127. AI Won't Replace You as a CSM (But It Does Raise the Bar) - with Dan Ennis!

Speaker A: Welcome back to, uh, the Customer Success Career Coach podcast. Today you are going to hear a conversation with Dan Ennis. Now, if you don't know who Dan Ennis is, do you live under a rock? Just kidding. But you really should know who Dan Ennis is. He is one of my favorite people in customer success. Just the smartest, kindest, most well spoken individual in all of customer success. He has spent time at Catalyst, which is pretty much all of us in CS are familiar with. He spent a lot of time@Monday.com and he now leads customer success as senior director at Workado. So tons and tons of really good, uh, CS experience, leading organizations, building organizations, you name it, he's done it. Because of where he's at right now, he is not only a key decision maker in the hiring process, but he also has a lot to say about AI because he works in the AI space. So Dan and I are going to talk about how AI has changed, what's expected of CSMs in the role, how AI should and shouldn't be used in your job search, what hiring teams actually care about when it comes to your AI skill set and what they don't care about, how to stay on top of AI for your own professional development. And we even get into like who should work in AI and who shouldn't. So this is a, uh, big conversation about AI. All of the things that you've probably read about, heard conversations about, we're addressing all of it in this one conversation and we're tackling it from every angle. So whether you're job seeking right now, you are just in a CSM role. You're trying to grow in your role, you're trying to figure out what's next. Maybe you're a CSM and you're just kind of losing sleep over AI and what it means for you and your career. No matter where you are, truly, you're going to get something or multiple things from this episode. So without further ado, let's get into the conversation with Dan. What if the only thing standing between you and your next big career milestone is just a strategy you haven't heard yet? I'm Carly Agar, customer success veteran, award winning career coach and your go to for getting hired and promoted in customer success success. Whether you're breaking into the field or ready to level up into leadership, this podcast is your shortcut to real career growth. Every episode is packed with practical takeaways, data backed strategies and zero fluff advice that actually works so you can start making moves towards your goals immediately. If you're ready to take control of your career, well, then you're in the right place. Welcome to the Customer Success Career Coach podcast. Why don't you start, uh, by just sharing what aspects of the hiring process you're personally involved in now and maybe give a little context as to what you were involved in in the past as well.

Speaker B: In prior roles, I have primarily been involved with kind of standard recruiting process as the hiring manager, interview and final round as the hiring manager in my current role, that is still a big part of my function, but I'm also a part of the formal actual headcount planning, designing the roles a little bit more in depth as well as as a skip level in a number of interviews and still the final round in quite a few CSM interviews across the board. So very involved in the hiring and recruiting process right now in my current role at most levels, helping both design the actual interview process, running the interviews as the skip level at one point in the process, and then part of the panel for the final round and the headcount planning overall.

Speaker A: So it's safe to say that you know a lot about the hiring process from the other side.

Speaker B: I have had to learn and know a lot. Yes. That is absolutely an accurate thing to say.

Speaker A: Okay, so it's no surprise. The customer success job market, it's very crowded. It's just continued to get more and more crowded over the last couple of years. Everyone kind of knows this and it's very obvious what that does for job seekers, the challenges it creates in terms of standing out, getting noticed, all these things. But I want to hear from you what has become more difficult on the hiring side of things, just given the sheer volume of people that are seeking customer success jobs right now.

Speaker B: I would say there's two things that are directly correlated. The first is just the sheer diversity and variety of what can go into any given CSM role. And so what that means as a hiring manager is our specific needs for a, uh, CSM like any Org. While they're broadly applicable to folks with CSM background, there are also some fairly specific aspects of what we are looking for that makes a CSM uniquely qualified and particularly beneficial for, for the roles on our team. That is not unique to us. But the challenge has been, especially when it comes to a resume pipeline, is identifying that from resumes. Because a lot of csm, um, resumes and backgrounds, given the diversity of what can go into roles, can look very similar for very different roles, some of which are a very strong fit for what we're looking for and we want to prioritize others, not so much not on a candidate, but it just makes for a different experience than what we're looking for somebody with the background in. So that's a challenge on the pipeline side and that's led to the second piece, which is therefore because we can't take for granted what someone's background means. When I look at what a CSM role is, that second piece is there's been a much bigger need to actually see skills in play in the process. Not just talk about them, not just highlight them. I know folks don't love take home assignments, but this is a big part of why they've become so crucial and a part of the hiring process is there's just a incredibly high need to see the skills in practice because we can't tell from just a resume if somebody's actually got the background and skills to have done what is most needed for the role.

