EVERY SPOKEN WORD
55 min read · 11,436 words- 0:00 – 1:00
Intro
- SPSpeaker
There are many things that made software sticky, but a lot of it had to do with the fact that the way a human interacts. In an agentic world, do you actually need that? The data, the logic, everything stored below it is really where the value is.
- SSSteven Sinofsky
There's this wild underestimation about, like, you could vibe code your way into enterprise software. Larry Ellison at Oracle, he went on a rant about how enterprise software was so stupid because everybody customized it. The minute you automate the most mundane thing and think you have it all squared away, whole new things appear.
- SPSpeaker
Misconception right now is that you can just have, you know, Postgres database and APIs, and then bam, like, you can replace SAP. That's, like, absolutely not true. That piece around the logic and everything else that is encaptured in SAP is way, way more important than the fact that, like, oh, this data just happens to be in this database.
- SSSteven Sinofsky
One of the things that happens in technology shifts is nobody understands exponential when it's happening. The biggest opportunity right now is...
- 1:00 – 6:57
What "Headless Software" Actually Means
- EBElena Burger
Welcome to the a16z podcast. I'm here with Seema Amble, a partner here on the enterprise team, and Steven Sinofsky, who is a board partner at a16z, as well as a former, uh, member of, of Microsoft, friend of the firm. Um, and here we are today to talk about, um, a piece that Seema wrote about a month ago called Is Software Losing Its Head? Uh, and this piece, I'll, I'll let Seema talk about it in her own words. Um, but this piece was written a couple months ago. Salesforce announced that they would be going headless. Um, and today we're here to kind of discuss, you know, what does that mean? What does that mean for, you know, the future of SaaS products, the future of, um, you know, just, just kind of software more generally. So Seema, um, can you just walk me through first what headless software means and explain kind of what changes it introduces?
- SPSpeaker
Yeah. Um, so headless software is really... It's, it's not a new term, but I think has really risen in, uh, in like the, you know, public domain of, of interest in, in a, a topic that people are talking about. One of the interesting news points has been Salesforce making this announcement. They were launching Headless 360, which was really, in classic Salesforce moti- you know, uh, history, a, uh, a marketing announcement more than anything else. But it does capture, um... It's sort of a, it's an acknowledgement of what's happening, which is, you know, traditional software, uh, had been built around humans accessing it, and, um, it was workflow to capture data, and we could talk more about what that meant. In an agentic world, do you, the, you, do you actually need that? The UI doesn't matter because the agent isn't accessing the software via the UI. We could unpack whether the UI matters or not, but in the idea of it that being headless is the, the data, the logic, everything stored below it is really where the value is, not just the workflow software that's being tracked at the top.
- EBElena Burger
Gotcha. Um, and, uh, this was announced a couple months ago. I'm curious kind of in, in the past couple months, what have we seen? I mean, you wrote even in the piece kind of you... At the beginning you were a little bit, you know, funny maybe, and you said, "Is this really even that big of an announcement? Is this sort of a rebrand of, you know, APIs that they had kind of already made available?" So does this feel like a significant change? Is this maybe more of a branding exercise? Um, and kind of like what have we even seen in the past couple months since we've been able to kind of observe what changes have, have really happened?
- SPSpeaker
So I'll separate it out into the Salesforce context and then, like, the broader context, which I think the broader context is more interesting.
- EBElena Burger
Okay.
- SPSpeaker
In the Salesforce context, probably not that interesting. Uh, I think Salesforce, I think rightfully, again, is acknowledging a shift that's happening in the market. I don't... From what I could tell, nothing actually changed. Their 360 product was, uh, the same APIs that had always been exposed, now rebranded as, as, as their 360 product. How- And, and APIs have always existed, so, you know, m- many, uh, or I shouldn't say always, but for a long time have existed. Um, but I think the broader trend here is they're, you know, Salesforce among others are thinking about how they build themselves for the agentic world. Um, and so if an agent needs to access the data in a CRM like Salesforce, um, what are they doing? And are they doing it via the UI or are they using the API? And that's the, you know, Salesforce is saying like, "Okay, hey, we know what is changing, that there are agents who are needing to access the data. Let's look at the, you know, let's offer a headless version for them to interact with, um, the data versus going via the UI." That said, again, I don't think any actually changed in the Salesforce context, but Salesforce isn't the only one. Another example is Notion has a headless product, and actually I think that makes, uh, even more sense because it's much har... Like, I think many users of Salesforce are probably less technically adept, less likely to be building their own agents, although there are many, many more people who are doing that with Salesforce. Notion users tend, uh, you know, all things being equal, are more, I'd say, tech savvy and more agentic as, as builders.
- EBElena Burger
Mm-hmm.
- SPSpeaker
And I think Notion is, is one of many other companies that is also trying to figure out, "Okay, what is it that I offer? Um, and, you know, h- how do I make... You know, what APIs do I expose?" I think Steven will talk more about MCP. Um, and, and again, I think a lot of this is also getting caught up a little bit in nomenclature and like, okay, what are we calling things?
- EBElena Burger
Mm-hmm.
- SPSpeaker
Um, and I, I, I think that's one thing, but I think the, the broader trend around how agents, um, access systems of record, I think is the, the bigger point.
- EBElena Burger
Yeah. Yeah, and, uh, from my understanding, it's also, I mean, it could also apply to something as simple as a chatbot. You know, it's not necessarily just an API or an MCP server. You know, you, you could be, you know, Salesforce, um, acquired Slack a couple of years ago, and, like, it could be something as simple as, like, you, you sort of interacting with, with a CRM via chatbot.
- SPSpeaker
Totally. And I think I read somewhere that there has been, like, a 300% increase in Slack bot Yeah, and Slack agent usage.
- EBElena Burger
Yeah.
