sriram-iyer-audio
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[00:00:00] All right, Sreeram, what's up, man? Good to have you on the show. Hey, nice to be having this conversation, Jeff. Good to see you again. It's been a little while, and glad we put this together. You've spent a career at this point walking into the big orgs, like the big boys of product here, walked in big, complex, high-stakes organizations, and basically over and over and over again, driven initiatives to speed things up and make them go faster.

And you've had this one point that you've made that I heard over and over that I really liked, and I wanna dive into, where a lot of these things are not driven by tech problems, it's a trust deficit. So this concept of, like, the trust deficit and this other kind of concept you put out there of the simplifier in chief, and I, I think these two concepts are so powerful, especially right now, given all the change going on across every company with AI.

So that's what I wanna cover with you today. But before that, how'd you get here [00:01:00] to being a product executive, and what's that run-up kinda look like? So you and I have spoken about the part of my journey where, you know, I spent about twelve years at Salesforce, about four and a half years at Adobe, and both places running a massive businesses, you know, Sales Cloud, the platform, digital media, Creative Cloud products, and Freshworks, the vertical businesses, platforms, AI solutions, et cetera.

But part of the story that a lot of people do not know, including you, that I've never shared, behind this whole simplifier in chief concept that you and I started talking about, I witnessed my dad being an entrepreneur or converting or turning into an entrepreneur at the age of four. When I was four years old, he left his stable job, and he started an ice cream business.

And back in the day, he roped me in as his right-hand person. And ever since then, all the way till I left home for college- Mm-hmm ... I helped grow the business with him side by side. And when you do that, that [00:02:00] early experience in your life helps you ground a lot of things. You learn about unit economics, you learn about customer empathy, you learn about negotiation, managing vendors, emotional customers, whatever have you.

Like, there are just so many things that happen when you run a small business and you had the opportunity of seeing it grow to a medium-ish sized business. So then, later in life, when I found myself running a five billion dollar business, those same concepts and that same framework kinda kicks in to say, "Okay, what is the right thing to do for the customer?

What is the right thing to do for the company? What is the right thing to do for the employee?" And then you start kind of working backwards from those principles, from ethics or values or morals, and those systems guide you to make the right call. So that is the gist of simplifier in chief. I'd love to hear how this kind of relates into it, 'cause I think there's probably a parallel.

Let's just take the small business and raise the stakes almost a billion dollars. But obviously, the last couple years have been really, really marked by [00:03:00] some companies moving incredibly quickly, and if you don't, you kinda got into trouble. But most recently, I think we talked about you came into an org where there was a hypothesis for, like, the ability to build kind of a verticalized business, where we got that idea, the concept of, like, simplifier and chief for you, is between that and kinda the idea of, like, how do you get this moving quickly?

It was just what is the key thing? Slash everything else and just move as fast as you can. Maybe let's dive into that. It's starting to think in terms of first principles, right? And starting to think about what is the problem we are trying to solve, who is it for, and what is the fastest way to get there, suspending all current beliefs.

Mm-hmm. And those beliefs are formed over ages in a lot of companies, and many a times, you know, people stop questioning as to why something happens a certain way. So in this example that, you know, you and I have been discussing, imagine you walk into any midsize company or a big company, and you say, "Well, we wanna grow this business from X to Y, and we are launching a new vertical."

Right? So that's [00:04:00] a pretty massive kind of transformation, and typically what ends up happening is you start forming projects, you start forming multiple stakeholder meetings. There's a cadence, program management gets involved, and very quickly it turns into this multi-month, if not multi-year, kind of project.

Mm-hmm. And at some point it was okay. That was the norm. That's what everyone did. But in today's world, when you have all these AI tools and all these new ways of thinking about a problem, I just walked into one of these leadership meetings, and the program manager literally was kinda like walking us through this program management plan which said that the first deliverable would be like six or nine months away.

And I said, "Why not six weeks? Let's just put it out there and kinda work backwards to say, 'What can we do to make this happen in six weeks?' Because our competition is running fast. Speed is one of those vectors, right?" And for a second I think people thought I was joking, and these are like 20 senior leaders from across engineering, design, product, marketing, [00:05:00] what have you.

And then I said, "No, no, I'm not joking." And, and now actually, you know what? Now that I think about it, let's increase the stakes. I want this shipped in six days. And that's when the pin dropped, and people are like, "That's impossible." Obviously, then people look up to you as a leader and start challenging you too, and they said, "Tell us, how would we do this?"