Speaker A: So what you're saying is a, uh, CSM is not always a CSM. 1Cs background with 5 years of enterprise experience is not equal to someone else's CS experience of five years in enterprise. They're all different flavors, if you will.

Speaker B: Absolutely. Let me give a really concrete example on that. A CSM who has worked for a highly technical product but has maybe had a very large technical supporting team and their role is primarily focused on strategy guidance and commercials even in the enterprise space is radically different than a CSM who maybe worked at a slightly less technical product but had a significantly smaller supporting structure around them and therefore had to be more technical in the process and more hands on with the tactics of their customers. Both are Enterprise CSMs. Both are responsible for delivering successful outcomes. Neither is better or worse than the other, but one has a skill set that might be more closely attuned to what we are needing at any given time.

Speaker A: That's a perfect example. Can you tell us a bit about your internal processes for hiring? Specifically, are you using AI at all?

Speaker B: I would say the biggest thing we're not necessarily using AI to filter out candidates. I can say that pretty directly. I don't know if many orgs are given the volume. There has to be some sort of filtering to help understand and prioritize. Some yes, absolutely. But nobody has filtered out the because of that. But a volume issue, there is just a volume game at play. That truly does mean that there are some that need to be surfaced there, but nobody is qualified out because of that. From our end, the biggest thing that AI has done and I've talked About this with other leaders is it's truly raised the bar. That's the best way I can put it. And I know sometimes candidates don't love hearing that, but it's the reality. The most capabilities that AI has allowed candidates to do and the way it has raised the bar on the kind of prep they can do candidly in even less time than before with even more tailored results, has played out in my bar going up has played out in somebody can actually find through AI tools a really accurate way to describe the way they could be a csm, um, with our product, the way that our product interacts with our customers, business outcomes and things like that. So it's less something that we are formally using and evaluating and more almost where it has become the table stakes, where if I have to tell somebody to use AI in the process, we're probably already at a different mismatch in value in how we approach the role. Because when we talk about the skills that we want to see CSMs display in our interview process and in their roles here at our company, at, uh, Workato, Absolutely. Using and deploying AI is a core piece of that. But ideally it's because they know that that's the tool in their arsenal that they should use. And it's very similar with the hiring process. It's less about telling someone, hey, you need to use AI in the hiring process and more. Here's an assignment, for example, or here's who you're going to be speaking with and the assumption along the way that somebody who's aware of all the tools available to them will then take advantage of those.

Speaker A: Okay, so can you give some concrete examples? I loved your example earlier about 1 CSM is not equal to another CSM when you're looking at a resume. Now, I want to hear some examples about where AI has raised the bar. Specifically, when you're assessing candidates, the two

Speaker B: biggest areas I see it most play out in is, number one, the questions that a candidate asks and second in their final assignments. So I'll give the examples on both.

Speaker A: Okay.

Speaker B: In the questions that a candidate asks, there are certain questions that kind of historically have always been the go to questions to ask about a role in an interview process. And those are still helpful, but they can feel generic and show that somebody hasn't done the research. And the reason I talk about questions in particular is it's the one part of the interview that the ball is completely in the candidate's court to take whatever direction they want to in. Obviously, a really good candidate can pivot their answers to a question I ask into whatever direction they want to go. But the questions, the ball is completely in the candidate's court. An example of not using AI would be somebody who asks me kind of general questions about the CSM role at workado or asks questions just generally about our customer base or even like somebody who's done a step further the research a little bit, but isn't necessarily using AI. I've had folks say, oh, I see you post About X on LinkedIn. What's something that you think about that that's better? It's a little more tailored. But when I think of somebody who's using AI, I think of it as things like, hey, I was researching workato and I imagine that, uh, when I saw that customers can use it to do X, this would probably be a challenge. How is your CSM team tackling that today? That's a question that gets me excited and I'm leaning in suddenly and I'm brainstorming with them in the moment. And that shows somebody who's already done candidly, it's not like they have to do in depth research to get there. So that's something that they can do that on. Um, the question side shows me that this is somebody who knows how to efficiently leverage AI in a way that will make them effective with customers. And that's why I care about it, because I want them to be able to apply that same skill not on me as the interviewer. I don't care about it for that reason. I care because I want our CSMs to be able to do that and point that at a customer to ask them a question about their business that gets them to lean in and sit up. Uh, the way that that question gets me to lean in and sit up.

