting is, you know, as soon as I saw that announcement, like I had like five to 10 personal use cases where I would …”
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Ridealong summary
AI should be treated as a user, not just software, to unlock its true potential in product development. This shift means re-architecting products to allow AI to operate as an agent, rather than simply integrating AI features. Companies are realizing that this fundamental change is necessary to avoid the pitfalls of hybrid models that have failed in the past.
“… Interesting. So that sounds a lot like one of my favorite blogs on the topic from F Sharp for Fund and Profit, which I believe was described as the Enterprise Developer from Hell. Yes. Oh, yes. So that was you he was writing about. I don't actually fully remember the Enterprise Developer from Hell from the book. I mean, if you want to give me a minute, I'll go pull the book off the bookshelf over here and read it. We can we can pick this up. But well, it's a great series because it talks about very much walking through this sort of process where any I think they use the concept of addition, where if …”
“… think the biggest thing you see with a lot of workloads as a problem is that people were not thinking about what are all the inputs that I could see here. And let me make sure that my workload is getting all of those possible inputs as a possibility. Interesting. So that sounds a lot like one of my favorite blogs on the topic from F Sharp for Fund and Profit, which I believe was described as the Enterprise Developer from Hell. Yes. Oh, yes. So that was you he was writing about. I don't actually fully remember the Enterprise Developer from Hell from the book. I mean, if you want to give me a minute, I'll go pull the book off the bookshelf over here and read it. We can we can pick this up. But well, it's a great series because it talks about very much walking through this sort of process where any I think they use the concept of addition, where if you just take two operands, you can switch all the way down all of your different hard coded answers. And what does it take to level up and up and up into a more effective sort of type focused property based testing algorithm? But when we're thinking about workloads, we're not usually thinking about one function, right? We're usually thinking about …”
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Many developers unknowingly limit their testing inputs, leading to undetected bugs. By expanding test workloads beyond simple cases like '1 + 1', they can create a library of diverse scenarios that reveal hidden issues. This approach transforms testing from a basic function check to a comprehensive evaluation of system behavior.
“… also add to that real quick that you know that goes far beyond API usage as well You know, I think in the AI space, there's a tendency to refer to enterprise as API, refer to API use as like the extent of enterprise. But I mean, there's also the, you know, there's that element as well as the element of what do we want to provide to our 2000 employees, I think. Right. Sorry. I just wanted to tack that on there before we got an answer. No, I mean, that's a great point. I think, Grant, to your question, the answer is yet to be determined. Fair. In the channel conversation specifically, I would say …”
“Yeah. So what in your mind does that change for everybody else in the ecosystem if anything I would also add to that real quick that you know that goes far beyond API usage as well You know, I think in the AI space, there's a tendency to refer to enterprise as API, refer to API use as like the extent of enterprise. But I mean, there's also the, you know, there's that element as well as the element of what do we want to provide to our 2000 employees, I think. Right. Sorry. I just wanted to tack that on there before we got an answer. No, I mean, that's a great point. I think, Grant, to your question, the answer is yet to be determined. Fair. In the channel conversation specifically, I would say there are so many players already in that I find it, I will find it very interesting, I'll say this, to watch how an open AI and Anthropic, etc. kind of enter enterprise now, for lack of a better term. right now that's not to say companies don't switch tools they do yeah by all means right so we could absolutely see a world where everybody goes …”
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Ridealong summary
In 2026, enterprises may face overwhelming challenges as they integrate new AI tools into existing tech stacks. Many companies already use multiple legacy systems, making it crucial for new AI solutions to seamlessly connect with them. As competition intensifies, businesses are forced to choose reliable partners rather than risk adopting numerous disparate systems that could disrupt operations.
