← Liftoff with Keith: Conversations with Super Founders and Growth Experts sharing useful insights
Liftoff with Keith: Conversations with Super Founders and Growth Experts sharing useful insights
Context Over Content: How Sreedhar Is Redefining Revenue Activation in the AI Era
00:33:59
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- [00:00]
A
Foreign. Liftoff with Keith is the one and Only Compass Strategic Advisors.com an experienced partner to help you navigate everything from cap tables to stock option and compensation plans and all types of backroom and marketing services. There is no better friend to the startup CEO than Compass. Check them out at Compass Strategic Advisors. We are live now with the CEO of gtm, Buddy Shar Panini. Shar, welcome to lift off.
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B
Thank you so much. K. It's wonderful to be here. Thanks.
- [00:38]
A
It's great. It's great to have you here. Somebody like myself who's been around the block a little bit and also has found himself in the AI roller coaster ride with. It's not, it's. It's an amazing journey you've had had. But I'm anxious to dig into how you're finding life inside the AI application layer. But first give me a little bit of that famous background just to set the context, would you?
- [01:12]
B
Yeah. Thanks again Keith. Like you have been around the block for a While now, about 25 plus years in the industry, been fortunate enough to see the dot com era and more in my context, the birth of SAS if you will, the late 90s, the transition from on premise software to SaaS with my first company now called Planful and built that company between 2001 to 2010 as a co founder as that company was scaling the idea for my second company. Okay, as a SaaS company we're growing. How do you keep the customers? How do you keep that installed base of customers and maintain your retention numbers? That idea led to founding of my second company, that's Gainsight, which was the first company in the customer success category which later on became a function leading to an exit in 2020 and in 21 I started on this journey of building GTM Buddy which is in revenue activation category. We are coining that right now. It's an evolution of enablement moving into revenue activation. And like you going through this roller coaster ride of AI, I still remember that back in 2007 in my first company we used to talk about, you know, predictive analyt was a fancy thing to say. And what we were doing is the glorified what if analysis that you would do with Excel, the kind of a goal seek function and you would say that okay, this is predictive analytics for you, this is AI. Then we had the churn prediction in the early 2011, 1213 where we give you a crystal ball in terms of who is the customer, who's going to stay with you, who's going to churn. And so on but since those days, what's happening now in the past four, five years now, including ChatGPT, which is three years, but it's phenomenal. It's a kind of a change that I've never seen in my life.
- [03:10]
A
Yeah, I mean we saw the introduction of the whole rev ops role. You've started this thing. And by the way, I'm a huge fan of Gainsight too. I met a bunch of your friends from there. But your pitch is more. Less noise, better guidance and that's. That really resonates with me, you know. So that philosophy came out of that experience.
- [03:33]
B
Absolutely, absolutely. Yeah. So as I was thinking about my third entrepreneurial journey, I was thinking about, okay, now that I've gone through a journey of, you know, a paradigm shift from on Prem to SaaS and creation of a new category which does require a lot of capital with gainsight in terms of education, a lot of awareness and education that that's needed. I wanted to work on an existing category where companies are spending a billion dollars or more and there is an opportunity to disrupt that category. Call it ponder optimism or call it ponder foolishness, either one goes. But where we felt that we could disrupt an existing category that has a sizable tab.
- [04:17]
A
Yep, of course.
- [04:18]
B
And that journey kind of led us to revenue enablement, which was basically a glorified terminology for content management systems for sales teams and learning management systems. The LMS again focus on the sales teams. These two combined together is a revenue enablement market where there are multiple companies that were operating. They all started in 2011, 12 timeframes, right about the time when we started gainsight, traditional SaaS and we felt that, okay, the reps in 2000s, they don't really have a content problem or a learning problem. What I have consistently seen is they have a context problem. What's the right thing that they need to say in a given selling context? In a high stakes selling scenario with a buyer Persona, what is that they want to be talking about? What is that social proof that they want to be sharing? How do you. That context is everything. Right. So our goal with the platform that we set about building is about delivering that right subset of the information that the reps require in the moment of need in their workflow. So that's what we're building, leveraging AI, of course, without using a lot of the buzzwords yet.