- SPSpeaker
Which is essentially saying that you don't need to log into the Salesforce ecos- uh, yeah, interface to get the data-
- EBElena Burger
Yeah
- SPSpeaker
... or whatever data it is. So yeah, it's, it's essentially, again, all these are agentic ways of accessing it versus the human needing to go in, log the data, or, or, um, from a read perspective, go back and see, okay, here were the like, here's this opportunity, here's what happened, and, um, look at them, at themselves.
- EBElena Burger
Mm-hmm.
- SPSpeaker
Um, and so the, that interface is, is less relevant.
- EBElena Burger
Yeah. And Steven, do you have anything to add here just on the cur- kind of like definitional territory that we're covering right now or, or kind of this discussion?
- SSSteven Sinofsky
Well, so, I mean, like we're in Definitional
- 6:57 – 10:00
Agents, APIs & the Definitional Hell We're In
- SSSteven Sinofsky
Hell right now-
- EBElena Burger
[laughs]
- SPSpeaker
That's true
- SSSteven Sinofsky
... where everybody is, is, you know, part of a new wave of technology is you make up a lot of new words for things that you kinda did before, and that's just a natural part of technology evolution. Um, but I, I actually think it's super important. Like, first you have this, you have a- agent, which as far as I can tell right now, is also a new word for program that takes a very long time to run and might not finish.
- SPSpeaker
[laughs]
- SSSteven Sinofsky
And, and so you have to, that's just like a, a branding, that's the best branding ever, is to call a program that takes a really long time, which we used to call a bug, is now like the coolest new feature ever, and it's just now an agent. But in, in seriousness, the most interesting way, I think, to think up what you're really talking about doing differently between an agent and an API is really what are you actually doing? What is the agent itself doing? Is it looking something up? Because that's actually a pretty lightweight thing that all systems are pretty good at, and in fact, many, many of the newly announced, you know, headless agent APIs are, are just lookup, and they're just, you basically have a new interface to the old way to look something up, which is a lot more forgiving, a lot less UI goo and stuff like that. Then there's like, I wanna do something, and that's where you get into very interesting issues over like, well, if you do something, you have to be impersonating a specific person, you have to have their credentials. Like it's a very, is it a s- another paid seat? Is it the same paid seat? You have all these interesting enterprise software issues that come up if you actually wanna cause a change to a system of record. And then there's the third thing, which is analyze. And so analyze is more than look something up, it's actually look up a bunch of stuff. It often involves multiple systems. And that seems very, very tuned to an agent because you, you're not time-bounded, you can spend energy, iterate, you can route it to different models and get different answers back and compare them. But it's also where hallucination really is a huge issue. Because if you're gonna go and analyze something, you actually need a way to verify that everything, every step of that analysis was correct. And so it's, I think it's super interesting and important when you look at headless and agent, which are conflated, and you sorta have to figure out what you're talking about. Because we're on different places in the evolution, the learning curve, and the deployment of agents relative to sort of that three-way matrix.
- EBElena Burger
Yeah. I, I think this is actually a good lead-up into a follow-up question, which is kind of like historically, what has made software sticky and how are agents starting to s- disrupt that? And I, I leave that to either of you to answer, and maybe you guys can both kind of
- 10:00 – 15:00
What Makes Enterprise Software Sticky
- EBElena Burger
debate about that.
- SPSpeaker
Yeah. I'd say there are ma- there are many things that made software sticky, but a lot of it had to do with the fact that, um, it was built around like the, the way a human interacts, right? So, um, the UI was sticky because, you know, the number of times you had to read and write, the frequency of access, the downstream workflows, all of the, like, undocumented, like, uh, you know, what we call SOPs or, uh, standard operating procedures, all the stuff that happened around the software that got ingrained in muscle memory and process, and then external parties, et cetera. So, like, a CRM may be sticky because a sales rep needs to go in and out of it all the time. They're used to interacting with Salesforce. A lot of times when, like, new VPs of sales, uh, come into our companies, they, they're like, they mandate that Salesforce is there because they're used to using it, their teams are used to using it. Um, and then there's, you know, finance may rely on the Salesforce, um, output for billing, and upstream marketing is gonna rely on it as well, and so there's these dependencies. Um, and these all are driving stickiness. It-- But I think the other piece too is there, you need one single set of truth, right? You need to know, like, an account is closed and who is working on it, and all of that needs to be logged in one place. Um, and I think if you go from CRM to, say, an ERP or payroll, like, that absolutely has even, like, legal reasons w- and compliance reasons why you can't have, um, numbers that are not being, you know, tracked, uh, as cleanly and, and correctly as, you know, an auditor might like, for example. Um, so anyways, this all drove stickiness there, and, and, and durability because, you know, you were used to using Salesforce, the whole ecosystem was using Salesforce, and it was the default option. Um, maybe, you know, there's one or two others in the market. Um, and so I think historically those were some of the things that were, were driving stickiness.