“… of what that other aspect does that actually makes sense to deprecate and then remove that first one it does get harder um as we get more and more enterprise focus even with these tools because they come to depend on it i'll never forget we um one of the things i did maybe six months into when I was still a chief product officer, was we did a big sort of redesign of Cloud AI, and we were so proud, and we shipped it, and we got a bunch of kudos, and then we got this really angry email for somebody that like I just recorded 20 hours of enablement content for my company to do for Cloud Enterprise and …”
“… they have sort of the leading features as a sort of imperative of people on the team like if this is not working let's go unship that you know and it's often when you've created something else that even if it doesn't entirely supersede it does enough of what that other aspect does that actually makes sense to deprecate and then remove that first one it does get harder um as we get more and more enterprise focus even with these tools because they come to depend on it i'll never forget we um one of the things i did maybe six months into when I was still a chief product officer, was we did a big sort of redesign of Cloud AI, and we were so proud, and we shipped it, and we got a bunch of kudos, and then we got this really angry email for somebody that like I just recorded 20 hours of enablement content for my company to do for Cloud Enterprise and now I have to redo all of it and we like okay like they you playing at a different release cadence and of course like shipping twice a year at one of our conferences is not an option so we are going to keep moving quickly but then we've since like learned to maybe moderate how we roll it out to the enterprise side a little bit more but yeah i think …”
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Scaling a product team too quickly can actually hinder progress, as Mike Krieger discovered while building Instagram and Artifact. He emphasizes that keeping teams small allows for faster iteration and easier decision-making, especially in the rapidly changing landscape of AI products. This insight is crucial for startups aiming for product-market fit without getting bogged down by coordination issues.
“… takeaway is that context engines and the idea of context AI is not a buzzword. It's not just a buzzword. It's the competitive edge that every enterprise needs at this point. And that it's possible with trust. We can have context AI and give this AI all of our information, the ins and outs of our organization, and still be able to trust that there won't be data leakages or things like that. And then it is industry-wide and it is C-suite-wide. Whether you are a CEO, a CFO, a CTO, it is something that needs to be integrated in all parts of an enterprise for it to be successful. 100% this is a …”
“I think my biggest takeaway is that context engines and the idea of context AI is not a buzzword. It's not just a buzzword. It's the competitive edge that every enterprise needs at this point. And that it's possible with trust. We can have context AI and give this AI all of our information, the ins and outs of our organization, and still be able to trust that there won't be data leakages or things like that. And then it is industry-wide and it is C-suite-wide. Whether you are a CEO, a CFO, a CTO, it is something that needs to be integrated in all parts of an enterprise for it to be successful. 100% this is a question of the maturity of AI in enterprise. I think as this has matured, I think the problem of context has become right. Our expectations from agents have become, I would say, higher. and as these expectations become higher, we find out that in order to meet these expectations, we need to equip the agents with better understanding of the universe …”
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Ridealong summary
Context engines are not just buzzwords; they're essential for enterprises aiming to succeed in AI. By integrating context AI across all levels—C-suite included—businesses can trust their AI systems to navigate complex environments without data leaks. As expectations for AI agents rise, equipping them with a deep understanding of their operational context becomes critical for success.
“… that will shape AI are a little bit more back in the realm of operations and AI in practice. And the first is, how fast will differentiated enterprise adoption compound? And so the key terms are differentiated adoption and compounding. You have probably already heard me talk a lot about efficiency versus opportunity AI. Efficiency AI, in short, is doing the same with less. Opportunity AI is recognizing that the real power of this technology is not just to be 30% more productive, it's to do things you never could before. Now, right now, we are living in the shift from efficiency to Opportunity …”
“Now, our last two questions that will shape AI are a little bit more back in the realm of operations and AI in practice. And the first is, how fast will differentiated enterprise adoption compound? And so the key terms are differentiated adoption and compounding. You have probably already heard me talk a lot about efficiency versus opportunity AI. Efficiency AI, in short, is doing the same with less. Opportunity AI is recognizing that the real power of this technology is not just to be 30% more productive, it's to do things you never could before. Now, right now, we are living in the shift from efficiency to Opportunity AI. The changes that are happening right now are not little. They are insanely huge. We've gone in the last three months from people viewing agents as these things which might be interesting in some vertical areas or functional areas, to people building massive agentic teams with OpenClaw that are changing literally every single thing about how …”
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Ridealong summary
The enterprise landscape is about to be transformed by AI, with a significant divide emerging between fast-moving startups and established companies. While 80% of enterprises may struggle with slow adoption, the top 20% will leverage AI gains to outpace competitors, reshaping their industries. This shift will redefine organizational structures and accelerate innovation like never before.
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Robert Pack was on the verge of an All-Star season, making the game easier for his teammates, when a bizarre injury abruptly changed everything. During a scrimmage, an assistant coach accidentally caused a nerve injury that left Pack unable to walk, ultimately curtailing his promising career. This story highlights how pivotal point guards can be and the fragility of athletic careers.
