EVERY SPOKEN WORD
65 min read · 12,874 words- 0:00 – 1:05
Trailer
- SPSpeaker
So the board goes to the CEO and what does the board say? "We need more AI." [laughs]
- SPSpeaker
Yeah.
- SPSpeaker
And what does the CEO say? "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.
- ALAaron Levie
The funniest concept that the more code we write, the less we would need engineers, it'd be the opposite because n- now your systems are even more complex than before, which means that you're gonna be running into even more challenges of when you need to do a system upgrade or when there's downtime and you have to figure out like, what, well, how do I fix that problem, or when there's a security incident. I mean, we're just getting started with the jobs on this front.
- SPSpeaker
They're gonna hit a wall at integration.
- ALAaron Levie
Yes.
- SPSpeaker
And, and this, the thing that's not different about AI, and that agents don't fix, that nothing fix, is that any enterprise of a thousand people or more or that's older than 10 years is just a mass of stuff that's sitting there waiting to be integrated. And, and you can't just say it's gonna integrate. AI actually doesn't help to integrate anything.
- 1:05 – 4:30
Introductions & The Silicon Valley vs Enterprise Gap
- SPSpeaker
Hey, we are here monitoring the situation l- live, and we're very excited to talk about a bunch of AI stuff, and we have, uh, three of us are here today. Uh, there's me, Steven Sinofsky, and M- Martin Casado, who will wave and say hi. I'm Martin. And-
- SPSpeaker
Hello. Hi, Martin
- SPSpeaker
... and Aaron Levie, who is, is working on the elevation of his hair today, so we're excited about that.
- ALAaron Levie
I, it, it just keeps getting more vertical, and, uh, I thought I could kinda tame it, but it didn't work.
- SPSpeaker
A- and is that just a token issue or a parameter, number of parameters issue with the-
- ALAaron Levie
[laughs] It is too many parameters. Too many parameters.
- SPSpeaker
Okay. I have the same thing, but in reverse. Okay. So-
- ALAaron Levie
[laughs]
- SPSpeaker
[laughs]
- ALAaron Levie
You... Hey, listen, you have a distilled model.
- SPSpeaker
There... Yeah. [laughs]
- ALAaron Levie
Yeah.
- SPSpeaker
That's my... I run local.
- ALAaron Levie
Yeah.
- SPSpeaker
So we had a lot of, uh, there's been a busy week of things, but we're- we wanna bubble it up a little bit and just start talking about where, where things are, are heading. Um, but I'll, I'll let... I- just kick it to you, Aaron, and you start where you are the most excited this moment because you have visited a ton of customers this week and have learned a lot. You've shared a lot on X, but I think you're the most in-the-trenches CEO who is really talking to customers every single day in the enterprise, which is what the three of us tend to look at the most.
- ALAaron Levie
Yeah, I think my, uh, it feels like my job these days is just bring reality to the Valley and then bring the Valley to reality as, uh, as much as possible, and it's a, it is a kind of a crazy divide that, that, that exists at the moment. Um, you know, the past couple week-
- SPSpeaker
Well, so let's take a step back.
- ALAaron Levie
Yeah.
- SPSpeaker
I actually think it's super interesting. What, what is it, what's the gap caused by? What's, what, what is that?
- ALAaron Levie
The gap is caused by... Yeah. Well, I think the gap is, and M- Martin, I'm sure you see this, but I think the gap is caused by the styles of work that exist in Silicon Valley and in engineering roles versus sort of the rest of the world. So, and we've talked about this a couple times in, in different forms, but, but, you know, the, the technical aptitude of an engineer is just like insanely high. The level of wiredness to what's going on in the internet is insanely high. The, the ability to use your own tools and make your own choices is insanely high, and when things go wrong with the systems that you choose, you can just like quickly debug them and then make them sort of work for you. And then obviously you have all the benefits of just the models are really good at code and, and the work is verifiable. So you have like, you know, five or 10 things that make agents work in an enterprise context for engineering, or at least a, even a startup context for engineering, that, that tend to be a, th- there tends to be a gulf between the way you work that way in engineering and the rest of, of sort of knowledge work. And so, and so a lot of what I see is trying to figure out how do we kind of, you know, bottle up all of the greatness that is, you know, what we are seeing from coding agents, what we're seeing from agents that can use computers, um, to how do you bring that into the enterprise where the workflows are, are, you know, quite different. The users are less technical. The data is much more fragmented. The systems are much more legacy. And so that, that tends to be the divide. So it's not even that we're like talking past each other, like in a, in a, one of those kind of classic like government versus industry. It's, it's just literally like there is just a pure workflow and, and, and technology set divide and, and that's why it's gonna be, you know, a number of years for this sort of diffusion to, to roll from what we're seeing in Silicon Valley, what we're seeing as tech startups all around the world, into the rest of knowledge work.