- SSSteven Sinofsky
Yeah, I mean, I, those are all exactly right. I, I think it's important to also consider that the most sticky thing you could do is actually collect money from a customer. And if you're collecting money, it turns out it's really, really hard for them to stop sending you money, and it's really hard for them to figure out what to do if they stop sending you money. And, and it, it sounds really trite, but- The, the stickiest software is software that's getting used somewhere. Then when you dig in and try to come up with reasons, well, it just depends on who you talk to in a company. You know, you talk to the HIPAA compliance people in some company, and they're gonna tell you, "This is the software you have to use because it's, like, the most bestest HIPAA compliant software." If you talk to the administrators, you're gonna hear about onboarding new users. If you talk to the users, you're gonna hear about muscle memory and keystrokes or labor unions or whatever. And, and so you have to be, you, you really wanna get the software sold, and that's your fastest path to sticky. And after that, it, it's sort of y- you know, a winner's tale over, over what caused it to be sticky. And, and in fact, the best thing about sticky is if you're the rep for a company that you've sold something to, and the company is threatening you, like, "Hey, we're gonna replace you. We're gonna..." You're just gonna listen to them, and you're gonna find what's sticky. And if that works, like, three or four times across different accounts, then you've just told the tale as to what made the product sticky. It doesn't matter what the PMs or what anybody else thought of. It could be some crazy arcane thing. You know, I, I have stories of lots of sticky software and lots of arcane things. But like anyone who's ever tried to displace, um, Microsoft Outlook as email very quickly learned about delegate access and, and having me- calendars owned by multiple people and all of this crazy stuff. And like, I can tell you, there was no meeting where we said, "Okay, let's figure out how to make the calendar the sticky part of Outlook and make sure we handle recurring meeting exception handling well." And then you go and you find out, you know, General Motors isn't gonna displace, like, 600,000 seats because of the calendar or some crazy thing like that. And so you can... It's really amazing in enterprise software what causes sticky and how you can actually capitalize it, on it when somebody threatens to take you out of the, out of the enterprise.
- SPSpeaker
I, I think there's a really good point there. The... And it... Two things. Inertia is a really powerful force.
- EBElena Burger
Mm-hmm.
- SPSpeaker
And then I think the other thing is, yeah, nobody when they're building the software, they're at, like, thinking about, like, this rubric we put together and like tick, tick, tick. We got all these features that are gonna do all these things. But I think the practical reality is also as software extends its tentacles across an organization, and it gets ingrained in pr- people using it, and they've been paying for it for a long time, it just seeps into how people are doing things.
- EBElena Burger
Mm-hmm.
- SPSpeaker
And that's, like, hard to rip out.
- EBElena Burger
Yeah. Yeah, you even talk about this in your piece, Seema, where there are sort of all of these,
- 15:00 – 22:00
The Death of Software? Why SAP Isn't Going Anywhere
- EBElena Burger
like, invisible, tacit sort of understandings about how to use different products or things that are embedded both within the software but also within the people using them, where it's just like, it does become hard after a while to, uh, to extricate yourself from, from whatever ecosystem you happen to be in.
- SPSpeaker
Yeah.
- EBElena Burger
And, and in fact, Steven, I think you, you've even, you know, said the SaaSpocalypse is overblown. You've written an essay called "The Death of Software: Nah," um, [laughs] where you-
- SSSteven Sinofsky
[laughs]
- EBElena Burger
... where you, you know, emphatically sort of rejected this idea. So maybe if you wanna, if you wanna maybe just recount that piece a little bit for us.
- SSSteven Sinofsky
Well, I mean, Seema co-wrote a post on, on SAP, which is sort of the ultimate, ultimate example of sticky software. I mean, there is nothing... The, the only software that's stickier than SAP is behind the scenes, and it's the software that insurance companies wrote. And they wrote all this software, like, 50 years ago or 75 years ago. And if you ever... There's no replacing it. Like, it, it just, it... I- in fact, you... Whenever jokes come up about, like, businesses that are, uh, looking for COBOL programmers, it's to go and work on the insurance software that exists in-
- EBElena Burger
Or banks, yes
- SSSteven Sinofsky
... in every state of the union. And, and in many ways, what you're seeing, like with the one of the biggest successes to date in Stripe, has been somebody actually went in and for the first time in, in two generations, coded up the software to collect money from people, which itself had previously been an unsolved problem on the scale of insurance because nobody put together the tax laws for every country, every, every jurisdiction, every locality, every border crossing, every currency exchange. Like, it, it, it, it's mind-blowing that... And so now that is the most sticky s- like, that is not going anywhere, ever. Like, it, it'll be a r- like, we'll be doing this podcast with, like, great-grandchildren-
- EBElena Burger
[laughs]
- SSSteven Sinofsky
... 100 years from now talking about how sticky that experience was, just like I told, like, "Oh, you didn't know this, but the software that runs Allstate is older than me, and it's not going anywhere." And that's because the, these examples are ones that codified an external force, and that external force was the regulatory body that they embraced. The Seema's examples of SAP, like, it just codified a company. And, and so, like, if you take SAP out of a large automobile manufacturer, there's no automobile manufacturer left, or, or Walmart. Like, the company just evaporates because the, the company is defined not just by purchasing the software, not even by just using it, but by how the they codified the business rules into that product.
- SPSpeaker
I think this is a good point to double-click on, because I think a, a misconception aro- uh, right now is that SAP, okay, well, you can just have, you know, Postgres database and APIs, and then bam, like you can replace API, uh, uh, replace SAP. And that's like absolutely not true. I think partly, I mean, Steven, I don't know if you wanna elaborate on it or not, I'm happy to, but I think it's that piece around the logic and everything else that is ha- like that is encaptured in SAP is way, way more important than the fact that like, oh, this data just happens to be in this database.
- EBElena Burger
Mm-hmm.
- SPSpeaker
There's a reason why also SAP like takes m- you know, multiple years to implement, and again, it's not because like, oh, you know, yes, the system integrators are slow and part of it, but it's, it's customized to the way that business actually operates. Um, and I think that's like an important part about why you can't just obscure away the software completely from, and, and turn it into a data- database plus APIs.
- EBElena Burger
Yeah.