Speaker A: I love how you just pointed out the behavior of a candidate in an interview, giving you a really good and real glimpse as to what they're going to be like when they're interacting with customers. I can't tell you how often we're emphasizing that. It's as simple as if you don't ask good questions in an interview, the hiring manager is thinking you're not going to ask our customers good questions. So I'm glad that you just called that out from your perspective 100%.

Speaker B: And that's kind of what I was getting at at the beginning. The market right now has led to me needing to see the skills in practice.

Speaker A: Mhm.

Speaker B: That's an example. I don't need to just hear them tell stories of how they've done good discovery. I need to see them do good discovery on me. That's leveraged by A.I. uh, which actually speaks to the assignment round where good candidates, where I've seen AI play out here is two things. One, it's really proven that with our assignment round, the best candidates who've nailed the final round ironically don't spend nearly as much time as the candidates that don't nail that round. And it's because they know how to leverage AI and they have a clear strategy and perspective. Our final round, for example, is an account strategy, right? It's not a mock ebr. It's not any of that. It's presenting an account strategy. So they have a clear perspective as a CSM on what a strategy could look like and how to make that apply to workato. And I can tell that they've finesse the thoughts with an AI, uh, kind of thought partner, so to speak, asked it to challenge from the perspective of Workado. And they've used it to put their brain power to work for the majority work and let AI take care of the brute force of getting a deck together. Because we're not measuring on the quality of the graphics in their deck. Right. That's one example on the positive side versus on the negative side where I've seen really well constructed slides that look really good, but uh, could be for any customer at any company. And that is a red flag to me because we hope to see it be something that is specific to us. They don't need to know every inside baseball thing about the org, but specific to us in our value prop and specific to the name the customer we put in the account strategy plan. And so that's something that we do there. And I do think that that shows a really big emphasis on, uh, how we expect to see that play out.

Speaker A: That's super helpful. Something I'm taking away from this is if anything you're doing as a candidate can be copied and pasted and used for some other company's process, albeit a question in an interview or a, uh, final round presentation, then you have not leveraged AI enough to personalize it to the company and the role you're interviewing for.

Speaker B: Spot on. And I think that that's what I mean when I say the bar has gone up. Whereas pre AI days, frankly, I think that might be like only the most exceptional of exceptional of exceptional who are highly committed to one particular role might be able to get to that level. Whereas now the proliferation of these tools available when you know what you're Doing makes that really simple. One of my favorite candidates we ended up hiring, one of my favorite things, had one of the best final rounds I've ever seen. Really powerful, compelling stuff, very specific to us. Out of curiosity, I asked them later on after you hired them, how long they spent on it. My hunch said not long, and they said an hour. And then maybe an extra 20 minutes after I had the prep call to confirm my direction, and they nailed it. So it's not about candidates. You need to go spend all this extra time because they were able to leverage the tools the right way.

Speaker A: So I think what you're saying is probably going to be both a, uh, relief and maybe an added stressor for candidates. But it's good to hear the truth, because what you're saying is, on the one hand, as a hiring manager, I embrace candidates using AI. In fact, I want and expect you to use AI so don't be afraid to use it as sort of a shortcut. But on the other hand, because you have this shortcut and because you have these tools now, the bar is higher. So you better be personalizing and tailoring to our company and the specific role.

Speaker B: It's 100% those both things. Intention, on the one hand, that's easier than ever to do, but it also means it's no longer a nice to have.

