Tom Scott — Wrike | Why Most SaaS CEOs Are Sequencing AI Wrong

Tom Scott is the CEO of Wrike, a $250M+ ARR intelligent work management platform owned by Symphony Technology Group. Three years into PE ownership and squarely inside what he calls the AI "rebuild moment," Tom is running the experiment in real time — and this conversation is the operating playbook, not the LinkedIn version of it. He walks Stu through what's defensible in enterprise software now, where most CEOs are getting the AI sequence wrong, and the actual mechanics of rebuilding a SaaS business while the numbers still look fine.

You'll Learn:

• Why the market is pricing every SaaS company as if they're disrupted equally — and why the real story of the next two years is execution variance, not disruption itself
• What's actually defensible when coding agents can clone a UI in a weekend (and why "system of record" companies get demoted while "system of agency" companies don't)
• The 5-step rebuild playbook Tom is running inside Wrike — including why subtraction matters more than addition, and why personal disruption is non-negotiable for the CEO
• How AI transformation actually rolls out in engineering and marketing (with the J-curve, the early-adopter dip, and the specific numbers Wrike has seen: 25% engineering velocity lift, 3x marketing article output, 87% faster account research)
• What PE investors should be asking in diligence now that almost none are — and the three failure modes that quietly deconstruct companies over 2–3 years while their numbers still look fine
• Tom's 12-month playbook for a $100M–$500M CEO starting today: one thing to do, two things not to do, and how to know in 90 days whether you're on the right side of the J-curve

Chapters:

00:00 – Intro

01:00 – Who is Tom Scott / what is Wrike

02:11 – Should SaaS CEOs be bearish on SaaS in an AI world?

05:11 – Commoditization: what AI flattens vs. what survives

07:01 – What's actually defensible: "Know your customer"

08:51 – System of record vs. system of agency

11:02 – Accruing memory: where the value of agent training accrues

12:39 – What Wrike is doing internally: agency, MCP, governance investments

15:27 – Will Microsoft / OpenAI / Anthropic just own this layer?

17:50 – The future of seat-based pricing (and Apex)

20:25 – What "rebuild the company" actually means

23:43 – What happens to companies that don't rebuild

25:08 – Why hands-on personal disruption is non-negotiable

28:56 – The first thing Tom changed: his own approach

31:29 – The 5-step rebuild playbook

35:37 – AI's impact on engineering velocity (25% Q4 lift)

36:36 – Where most CEOs get the sequence wrong

38:30 – Inside Wrike's marketing transformation: real numbers

41:26 – Advice for $100M–$250M+ company CEOs starting today

42:51 – The leader asking you to slow down: how Tom responds

44:46 – Failure of imagination and the real source of resistance

47:30 – The PE playbook under pressure: new diligence questions

51:25 – ROI timeline and the J-curve in practice

54:39 – Offense vs. defense in an AI-disrupted category

56:02 – What separates the winners from the deconstructed

57:07 – Advice for CEOs over the next 12 months

🎧 Listen on Spotify: https://open.spotify.com/show/3OlTNvh2FGlE4VJyCrMJVE

📺 Watch on YouTube: https://www.youtube.com/@JustCuriousAI

🔗 More Expert Interviews: https://checkpluris.com/expert-interviews

Proof of Work is the podcast of Pluris, a platform connecting investors and operators with the world's leading applied AI experts. Each episode features the builders, operators, and investors who've actually put AI into production, turning it from buzzword to bottom line through sharp case studies and practical conversations. We explore how AI is used to grow revenue, expand margins, improve operations, and create measurable value inside real businesses.

Learn more at checkpluris.com

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://proof-of-work-ai.beehiiv.com/

Transcript

SPEAKER_00 0:01

They were joined by Tom's gone. Right. 250 million ARR enterprise software company. Three years into PE ownership in the middle of figuring out what AI actually does with the SaaS model. The lazy version is that AI breaks out. Is that the market is rising every SaaS company? Is that they get disrupted equally? And the real story of the next two years is going to be execution variants. He calls this the rebuild moment. And he's running the experiment in real time. And then he's walking us through his actual playbook. What do you change first? Why most EOs are sequencing wrong? And what does that bring to the companies that come out of this stronger from the ones that get slowly deconstructed over the next two to three years? Tom, thanks for joining us. For those meeting you for the first time, who are you? What is Rike? And what problem do you solve for customers?

SPEAKER_01 1:02

So thanks for the introduction. As you said, I'm I'm Tom Scott. I'm CEO of Rike. Rike is an intelligent work management platform that's used for the delivery of complex work. So I've been with Reich for a little over four years at this point, and coming up on three years a CEO. And I'd taken over as CEO during the current uh sponsor hold period. RICE was founded about 20 years ago to help business users collaborate and orchestrate work. And that's kind of moved from like really simple task management to workflow management to now this hybrid type work that we're going to be talking about here in the future. You know, from my own background, I've been doing this for you know 20 plus years at this point. So executive roles across everything from communication services, infrastructure, robotics, and SaaS. And interestingly enough, it's spanned a whole type of you know, a load of different capital structures, everything from publicly traded companies to very fast-paced, early stage venture opportunities to now PE.