- SSSteven Sinofsky
Th- this, it's just so important because this is one of the things where like startups look at enterprise software, and they think about it in terms of startup scale. And so they take something like mundane, like expense reporting, and like, okay, well, we have 40 people, and like, you know, one person can figure out expense reports for 40 people. Like, you, you could hire a human and that, and be done with it. They, like literally you come back from a trip, you dump the receipts in a bucket, and one human rifles through them, and the expense reporting problem goes away. And or you say, "Oh, forget the human, we'll just all take pictures of our receipts, and OCR it, and categorize it, and the whole thing will go away." And, and that's fine until you have 100,000 people in 20 countries with different national laws and policies about business expense and all of this, and then you overlay corporate policies and, and the whole thing just... And then your business is just codified that way, and it, and you can't replace it. In, back in the, um, in the late 1990s, who now is sort of the godfather of enterprise software, Larry Ellison at Oracle, back then they were only a database company and entering the world of NetSuite and ERP and all this. But he went on a rant, he, a multi-year rant about how enterprise software was so stupid because everybody customized it, and he had this saying that just said, "Businesses should just stick with the 80% solution, and they should just use whatever works like 80% of the time." And most enterprise people were like, well, A, you're just talking your book because your software only does 80% of what I need.
- EBElena Burger
Mm-hmm.
- SSSteven Sinofsky
But B, like that's, that's just not how it works. Like if you take the auto industry and you just take the top 10 companies in autos, they, they all, you know, putting aside EV versus gas or whatever, they all just make cars, which is a lot of known technology with assembly lines and workers. Like what differentiates the, the companies? And what differentiates them is how they operate, and the internal processes to decide what car to make, how many raw materials to buy, what currencies to hedge, how many people to hire, when to introduce a new product line. All of that is enterpr- enterprise resource management and planning. And how is all of that done? It's all in SAP. So those companies are effectively run by people sitting in conference rooms looking at SAP screens. And, and the, the difference between F- Ford and Toyota and General Motors and Daimler are just, are not just that they're looking at the same screen, it's that they chose which screens to look at, which customizations to make in those screens, and then they go and they buy steel and aluminum and wire and dashboards and radios from all the same places. And so it's a... I, I just think that people wildly underestimate the, the level of how, of sophistication that customers apply to this software. Like wh- when, back when we were s- first starting to get Excel used in companies,
- 22:00 – 29:00
Vibe Coding Your Way Into Enterprise: Why It Fails
- SSSteven Sinofsky
you'll laugh at this, Seema, like, like the, we used to do these little visits and we'd go visit bankers. And so we're sitting in Goldman Sachs and we're telling them about Excel is better than Lotus 1-2-3, blah, blah. That's super old. You don't even know what 1-2-3 is.
- SPSpeaker
I know, I know what that is, but yes. [laughs]
- SSSteven Sinofsky
Trust me, it's old. And, and the, the guy at Goldman looked at us and said, "I don't think you understand. We make more money from Excel than you do." And, and you're like, and we're just sitting there like, what is he talking about? Like it made no sense to us. And then we started to think about it, and it's like, well, we sell Excel to Morgan Stanley and JP and Chase and everybody else, and what Goldman was saying is their application of Excel is so differentiated. A- and that's, and that wasn't just people typing. They built add-ins. They wrote all this code. They defined their work processes. So there's this wild underestimation about like you could vibe code your way into enterprise software.
- SPSpeaker
I, uh, was at a dinner last night, and there was someone there who, um, was like the head of rev ops at a, I don't know, maybe growth stage startup, and his task, this is like a thousand plus person company, was to rebuild their Salesforce instance internally. Uh, and you know, I think he's like, "Oh, well, you know, we know all the fields. We can import all the data." And I was like, that's not really the part that's tough, right? It's, well, how are you deciding what g- like what gets captured, how the whole organization aligns around it, uh, and then who's gonna maintain this also over time? I think that's like a piece that just gets, falls off. You know, you can v- you can vibe code a CRM. We've all vibe coded projects that have like already gotten stale and no, we haven't touched again because it's painful, and it's, it's, it, it takes time and needs to adapt to the business.
- EBElena Burger
Mm-hmm. And, and Seema, you've also written about how, you know, there are, there's an entire ecosystem of startups now that are just building on top of SAP and that are, you know, like sort of building around all of the kind of headache-inducing stuff and, but still using SAP. So like to both of your points earlier, like th- these, these like legacy SaaS systems are just like so deeply embedded that the newer insurgents are just coming and they're, you know, building on top and around them rather than kind of like trying to rip out and get people to migrate completely.
- SPSpeaker
A, a lot of what we're seeing AI being used today f- is, for is how do you make it like, I think the word is often used, like conversational or like how do you pull the information out and actually make it more usable? How do you retrieve the information from SAP without needing to go, you know, run a SQL query and get all the information or like look at a bunch of screens? It's like, okay, well, if I wanna be able to connect to Steven's point around analyze, like f- You know, three different, uh, sets of tables and different geographies. Like, can I quickly q- you know, query that in, like, a natural language way? Um, can I get reports automatically generated that are customized to me without needing to, like, go back through the, like, SAP customization process? And I think that is-- that usability layer is, I think, indicative of what's happening now with software in general, which is accessing the UI is optional, and, like, going back to the Slack bots point, like, you want the de- information delivered to you versus needing to go to the UI. But, but the data and the business logic inside, either it's SAP or something else that's being-- replacing it, that's building it, but that all still needs to exist one way or another. Mm-hmm.
- SSSteven Sinofsky
That's a, that's an incredibly important point is, for, for folks to take away, which is that the, the, the biggest thing about enterprise software is it almost always does what somebody is-- wants it to do. They just don't know how to make it do that.