- [05:38]
A
Yeah. It's interesting. You described somebody who thrives on product development unlocking practical value. We're in this age of AI. How do we define what practical is and Especially when it comes to AI for sales. Right. That's. What does it look like when a product crosses the line from practical into gimmick?
- [05:58]
B
That's a great question. So we are seeing especially the GTM stack, the broader sales tech stack, all the categories that we have seen, the categories that we have seen becoming gigantic, including enablement, they're all crumbling at, at many levels. If I take an example of enablement, a billion dollar category, the top four players, seismic and high spot, the top two in the category, which collectively raised $2 billion in venture capital, collectively valued at about $7 billion, they just merged. So two rivals who were at it for 15 years, they couldn't really go to the market, go get to an ipo, an outcome, and they both get purchased by, by, by a private equity player and merges them together looking for scale that hopefully gets them to an ipo. We are seeing that happen across the GTM stack. Right. Everybody is talking about AI, but it's about I, I just slap a, a, a, an API call to an LLM, I build a chatbot and I would even call that an agent. I would create, you know, this chatbot talks to this, this document, that's one agent. This talks to another set of data, that's another agent. No, the people use the words very, very loosely. And every, everybody is AI, everybody is agentic, and everybody is stepping on each other's toes by way of mergers and acquisitions. A lot of consolidation that's happening now. It's a time that I truly believe that we all probably want to take a step back and actually place the customer first in terms of given all the technology that's possible today, acknowledging that maybe many of those were not possible five years ago, three years ago, they're possible now with skills coming into play with anthropic things that were not possible six months ago are possible now. That's how fast things are changing.
- [08:01]
A
And that's incredible. And the dovetails into the question I wanted to ask you most, which is I know you're very focused in terms of smaller, more agile and that's going to be a key criteria to success. So how do we structure at this application layer today? How do we build the right team and perhaps more than the actual number that everybody seems fixated on, but what are the right roles to structure the right team for the right opportunity, as you mentioned, TAM and an available opportunity.
- [08:36]
B
Yeah. So the way look at it, regardless of which category that I'm operating in, first we need to look at the use cases first as we Both know the cost of product building a product is tending towards zero, especially with the level of maturity that we are seeing with cloud code or Even codecs with 5.3 models, cost of building is trending towards zero. It's the idea that matters. And that idea is not. That's not for me. But for who? And what's that value that I'm delivering to that use case, to that user base and how friction free is the experience? Is that experience something where I'm expected to switch over to a completely different ui or is that intelligence getting delivered to me? And for what use case? That's going to be the key differentiator in my view. If I were to take the sales as an example,
- [09:38]
A
which by the way, can you think of a market that has more tools and tech and stuff thrown at it today than the intersection of sales and marketing. So super crowded market, how do you get through that noise?
- [09:53]
B
Yep. So the initial talk track for us, this was pre chat GPT era. We're trying to get free of, you know, you're getting all of this content. Your marketing is producing thousands of pieces of content. You're manually tagging and you're hoping that the search is working better. And it doesn't. Search is broken even today with the legacy vendors that used to be the play. From there in the past two years or so, it's more about the context. Engineering is what is helping. So to make it concrete, I'm a rep and I was routed a lead for a discovery call. On the discovery call, we expect that going into the call, how prepared is the rep going into that call? Did the person do a basic amount of account research and a personal research, who they are going to meet with or they're just going to show up and talk about their product or service? I'm talking about a very simple use case. Now this is an example of a realistic agentic flow. Call it an agent or a workflow or just prompting somebody who's working harder, who can do a little bit of research and AI makes it simpler to know more about the account, more about the people. And then tailoring the talk track based on the Persona, based on the person's profile. I've looked at the LinkedIn profile. What's my talk track? How do I activate all things that I have learned about that buyer Persona in my business context? How do I get into action? What questions do I ask? How do I come across as this trustworthy person who understands the problem statement? That's level one conversation has happened. I decided that As a rep, I have qualified that, that, that particular opportunity. Now, how do I leverage that conversation or the conversation transcript that's available in gong? How do I leverage that information to get my next meeting booked? If I, if it's. And if I'm keeping in touch, how do I make sure that I'm sending information that prospect would find valuable? We're talking about context here. How do I leverage that call transcript to surface a subset of information that the prospect will find useful and book
- [12:14]
A
that second, what you're explaining is how you see things and how GTM Buddy kind of works is really understanding the user activity already and you're trying to not necessarily change their workflow, but you're trying to work within that existing structure.