Mm-hmm. And I'm like, "Okay, let's take five minutes to examine what we are trying to do and how we will do it." So in this case, for example, you are trying to get into a new vertical, let's just say legal or finance or what have you. And I said, "The first job is let's do a sprint zero, where instead of boiling the ocean and trying to kinda ship the whole pie, let's figure out what is the thinnest slice of pizza."

It should be a viable slice of pizza, you know what I mean? Like, it should still have all the layers. It should have the toppings. So when we sell that pizza, someone's still able to eat it and consume it. So it's not a prototype, it's not a POC, it is live production code. So that's the first thing we wrote down, right?

And then I said, okay, but the constraint is not that it has to be the full [00:06:00] stack. The constraint that we are placing is it has to be the thinnest slice. And that's where, you know, I feel like a lot of teams, I don't know, like they get better of themselves because they assume that you also need this, and then you also need this, and then the requirements start ballooning.

Scope creep happens to the best of us. Right. So we said, okay, we are just gonna take two or three days and come up with what is that thinner slice of pizza that everyone from sales to engineering can cohesse and say, okay, this is something that is sellable. Mm-hmm. Once you have that hypothesis, then the second thing we said is, "We are gonna co-locate the teams."

Now, this is not saying that everyone has to come in, return from work. No, no, no, no. We, we are just saying, just for this one sprint, it's super important that the people who are delivering this need to be co-located because a lot of magic happens during lunch breaks and during these offline conversations.

You're trying to ideate and you're trying to innovate and create something from zero to one. You need people in a room because [00:07:00] no matter what AI we have, people still create magic for people. Mm-hmm. So we said, "Okay, we need to get everyone," and in this case, you know, our teams are in India, so we said, "Let's get everyone in Bangalore or Chennai or what have you."

So we said, "We are gonna start on a Monday, 8:00 AM, and end on a Friday, 5:00 PM." So boom, that's the week. We're gonna take three days prior to that week to really come up with the shape of what that scope is gonna be, and then we are doing a marathon, unlimited food and a $1,000 bonus or whatever, right?

And by the way, we said we are also gonna rope in our internal customers- Mm-hmm ... because that's the other kinda aha moment that happened for the first three days. We said, "You know, we don't have to go and do, like, a three-month research project. We have people in this company who are employees, but who are also potential customers.

So why don't we go ahead and talk to them?" And we roped them in in this kinda customer zero or sprint zero mechanism. So they became a part of that tiger team, and then boom, by the time it was [00:08:00] Friday, we had shipped something. Mm-hmm. We had shipped something meaningful. We had shipped something consumable.

You know, it was hidden behind a flag, so our customers still didn't have exposure to it. But at least for an internal team, there was something material that they could go ahead and test and they could give us valid feedback, and that was now a part of the production code. But that's how you go from, like, nine months- Yeah

to, like, six days, right? And now you can take this philosophy, you can take what has worked and scale and replicate, right? And that's the process. What I love about it is it hits on so many things that we're seeing right now, where across the board teams are trying to figure out how to move faster in this new world of AI.

And every single team and leader I talk to is being pushed How are you doubling speed? How are you moving faster? And so far we haven't actually talked about anything AI, 'cause part of it is there's amazing efficiencies you can gain just by looking at it. But a key thing is having the leader there who can get into the weeds, who isn't just up in the clouds [00:09:00] talking directionality, but they ask you, "How does five business days look?

Like, what does that actually mean?" And you can sit there and go, "Well, it's this. It's, you know, here's what we gotta do," and you can work with a team. Because I think one thing that happens here a lot is people start with the best intentions. They start with, "Let's do as fast as we can." Like the program manager you were talking about was not trying to slow the company down, it was just they have all these constraints that they have to, 'cause that's the process that's been built, and there's not many people in an org who can walk in and just cut through it all.

And that's where, like, involved executive layer that knows how things work can actually jump in and go, "No, we're not doing that. Cut that. We don't need to do that. We can break that rule if we want to right now." And, like, the success is this narrow thing. 'Cause without that, people are trying to do, you know, a million things and they all wanna look good on reviews and da, da, da, da, da.

And, and here you can say, "This is success. You will look good if you get this little tiny piece of pizza done in five days." Exactly. And you're spot on. When I said this, till you pointed out, I realized that I didn't use the word AI at all. Yeah. But it's implicit. The fact that we are able to [00:10:00] do this in 2026 and we probably could not have done this 10 years ago is purely AI, right?

Because obviously what I skipped in my contract was the designer had Figma Make, the engineers had Cursor, and we came up with our own tool to write PR using Cloud Code, right? All these AI tools are meshed together, so there's almost like this chain of humans working with each other, but there's also this implicit chain of AI agents and AI tools that are working alongside, so there's a partnership.