- SPSpeaker
[laughs]
- SSSteven Sinofsky
Like, there's no report that S- that SAP can't generate. No graph, no chart, no analysis or whatever. But you, you just can't figure it out. Or maybe it's configured so you don't have permissions or something. So the two-- The way to think of it is, in enterprise software, the two most frequently used features exist in no enterprise software natively. It's export to Excel and export as CSV and, or PDF. You pick. And so all enterprise software, the first thing they have to do that's missing when they show up and they do that first demo, is the customers say, "Does it do export to Excel, or does it do export to CSV or PDF?" Because then you know you have an escape valve to do the thing that you couldn't do before on analysis. And, and so what's so cool about where we are today is that now with, with the language models, you have this incredible way to actually consume those in much easier than you could before. If you think about PDF, like, the old way used to be like, okay, I wanna figure out, like, exception handling, some report that, that my system emits, y- you know, declined expense reports or whatever. But I wanna do it over some weird time period or across different currencies that it doesn't handle, or some weirdness that you can't figure out the UI. So now you can export them all and take these 20 PDFs and put them in a model and do a bunch of analysis that you couldn't do before. Or if you did, it was all copy and paste and this mundane thing. And to something that Seema wrote about, these sort of, I don't remember the word you used, but these ad hoc business processes are the ones that really become the most interesting. Because they're interesting because that's how a business runs, but they're also interesting because those are the next products. Like, those are the next companies that people start. You know, CRM used to just be a spreadsheet. Like the, this-- If, if you were in a business and you were account manager and you kept track of your accounts, you just kept track of it in Excel. And then a company got started to, to do that. It wasn't SA- it wasn't Salesforce first, it was the predecessor called Siebel. And, and then, like, people are like, "Oh, we should make a whole company that does this." And that's what's, uh, that's what some of these apps are that you're seeing using language models and interfaces that are chat to SAP or to Salesforce. They, they are just trying to take advantage of what the LLMs are really good at, which is synthesizing and orchestrating unstructured information.
- SPSpeaker
Yeah. I think we also forget that, like, Salesforce is, like, really an enforcement mechanism for, like, the, the, the go-to-market team, which is like, okay, are you collecting all the information that you need to? And of course, we can talk about Salesforce hygiene, et cetera, as a separate point. But, like, do you have all-- You know, is the human, uh, doing the-- getting the data to then have, um, like, the, to, to then, you know, capture the state of the business.
- SSSteven Sinofsky
Mm-hmm.
- SPSpeaker
Um, which, okay, but I think if we, like, now switch to the agentic world, um... You know, I think again, we can talk about what agent means, but imagine there's an agent that needs to do a outbound calling or outbound messaging.
- 29:00 – 37:00
Exception Handling Is the Entire Game
- SPSpeaker
They wanna be able to retrieve that information. They don't really care about how the fields are organized or, you know, how many clicks it takes. But they do wanna be a-- They still need to access that information. But then the second piece they need is this context thing. So we've talked a lot, I think, I feel like the internet has talked a lot about context graphs, uh, over the last six months. But what is that? That's all, like, the exceptions. What do you do? W- what do you, how do you handle certain cases? It's the edge cases and the permissioning and all that stuff that needs to be, um, and all the policies that are not necessarily in the fields of Salesforce. Um, and so for the agent to then go, go back to this 80/20 thing, the agent can, you know, extract all the information, send an outbound email based on the information that's in the CRM around the person and their persona and what they do and all that. But then, like, okay, how do you deal with, um, a case, one case versus another and how they respond? And it's like, oh, well, normally, if it's a person who's in Asia, we respond this way. But if it's a person in the US, we respond this other way. That's not captured in Salesforce, but that's, that's, was in someone's head. And so that's the context that I think is really important now for agents to be able to act on behalf of this data. Mm-hmm.
- SSSteven Sinofsky
Oh, that's so-- I mean, for Salesforce in particular, that's incredibly important because I've never met a salesperson, an account manager, an account executive who thinks that the default is the right answer for anything-
- SPSpeaker
Right
- SSSteven Sinofsky
... with their account. And, and, like, no, even if they get the Japanese language right, you know, "Oh, it's spring and the birds are chirping and..." But you're, you're overdue on your payment, your license count is wrong. That even if you do that correctly, the rep is gonna wanna handle it in their, in their specific way. And I, and I think that this notion of exception handling is just the root of the challenge with, with agents, which is- Almost everything interesting in an enterprise is an exception.
- SPSpeaker
Yes. Yep.
- SSSteven Sinofsky
Like, that, like, all the people are about exception handling. It, it, it, you know, it's basically, like, spend 15 minutes at McDonald's and watch people start in the kiosk and give up, and then go watch what they really want, and they're like, "Well, I wanted a McFlurry, but I wanted two flavors and mix them together," and that's not in the... And it's always the exceptions. And everything about automation and enterprise is handling exceptions. It, it just is. It's the strangest thing. Like, but, you know, enterprise pricing is a great example. Like, how much is it per seat? Well, you have to call us. Well, you call, then you talk, and then it's still an exception.
- SPSpeaker
Yeah. And that, that's exactly right. So these exceptions, and aren't, they're not captured anywhere right now.
- EBElena Burger
Mm-hmm.
- SPSpeaker
Um, now I think if you say, if there's, you know, a voice agent that is doing, um, let's say, compliance check calls for freight, as one of our portfolio companies does, they're now collecting the exceptions through their voice agent and, and getting some of that context. Or if they're, we're looking, we can talk about computer using agents. If you're observing humans and how they are clicking through software, how they are responding to things, and now we have this ability now to, you know, not only record data or, like, record interactions, but then process it via LMS, then you're able to start collecting some of this context. But it's a lot. There, I mean, as Steven was saying, it's ev- all the interesting work is around the exceptions. So it's not like, okay, you know, three days later, we've, we've, we've got it all. We've got all the context. Because also, like, sales cycles take a long time.
- EBElena Burger
Mm-hmm.
- SPSpeaker
Each exception isn't, like, handled, um, with the frequency that you get the data immediately, right? Um, and so you have to feel comfort- you have to get to that point where you're like, okay, we've ca- we've observed enough interactions to actually capture, uh, to understand the exceptions. And then on the sales side, the buyer trusts that, uh, that, you know, this piece of software can actually, you know, has captured all the context to handle the exception.