- [12:34]
B
Correct. In the workflow, how do we provide the. Not just that's. We are talking about a behavior change that's easier said than done. And by reducing the barriers to adoption by being in the reps workflow. That's what we call revenue activation. Live in their workflow and deliver information. Don't deliver noisy information. Deliver information that the user considers valuable,
- [12:59]
A
like almost one step ahead of them. What they're needing, what they're going to need next. So how do so many people get it wrong? It's just that seems kind of obvious, but maybe it's not.
- [13:09]
B
Yeah. So it does require a level of context engineering, which was, to be honest, may not be entirely possible in the earlier era. AI is making a lot of that possible today. So today we are able to build. Just to give an example, a lot of people talk about mcps and I have seen every company has some kind of a launch with an MCP server. You go and look at, you know, MCP server. What's the role of an MCP server in this world of AI? It's a data provider of sorts. How well structured is that data and how is it combined with a skill that you are building where you're telling the combining with a recipe that LLM can use to do something of value. Right, Right. So that data instrumentation is something that has, that has evolved quite a bit over the past couple of years now. And that combined with the power of AI in terms of context engineering is making it possible today.
- [14:11]
A
Very cool. So let me ask you, we'll do a quick pivot here. Give us a sense of where you're at with GT and Buddy, like who are your customers? And I know you've been around for a little bit, but you're still kind of in that growth phase yourself. And who are you Selling to where is the product really resonating most?
- [14:31]
B
So we are selling into any businesses that have complex sales involved. You are selling high value product or service offering and it has multiple stakeholders involved. Typically a customer of GTM body has 10 to 20 people in the buying team that they need to convince to get them over the line and high value product offering or service offering and that universe kind of is really, really converging into more of high tech sales with high value products and services.
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A
So what's the ICP then?
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B
So we're selling into mid market to lower end of enterprise at this point in time. In terms of technology organizations, okay. We're selling to companies like Lean Data, Visible Currency. These are some of our customers.
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A
So they're probably 50 million in sales
- [15:25]
B
or above and above we have, we have customers who are over half a billion dollars in terms of the current revenues.
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A
Okay.
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B
We have Thoughtspot Irides, many of them. Yeah.
- [15:36]
A
Fantastic. So you have 100 customers.
- [15:39]
B
Yes.
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A
Okay, great.
- [15:41]
B
Little over 100 now.
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A
That's fantastic. And when you look at the market overall, there's a lot of people going into that space. How are, what are the mistakes that they're making that you see and not that you want to tell your competition, you know.
- [15:59]
B
Yeah, I think what is happening today we are seeing new competition emerge every single day. That's probably a little bit of an exaggeration, but I would say every week the companies that are sponsoring.
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A
Yeah, no, that's true. That, that's kind of what I'm, that's what I'm addressing is like it's a crowded, it's a crowded market. It's also changing super fast. So you always need to be, you know, have that smarter approach. So what?