And then the beauty about this is once this rinse and repeat cycle works for one small slice of pizza, the AI has just become better because you've kind of worked out- Mm-hmm ... things. You've worked out, like, all the bugs and, you know, all those things, and now the second slice is gonna be even meatier and it's gonna be better and faster.

So the gains just keep compounding because AI continues to accrue context, it continues to accrue memory, and you've made sure that all these tools are daisy [00:11:00] chained properly with each other. So this human AI collaboration just keeps getting better and better, and then that's the vicious cycle or the amazing loop that you want to inject your organization.

And to do this, did you have to go find the engineers who were already on the train of how they've really tweaked their build process to take advantage of the economies of scale that we're seeing from AI? Or- Was this pull five great engineers and, and here's how we're gonna enhance their speed this week?

Yeah. I think organizationally what's happening is, and this is my, this observation talking to a lot of my friends in the Valley as well, almost all organizations have approved and written AI tools and costs into their budget. So that is not the constraint anymore, right? In fact, the reverse question is now being asked, like, okay, holy cow, right?

Like, we have burned so many tokens, what, what is the productivity we gained that we are getting with, with this big bill that the CFO is gonna get at the end of the quarter, right? Mm-hmm. Which is a good problem to [00:12:00] have, in my opinion. We could get into that. So I don't think the constraint, which was there six or eight months ago is, hey, which tool should we use?

We are still in this procurement cycle of getting Claude or getting Cursor. Like, all those are gone. Almost every company that I speak to has their preferred set of tools. Now, you could argue, is it Figma Maker? Is it Lovable? Is it Cursor versus Claude? What is it? But every company has now identified a standard set of tools that seem to work together.

Mm-hmm. So that's not the constraint. To answer your question, the real constraint is mindset. Imagine, like, 500 engineers, all of them had this tool to their disposal. Is every engineer using this the same way? The answer is clearly no. Yeah. Some of them are obviously leaning in, and you had to find those five engineers, to your point, for such an experiment who are absolutely aggressive, who are leaning in, and who have the mindset to say, "Yeah, let's go ahead and break barriers, and let's make this thing happen."

And then what happens is that energy, that [00:13:00] enthusiasm is infectious, and once you show that this is doable in five days, others say, "Hey, I wanna be a part of that magic. I wanna be a part of that team that makes things happen in that fashion." I think what I find interesting here is this is happening at a big organization.

We're not talking a couple hundred person startup. This is multi-billion dollar company, but kind of works the same where, like, you can take five people, accomplish this in a week versus, you know, last being told that it was gonna take six to nine months. So you can constrain that down. Almost ninety-nine percent of the time you can knock off of it, and it still has the effect though of like, you do it once, you've broken the glass on that tactic now.

You accomplished that task that quickly, and you set out how to do it. Now, no one can question it's possible. Like, before that it's like, "How can you do that? That's wild." Now it's just, "Well, Sriram did it." I think that's the most game-changing thing. If people look at this, it's not, "Oh, sure, you can do something fast," and then go back to your old thing.

It's, "Sure you can do it fast," and learn from it and use it [00:14:00] and develop it. And maybe a week is a little extreme sometimes, but it shouldn't go back to six, nine months, I'll tell you that. Yeah, exactly. Exactly. And then, you know, what ends up happening is the same audacious nature kind of permeates other parts of the conversation.

For example, in terms of revenue goals, right? Like, "Hey, let's grow this business a hundred percent year on year," right? Why are we talking single digits or double digits? Like, why even twenty-five percent? Why forty percent? Why not a hundred percent? And you will hear the same resistance. "No, our business is a twenty percent growth business," or, "Our company or our sector, our domain is growing at nineteen percent."

People will come with all kind of facts and data to support the LCM argument, and you have to kind of break that same glass to say, "Yes, but that's the average of how this industry is growing. That is not the ceiling," and can we do something that bends the curve? And then, you know, you can start growing businesses at ninety percent, a hundred [00:15:00] percent year over year, and then that kind of becomes infectious as well, right?

Like, again, done this multiple times, but at Salesforce, for example, when we were, you know, I think Sales Cloud was already like a five billion dollar business. But just to use this analogy, imagine you have a billion-dollar business. That's a massive rocket ship, right? And now imagine that you've reached like forty, forty-five percent market share- Mm-hmm

in North America, which is pretty much the ceiling. And now imagine that the CEO says, "Okay, you have to double this business in three years." How do you do that? It's already massive, and it's already at the cusp of its market leadership. Well, one theory that we came up with, a thesis that kind of worked, was why don't we attach 10 booster rockets worth a hundred million to this massive rocket ship, right?