“… betting with on really small teams that we think have very defensible businesses in a world of uh you know agi but it's what happens to all these enterprise software companies? Do they become PE takeouts? Do they get consolidated? Or do they just have to adopt these AI technologies and solve this problem of, hey, the frontier model is just going to solve for whatever these niche software companies do? I think the market's probably being a little too pessimistic with respect to at least some of these software companies. I mean, obviously, there's going to be big differences in the quality of the …”
“… value to chamas insights over the last few weeks is very difficult to do that's why you see this crowding so we've taken a barbell approach right we've got a lot in what we think are the most important companies that are on the frontier and then we're betting with on really small teams that we think have very defensible businesses in a world of uh you know agi but it's what happens to all these enterprise software companies? Do they become PE takeouts? Do they get consolidated? Or do they just have to adopt these AI technologies and solve this problem of, hey, the frontier model is just going to solve for whatever these niche software companies do? I think the market's probably being a little too pessimistic with respect to at least some of these software companies. I mean, obviously, there's going to be big differences in the quality of the moats of these companies. companies and so look software is going to be a lot cheaper and easier to generate but i'm not sure that was the competitive advantage of a lot of these companies so there probably a little bit of the baby being thrown out with the bathwater right now and there probably are some value buys in enterprise software I think the …”
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Venture capitalists are increasingly wary of investing in enterprise software due to the rise of AI, with many fearing a market collapse. Brad Gerstner reveals that while some software companies face existential threats, there may still be hidden value amidst the chaos. The future of enterprise software could hinge on whether these companies adapt to AI or face consolidation and takeovers.
“… brain and a database Right. And like right now, all AI development is like, would you like to just chat with this database? And the answer in the enterprise appears to be yes. Like, let me just talk to my analytics database directly like a person and it will give me some insights. And the answer in consumer maybe is no, right? Like Google Photos just walked back its AI search because it turns out people prefer the regular search. And I don't know which one is going to win out over time and where it habits for everybody across work and their personal lives will change. But the notion that the …”
“… that becomes the most valuable thing One of our own designers here at The Verge said to me right before I came to talk to you he heard I was talking to you and he said all software development in 2026 is just calibrating the interface between your brain and a database Right. And like right now, all AI development is like, would you like to just chat with this database? And the answer in the enterprise appears to be yes. Like, let me just talk to my analytics database directly like a person and it will give me some insights. And the answer in consumer maybe is no, right? Like Google Photos just walked back its AI search because it turns out people prefer the regular search. And I don't know which one is going to win out over time and where it habits for everybody across work and their personal lives will change. But the notion that the database is the important thing and that's where the value is because anybody can ask an agent to go make a bespoke piece of software to do some business function. Doesn't it seem likely that the database vendors will just raise their prices or increase the barriers to access or find other ways to extract more value from having that data? Because that's …”
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Ridealong summary
In 2026, the real value in software will lie in accessing databases, not just creating applications. As AI agents become more common, enterprise users want to interact directly with their data, while consumer preferences may differ. This shift could lead database vendors to raise prices and control access, highlighting the growing importance of data over intelligence in software development.
“And this is the kind of thing that we want to enable for all enterprises. So this question of build versus buy, it is a spectrum. It is a continuum. and regardless of where you fall on that spectrum, where the dial is for you on that continuum, we are trying to give you all of the tools that you need to make it possible for you to pick the best possible agents that are there. Build what you need to buy what you can and then stitch them all together at enterprise point. Absolutely. And I still think leaders are …”
“And this is the kind of thing that we want to enable for all enterprises. So this question of build versus buy, it is a spectrum. It is a continuum. and regardless of where you fall on that spectrum, where the dial is for you on that continuum, we are trying to give you all of the tools that you need to make it possible for you to pick the best possible agents that are there. Build what you need to buy what you can and then stitch them all together at enterprise point. Absolutely. And I still think leaders are trying to find that difference, especially now that it's more of a ratio necessarily than a binary. What should leaders look for instead of buying more tools? How do they know when to hold back, especially with all the marketing around? So this is one where I don't have a formulaic answer because, again, like I said, this will be very specific to the …”
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Ridealong summary
Enterprises need to dive into AI experimentation to avoid being left behind, as the field is evolving rapidly. Papi Menon, a leader at Outshift by Cisco, emphasizes that while organizations should innovate, they must do so safely and with flexibility, adapting to new technologies as they emerge. The key is to experiment with important problems while maintaining the ability to pivot as the landscape changes.
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