- [16:24]
B
Yeah, yeah, yeah. So there's a couple of things there, Keith. One, as your, the, the basics of building for the enterprise that has not dramatically changed in terms of, you know, you build it, there will come kind of a mindset. The configurability, extensibility that you need to keep in mind for serving an enterprise. Those fundamentals is something that has not changed. That's 1, 2. The ease with which one can actually build the products today is resulting in an exponential rise of AI wrapper products that are coming about. So basically I get together with a couple of engineers and purchase a pro or max plan with Claude and I'm coding stuff up and I'm slapping a layer on top of an LLM for one specific use case. And that use case might even see some viral adoption. Especially when a price very Very low with low price product, the question of loyalty or evaluation. You know, people would experiment. If the marketing and the messaging seems cool enough, people do experiment. And I might even see early success. And that early success does not necessarily translate into tangible outcomes for the customers or the customers staying with them. This is something that we are seeing across every single category. And sales tech is possibly the biggest area of innovation where a number of companies are trying to come and do stuff. And on the other hand, what's also happening, probably extending the answer a little bit, we're also seeing consolidation. The legacy players getting acquired or merging, that activity is also increasing. So we're in this interesting space where consolidation at the top end, the larger players, and we're seeing the birth of many smaller players that are coming through the gap that we are seeing is a company or people, teams that are coming with a point of view, well articulated point of view. And that point of view is not just a wrapper, but something that addresses a foundational problem or a set of problems. And the infrastructure and the instrumentation they're building to support solving that problem. That vision is where the gap is in many of the companies.
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A
Yeah, it's interesting. Again, you've been around for a while. It's more challenging or more fulfilling selling in this environment than say enterprise software or SaaS software era.
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B
I think it's a little bit of both. It's very interesting because you start seeing that hey, this is possible, you can do this and you are not able to do this before with AI, a lot of possibilities are opening. We get excited and selling that to the market. There are people who are on both sides of the spectrum now, as you know, the people who totally believe in AI and they want to experiment. But gradually there's an increase of some level of disillusionment that's starting to set in. People are starting to ask whether there's a hype in terms of actual enterprise adoption of AI, what's the roi, what projects have succeeded and so on. So we're living through that picture in terms of how do you convince the buyer to see from your point of view, that's getting harder because there's just too much of noise.
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A
Yeah, it's a, it's an interesting point too. You know, you're, you're super experienced. So let me ask you this. I know you'll understand the context of this question because it speaks more to early, earlier stage founders, first time, second time founders, than yourself. But you know, staying focused is easy to say and hard to do for that earlier founder, that newer founder. But there's no shortage of customers who always want something special and, and customize investors still want, you know, growth at almost any cost. And customers are promising the world and, and coming up across your, your screen is doing interesting things or innovative things. But how do you maintain that sharp vision with that kind of backdrop of all those things happening and that kind of pressure?
- [21:05]
B
That's a brilliant question, Keith. I, I could argue again, being around the block for such a long time, I've come across two extremes, right? I've seen founders, I say this with all due respect, but building companies, and they reach a level of PMF, typically you have 50, 100 customers paying meaningful amount of subscription fees to establish that, okay, there's somebody willing to pay for your service and that evidence is objective, you're able to renew them. That evidence is there. And I've seen those founders getting a carrot from these large enterprises saying that, okay, if you were to do this, I like your product and all of that, but if you were to do this for me, I'm going to give you a million dollar contract. Or I've seen founders, fellow founders, friends who have been offered 2, 3 million dollars worth of contract, we need you to do this. And that would take them away from their trajectory. And it's really a hard question. It's easier to say that, okay, thou shall not waver in terms of your focus. It's easier to say than do it. That's really a difficult question, especially if the founder has not raised a lot of capital and that incentive of disclosing large business is tempting. On the other hand, I've also seen the younger founders was doing it for the first time and we're using the word. We have pivoted on ideas. It's almost too glamorous to say, actually thrive on that. We started with this and then we're trying to do this, then we are trying to do this until we figured out what's the thing that sticks. So they say, I'm not saying pivoting is a bad thing to do, but at the same time, I also have seen people glorifying the fact that they've pivoted multiple times.
- [23:03]
A
I do want to lean into this master class kind of product vision approach that you have. It's very, very disciplined. What's that decision making filter for what makes it into the roadmap and what doesn't.