SPEAKER_00 2:09

So a lot of people are bearish on SaaS because of AI. You're running a large SaaS company.

SPEAKER_01 2:16

Should they be? So I think it's it's really not a one-size-fits-all answer here. So if you you certainly see the the broad sell-off that's happened over the last five months based on you know that the model provider exposure. And so I I don't disagree with the the disruption thesis. I think where I take the bus biggest ex um sort of exception to this is the specifics really do matter for for each company. And the the lazy answer is you were talking about it in the introduction, is just saying if you are enterprise software, you are impacted by this. And I would say yes, and and the the dividing line for me comes down to what is the level of the complexity, what is the level of the compliance needs that are sitting within those workflows. So if you're talking about generic horizontal workflows that are sitting there, yeah, then I absolutely believe that there's a strong barricade there. But when you start getting into like the deep encoding of workflow logic, when you talk about incorporating compliance and the governance burden, that's a very different conversation from my point of view. And so when you when you put this specifically as it relates to the the company that I run today with Reich, we have been a leader in collaborative work management for a long time, but I've never been the biggest. And what that what that means is I've always had to be very specifically applied with customers. And that long predates this AI moment that we're in. And so our strongest use cases have always been really deep in with our customers, whether it was what we were doing with campaign management, whether it was what we were doing with client service delivery, with product launch, we always had to get very specific to be able to demonstrate that value to them. And this differentiation is just another wave of what we're seeing with this AI disruption. It's just happening a lot faster. Now, one thing I will say on this is this opportunity that's in front of us, you can't just stay still. And what I mean by that is every company that is facing this disruption, regardless of where that dividing line is, they're gonna have to go through this rebuild or this reinvention phase because that is really how you're gonna unlock it and present, you know, prevent yourself from ultimately being you know disrupted and taken apart in the end.

SPEAKER_00 4:42

Yeah, and we're gonna walk through how you are rebuilding the company. Maybe before we do that, I can ask you a few questions about some of the narratives about how AI is impacting um SaaS. I'd love to get your thoughts on what feels real and what feels overblown and what people are missing in their hot takes. The first is around commoditization. And you you spoke to that uh just now, but I'd love to unpack it a bit. Does AI make most SaaS products interchangeable?

SPEAKER_01 5:13

So I think this is a a real concern, but I think a lot of the hot takes over you know overblow it and you know miss some of the nuance that's there. So let's let's unpack a few of those points. So if you take a look at you know coding agents, so cloud code, codecs, this absolutely means that software is no longer remote. You can go out and you can clone a UI in a weekend, that's absolutely true, and you can continue to iterate and you can build more and more form around that. And so if you start thinking about where do you see some of that challenge within a SaaS infrastructure, that outer layer is going to commoditize fairly quickly. So if you think about basic features, the engagement layer, the UI, that is completely under a lot of pressure. When you start going into areas that I think have a little bit more staying power and it gets into that differentiation, the data that sits within these platforms, the operating telemetry, and specifically as it relates to what we do, the the governance, audit, compliance layer is absolutely something that that's completely important and that trust. And so I think as you start thinking about what is, you know, where is the moat, and we'll get into this a little bit later as well. The moat is really knowing what is the stickiness with your customer, and then what is the ability of your team to be able to execute. And again, that gets into a case-by-case differentiation at the company level.

SPEAKER_00 6:45

Yeah. Yeah, let's get into that. What is actually defensible? What remains defensible?

SPEAKER_01 6:51

So, yeah, every year I kick off our sales event in January by by getting up on the stage and saying three words. I I remind everyone, know your customer. And it sounds like trite and really, really simple, but it's something I want to remind everyone all the time. Because if you if you lose sight of that connection of what do they care about, what motivates them, how does their work get done, it doesn't help you understand where you as an organization need to sit within the value chain. And so if you if you take this back to the statement I made a few minutes ago about defensibility is like the moat is no longer the software itself. That means that this defensibility ultimately has to be positional. You know, are you orchestrating the work? You know, is it complex enough? Are you connecting the systems of record across people and agents in a hybrid manner for them to be able to collaborate? That really is the connective tissue, and that is what's harder to dislodge. And so then if you go on and you say, is that enough? It's not because the capabilities of agents are going to continue to advance. The capabilities of the models are going to continue to compound over time. And so what you as an organization ultimately has to do is you have to be constantly updating that that perspective of where your customers are today, where are they going? And ultimately, like where do you have to position yourself as an organization within that value stack to be able to meet those expectations?

SPEAKER_00 8:33

Yeah. You spoke to agents. One thesis is that agents render tools like RIKE more like databases. And so if agents are doing the work, do tools like Rike just become systems of record in the background?