Speaker A: Yep. So we've talked a lot about positive experiences of AI on the hiring side of things. I'm curious if you can think of any negative uses of AI meaning things that you see candidates doing where they're leveraging AI and it has an overall poor reflection on them as a candidate.

Speaker B: That, uh, final round's a good one.

Speaker A: If it's just super generic.

Speaker B: E is having the clear strategy and perspective. And what I mean is the AI is going to help you make it workato specific. The AI is going to help you tailor it to the customer that we've identified. Mock customer. We use all of those things. Right. But what AI will not do is give you a strategy. And when somebody uses it for that, I can tell because it's transparently very generic, very wordy, very clearly not somebody's immediate thought. And one of the ways it stands out, because part of our process is it's an interactive kind of final round. Right. They're sharing the strategy. We're asking questions as they go, pushing back as they go. I can almost always tell when it was AI, not just because of the way it, quote unquote looks in the process, but because of the lack of clarity behind it. When I press for more detail, when I'm confused on something, when I say, hey, I don't know why that that resonates necessarily. Can you almost maybe defend that point a little? And there's almost no ability to do so. That doesn't tell me that they're quote, unquote, necessarily bad tsm. Um, but it tells me that they didn't put that thought in. That that thought was from the AI. Right. That wasn't it. Positioning their strategy. That was strategy came from the tool they were using.

Speaker A: Yeah.

Speaker B: They don't know how to defend that. And that immediately is a red flag to me because again, use it to accelerate, use it to make this quicker, use it to tailor it to us, but don't use something that's not really your strategy, that stands out and becomes immediately apparent as a hiring manager when I ask and I get a. Well, I'm not sure. Or immediately waffling to, well, it doesn't have to be that way. It could be a different way. What do you think? And that, like, might sound reasonable, but what it actually tells me is a lack of conviction in their strategy.

Speaker A: Yeah. So what you're saying is when you're interviewing for a CSM role, you're selling your CS chops. So I don't really care how you get this deck done. That's not what I'm evaluating on. But if you lean on, um, AI to create the CS strategy, that's a problem. Because I need it coming directly from your brain.

Speaker B: Exactly. Exactly. Because if we're just using. And this is going to maybe sound overly blunt, but if I'm just going to get the AI strategy anyways, I could do that without hiring a person.

Speaker A: Yeah, I think that's something that people need to hear.

Speaker B: Sounds maybe overly candid, but I think it's just. It's the reality. I want somebody whose strategy is going to take a tool and get a better outcome, not just what I could have gotten from the tool on my own or someone else could have.

Speaker A: I think that's very well said. I want to shift gears a little bit. So we've talked a lot about AI during the job search, and certainly these two themes will overlap, but I kind of want to shift to AI fluency as a csm. So now almost stepping out of your hiring manager role and stepping more into just your CS leader role. I'm curious, how has AI changed what you and what the managers on your team expect from CSMs in your organization compared to even a couple months or a year ago?

Speaker B: Funny. Enough similar to candidates, it's the bar has gone up. And I've even said that to the team very directly in a way of bringing folks along for the change management of it all has been, hey, uh, if you're feeling like the bar has raised a bit, two things I want you to hear on in no uncertain terms. Number one, you're not crazy, you aren't imagining it, so that should be encouraging. The second bit is you're not crazy, you're not imagining it. But I mention that to say, here's what I mean when I say it's raised the expectation. It's not enough for a CSM to now generally talk about, hey, challenges that I think a customer has sort of talked about on calls before. A great example of where AI has raised the bar for it is I have a CSM on my team, for example, who had a customer who's facing a particularly acute challenge and they put together a one pager that I know they obviously had to leverage AI to put together that was very clearly outlining the story from the customer's perspective, where their pain was with quotes from relevant dates from relevant gong calls over a period of time on why this mattered, what it was meaning to their business, all these very specific things and what they've tried, which candidly would have been near impossible for a CSM to do before without spending an inordinate amount of time with the tools. They were able to pull that in, but they also couldn't just generically put in give me the answer to this thing because it wouldn't have known what to pull. There's too much context. Right? So the CSM has to know the strategy, what's going to be a compelling story to the exec readout for this audience. And they're going to put together an escalation plan that is clear with an ask. That's something that they would not have been able to do in that level of compelling way before. And then the other is the expectation truly is more about direction on AI than their current state on AI. And what I mean by that is I don't expect everybody to be on the team at the same level of how they use it, where they're at with it and their fluency. I do expect everybody to be on the trajectory of growing in it. And that's a big key thing for me has been this has been a tooling that also has allowed more creativity than ever to shine through for the teams because of the way that these tools work. So that's really where it's gone on an internal expectation perspective. And again similar to with candidates. I can tell when somebody's using AI in an almost kind of performative way to show something that is neat. But I don't see where the value is coming from versus just be more effective at the job. Mhm.