- 4:30 – 9:16
Why Enterprise AI Efforts Keep Failing
- SPSpeaker
Martin, just to build a... You have a ton of experience in big companies. I- one of the other issues, though, is scale.
- SPSpeaker
Yeah.
- SPSpeaker
And the, the way, the difference in scale that Silicon Valley operates at, at the startup level versus everyone else.
- SPSpeaker
Yeah. I al- I also think that, I mean, these secular trends, like the internet was like this, actually start with individuals, and big companies tend to make decisions centrally, and this is one of the fastest growing secular trends. So like, uh, there's probably a lot of individuals in big companies that are doing it where like-
- SPSpeaker
Yes
- SPSpeaker
... the big companies themselves don't know even how to think about it. And so when you hear stats like, oh, like AT&T had this stat, like 95% of AI efforts in big companies fail. Like, that's clearly silly because I am sure everybody's using ChatGPT very effectively. What-
- SPSpeaker
Yes
- SPSpeaker
... what they really should be saying is, you know, whatever. Like I, listen, I sit in these boards too, so the board goes to the CEO and what does the board say? "We need more AI." [laughs]
- SPSpeaker
Yeah.
- SPSpeaker
And what does the CEO say? "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. And so I don't... You know, when we say scale, often we, we think about things like system scale or number of peoples. I think the secular trend is scaling wonderfully, which is being reflected in the numbers of these companies, but organizations don't know how to adjust these kind of, you know, age-old processes that have been, you know, worked on for a decade around, you know, data and governance and operations and compliance, et cetera. That's kind of right now where I think Aar- like Aaron is right between the secular trend and the, the organizational decision body. Uh, and this is something that we actually track very closely because we're starting to see now, I would say in the last few months, finally some real kind of inroads into the enterprise, but it's, it's, it's tepid because... And, and the last thing I'll say of this, one of the reasons is there's a lot of skepticism because the board wants AI, CEO AI failures have created some-... amount of bruising, which is, you know, you know, requiring these companies to get past it in order to do kind of the second go at it.
- ALAaron Levie
Well-
- SPSpeaker
And so I think this is exactly where we are.
- ALAaron Levie
Yeah, I, I, a hundred percent agree with that, which is that it's good to start with agreements because we, we know how quickly that fades, uh [laughs]
- SPSpeaker
[laughs] Because we'll disagree the rest of the show. Exactly.
- ALAaron Levie
Yeah, exactly. Exactly. That's the only time we're gonna agree.
- SPSpeaker
[laughs]
- ALAaron Levie
Um, I, I think maybe one more point on the board for agreements, maybe, maybe you guys would, would agree. Um, there, there's also this very interesting, um, dynamic. I, I would say this is a minor one relative to everything else. It's probably 5% of the problem. I, I think it'd be more fun to talk about the, the real problem, but, but there is a fun kind of, as an aside, there's a fun dynamic where, you know, you go to an engineering team classically for the past, you know, and, you know, Steven, you can take us back in, in history on this one, and one of, like, the easiest ways to stall a project was just getting the architecture, you know, kind of the, the fights on, you know, what language to use, what architecture path to go down. That could take months and months to kind of work through as your teams work through that.
- SPSpeaker
Yeah.