SPEAKER_01 8:49

I'll acknowledge that I think that is one of the bigger risks that's facing the category as a whole is this idea that you ultimately end up with a headless database with agents sitting on top of it. And so I I think that that is one outcome, but it's it's not the only outcome that that is out there. Ultimately, the the agents have to run somewhere. They need to have that context, and a lot of the data that we've captured captures that context. It also needs that permission layer, that that collabor, that collaboration level, that that accountability layer as well. And that's historically what companies like Reich have been able to provide is the accountability of a decision maker signing off, being directly in charge of that work deliverable, where you're able to like stand that up, and that has consequences. So when I think about like where do the winners come out of this, it's a governed execution layer that's working with agents where that work happens in a hybrid manner across humans and agents. It happens inside boundaries that the business trusts, and that means that you've got the ability to say, one, we can work with multiple LLMs, so avoid like vendor lock on any particular one. Number two, make sure that you are accruing the memory of what you are learning through this for the organization and not necessarily just for one model provider. And then three, the ability to control costs within that infrastructure. Because that's that's one of the issues that's going to continue to come up as well as these tools proliferate. It's what is the transparency of how much some of these agent calls actually put on the business.

SPEAKER_00 10:34

Yeah. I want to ask you about what you're actually doing inside Rike to avoid that risk. But can I ask you quickly about accruing memory? By accruing memory, what do you mean? What is it and give us sort of a visualization of what that is for people who are listening?

SPEAKER_01 10:51

Yeah, so think about accruing memory of like where where does the benefit of what an agent learns actually set? So if you if you take an example of what of what Claude released or Anthropic released a few weeks ago with Claude Managed Agents, that is essentially like a full stack model that includes agentic runtime all the way down through like human of the loop, some governance elements around it. And it often, you know, it offers the ability to move much faster because they they own the entire stack. But by them owning the entire stack like that, what the agents are training on, that accrues into that particular vendor. It's almost like a closed loop system that that is sitting there. And it's great for speed. What it is not great for is flexibility if you want to maintain a multi-vendor model. And so as you're training this, like where does the value of what you're training these agents sit? Does it sit closer to your originating system of record, or does it sit up at the model level? And the risk that you face is you end up with vendor lock eventually by going down that by going down that path. And it takes away some of the pricing flexibility that you might ultimately want to build into your platforms over time.

SPEAKER_00 12:08

Yeah. Let's talk about what you're actually doing within Rike to avoid that risk.

SPEAKER_01 12:15

So I think there are three things that I would hit the ad flag in terms of what we're what we're building towards today. One of them kind of goes back to that question you were asking a few minutes ago of this the system of record risk. And I definitely acknowledge that there is risk around being a historical system of record. What we are building towards is more of a system of agency. And what that means is we're radiating out from the sort of system of record for work that we've got for the organization. But we're not just building out agents that watch work happen. We're we're looking to make them have autonomy to make decisions, trigger actions, be able to move forward. And so you've got the system of record that holds the data, and then you've got the system of agency that manage the work and actually does part of it as well. The second item that I would flag that we're working on is we continue to make big investments within our MCP infrastructure. And we made an announcement uh yesterday, day before yesterday, talking about getting placed within the marketplaces like OpenAI, that was our announcement uh yesterday. We'll continue to extend that into the other marketplaces. And what this is important is this is our ability to work with like other providers within the marketplace, where you're able to coordinate your work. You can work inside RICE in the platform or you can work outside depending on the nature on the nature of the work. And we're going to continue to extend this footprint so it's not just something that you're able to access on the human side, but it's ultimately an agent meeting place where you can work with agents that originate inside Rike and you're able to coordinate with those that come out on the um that come from the on an external basis. Third thing I'd talk about is if you look at what we have invested in in the first part of this year, we continue to invest within Core Platform at the same time that we're investing within our agentic framework. And most of our product updates in the first quarter actually were around governance. And the reason we're investing so heavily in this area is I believe that we're gonna have to have guardrails for enterprises to adopt this at scale. And that's pretty consistent with the feedback that we receive from our customers. So we're continuing to make transparency, visibility, and control an attribute of our platform, and then be able to plug both our agents as well as eventually external agents into that framework.

SPEAKER_00 14:51

Yeah. And another threat is um the model companies. Why why doesn't Microsoft or OpenAI or Anthropic just own this layer over time?

SPEAKER_01 15:04

I mean that that is absolutely a real threat. And I would I would argue that they're they're attempting to do that already. I mean, if you take the example I was walking you through a minute ago, cloud managed agents is a form of that. I mean, it is a it is a full stack agent that goes well into the application layer and beyond just like agentic runtime. Um I would say OpenAI's recent release on agents is another example. So I think if you say, why don't they own it? I'd say they are absolutely moving up stack. And in some categories, they're they're certainly going to get there. To me, I think the question is where do you draw the line of what is a piece of the race that vertical size should not be in, versus what are those elements where you you absolutely should be contesting where that DMARC line sits between these big model providers and the value add. For me, it sits within these areas that we were talking about before. It's the it's the governance, it's the human and the loop, it's the you know, it's the capturing of the of the memory. And it's it's not just an explanation around cost, even though I think cost is a part of it. It's the trust and it's the concentration risk that ultimately ultimately sits there. And so I think that what's ultimately gonna happen is you will see abstraction layers that sit between the foundation models and the systems, you know, and the systems of record. That's going, you're gonna see a lot of activity of companies moving into action. So whether they call it a system of action, whether they call it a system of agency, you're you're gonna see moves in that direction. And that's very much what we are building towards. You know, we expect the models to bring the reasoning, we expect them to bring the scale around those around those agents. And we're very focused on continuing to bring the workflows, the governance, and the accountability around that.