- SSSteven Sinofsky
Well, let me just add to building on that, 'cause I think it helps us to g- to go back to this notion of headless, and what are both the challenges and the opportunities. Because of course, if you're an engineer, which almost everyone talking about what's going on in the world in AI today is, y- you think headless and API, a- agent, API, just interchange them. And so you, you think, "Oh, well, it's code. I can write the business process down." And, and the, the problem that you hit right at the beginning is, is that if you're not an engineer, you can't even explain the process that you use to resolve a customer issue. Uh, you ... And in fact, it's sort of very interesting to watch Amazon really do some of the best work on this, because they really, really don't wanna have humans. Like, they, you, you, you can't call Amazon for anything. Like, it's just hopeless. And so what they're doing is they're learning with everybody, like, the best way to automate something, and it's their religion, it's their core principle, which is you just decide it in favor of the customer. You know? Oh, they sent the wrong thing. So you go to the chatbot, you tell them. The chatbot understands that you got the wrong thing, and it just sends you a new one. And I think that that's so interesting compared to sort of old school exception handling. And then they use the data to go and improve the internal shipping and handling and warehouse process. Maybe it's the product description, a zillion other things, or reviews. And, and so I find, that's what I find so interesting about the capabilities of AI, is that it's driving a different definition and different behavior at companies about how to handle exceptions. And I think when we get through sort of the 1.0 version of this, we're gonna get to a new version where people are, like, comfortable letting AI do or decide things because they realize it's adding a level of predictability and repeatability to their enterprise.
- EBElena Burger
It is, it, it's funny to think that maybe customer service gets worse in the short term because things stop getting default decided in favor of the customer. You know? [laughs] Like, suddenly, suddenly you actually have to defend your case again instead of, like, you being, you know, reshipped the, uh, the Sensodyne toothpaste like you, you feel like you were owed. Um, but, uh, I think, I, I think maybe then more generally, it, it sounds like you're both saying that automating the long tail is still kind of the hardest thing about, about all of this. Is, is that true, or would you say that there are other hard things, uh, that, that developers and founders also need to think about?
- SPSpeaker
I think that's, that's part of it. Um, I think there are a lot of other things around, like, permissioning, and it, this is, this is all, I think, I could, you could probably lump it into the hard tail, but, uh, oh, sorry, long tail. But, like, permissioning is part of this, right? And, like, you know, as you give people or give it, you know, API access, it's like, okay, so which, in which cases can people extract data? When, when can they write versus read? Like, that all needs to be figured out over time as well, and, like, interactions also between agents, right? Um, and I think if you go back to the idea of a system of record, right, there's, it's one s- ideally one cent- one central repository of data that is the s- the source of truth. Well, that, n- now if you're have multiple people accessing and writing to it, like, who gets to access when, and I, I think that's a, that, that... Anyways, these are additional problems that I think need to be solved. Solvable, but will take time. Um.
- SSSteven Sinofsky
Well, one of the things that happens in, in technology shifts is it, you know, everybody knows the thing about nobody understands exponential when it's happening. So you have to be very careful to extrapolate and end up extrapolating linear when something exponential is happening. But the same thing happens with productivity, or an analogous thing happens with productivity, which is people look at the existing body of work that happens today, and they say, "Okay, how do we make that easier?" And then all of a sudden there's all this fear that we're gonna automate everything away, that everything is just gonna become an API, which developers and engineers say, "Oh, that will be easy." And then we'll be in this nirvana world where everything is automated and easy and predictable. But they forget That productivity drives new scenarios. And so the minute that you can get something
- 37:00 – 54:00
Productivity Creates New Scenarios, Not Fewer Jobs
- SSSteven Sinofsky
easier with automation, and you can actually automate it, which I do think is happening right now with agents and with, with language models, well, then we're gonna dream up a whole bunch of new stuff to do. Like, I, I just mentioned this, this loop that Amazon must be in on customer service. Well, they got rid of all the phone people and the phone experience that would be miserable to do a return, and the, the challenge response and the fighting and like, "Can I return this?" And, "Do I have to package it up, or will you just igno-" Like toothpaste, they don't want it back. Like, that's a, a, a pioneering invention by Amazon is like, "You know, if somebody s- gets the wrong consumable, we just don't want it." Like, they're poisoning it. They used part of it. It's cheaper to just have them throw it away. Well, that never happened before. Like, you used to have to actually bring spoiled food to the supermarket and show it to them. And so they've fixed that level of productivity, but now there's this back end that's just out there constantly figuring out how to have it not happen again. And n- now they need a new level of analysis, a new set of tools, and the long tail got no shorter. It just got longer in a different way.
- EBElena Burger
Mm-hmm.
- SPSpeaker
Yes.
- SSSteven Sinofsky
And, and I, I think people forget that that's how innovation is this constant reinvention, and it's, it's a growing pie, not a static pie. And, and all the negativity around AI comes from just thinking that the work to be done is this fixed thing that ta- takes N people and M amount of software, and we're just gonna replace N people with M plus five, and then we don't... We're done. There's no jobs anymore. There's just an agent running. A- and that's just never gonna happen. Like, legal is a great example of this, like where people do contracts, and they think that the law is gonna help contracts get, get done quicker without lawyers. Except I can assure you, contracts will get longer and more sophisticated and encompass way more sets of scenarios than a person ever could.
- EBElena Burger
Mm-hmm.
- SPSpeaker
And there'll be more-
- SSSteven Sinofsky
And that's gonna create a whole-
- SPSpeaker
More litigation around it, and that creates a whole ecosystem.