Speaker A: Can you talk a little bit about that growth trajectory regarding AI and specifically how someone can prove that to you or another leader on your team? Because what I'm thinking about is that's not different from any other skill that a leader wants you to improve in. Right. Like if you struggle with driving expansion in your accounts, there's very clear things that you need to do to get better at expansion. And I would argue there's very tangible results that you could speak to to say hey look, I worked on this skill and I got better at it. But I'm curious, what does that look like when it comes to AI? How do you know that someone is growing in that skill?

Speaker B: Number one would be. And this is, that's not a hard metric to your point. Right. And I want to own fully that there, there's that component. But one way that we do is we do a kind of a quarterly measure for CSMs to submit what's one way they've used AI to be more effective? And it's just submitting. It's totally like it's not. You have to show the thing. It's not all that. So that's one way we're just helping folks show what's something you used it for this quarter to help you get more effective at what you're doing. And again it's not what did you automate what's this neat thing you did. But it's how did it make you more effective? And that's an intentionally open ended enough that somebody if they're growing will be able to find ways they're doing that. But the second on the journey. And this is something that I love about the frontline managers that are on my team because they work closely with their CSMs on this. It's really the, the tone of the direction as a CSM is using AI in their role because a manager will often then have the opportunity to coach them on um, opportunities to have better used AI in the process. Easy example would be a CSM coming with an account that they're struggling with. And it's clear they haven't done maybe that first step of maybe bouncing it off Claude as their thought partner as they're trying to think of some strategies. Right. Not come up with the strategy, but like there's ways to use it to help refine your thought. And a manager can sometimes pretty easily tell when somebody hasn't done that first step. I'm not a believer in don't bring me problems, bring me solutions. I don't like that as a management mantra, but I do believe in bring me a clear problem. Oftentimes managers will be coaching their teams on how they can better be using AI to actually come up with really clear problem statements. And like a lot of things in the CSM role, the proof is in the pudding. Do they do it? Do they action on that? Are we giving the same feedback? Is it never improving? And so that's a lot of how that plays out. I'm not a fan of just looking at raw usage because I think a that what you measure is what you incentivize and doing that can lead to, I mean, silly stories like what came out of Amazon not long ago with people token maxing on a useless use case just to hit some arbitrary metric. So we don't take that approach. But that's why it's the ethos along the way and why we say that growth mindset is not an optional nice to have in our position.

Speaker A: Mhm. I would assume that a lot of what you're saying would actually be a relief for most DSMs. Because what I'm taking from it is I want you to embrace AI, but by no means do I expect that by next quarter you're building 20 agents and it's running our CS department. You're simply just saying almost like we would mature an account. I can't uh, remove the CS from my brain. But you want your end users to mature in their use cases over time to get more value out of the product over time. And um, it sounds like that's what you're saying. Your expectation is absolutely right. Okay, now I want to ask you a question. Because Workato does have AI products, you're in a unique position where yes, you might be looking at how candidates use AI during the job search, during interviews. You're also keeping in mind how they use AI in the day to day of their role. But what about how they are fluent in AI as it comes to like managing their accounts? You and I had a conversation about change management around AI products and how that's particularly complex. Can you talk a little bit about that?

Speaker B: The way that I look at that is it's both the way that they use AI and the way they guide their customers on the use of AI. And so those are two related but distinct things. And so I'll talk about the second part first. Guiding their customers and then how that comes into how they use AI because it's actually working backwards from the desired outcome. Because I don't believe, and I don't think this is a controversial thing to say. I don't believe that the value is using AI for using AI's sake. It's using it to better effectively achieve an end.