SPEAKER_00 17:02

Last threat, pricing. What happens to seat-based pricing in a world of agents and AI-driven efficiency?

SPEAKER_01 17:10

Yeah, this this is one of those this is one of those questions where I think everyone loudly agrees on the answer and does not really know what the what the time frame is around it. So if the question is, do I expect seat-based pricing to evolve? Absolutely. Like there is no question that we are going to see a shift in what has powered SAS pricing for the last 20 years. The the speed of that diffusion is a little bit more of an open question for me because what is so great about seat-based pricing is it's deterministic. You know exactly what you're buying, you can you can budget for it. And some of the tension you have now is you know, customers absolutely want to look at outcome-based pricing, but they want to understand what that outcome is going to be up front so they're able to budget for it. And you you even see examples of this as you know, take to take the Uber CTO, the Uber CTO comment from a couple of weeks ago talking about how usage of Claude is already blowing through their you know their engineering spend budgets. And you know, there's reasons for that, and some of them are positive, some of some of them are negative, but it it leads to an inability to understand like what you are forecasting on that, you know, on that basis. What we are doing to try and create a bridge on this is we we introduced a new top-level plan at the beginning of this year called Apex. And the whole idea was to be able to increase the number of AI actions within the plan. The AI actions is just the unit of work that gets done within the right platform on our agents. And this actually gives us a bridging conversation to say, hey, look, you've got X number, this applies to this pool of seats that you have. So you're actually being able to talk about what did you deliver, how much of this was within your plan. And then over time, it gives you the ability to say, here's the value that you're getting from this and start to migrate in that direction. So we're we're fully committed to looking at that transition. I'm just looking for the right translation from point A to point B to be able to get there.

SPEAKER_00 19:33

Yeah, and that's a great segue into a conversation about rebuilding the company. So when you say rebuild the company, what actually has to be rebuilt? So product, workflows, org structure, you just spoke to pricing.

SPEAKER_01 19:49

Where do you start? I think it's really it's really all of it. And because you to me, you can't separate, you can't separate out any of these things and say, I'm gonna focus over here. You almost have to think of it in found the company type mode of if we're going to attack this market opportunity in front of us, how do we how do we optimize the organization to be able to get there? So let's let's talk about these things kind of like in three of them. So, in terms of product, one of the one of the things that you have to keep in mind with a business like mine is you can't ignore what made you successful for for the prior 20 years that got you there. You can't look at that and say, well, wouldn't it be great if we built a new product over here and raced after it? What you also can't do is you can't look at your platform and say, we're going to agentify it and put this wrapper around it and call it a day. And so you have to look really deep into the product and say, how are we going to change how we're pitching value to our customers? Take an AI first approach to solving problems that we we may have historically solved through a different mechanism within that platform. But you still have to do it on the basis of creating value with those customers and those workflows that got you to to where you are today. Second point I'd make around the org the org structure is that this is much more of a complete, you know, complete redesign. I think you have to start with the first principles approach on org structure and workflows and really understand like what are you doing today and why, and do those conditions still exist? And it's definitely a painful process to go through and kind of question everything that's out there, but it really means taking a look at how do you break the model that's been built up over decades of specialized individual contributors and move that more toward. A model of like full stack. And when I mean full stack, I'm not just applying that to an engineer. I'm applying that to pretty much like every role. It's like, how do you take someone who had been like a content marketer and turn them into like a full stack marketer that's able to draft items at scale, where they still have the judgment role, they still have taste, they still have editing, but you're creating a very different workflow that had existed before. And then obviously you mentioned pricing, and pricing comes into this both as a revenue input as well as a cost input, because you're also looking at things that you buy and applying that exact same logic to it.

SPEAKER_00 22:41

Yeah. And what what happens to companies that don't rebuild? And when will they know that they've taken the wrong path?

SPEAKER_01 22:53

I think the second part of your question is that is the challenge here, and that it's gonna it's going to take a long period of time for this tale to like play out, so you actually understand who made a serious misstep here and and who didn't. But I think that's and that's also one of the challenges of the moment. It's creating that urgency to say, it's like, look, you may not see it in the results, you may not see it in the, you know, in the in the customer, like all your customer conversations, but you have to have the conviction that if you don't do this over the next few quarters or the next few years, the business is slowly going to get unwound, and it's going to be too late at that point for you to be able to take action. And so the urgency is a theme that runs through pretty much everything that I do because it's it's not so obvious on a day-to-day basis that it's impacting your business.

SPEAKER_00 23:49

How do you gain that conviction without numbers suggesting that customers are churning or pricing is comer coming under pressure? How do you how do you gain that how do you personally gain that conviction?

SPEAKER_01 24:02

I think you have to personally gain that conviction by being hands-on. So I think if if you are not hands-on in this technology, and this is a theme that I talk a lot about at the company as well, is the is the personal disruption theme. If you are you are not constantly pushing the limits on personally disrupting yourself, I just don't think you have any real credibility to understand like what this could mean at a company scale or a sector or economy-wide scale. And so you you've got to get very hands-on to really have you that imagination of like, look, if this plays out at this level, this is gonna happen. And so we've got to get behind it.