- ALAaron Levie
Um, because of the pace of change in AI, um, you actually have this incredible dynamic where the, the labs, uh, you know, are, are obviously leapfrogging each other so frequently, but with, with not the exact same paradigm of how you should deploy agents and how they will work, and is the, i- is the, is the agent harness in the computer? Is it outside the computer? Do you run it in your cloud? Is it hosted? What tools does it have access to? Like, we are... Like, this is not a, a, a, a point where these are completely fungible technologies, and so that actually creates a, a, a bit of paralysis because now as an enterprise architecture team in the real world, you're like, "Man, like, what, what horse do I wanna, you know, kinda get behind, and, and which architecture path do I wanna get behind?" Because I've been burned by doing the wrong thing-
- SPSpeaker
Yeah
- ALAaron Levie
... in AI maybe three or four years ago, and I went down some path that now is deprecated or not the right strategy anymore. So, so to some extent, the speed of our change in, in tech actually reduces the ability for the tech to get diffused into the really, really important workflows because now you have a lot of paralysis in, in just making decisions. So, so I actually think it's kind of fine because there's still so much upgrade work people need to do in their infrastructure and their systems and their data, but this is kind of an interesting dynamic where I'll, I'll go have conversations with CIOs and their AI teams, and I'll say, "Hey, what, what are you using for your chat system or your, you know, core agent orchestration?" And they'll say, "Yeah, we're in the middle of a debate between these two or three paradigms."
- SPSpeaker
Right. Right.
- ALAaron Levie
And it's... And, and you, and you hear that across almost every single customer because there is a little bit of a nervousness of, like, who do you get in bed with and, and how, how much do you sort of, you know, fully lock yourself into one particular path? And we also know that, that if you don't lock yourself into a path, it's always... Then, then you're building for this sort of duality which is, you know, also takes a lot of work architecturally.
- SPSpeaker
Oh, and actually-
- 9:16 – 14:38
The Architectural Shift: Treating AI as a User, Not Software
- ALAaron Levie
Yeah
- SPSpeaker
... I, so I, I, I hate to jump in, Steve.
- ALAaron Levie
No.
- SPSpeaker
I just like, there's a, like... So Aaron is totally correct, and there's a, there's a very specific instance of this playing out in product companies right now.
- ALAaron Levie
Mm-hmm.
- SPSpeaker
And I'll tell you what it is. So, so, so software product companies, um, you know, circa six months ago, they viewed integrating AI was like you're actually integrating it into the product, right? So everybody was, like, adding, like, whatever, this chat feature or, like, the... You know, and so it's kind of like this fusion or this hybrid model. What we're seeing instead is instead of viewing AI as software-
- ALAaron Levie
Yes
- SPSpeaker
... like, just view it as a user. And so [laughs] 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 architectural and mental shift, right?
- ALAaron Levie
Yes.
- SPSpeaker
And so we started as pure product, and then we didn't quite know what the end thing looked like, so we created this h- you know, this, you know, AI software hybrid that hasn't worked, and now we're kind of going to the agentic model, which basically means th- th- the agent is gonna be whatever. It's gonna be cloud code or whatever, and then my product now just should be something that can s- consumed by that, and, like, that's the actual modality. But, you know, within a year now, you've had to rearchitect your software twice. And so I think no matter... But many places that you look in the industry is having this dilemma of actually trying to figure out what the final form looks like. And Steven, you will remember. Remember all the hybrid versions of cloud? [laughs]
- ALAaron Levie
[laughs] Yeah.
- SPSpeaker
Remember, like, you know, like, remote desktop and all these things? Like, I think we're kind of, like, speed running that evolution to the final form.
- ALAaron Levie
Right, and I, and I think that, that people, uh, in Silicon Valley don't quite l- appreciate when a big company says, "Well, we have to map out our bet that we're gonna make."
- SPSpeaker
Yes.
- ALAaron Levie
Because, like, that just seems stupid, and, you know, if you have... If your job history is, you know, five two-year stints at startups that went from seed to series A to acqui-hire or something-
- SPSpeaker
Yeah [laughs] you didn't learn anything
- ALAaron Levie
... you, you, well, you, you never... You, you don't... Your frame of reference is not, you know, picking an accounts payable system-
- SPSpeaker
Right
- ALAaron Levie
... that's gonna last 40 years.
- SPSpeaker
And living with the consequences. Yes. Right.