- EBElena Burger
And more deals. [laughs]
- SSSteven Sinofsky
The, the, look, there's the, the now apocryphal, semi-apocryphal famous example of radiology, which is a correlation, not a causation, but radiologists all love, love AI, and now we are having a radiology shortage. It, it's not, it, it's, there's a lot of reasons. It's complicated. But it, it, it, it just shows that the innovation wasn't static. And, and the market wa- for the demand wasn't static. And, and so I think that a lot of what happens just in the micro at the enterprise level is the minute you automate the most mundane thing and think you have it all squared away, whole new things appear. Like, actually, like expense reporting is a really good example. You know, first there's nothing. Then people figure out how to, like, do spreadsheets, and then people figure out, like, "Oh, now we have a whole system. We can analyze it." And now all of a sudden, business travel, you get ahead of the curve, and you're like, "Well, now let's just use miles for business travel. Let's, you know, route our travel requests to the best prices we can get at any given moment rather than just default to one carrier. Let's use a specific credit card for business travel that buys us a bunch of different added benefits that we know matter to our patterns of travel." And so suddenly, like there's a bigger job called business travel analysis that takes way more people than just booking the flights, which everybody can just do on their own.
- SPSpeaker
There, there's always another layer of analysis on top.
- SSSteven Sinofsky
Al- always, the, but the analysis then drives new processes and new behaviors that themselves differentiate companies. Look, business travel is a, to stick with that example, is a huge sink in most companies. It's just a giant expense hole that they wish they could shrink. But once they can tie it to how things perform in their company, then it's more than just expense moderation. It's actually figuring out performance optimization, and figuring that whole thing out becomes like a different kind of job than just booking travel and analyzing expenses. It just becomes this whole remote work optimization tool, and then it's a different thing.
- SPSpeaker
I think the other thing interesting, not to double click and, you know, to spend too much time on business travel, but I think the, it, it also ties, there are, the physical and, like, digital worlds. Like, there are always things that there will be humans doing. You know, maybe it's not back office TPS reports, but, like, f- salespeople will be closing deal. There will be human interaction to close deals. Um, people will be getting on planes as a result, and, uh, maybe they aren't spending as much time entering data into Salesforce or doing things along the way, but they will, there, there will be these humans doing online and offline worl- work, and I think that actually is something that, you know, there will always be a data exhaust from things to capture-
- EBElena Burger
Yep
- SPSpeaker
... optimization that needs to happen, and that, that isn't going away either.
- EBElena Burger
Yeah.
- SSSteven Sinofsky
Well, I think open source software development is actually a really good example of this because, like, the hardest thing in software development is, you know, you have to be finished at some point so that everybody knows this is a stable release and can go build on it. And the art of finishing is this long tail of, like, not changing the code, and, and there's no API for that. Like, developers think there, don't, they, developers don't hesitate to think there should be no API for that. They, they, they can think of a way to automate it with voting and with a discussion that has sentiment analysis or whatever, but they, you still need a bunch of people to concur over a decision to fix or not fix something. And yet they'll advo- those same people will just say some other business process, like closing the books for earnings, that should just be an API. And it's actually the literally the same mental model. Like, there's a bunch of stuff, and we're deciding when to close the books and what sales to account for what and where. It, it's fixing a bug. And there's a story around it, a narrative, and we have to explain it to our boss, and if something goes wrong, we need a trail that explains who did what. And, and so, so much of what a business really is, it, are just the people deciding things. And all that software does is it up-levels, abstracts, and changes what they decide and how and what tools they use.
- EBElena Burger
The, the other sort of follow-up to Seema's point is, like, it's the best case for just recording everything you do. Like, all... Like, just voice recording everything you do to, like, capture it. If, if people are, you know, going and flying and closing deals in person, um, make sure the software or the LLM can kind of capture everything that happens at all times. Obviously not advocating for, you know, full panopticon, but [laughs]
- SPSpeaker
But, but that is the context gathering that is happening.
- EBElena Burger
But exactly.
- SPSpeaker
Yeah.
- EBElena Burger
Exactly.
- SPSpeaker
And it... Whether it's like-
- SSSteven Sinofsky
Yeah
- SPSpeaker
... you know, recording and, you know, conversations or taking emails and, you know, written artifacts and ingesting them, this is all, that is the way the mo- the world is moving. And I-
- EBElena Burger
Exactly.
- SPSpeaker
So, yeah.
- EBElena Burger
Yeah.
- SSSteven Sinofsky
Well, it's also, to your earlier point, you know, expertise exists in this cloud in an organization, and, and it is the, the untapped resource, it, of the modern era. And Aaron Levie at Box has done the, the most eloquent job of explaining repeatedly the, the assets that exist in all of these, you know, Word and Excel documents strewn throughout a company. And it's actually very, very hard to, to understand which documents are important, which ones to believe. And part of being in a company and having a culture is really knowing the answer to that. And, and it's super interesting to watch the customers at Box use Box to, to, to actually answer those questions. You know, which are the sales PowerPoint presentations that are actually working? Which are the spreadsheets and the models that people actually rely on? And, and I think that, that AI is the first thing to come along that really taps into that unstructured information in a company.
- EBElena Burger
Yeah. I think, um, before we wrap up, it might be good to, to visit the sort of more immediate history and then the more far away history of kind of what, what headless software even is. Uh, I know, Steven, you wrote last year a piece, uh, in reaction to, to the rise of MCP servers. Um, and in that piece, you also related it actually to, uh, sort of, like, early Microsoft litigation that the, that the Justice Department levied against them, and, and part of the argument was that Microsoft had a lot of products that could be categorized as middleware. Um, and I- just kind of curious, you know, in all of these different software waves that you've witnessed, kind of w- in, in what ways is history rhyming and repeating? Maybe not on the litigation side, but on the, you know-
- 54:00 – 1:00:59
Where the Biggest Startup Opportunities Are Now
- SPSpeaker
out in the field, and pulling that back in. So like construction, manufacturing, all of that, so.