SPEAKER_00 24:45

Yeah, what does what does hands-on mean? And and what what is disrupting yourself look like?

SPEAKER_01 24:53

When I talk about being hands-on, it means actually getting in with all the various options that are in front of you from a tool standpoint. And that means not just prompt, you know, prompt engineering within Chat GPT or using Cloud. It means like actually getting in there and looking at where do you spend your time on a daily basis and looking to constantly chop that into smaller and smaller pieces and automated. And for for me, it started on work that you know, work that we delivered within within Rike, actually building some of the agents within Rike myself, and then pushing the the executive team around me to do to do the same. And when you start to when you start to do that at the at the executive level, it also creates a little bit of competitive tension where you do it, then your partners start doing it, and it creates this virtuous cycle that you're comparing notes, and then across the rest of the organization, they see that this is a top-down point of view that is coming. And they see that there's credibility. Now, I am not going to be as technical as one of my full stack developers that works in this technology every day. Don't have to be. And but I can still learn from what they are doing, and it gives me a common language to be able to talk to other corners of the business. But that that's what hands-on means to me. That's what it means to disrupt. It's like, don't do the same thing tomorrow that you were doing yesterday if you're able to find a way to do it more efficiently. And then you've got to build that into your operating cadence. You know, so I spend part of every one of my one-on-ones with the team that reports into me, and I ask them, what did you do this week that that was different? And then sometimes it's interesting, sometimes it's not. When it's when it's interesting, I'm like, go share that. Walk that around, make sure everyone has heard has heard that example. Because this is another piece. You've got to celebrate these these wins pretty broadly, or these insights pretty broadly, because you can easily walk around with this bias that, well, everyone already knows this, or they'll they'll figure it out on their own. They won't. You've got to share really broad, show people that this behavior is not only we want this behavior, but we also kind of reward and celebrate this behavior whenever it happens. Yeah.

SPEAKER_00 27:32

When you realized this was a rebuild the company moment, what was the first thing you changed?

SPEAKER_01 27:37

So I think, you know, one of the biggest things that I'd had to change was my own approach. And I'll I'll give you a little bit of back background on this. So when I when I took over as his CEO almost three years ago, I I was replacing the founder. And you know, he he'd run the business for 17 years at that point. And I I think very highly of Andrew. And he he's extremely he's extremely technical, he's extremely driven. He he ran this business up to a massive scale, you know, largely through him, far longer than I've seen businesses kind of operate in that manner, where the founder is like driving that that that much like intensity and individual decision making. And so when I came in, one of the one of the very first things that I thought to myself was I should not pretend that I'm Andrew, because I'm not. Like I I should take a I should take a different approach here. And I tried to build up more formal, formal processes, I delegated authority, I picked areas where I wanted to make a big impact, and I got some really big benefit from from doing that. Because even though I traded away some speed and decision making, I got a lot more alignment in the organization and buy-in. And it it made it possible for me to do some of the the really hard things that I had to do as we as we entered into PE ownership through three years ago and were kind of re-repositioning the company. Now, as it became clear that we were in this this rebuild moment, that meant that I had to reverse some of that. And that that meant that I had to reconsolidate decision making, and it meant that I had to start forcing top-down alignment in in real time. And that was not super, you know, super popular because I had gone from one direction to the to the other. But I now like I see at this point that speed is what I need more than alignment, and I've gone I've gone full kind of full force in that direction, and I've had to make it make it mine as a way to be able to get the pace that we need.

SPEAKER_00 29:57

And with rebuilding, maybe you can break it into steps. What's the actual playbook that you followed?

SPEAKER_01 30:04

So there are several steps that I would that I'd touched on, and I was kind of leading, I was kind of leading towards one of them a minute ago. Is that the the first is it it has to come from it has to come from me. And especially given the the history here of how I tried to you know transition the company post-founder in PE ownership. When when it came time to make a different call here, it absolutely had to come from me. And the the other thing that I would say that was really important is I had an insight last year that I had to subtract. And by subtracting, I meant that I had to simplify a substantial number of our of our corporate goals. And I was I was very visible in in how I did this. So I I got up in front of the company, I did a number of AMAs, like at Ask Me Anything sessions that I did in person, I did a number of virtual events, and I walked around and said, We are too we are too complicated in in the goals. And when you're when you're pushing on multiple fronts, that's fine. But when you're in these moments where the the external environment is so completely volatile and you need to move much faster, the only way to do that is through is through subtraction. Third third thing is I I shortened the measurement period on those sort of simplified goals, where rather than quarterly, quarterly objectives, I was looking at short-term sprints on deliverables across the company. And I'm I'm still doing that. Where I'm looking at small initiatives that we go drive, are we making progress on this? If yes, double down. If no, drop it, move on, move on to the next one. The fourth one we we talked a little bit about when I was talking about being hands-on. I expect all of my executive team to be to be hands-on. There is no place on my team at this point if you are not physically feeling what is happening. And that means that in many ways, I'm asking them to do the equivalent of what I did is like be very careful about what you are what you are delegating. And don't don't delegate those things that require you know that that sort of like look and feel, you know, that that touch, um, sensory touch. And then the last thing, and it's it's almost it was almost somewhat accidental, is like you you've got to you've got to identify the the emerging the the emerging talent. Like what one of the examples I share is I identified one of these people inside the company through a LinkedIn post that he made last year. And I I didn't know him. And I I sort of saw through a connected post this really cool thing. It was not even related to Reich, it was just something he was working on that he that he posted about. And I read it, I'm like, why are you not doing that for me? And I reached out to him on Slack and I was like, hey, I'd like to, I'd love to hear about this. And I'd I got on the phone with them, and like five minutes into the conversation, all I could think about was, you're in the wrong job, and moved him into a role where he he's helping roll this technology out and has made a huge impact for us. And so that was connecting this like idea of like, how do we A, how do we like go find like talent? And that that one was accidental, but you've got to be very like forceful about that. And then how do you empower them to go do that across the organization? So that those are really the five things that I thought about.