- ALAaron Levie
Yeah, I, I actually, m- I have, like, all these visual aids today. So here's, like, the ultimate, the ultimate engineer if you're in Silicon Valley, is, is-
- SPSpeaker
Lower, lower, lower, lower, lower
- ALAaron Levie
... oh, lower, lower. Where?
- SPSpeaker
Yeah. Yeah, exactly.
- ALAaron Levie
Yeah, yeah, is Guilfoyle.
- SPSpeaker
[laughs]
- ALAaron Levie
And, and Guilfoyle is like, "I, I don't wanna talk to anyone."
- SPSpeaker
Yes.
- ALAaron Levie
"And I, I will just write the code, and you go do your thing." And the, the thing is, is that you, you have people in, in enterprises that are saying, "I'm gonna use the model and do my thing," but they're only... They're gonna hit a wall at integration.
- SPSpeaker
Yes.
- 14:38 – 20:12
The Integration Wall Agents Can't Climb
- ALAaron Levie
No, no, I, well, but we should, we should drill into your integration point, because I do think this is something for, you know, sort of some reality to settle in, in, in the Valley on, on the real world's sort of journey to fully being agentified, and what that's gonna take and what that's gonna look like. And, and your, your point about b- being passed to the different human, you know, based on the role that you need to interact with, you know, agents basically don't have any... There's no real exception yet for the agent having the same problem, because you basically, you know, as you pass through a different human, it's, it's a different set of access controls that, that, that that human has. And if an agent can sort of bypass any of those steps, then, then that's how you instantly get the security risks that, that, like, w- you, you need to kind of pass through those steps so that way you don't accidentally, you know, get to the wrong piece of information-
- SPSpeaker
Right
- ALAaron Levie
... and there's verification. And so there's a lot that, that you need to kind of build out for agents to be able to go and, and work with all these systems. And, and we've talked about this, but, like, most legacy environments don't have the most authoritative, you know, access controls. So you're always as a human going and saying, "Hey, Sally, can you share that thing with me that, that I don't have access to?" Or, "Hey, Bob, what's the number inside your data system for this question?" And so if agents just get the exact same permissions that you had, then they'll just run into these walls everywhere and they won't be able to complete the process. And unlike a human, they're not gonna know to go talk to Sally or ask the question of Bob, so they're gonna just be kind of s- you know, stuck. So what's gonna happen is you're gonna have a lot of agents that don't have access to the right data, um, they're, they're kind of working through systems that, that are, you know, not, not the real sources of truth for the information. They're getting the wrong number. They're getting the wrong document. So this is the real work that enterprises have to go through right now. The good news is that, that it's actually a great time, again, if you're a startup, because you can just, you get to know all the problems, uh, right at the, right out of the gate, so you can design your organizations, you know, to try and avoid this. But for big companies, there's real work that goes into, how do I upgrade my systems? How do I modernize my technology environment? How do I make sure that, you know, agents will have access to the right data, the right documents, the right context to be able to do their work? And that's sort of the, the, the work ahead. And, and there's, you know... I, I, there was this, uh, uh, you know, kind of headline of, of OpenAI working with, um, uh, in Codex, you know, working with Accenture, Deloitte, all, all the major system integrators, and there were some kinda, like, you know, snarky comments online around it, um, that, that I was fascinated by because it sort of sh- showed how, uh, h- how maybe, you know, great that divide is from the rest of the world versus those in tech. Because to me, it was, like, the most obvious announcement of all time-
- SPSpeaker
Right, right
- ALAaron Levie
... which is a large enterprise is gonna have to go through the, the change management, the systems implementation, the integration of technology for these agents to be able to go and work. And so there was this sort of, like, you know, people thought it was somewhat ironic that, oh, we need people to implement the agents that are gonna go automate the people, and it's like, no, that's exactly how it works.
- SPSpeaker
Right, right.
- ALAaron Levie
Like, you, you, you actually do need to do lots and lots of work to be able to be in a position where agents can actually go and, and help you do, you know, any of the automation. So, so that is... And that's gonna be, there's gonna be businesses that are doing that for decades. Like, it's gonna be an incredible opportunity for this kind of next generation set of firms, as well as existing ones that, that lean into that.