- [23:19]
B
I think the most important one, in my view, is being honest to ourselves as founders invested our life and blood into this building this stuff. It's very easy to convince ourselves that our idea is good and continue to beat the dead horse in some cases, as the saying goes, or overreacting to the advice that comes by. Advice is free and a lot of people that we as founders talk to almost you talk to people, you get 100 different advices. But being honest to ourselves, being objective in terms of the thought process, again, easier said than done. That will be the, the number one thing that I, I struggle to struggle with it myself. Even though I'm saying it,
- [24:10]
A
you're being. Being a little bit humble, but along the same lines. I hope this doesn't sound redundant, but I was curious because a friend asked me to share this question. What's the builder's lesson you wish more founders in the AI space internalized right now, Something the hype cycle is actively working against.
- [24:28]
B
Yeah. So that's great one actually I'm going through this lesson myself, Kate. So I've been close to building products and in both my, my prior companies have been a CTO and a product visionary in terms of when the company was founded and all of that. That's my core strength. Superpower if you will. But at GTM buddy in the CEO role I have gotten into multiple other things in terms of, you know, working with the customers and prospects and investors. Lots of different things probably with AI. One mistake that I have made early on, I try to keep abreast of myself in terms by reading stuff as opposed to building stuff. What I have done over the past six months now is actually becoming hands on like every weekend I have work cut out for myself in terms of okay, either I'm going to take a course or I'm going to build something. And building something can be in any language with the technology where it is, it's language agnostic, right?
- [25:33]
A
Yeah.
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B
I have this idea that I want my team to work on. Let me try to try to show them a working prototype of what my idea is about. That's actually building my muscle memory in terms of where this is headed, what it's uncovering new possibilities that it was theoretical to me before. Now I can see with conviction. I'm starting to see the opportunity that I had not seen probably six months ago, rolling up my sleeves and working with AI on a day to day basis. But weekend projects, they have made a big difference for me. I wish I had done here.
- [26:07]
A
And in speaking with someone like yourself, I just have to ask because you've gone through these phases or these cycles of the software development, how much of it's changing in terms of the code that's written by AI versus developers versus engineers and that whole structure of things.
- [26:25]
B
What.
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A
How do you explain where you're at today in terms of building product?
- [26:31]
B
Yeah, I think it's been a journey. Like if you were to ask me this question, year earlier my co founder would have said like he was not too happy with AI, he would use it, but not totally convinced and so on. And it was really wonderful to see him change his stance. Now, now it's a mandate is for every one of our team. We're getting to a point where if you're not coding with an AI tool, you can't commit. So it's a, it's, it's a way of forcing everybody to, to get into that discipline of leveraging AI.
- [27:06]
A
Yeah. And probably using various different AIs for different LLMs versus different chips versus everything.
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B
I'll do one more example. Sorry to take up1.1 to make it concrete. In the last year we have tripled our size in terms of customers. The revenue numbers. Now our head count stayed flat.
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A
Good.
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B
It's the power of AI. This was not possible before.
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A
Now the only other question is what's happening with your pricing and your margins?
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B
Yeah.
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A
Because again, as things get more competitive and you're saving costs, the customer is going to want to see that save savings in some way too. Hey, are you ready to jump into our lightning round? I want to respect your time and I know we're getting close, so.
- [27:54]
B
Absolutely.
- [27:55]
A
Now I got three questions in my lightning round. This is, you know, meant to be a little bit of fun, but also a takeaway for the founders who are listening and some of them may even be on your team that we get to, we get to share some thoughts with. But what's one thing sellers actually want from AI that almost no tool is delivering yet?
- [28:19]
B
The, the promise of agentic autonomous execution that everyone talks about. There's way more hype than the real reality of what's getting delivered in the market. And I do believe that it's going to change in 26. That's not already changed, but in 26 we're going to start seeing real use cases, more more complex, sophisticated use case getting solved.