SPEAKER_00 33:39

Yeah. How have you seen AI impact experimentation capacity and velocity? You mentioned these two to four week sprints. How's that different from what you could have done um a few years ago?

SPEAKER_01 33:52

It's it is much at this point, it is going so much faster. I'll give you I'll give you like a tangible data point. So if even if you just look within within the engineering over the the course of the fourth quarter last year, we we had a 25% improvement in the fourth quarter on delivery velocity. So like like idea to story point delivery. And so, and that's a pretty consistent theme that we've seen across like all these experimentations. And it's it's not an immediate 10x, it's just a constant compounding that that you see as you get the right as you get the right people into this and get those experiments spun up. Yeah. Where do you think most companies get this sequence wrong? I think the biggest thing that you get wrong is outsourcing ownership of this topic and thinking that if you just make the right hire, uh you bring them in from the outside, or you you you pick a consultant. And look, both of both of those can be helpful in the right in the right setting. It's just not a substitute for the the CEO saying, this is mine, and directly driving it and owning it. I think the the other thing people get wrong is skipping the personal disruption stage. You know, I think I think a lot of times companies will look at something and say, let's go for the big bang approach. And what what I have found is that individuals and leaders and even like the the middle ranks, it often starts at that personal disruption phase where they get some wins, they get excited, they get imaginative, and then they they pair it up with like broader, broader initiatives. I have not yet seen it work where that doesn't happen first, and then you go after like the scale. It's it's really hard to go after the scale until you've like fully tested it out. And then I think the third thing I would flag is, and and I I made this mistake too, I added objectives instead of subtracting. And I then I then realized that you gotta you gotta take away. And I I got much more immediate bang by subtracting than any of the work that I had done in the quarter plus before when I was adding on top.

SPEAKER_00 36:19

Yeah. Can we walk through an example, a function within Rike, a workflow that was transformed and what you did and what it looked like before?

SPEAKER_01 36:28

Yeah, so the two the two areas that I would say we were the earliest, earliest adopters on in inside of Rike were marketing and within within engineering. And let's let's use marketing as an example because I'd say within engineering it's it is fairly well discussed, like how to go after re redoing the SDLC, bringing coding agents, bringing, bringing um MD files and the like. Marketing is a little bit is a little bit more challenging, and we we picked marketing because one of the primary use cases we have in SEDRIC is marketing. So we we support a lot of workflows for campaign production, um, and we we do this for both marketing agency as well as corporate marketing groups, and so we wanted to apply this deep within our organization as well. And we we did a lot of work starting within content operations in particular, and we we've kind of expanded it out. And so if you if you kind of look, we've done everything from blog article creation and we've used a variety of tools for that that have had impact on throughput, where we're driving roughly 3x the number of articles per month versus what we were doing in the in the year-ago period. So very meaningful you know impact, especially on a company that has to produce like a lot of content out there to drive the you know, drive the leads on that side of the business. It's enabled us to get deeper into personalization. So um one particular team is using um a particular LLM for account research. We are running the campaigns through RICE, so we pull it in. We've cut multiple hours off of this, it's about 87% faster. You know, an individual ABM manager is saving roughly six hours a week on that. We're also doing a fair amount of work on um image generation for um for demand gen and for um um other like production time for gated assets that we're working on. This has helped script writing for events roughly 50%, and on the gated assets about 75%. And so, one takeaway I'd want you to have on all of this is like there was no big bang that was there. We had a bunch of like bespoke processes that sat within marketing, all broadly around content and digital ops, that we really brought together to start getting an impact. And those compounded over time. And yes, we were able to get some cost efficiencies there, but we were also able to produce like a substantial amount more content and higher quality content for our campaigns.

SPEAKER_00 39:09

And you were if you were advising a 100 million, 250 million plus company starting today, what would you tell them to do first?

SPEAKER_01 39:18

I would I would tell the CEO to personally get hands-on in building this technology himself. And one of the big blockers historically was obviously you needed a certain level of technical fluency to be able to do that. That is not true today. And so there really is no excuse to get in there and personally build this. Kind of no matter where you are in the organization, automate a piece of your job. And that is that table sticks credibility moment that you have to do. I would also repeat what I said a few minutes ago, which is do not outsource this. And by you taking control, it's you signaling to the organization that this is important. You will be leading this directly from the front, and that means that you expect everyone in the company to be doing this as well. And you can, again, whether it's a consultant, whether it's a new CXO that you're bringing in, doesn't matter. That this is ultimately the CEO's job. Yeah.