- SPSpeaker
Let me throw this out there. Well, first, I think the other thing that people shouldn't celebrate when those fail, uh, because they will fail, because they're, as Martin was describing, they're gon- a lot of them are gonna be these sort of top-down mandates where they pick, like, the most acute problem in the company and think, "Oh, AI is gonna go solve that." And the IT people are gonna be like, "Oh, God, that's the worst-"
- ALAaron Levie
Yes. Yeah, don't do that. Yeah.
- SPSpeaker
That's, that, that's the worst system to try to do that. But the CEO or CFO or whatever is gonna be obsessed with solving, or the most likely the customer service person will be obsessed. But, but I do think if I were, if I were advising a startup specifically in order to, to, to sort of enter the enterprise space in that way, definitely would be thinking about not just, like, building a company that's step one. I only work with all the headless SaaS software that's out there, because there just won't be any. Like-
- ALAaron Levie
No
- SPSpeaker
... the, but the, the thing you can do is structure the value that you offer, and also this applies to what you go do in a company, is it's really a fork, and the fork is-Is this an agent that is seeking information and presenting it to an, to some human, or is this an agent that's supposed to go act and do something? Like, is this-
- ALAaron Levie
Yes
- SPSpeaker
... is it acquiring or is it doing? Because if, if it's, it turns out that's how, what happened with the internet. The internet got very, very valuable when the first step was just providing access to things to people.
- ALAaron Levie
Yes.
- SPSpeaker
And, and like all of a sudden, all the sites that were like that literally did integration. Like, "Hey, I need expense reports, but viewed by department," or, "I need to see our current inventory status across, like, the two companies we've acquired." All of a sudden, the web became the integration point. And so I do think that, that if you just show up first and just say, "Hey, we can actually use agents to learn stuff about what's going on in a company," and in particular, because you're here, Aaron, like, learning across the files becomes way more possible than it ever was before. In fact, AI might be the first time that inside a company's search can actually provide-
- ALAaron Levie
Yes, yes
- SPSpeaker
... immediate value.
- ALAaron Levie
Yes.
- SPSpeaker
'Cause the web just wasn't structured to deliver those results. And, and then you start to think, once you can bring them all together, then you can add, like, an Approve button or a Reject button or something like that.
- 20:12 – 24:40
Should Agents Be Treated Like Humans?
- SPSpeaker
Let, let me, let me just try and provide... Finally, the point where I get to disagree. [laughs] So let-
- SPSpeaker
Uh-oh. We're in trouble now.
- SPSpeaker
No, no, no. I, I just-
- SPSpeaker
Well, you can get invited back. You're invited back, so good.
- SPSpeaker
No, no. I, I think this is a very legit view, but it's not the only view, and in light of AI, it's, I think it's not the only kind of compelling view. So here's the oth- so the, let, let me just try and rephrase. So the, the current view is we've got, like, AI is software. It, it, it works in a different way. Um, we have a current set of systems, and we have to integrate this new type of software with our existing systems so that it can get access to data, it can do things, but in a safe way, right? So here's to the kind of end-to-end argument of why this isn't abov- about evolving software systems. The end-to-end argument is these LLMs are non-deterministic, they are smart, they deal with the long tail of complexity, and it turns out those are all things humans do, too, and we've spent 40 years building interfaces, processes, and design to deal with messy humans. And, you know, we know who to access and we have access control. And so if you have the mindset that an agent is more like a human, and you hire the agent, you give it its own email address, it can access documents like humans can, it can log in, it can request the things that it needs, then it will be drafting on all of the process that, that we've put in place for humans, not for software. And so I would just encourage us as we have this discussion, like listen, I grew up like you guys in software. I always think of every system like software, but 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've put in place for humans, they're much easier to integrate.