The trick here is, okay, you can build those 10 booster rockets or adjacencies, right, yourself, or we can go ahead and acquire 10 businesses. Now- Again, the trick here is not to acquire 10 hundred million dollar businesses, but to acquire [00:16:00] 10 five to 30 billion dollar businesses, attach it in a thoughtful way, take like two years.

But once you attach it to the mothership, you take advantage of the tailwinds that this massive rocket ship already has. You know, go to market motions, experienced salespeople, the brand name, or whatever have you. And then all of a sudden, you know, in two years, that $30 million business has become $100 million worth.

Mm-hmm. And if you do that 10 times around or you do that simultaneously, then now you have grown a billion dollar business to two billion dollars, right? But those are the kind of things you have to think outside the box. And if you go back and check, uh, history notes, you know, it was around this time that Salesforce ended up acquiring, I think it was like 18 companies in one year, which at that time was the highest number of acquisitions for that year.

But that's the reason behind it, right? They went on an acquisition spree because they were turning from an organic growth engine to an inorganic growth engine, and that's what it took. But you have to constantly think outside the [00:17:00] box because a traditional business mindset would have said, "No, you're already at the ceiling.

You cannot further grow this to two billion dollars or five billion dollars." The piece I wanna make sure people remember is when you do it, it's not just doing it and proving you can do it, it's also how do you make sure that you do it in a way that you're documenting and you're talking, you're showing people so you can do it again.

Like the idea of like how do you turn it into a stencil so the whole business can learn- Here's how we can press timelines from nine months to, you know, one or two weeks, is here are the things you have to look at and have to do. And like I said, I'm sure it was not that ops person or that program manager who wanted to have it be a nine-month project.

It was just that was the process that was there. So I guess looking at that, like how did you kind of work with the team to make sure you were building a muscle, not just pulling off a stunt? Yeah, great question. So we spoke about mindset, and we spoke about culture, and I think we should go deeper into that vector because once you do it, to your point, you know, then you show the art of the possible, and then the wheels [00:18:00] start turning, and then your cultural posture of the organization shifts.

Mm-hmm. But the other piece is the word you used is stencil, which is the frameworks that you have. So what you're doing is when you're re-architecting something like this, you're also rebuilding the framework from the ground up. So for example, classic traditional frameworks have supported this nine-month motion, and there are these meetings that happen.

There are these stakeholders that have to be brought in. Mm-hmm. And every point you had to question why, and you had to say, "Can we do it differently?" So for example, if there is a DDAC, and there are all these informed people and contributors and drivers, and I've seen DDACs like with five decision makers.

Yeah. And you'll say, "No," but who's really making the decision? Who is really the one person who needs to sign this off? Because someone's taking the risk for sure, right? But you need to also be that courageous leader to say, "You know what? Put my name down. If this thing goes south, I [00:19:00] will take the hit."

That's done, right? And the organization has to see you taking that risk. For all you know, some of these experiments will not go well, and you should be willing to fall on the sword for that. Yeah. So you've changed the framework, but you're also changing the cultural piece to it. I'm just giving you an example here, right?

But you have to do both of these simultaneously, and this is where the organizational maturity, the organizational risk framework or the risk appetite kind of comes into picture. There are organizations that are willing to accept that kind of risk and are willing to reward that kind of risk, and then there are organizations that are not willing to do that, who just pay lip service to it.

But the beauty is it just exposes that piece, right? So now if the organization was just paying lip service, and you really had to fall on the sword for that, you know that, okay, this is not the right organization for you to be spending your time in, right? So that's a great outcome too. But irrespective, you need to be true to who you are as a builder, as an innovator, as an engineer, as a product leader, as a [00:20:00] designer, and you've got to kind of shoot for the stars and make a dent in the universe.

So do whatever it takes to do that, and if it works out, great. If not, you kind of walked out with a very valuable lesson, and there is no real downside to it. I think that right there is one of the key elements of if you want to be in a company that does something interesting and powerful and actually move a purpose.

But more than that, like, for people coming up in career too, if you want to be an executive, or if you are an executive and you wanna look at what, what good is, it's not having a big team. It's not having a big budget. It's not the personal fiefdom or any of that BS. Your job is to move the company forward, and you have to have conviction, but at the same time, with great power comes great responsibility.