SPEAKER_00 40:22

You shared an example with me of a leader asking you to slow down experimentation. How common is that dynamic and how do you respond to it?

SPEAKER_01 40:31

I think it's fairly common. And I'll even say it's not entirely irrational from that person's perspective because they've got metrics to hit inside their teams, and they've got a a certain way of doing things. They have customers to manage, they have teams to motivate, and they also feel the J curve. And what what I mean by that is like any any type of transformation initiative ultimately is good in the medium to long term, but it's almost certainly short-term hard. And so you you see that J curve where things get worse. And we saw it when we rolled out agents within our SDLC. Things got worse before they got better. We saw it in those marketing examples that I gave you. There was some upfront chaos as we broke existing things and it got got better. And I think that what you have to do in these situations when this comes up is it's it's a very coachable moment where you're trying to get these leaders to understand that I need you, I need you to lean forward into this. I need you to understand that disruption is sometimes coming beneath you. So as I was talking about that emerging talent point a few minutes ago, that's often emerging organically beneath some of these leaders. And then they they're also feeling the disruption, you know, the disruption impact from me top down. And I'm telling them that you you ultimately have to embrace this, and I'm gonna I'm gonna work with you, but sort of like pumping the brakes is not is not the answer. I I need you leaning forward.

SPEAKER_00 42:08

Yeah. What do you think actually blocks transformation inside companies? And um, yeah, what do you think actually blocks transformation inside companies?

SPEAKER_01 42:18

I think it's uh I think it's two specific things. One of them is this concept of failure of imagination. And let's get specific on what that means. It's like what what makes people good at what they do is they they gain context by doing jobs over a period of like months, quarters, years. And as they get more and more time in those roles, they get pattern recognition. What's happening right now is the the transformation impact is so large that that pattern recognition is is more is actually a negative rather rather than a positive. And you can't expect that you should just get incrementally better. You actually have to be rethinking like how would I do this on a you know clean clean sheet of paper and do it as if I was starting the company tomorrow. So that's a that's a failure of a it's a failure of imagination. And like part of my job is to like lean on people to come up with like new ideas and push their thinking when I think it's incremental versus transformative. And I think the the other one is like fear on this technology is real. And it's it's always been real whenever you face transformation because people wonder, it's like where where do I fit in this new world order? And the thing that's different in the current moment is it it's happening to everyone at the same time. But it it's kind of always it's always existed, and now you can start to see the pushbacks come from people saying, Well, it's the technology is not ready, cut customers won't accept it, you know, maybe we need a few more weeks, we we need A few more months. And again, you know, my role in the organization is to push past that when I think that the consequence of failure is not that high of launching. We relaunch and we push it. And if we find out that it's it's not quite ready for prime time, we reiterate. But I'm kind of constantly listening for those types of objections that come back. And then I try and understand all right, is it is it worth giving this a little bit more time or can we push back it? But ultimately, these are essentially those those friction elements that exist in an organization that kind of rebel against transformation.

SPEAKER_00 44:39

Yeah. Let's talk about PE. It feels like the PE playbook is under pressure. Um, how should investors think about value creation today? And what were you what would you look for in diligence if you were looking at acquisition?

SPEAKER_01 44:55

So I think you know, if you if you go back to the private equity playbook, it has been powerful within this space for you know a variety of reasons. One is you could buy a software company with a solid, solid platform, good customers that had maybe seen their growth decelerate some and profitability not match that. And you could you could absolutely create value by looking for ways to optimize the business, get some incremental growth, all without necessarily facing a ton of technology risk. Everything you and I have been talking about in this conversation is largely sort of like revolving around the fact that everybody has technology risk at this moment in time. Technology risk does not necessarily lend like an easy playbook to be able to go solve it. And so as you start thinking about like what has to change around that framing, a lot of the framing now is are you buying an organization and a management team that's able to rebuild itself? And not just can they execute the plan, but are they able to be kind of disruptive at every step of the way? And that that goes through some of those tests that I was talking about of how hands-on are they? Are they able to operate at pace? Are they talking about last year's playbook with you? I think the next thing that's really important is just what is the technical depth of the team. And I'm and I'm not just referring to like a CTO or a CIO, but I'm looking across like multiple functions in the company and understanding like what is the depth that they've got, and because that's the leading indicator of just you know how much are they able to transform themselves. And I think that this next point is is a corollary to the last one, but they they are somewhat uh they are somewhat related. It's like who are the builders in the organization? Because historically, and I don't I don't mean this in a negative way, but historically PE was more about like an optimization exercise. And I think you have to be looking for who are the builders in the organization? And if the if the founder is no longer there, I think you've got to be able to point and say, here, here are our builders that have the the conviction and the pace to be able to be able to do this. They need to be like directly tied into the the the decision power of the organization to know that they to know that they've got influence. And this this is why I keep bringing it back to the CEO, especially if they are not the technical founder, has to be hands-on to be able to feel that to be able to feel that signal. And then I think the the last thing that I would talk about as a diligence item is just like where where do the customer relationships sit? As we're talking about this disruptive potential, that means that executives at at all size companies are involved in this decision making. And that means that purchase decisions are moving more and more up the organizational food chain. So you you really need to understand like where where are those buyers positioned and how is that value going to accrue to them over time?