- SPSpeaker
Well, that-
- SPSpeaker
And I think we're seeing-
- ALAaron Levie
Yeah, I love that point. I, I think we, I think we agree with that, for sure. I think the issue is humans have a bunch of extra benefits that the agent doesn't have. The human has a lot of context that it gets for, that they get, that we get for free by virtue of we can keep track of the myriad relationships that we've built in our organization and the person to tap on the shoulder when, when we need something done or we need to get information. That's not documented in a company yet, um, in a, in a way that the agent can just sort of draft on. And so, so I, I like, I, I mean, I think we all would agree that, that you ha- you can't treat this like software. You treat these as, as people accessing systems and tools, but they are at a, they're both at an, a massive advantage that they can work in parallel in, at, you know, at infinite scale, and they're at a disadvantage in that they don't know who to tap on the shoulder.
- SPSpeaker
Right. I, let's-
- ALAaron Levie
Yeah
- SPSpeaker
... Aaron, I am all for agent onboarding. Like, you know-
- ALAaron Levie
[laughs]
- SPSpeaker
... the agent comes and it goes to orientation.
- ALAaron Levie
Yeah, yeah, yeah.
- SPSpeaker
And then the CEO gives it the culture discussion, and then every... [laughs] I'm not kidding.
- ALAaron Levie
No, you're probably right. Every department-
- SPSpeaker
Every department-
- ALAaron Levie
100%
- SPSpeaker
... every department does their pitch.
- ALAaron Levie
Yes.
- SPSpeaker
Like, "This is what we do."
- ALAaron Levie
Yes.
- SPSpeaker
And like, I mean, I think, I, I actually honestly think given, given the technical nature of these agents-
- ALAaron Levie
Yeah
- SPSpeaker
... and how much entropy they have and kind of how unruly they are, we're gonna have to go through the processes that we've refined around humans.
- ALAaron Levie
Yeah, 100%.
- SPSpeaker
Because humans have all of those things.
- ALAaron Levie
Yes.
- SPSpeaker
And so I just, you know, it's more about providing schools for them than somehow building some, you know, fancy index database.
- ALAaron Levie
No, no, no.
- 24:40 – 39:16
Salesforce Goes Headless & What It Means for SaaS
- ALAaron Levie
Well, well, and so, so the big news last week was, uh, was I, I, I think, you know, Salesforce, I don't know if they surprised people or not, but, but I mean, based on the reaction, it seemed like it was maybe a surprise. They, they went full headless, and they basically said, you know, like, "We wanna be used everywhere across all of our, uh, all, all the different agents."Um, and I see that as a, a little bit of a bellwether because I think as Salesforce goes, so does a lot of, of, of enterprise software. And I think a lot of people are gonna try and f- you know, 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, a small just API tax? Is there a seat for the agent? So there's obviously some work to do with that, and Steven, I, I saw one of your tweets on, you know, s- some of the, some of the, you know, complications there. But, but, but, uh, but I think as a, as a moment it's a big deal because, because I think it's a recognition that, that, you know, 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 and, or non-deterministic machine users. And what's cool and, 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 need, you know, the headless version of Salesforce, 'cause I'm always doing just a tremendous amount of, of customer-related intelligence work. I'm going into a meeting-
- SPSpeaker
Yeah
- ALAaron Levie
... I need some information. I need to do... I'm going into a city. Who should I be meeting with? And so if you imagine, you know, being able to run compute in the form of agents across all of your data systems, like, the use cases become, you know, pretty wild around what that opens up. So I think this gives, I think this gives a lot of software platforms all new use cases that they can tap into that where, again, you were normally constrained by the number of people on these platforms, but now the headless user can be, you know, 100 or 1000 X the scale, um, of those human users. So this is a, a, I think an exciting moment because as you have more of these agents running around and the headless software modes, um, you just have, you know, way more use cases for these tools.
- SPSpeaker
I also think-
- ALAaron Levie
So-
- SPSpeaker
All right, just, I think on this one-
- ALAaron Levie
Please, please. Yeah
- SPSpeaker
... what's so, what's so super cool is, is that of course the first step is doing exactly what you described, which is just looking stuff up. And so the, the most interesting thing is using this notion that an agent is just a, an entity, it's mo- it's incredibly obvious to me that it's another license. Now, it might have a different-
- ALAaron Levie
Exactly
- SPSpeaker
... license model, but it hac- it has to have an identity. Like when you go look something up in, in the Box, um, CRM system, I, I don't know if it's Salesforce or not.