I think it goes both ways in that, like, you can't have great responsibility... If you're not willing to take the risk, if you're not gonna go out there and say, "This is what we need to do," and stake yourself on it and say, like, "If it goes down, it's going down on me 'cause I'm saying we can do this in five days, [00:21:00] not nine months," you know, you're not really a leader.

Maybe you have the title. To get these things done and to build the team behind you that's gonna follow you through these ridiculous things, you have to be willing to go take your licks once in a while if you made a wrong bet. You know, I've been here for seven and a half years now from when we were almost nothing to much larger now, and we've had this consistent thing of we're gonna do risky things sometimes.

We're gonna take big bets. We're gonna try to move very hard, very fast, but we're gonna work on strategy together, and we're gonna agree on what the big picture things we're doing. And if something doesn't work and if we fail because the idea just wasn't the right one, no one's going down for that alone.

Like, we decided that that was a priority, and we're gonna do it, so we take responsibility together, and we look at success for the team. So if you're in an org like that where you're moving like you described, and you do catch the blame, and you go down in a blaze of not glory, but shame, like you said, maybe it's for the better.

Maybe that wasn't the right place. Maybe that's not gonna set you up for success. But if you're not willing to kind of, like, take that chance, are you really an exec? I'll say especially in this dynamic times that we are, in this [00:22:00] magical times that we are with AI, not taking the risk or not taking a risk is the biggest risk.

Yeah. And the only thing I'll disagree with what you said is sometimes. It's not sometimes. It's- It's all times. And I'm being deliberate here because I have definitely changed my posture and my stance- Mm ... to say I will be the person... And again, no right or wrong answer. You can define your own personal identity, right?

This is for all the product and engineering leaders or design leaders out there, but it's like, what kind of leader do you want to be known as? Yeah. And in my situation, what I've decided is I'm gonna be the leader who people know will come and swing for the fences. Yeah. This is what initially we took note of when we wanted to invite you on here is you want people to take that big bet with you, they have to trust you.

You have to be the person who's gonna put that on your shoulders, and, like, you were able to do that 'cause those five engineers went, "Yeah, we're gonna go with Sri on this 'cause if we do our best and it doesn't work out and he knows that we did the right things, he's gonna have our backs, and if he says we can do this, we [00:23:00] believe it Taking a step back, you know, thinking about it philosophically, what else can you do in life?

Yeah. In, in life, it's always gonna be high stakes, and we are just talking about a very thin slice here from a career vantage point. But think about everything that we do in life is high stakes, and it's about the posture that you have in life. Yeah. Some people are absolutely risk-averse, which is fine, right?

If that's how you roll, and that's your mindset, and that's what you want to do, you wanna protect your downside, you wanna protect the floor. Yeah. No, no shame, right? Like, that's my strategy. There are people and there are organizations where they just declare that's a strategy. Now, within those organizations, too, there could be certain thematic bets that that organization could take, and if they want you to come and lead that, then yes, I'm the right fit.

But if it's a ladder, then I'm the wrong fit. Now, the question for the organization is, am I the right cultural fit for you or not? Right. And every person, every leader, and I'm using the word leader irrespective of the [00:24:00] titles or grades or functions, but every leader needs to make that assessment for himself or herself and say, "What kind of player am I, and which kind of team do I want to join?"

I'll just leave the audience with this piece, too, especially, like, I, I know a lot of product people probably are listening to this. Yeah. It's like, you know, a lot of product people are also questioning what is the role of product managers going to be in the future. Yeah. But just connecting the dot to what you just said, it's like in the world of AI, someone's gotta answer the question, why are we doing this?

What is the business rationale behind this? What is the thesis? And to be able to see the forest for the trees and to say, "Okay, if this strategy is really gonna work," someone's going to write that down and risk their personal, as I said, refutation to say, "This is what I believe." You know, there's always going to be an element of uncertainty in any decision you make, otherwise AI could have made all the decisions.

It was just, like, black or white. Right. There's always a reserve gray in real [00:25:00] life, in real business, so the product manager who is able to bring clarity to that room, define the why, define the thesis, and show direction is still worth amazing, right? Like, worth millions because, because no AI is going to be able to do that for you.

Mm-hmm. You've gotta kinda, like, believe in yourself and to just tie the thread, like, the things that mattered 20 years ago, 25 years ago are still gonna matter tomorrow. Yeah. Just keep doing what you're good at and keep believing in yourself. I think that's a good place to kind of leave it off on because so much of now is still just what has it always been.

So, Sriram, it's been a real pleasure, man, having you on. Uh, we'll have to catch up again soon. Thank you so much. Thank you so much. Cheers. Bye.