SPEAKER_00 48:17

Yeah. You you talked about the J-curve that you saw within Rike around some initial AI investments. How should companies think about or how quickly should companies expect ROI from AI transformation?

SPEAKER_01 48:36

See, I I think that you can very quickly get it in small in small deployment. So you you can very quickly see the potential there. As you start to deploy it more at scale, you do have that pronounced J curve. And so just to give you an example of what what we saw within our our own engineering team, it was about a quarter's worth of decline that we saw on productivity. And then it actually stabilized, and it took like another quarter after that to actually see the the significant growth, the significant growth that we experienced there. And I think I think it's because there the natural phenomena that you get is some of your some of your best people are the early adopters, and they are your best people because they are all in. And they they're really efficient, they're working really hard, they've got a system that they've built and they're working around. When you ask them to disrupt, you actually take some of your most productive people for some period of time and make them worse. And so, and but no one no one else is jumping in at this point, it's just them. And so you go through this worsening phase. Then it's stable. And by the way, when that worsening phase is happening happening, you have a lot of people standing there going, told you, it wasn't gonna work. And then you get to that stabilized point. And that stabilized point still runs through your early adopters, by the way. It's just they got back to where they were, and then some. And then you start to attract people that are like, Oh, I want to be a part of that. What did you do? And that's when you start to see the proliferation of you know, of guardrails, of libraries, of MD files that start coming together and you start to accrue that. But you you do have to recognize it's it's a journey, and you do have to have the conviction that there are now enough data points out there that you are going to get a return. One thing that really stuck with me is I I I was chatting with I was chatting with Reich's founder a while back, and he he told me, He's like, look, the people, the people who get the most gains are the ones that adopted and then kept pushing through the plateaus because they get the they they started to get the compounding impact of that. And those that kind of went in, did a little bit, got something and called it a day, they're falling further and further behind. And so I that that's the message I have is like you've got to keep pushing through that compounding, even when you get to those inevitable plateaus that are there.

SPEAKER_00 51:13

Yeah, and I guess related, like what is what is playing offense look like right now and and how does that right now, not right now, uh what is playing offense uh look like right now, and how does it compare to playing defense?

SPEAKER_01 51:25

So I think I think the defense side of things is how do you protect the protect the franchise? And by that I mean how do you how do you continue to to optimize on the cost side? How do you go after how do you go after the workflows? But it's not necessarily, it's not wrong, but it's also not kind of completely changing and going after the market share gains. The way I think about offense as it relates to to my sector is I I believe that the guardrails and the governance and the ability to create that abstraction of working with the agents ultimately makes what we at RICE do even more valuable. That should enable me to gain share, but it's gonna require me to re-examine all of these pieces. It means that I'm gonna have to continue to open up like more of the platform. It means I'm gonna have to make it possible to work with both Reich as well as external agents, and it means I'm gonna have to re-re look at pricing models as this continues to evolve.

SPEAKER_00 52:28

Yeah. Um what separates companies that win and adapt versus those that don't?

SPEAKER_01 52:36

It all comes back to it all comes back to the leadership. I mean, if you're if you're thinking about this as here is this tool that we can roll out, or here is this wrapper that that we can put into the product, it's not gonna cut it. If you are thinking about this as one of these evolutionary waves that happens in technology, and you are thinking about re-architecting your your business accordingly, it's it's gonna move in that direction. But I I think the reason we we're talking about rebuilding is it it has to come from that founding instinct to be able to make it because I don't I just don't think there's gonna be anywhere to hide. The the only question is just like the time scale at which you're working with.

SPEAKER_00 53:24

Yeah. One last question. And this has been a great conversation. I really appreciate the time and the candor and the fidelity of the answers. For for people who are listening, maybe some practical advice or a CEO of a company. What should they do in the next 12 months?

SPEAKER_01 53:42

So over the next 12 months, I'll repeat that the the personal disruption is paramount. The the the subtraction piece on the corporate goals is is absolutely paramount. I think the next thing that I would I would talk about is pick somewhere specific and re and digestible as it relates to workflows and go about redesigning that that end-to-end. And I think that that process starts by being very clear-eyed about what you're doing right now and why, and taking the clean sheet of paper approach to go after that. And it's a it's a very technical endeavor, but redesign it end-to-end and fully automated so you've got a complete understanding of what it takes to be able to deliver something like this. Then you go after the the scaling, you go after the pricing moves, you go after the talent, but everything starts at that very personalized, detailed level, and then you can start to evangelize inside the company. I think I think I read you know saying somewhere it's like just start. And that that is absolutely the approach. It's like the the the worst thing that you can do is say, Oh, we'll get to that.

SPEAKER_00 54:55

It's a great place to end. Tom, really appreciate it. And I'm sure the listeners will too. Best of luck in rebuilding the company. Yep. Thank you.