- ALAaron Levie
Yep.
- SPSpeaker
When you use the Box CRM system, it has to be a person, like with a certain amount of access rights.
- ALAaron Levie
Yes.
- SPSpeaker
And you presumably, as CEO, you might have access to a bunch of stuff. But also there's a lot of ways that they actually don't want you to have-
- ALAaron Levie
Right
- SPSpeaker
... the rights at the right time. Like, you might be able to look and see who is on the account, but you don't need the up-to-date quota-
- ALAaron Levie
Right
- SPSpeaker
... of those salespeople and stuff, and that might be HR sensitive, and you should probably have some other level to go see that. But as you go down the org, the agent is never gonna have more permissions than the person who's getting it to go do something. And in fact-
- ALAaron Levie
Right
- SPSpeaker
... it's just gonna be like a peer to somebody else in an organization, because otherwise you have all of these issues where the peer, where a human can just say, "Oh, get me the super smart agent that knows everything that I'm not allowed to know."
- ALAaron Levie
Right.
- SPSpeaker
And to, to the, in the mo- in the IT architecture sense, what's so fascinating about that is you have to build... You, you can't let the agent get the results and then try to figure out what works or not. But first of all the points that Martin made about, about, um, who, about the, the LLM stochastic model, which is you're not gonna be able to figure out. It's not like a record in a SQL table that you could just apply ACLs to. It's-
- ALAaron Levie
Right
- SPSpeaker
... it's actually like it could be words in a sentence or just the number that shows up.
- ALAaron Levie
Yeah.
- SPSpeaker
And so I actually think it, it, that whole discussion about headless for me made the SaaSpocalypse seem even dumber than it was already, and it was already dumb.
- ALAaron Levie
[laughs]
- SPSpeaker
So like, it was like at first it was dumb, and then I'm like, oh my God, it's actually much dumber than I thought it was-
- ALAaron Levie
[laughs]
- SPSpeaker
... in the first place.
- 39:16 – 47:53
Scale, Entropy & Why AI Coding Creates as Many Problems as It Solves
- SPSpeaker
Let me, let me ask this. It occurred to me as you were saying it. Like, I, my, I sort of got all tense when y- when the idea became-
- ALAaron Levie
[laughs]
- SPSpeaker
No, like, oh, we have 10,000 people hitting our, hitting our SaaS system today, and we've got it all working and it's all great, but, um, now we're gonna have 10,000 new pe- people, which are the agents for each of those 10,000 employees, and they're, they're actually hitting it 500 times as much.
- ALAaron Levie
Mm.
- SPSpeaker
Okay, so that SaaS product will collapse.
- ALAaron Levie
[laughs]
- SPSpeaker
So, like, that's the, the first order because it wasn't architected for that volume. Like, we saw this with, with all the BI tools. Like, when all the-
- ALAaron Levie
Mm
- SPSpeaker
... BI tools came out, all of a sudden they, they were looking at the SAP data and trying to snapshot it and absorb the whole thing every night for a new kind of set of slices and dice that your view across all 500-
- ALAaron Levie
Yes
- SPSpeaker
... pro... And, and, like, all the people making ERP were like, "Well, we don't do that." And so they had to go build all of this themselves because they had the knowledge of the data. Their API just couldn't, was not designed for, for that kind of lookup. So my, my sort of thing to throw out there and, and fight about is what is it, what does the change management look like in a company? Because you, you can't let loose an agent that hits the system at 500x the humans. And it's not a token thing. It's an actual, like, wow, we don't have the network bandwidth and the, the throughput to handle 500x for any one of our customers. So what happens?
- SPSpeaker
So, so I've, so I've got a provocative adjacency, which you guys can tell me if I'm doing too much on a tangent here, but, but here's my provocative adjacency, which is I don't know if having more agents is that big of an architectural shift. I just feel like we understand, like, whatever. If it's read-only data, you cache it. You know, like, all the state issues are around mutable, mutable globally shared state. We understand the limits of those. We know how to architect around those. We had to tackle all of those things when we went to the internet. And so if you built your system not to handle it, like, you suck at building the system-
- SPSpeaker
[laughs]
- SPSpeaker
... and you deserve to go down, and just go build a system that doesn't suck. And, like, I just feel like this is kind of standard computer science. However, I do think agents do introduce, um, something that organizations, uh, technically have to deal with, and I'll- l- let me just give the analogy in code, which is in-
- ALAaron Levie
I think, uh, Steven, this is what we call mogging on a, on a podcast.