- [28:47]
A
I think that's going to open up a lot of, of checkbooks also, you know, budgets, because a lot of people are saying we'll pay for results now. We're not going to pay for promise. So I think, you know, there's, there's a shift going on in the world today where, you know, and that's affecting the pricing models too, right?
- [29:06]
B
Yep, totally.
- [29:08]
A
We love SaaS models, but usage models are going to start to continue to encroach. What's the biggest red flag you see when evaluating whether an AI product has real value or just great marketing? And that's kind of the theme where we just touched on, right?
- [29:29]
B
Yeah. So that, that one thing goes into, is it getting adopted? The adoption. Adoption has different meanings in terms of if AI is going to adopt the outcome of your product, that's a different league. But the adoption, consistent and continuous adoption of the people coming back to your product or service, consuming what you are delivering on a day to day basis. That was a traditional SaaS model as well. Yeah, but does that really change in terms of like okay, I could build, take something as simple as Claude, right. Purchase a team subscription of cloud and I'm buying even credits for cloud code and so on. Or the people using it or the credits getting consumed so that measure does not go away. Adoption to me remains one of the central tenet of delivering value.
- [30:29]
A
What struck me in our conversation earlier, you talked about how many people were involved in the buying decision. Yeah, 15 people I think you said. I mean that's amazing, right? How about in the usage in the implementation phase? How many people are touching the product? Have you seen that change? How many people are using GT and
- [30:48]
B
Buddy for example, within the organization that is expanding. So usually it used to start off with a sales team as the primary buyer and from there we are seeing organic expansion, we're seeing twofold expansion, buying other products from us and more importantly other functions. All customer facing functions. Adopting GTM body. So we see from sales, sales development, pre sales in the post sales organization we'll see the implementation teams and customer success teams and partner teams, all of the customer facing functions or buying more. So that's an expansion that we see.
- [31:26]
A
Okay, well that's exciting. Okay, final question. What does winning look like in three years from now for you in gtm Buddy?
- [31:35]
B
So we're looking for continuing the current pace of growth that we have seen in the past year and continue to innovate. And as the technology as I mentioned, like what was not possible three months ago or six months ago is possible now. So three years today. Honestly Kate, seems like so far ahead in time. I can talk about the financially and the customer wise, the revenue wise, where we want to be, but things are changing so fast that continue the current pace of growth and innovation. I would leave it at that.
- [32:11]
A
I try to put myself in the seat of the person I'm talking with and understanding what their role feels like right now.
- [32:18]
B
Yeah.
- [32:19]
A
Doing a three year forecast, I could probably get to 12 months, maybe 18 months. But after that, with everything that's going on, plus the other thing that we've seen is the changing of who's the lead dog in all these different races, whether we're talking about chips or LLMs or whatever. Right. And how that changes so rapidly. Certainly when we get into horizontal or vertical AI apps, I mean, that's going to be fundamentally. Just look what's happening in security right now. Right. Chrome comes out with it. So all these security software companies are now, people are questioning their existence. They've been, you know, bellwethers and key pillars in the industry for years and now we're wondering, are they going to be around in a year?
- [33:02]
B
Yep. Yep. So living through that. In my category, enablement, the as well leaders, the bellwethers of the industry, as you put it, are they going to be around in a year or two from now?
- [33:15]
A
In three years? You want to get acquired by Salesforce or HubSpot, Is that what you're saying?
- [33:19]
B
No, no, I'm, I was talking about enablement, by the way. Yeah.
- [33:26]
A
These are, these are no doubt exciting times. You're in a great position. I'm excited to see the growth that you're doing it at gtm Buddy. I'm going to encourage the folks on the podcast here to listen, to take a look at what you're doing and, and follow what, what your progress is again, it's a masterclass and how you're building and growing the business. Congratulations. Thanks for sharing some, some of these thoughts with us.
- [33:52]
B
Thank you so much, Keith. Wonderful to be here. Have a good day.
- [33:55]
A
Thank you.
- [33:56]
B
Thank you.