- SSSteven Sinofsky
Well, the universal truth for enterprise software is the, the most difficult thing to do that happens to be the dumbest is to attempt to just compete head-on with, with an existing category. And, and by head-on, I mean not just the same category, but doing it the same way. The biggest opportunity right now is always, always to look at the existing, uh, sort of mental map of enterprise categories and be in between two established players. Because the thing that you know right now during a massive technology shift is the one thing that established players won't do is disturb their existing product line and go to market. So they absolutely will just be bolting AI on top of their existing product. They, they won't be getting rid of it. They won't stop working on it. They won't do anything to, to break it. They're just gonna try to weather this technology storm by sort of power throughing it, power- powering through it. And so your opportunity in a startup is to just look at two big players Who are bolting AI onto the side and exposing some existing API as an agent or whatever, and just aim for the middle and do things in an, in the new way, and in the new way exclusively. And by not attacking head-on, you don't show up at every single customer and have them go, you know, "Well, you need to these, do these 8,000 things before you even enter the door." Instead, you have a equally difficult question, but one you're in control of is, which is why do you even exist? And, and that, but you, that's your own question. You, you don't have to answer to a, a series of 20-year frameworks that, for a 20-year-old framework that got created to answer a bunch of questions that aren't even relevant anymore. And, and the best example of this is, is, is HTTP and HTML. Client server existed, but the reason that those took over was not because it did all the things the client server did. In fact, it did none of them. But it implemented that concept in an entirely new way. And so the web exists in spite of the fact that legacy vendors had a trillion dollars invested on how client server should work.
- SPSpeaker
Well, and I, and I, I would say the, the other piece too, it's not just two between two legacy vendors, but I think now there's like a layer of translation between two different functions within an organization, too.
- SSSteven Sinofsky
Oh, yeah, yeah, for sure.
- SPSpeaker
Software has always sold to like, oh, I'm selling into just, you know, the sales team or the finance team, but then there's like these handoffs and which is now the context, right, but on bills and deals, and like that actually also presents an interesting opportunity. So the last question I have, which is for Steven, is, um, so network effects is this thing we always talk about on the consumer side, and it's a great, you know, source of defensibility. No enterprise software business, as far as I can tell, has successfully d- you know, implemented network effects. But you could argue that is a good source of, um, durability over time, right? And I think Salesforce has tried this in, in, in, in a couple ways in the past. But do you think that like enterprise software will start entering the f- the, uh, the, you know, the field of network effects in terms of like, okay, we're gonna have both buyers and sellers on our CRM, and therefore be able to like mediate these transactions? Or like, yeah, I'm curious to get your take on that.
- SSSteven Sinofsky
Well, certainly network effects outside of a company are extremely difficult for a bunch of compliance and security-
- SPSpeaker
Right
- SSSteven Sinofsky
... reasons. But, but the biggest network effect in enterprise software is inside of a company, and we're seeing that happen now with, with just chat. Like, all of a sudden you're seeing the, the ... It's, it's so incredible to be at this dynamic that, that almost felt like the good old days, when some very motivated person ... Like, most people who work in enterprises, it turns out, are not like super interested in making their job better. They actually just wanna go to work, get paid, and go home. And they don't come to work every day going, "Ooh, how could I make my ... How could I streamline my task?" They just wanna not mess it up. That is a lot of the world. But there's a small set of people, like those bankers at Goldman Sachs, that were like, "How do I do more deals faster, better, more clever models?" And so they were using Excel when, when the other bankers were using 1-2-3. There's actually, floating around on the internet is this old commercial for Excel, the launch, this launch TV ad from the nine- from the late 1990s, where, or sorry, the late 1980s, where the first Excel spreadsheets were being used. And it's a person sitting there with this monstrous laptop that weighed like 12 pounds in an elevator trying to use it. I, I'm laughing because of course they were trying to not run out battery life-
- SPSpeaker
[laughs]
- SSSteven Sinofsky
... in the, in the elevator ride, which was invariably the case. But all, all of a sudden, this crowded elevator, a bunch of people in, in these 1980s ties and 1980s wearing glasses looking at the spreadsheet going, "What are you doing? How are you doing that?" And getting all excited. And fast-forward to 2025, and that's exactly what happened with chat. Like, in fact, I had a friend at SAP that was, was writing like a, um, a SAP white paper about something. And, and I, I just asked them, "Tell me what questions you're trying to answer." And I did the prompt and sent them back a white paper. And I'm positive I kicked off some sort of viral loop, not technically a viral loop, but some sort of network effect viral loop inside of her team. Because like all of a sudden, people are seeing how to make their job better, and it's accessible to them, and they're doing it. So I, I think, and to your point, Seema, like this idea of, of a tool that enables two functions to talk together that couldn't before, i- is golden. Like, that's exactly ... Like, that's literally what enterprise software integration is, except that's all manual, brute force, hire Accenture kind of stuff. And so if you have products that bridge this, and you know, Figma did a bunch of this with design and product development. And so i- if you can develop software that leverages AI in order to bring together parts of an organization that don't normally communicate, that's a whole- that's a new category. And we've seen that with things like IT budgeting, where IT and finance would end up with tools that ended up helping them both do forecasting, and the cloud enabled that. And so I, I think that that's, that's a huge opportunity.
- SPSpeaker
Nice. Well, I think that's also an amazing note to end on. Uh, thank you so much, Steven, for, for joining us here, and-
- SSSteven Sinofsky
Well, thanks, Seema.
- SPSpeaker
Yeah. Oh, thank you. And thank you, and thank you, Seema. [upbeat music]
Episode duration: 1:01:08
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Transcript of episode Mxs4erDxOEE