- SPSpeaker
[laughs]
- SPSpeaker
I, I don't know. No, no, I think it's a great question.
- ALAaron Levie
You've been question mogged.
- SPSpeaker
I just-
- ALAaron Levie
He's been question mogged
- SPSpeaker
I have no idea what he just did, but I-
- SPSpeaker
[laughs]
- SPSpeaker
... I'm, I'm just looking forward to how he magically made the problem go away. But go ahead. [laughs]
- SPSpeaker
No, no, no, no, no, no, no, no, no. No, the problem is there. I just think, like, we know how to go from 10 users-
- SPSpeaker
Yeah
- SPSpeaker
... to 1,000 users.
- SPSpeaker
It's there for stupid people.
- SPSpeaker
But-
- SPSpeaker
We just got rid of the stupid people, so now everybody's smart.
- SPSpeaker
No, no.
- 47:53 – 58:22
Will AI Kill Jobs or Create More of Them?
- ALAaron Levie
S- by, by the way, this is actually why I remain unbelievably optimistic on jobs.
- SPSpeaker
Yeah.
- ALAaron Levie
Because I don't think-
- SPSpeaker
Oh.
- ALAaron Levie
You, you, like, I just think we've gotten it wrong on, on thinking w- you know, all the places where you're gonna remove humans from this because you still need a human in that, you know, somewhere in the loop. Maybe the abstraction is a little bit higher and you don't need the human in the loop at every, at every single stage that you needed a year ago, but, uh, but you do need a human sort of kicking off the process, reviewing the process, and incorporating whatever the work was. Um, and so that creates just still a tremendous amount of opportunity and jobs across these organizations.
- SPSpeaker
Oh, let me, I have to jump in 'cause I, I have, I have a whole bunch of, like, visual aids I brought today to make it exciting. We got-
- ALAaron Levie
Okay.
- SPSpeaker
You got a bunch of comments on, on the MTS Live thing about people agreeing with you, so I don't wanna let that slide because-
- ALAaron Levie
Okay
- SPSpeaker
... you know, we complain about not agreeing with you. But, but, like, here-
- SPSpeaker
Well, totally agree
- SPSpeaker
... to your point, to your point, this was a book in the '80s called The End of Work.
- ALAaron Levie
Yeah.
- SPSpeaker
[laughs]
- SPSpeaker
And, and I... This, so or actually, sorry, it was in the '90s. It, it, it came out, like, six months before the internet hit, and the whole thesis was the technology revolution was a complete bust and we got no gains in productivity, but now there's gonna be no more jobs 'cause the economy is stagnant. Well, and it just w-
- ALAaron Levie
Yeah.
- SPSpeaker
And this was a guy, he called himself a futurist.
- ALAaron Levie
Yeah, yeah.
- SPSpeaker
And, and, and, like, so the whole-... notion that it, it, that's a, like one of the neat things about this whole AI moment is, like, the number of things that when you hear them the first time you think they're stupid, and then you go back and think about it and you're like, "Oh my God, it's way stupider."
- ALAaron Levie
Yeah. [laughs]
- SPSpeaker
And, and this idea that, like, AI just gets rid of jobs, it's as ancient as, like you p- talk about the accountant. Like, one of the things people thought was that computers would get rid of accountants.
- ALAaron Levie
Yes.
- SPSpeaker
And, and that was, like, IBM's pitch in, like, 1965, but-
- ALAaron Levie
Yeah
- SPSpeaker
... what it actually did was like, "Oh my God, we could do so much more with accounting-
- ALAaron Levie
Yeah
- SPSpeaker
... now that they're not, like, literally just adding numbers all day."
- ALAaron Levie
Yes.
- SPSpeaker
And, and I think-
- ALAaron Levie
Well-
Episode duration: 58:23
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