Speaker A: Yes, that's very CS of you.

Speaker B: I mean, you know, it's uh, I'm in the, I'm in the space I'm in for a reason, Carly, you know, on that end though. So the outcome for us with Workato is guiding customers on AI adoption journeys. Customers are getting a thousand things from a thousand different directions on how should I be using AI? Everything from token maxing to knowledge retrieval to real meaningful change in their business accomplished because of it. Achieving real things. And all of that is the messaging they're hearing. And customers, especially in, in our space, some are facing a, uh, pressure, two things at once and they don't know how to navigate it on their own, which is where the CSM really comes in, which is a high pressure to be using it a lot and to be achieving big things. And so there's this velocity and these things kind of end up competing with each other because they're just using a lot and using fast to try to do that mandate, but not necessarily effectively. And so they might slow down and it results in just a lot of maybe m potential friction as customers are thinking through how do we use this to achieve real meaningful business change and outcomes and how do we really think about what we're launching from an AI perspective? I think one of the interesting things for companies that are rolling out AI tools and I don't get to. I'm not going to take credit for this observation. This was somebody on my team who commented this. Many folks internally are now having to act at their businesses as internal product managers for AI tools. They're launching in a way they've never had to think about it before. Uh, they've maybe launched a tool and it's just an out of the box thing that works a certain way. It's deterministic. They don't have to think like a product manager at all. But the benefit of AI tooling that they're rolling out internally is that it can be customized, they can tailor it, they can tweak it, they can tune it over time, which is incredible. But suddenly that means the pressure is on them to act as a product manager for their own orgs. And so that's something that is a, uh, change management process that our team walks customers through all the time. So that's just one of the bread and butter of what the team does. So that's one piece to it. Getting to how AI enables that, what a customer's specific challenges are, and where they're going to most effectively leverage our tools. And our AI tech stack is going to be different depending on their business, where they're at in their maturity. And a, uh, CSM can spend a lot of time doing natural discovery to try to figure this out and grill the customer, or they can use the AI tooling that's available to pull together a really good strong hypothesis out the gate. They still need to validate, they still need to do more discovery over time with the customer. But odds are between what's publicly available and things that have already been talked about. If a CSM has really been doing their job already, there's enough context to form a really strong hypothesis to come in and validate with a customer that suddenly whether it's fully right and they say, yes, that's me, that's what I need. How do we do it? Or oh, that's mostly me, but here's where I think it's actually wrong for our business. Both of those are successful customer conversation points that AI really enables them to do instead of starting from a blank slate.

Speaker A: It's almost as if. And the reason I wanted to ask you these questions is I think it's important for folks who feel a lot of pressure around AI, or even those folks who are just excited about it and want to eventually work for a company that sells AI products. As with any role that looks exciting and sounds like it's, you know, the best thing in CS right now. I think it's important that folks understand the reality of it. And if the reality makes them more excited, great. But if it points them away from something that maybe isn't what's going to mesh with their skillset, then I think that's also just as productive. I'm almost hearing from you that when you sell AI products, almost everything you're doing as a CSM becomes more difficult in some ways. Because I, uh, liked how you described this dual pressure to like, roll things out quickly, but also to achieve these really, really big results. That's just not always the case when it comes to rolling out a SaaS product. Like if we were rolling out a CRM, um, yeah, of course there's pressure to get it done fast and to have results, but it's not quite at the velocity or the widespreadness of something like AI, is that fair to say?

Speaker B: Yes. And I would say the onus in one case is more on the vendor than the individual. The pressure that customers are facing internally, like if a customer makes a bad investment on the CRM or whatever SaaS category they're doing, typically, unless it was an overly large gamble. Right. That they were taking, they're not worried about their job for the outcome. That's not the case with AI. They're being kind of told, hey, you need to accomplish this, and that's something that's a now core mandate for you. So the pressure they feel has gone up.

Speaker A: So interesting. And when you couple that pressure with the fact that these people who are the project managers or the main point of contact, the champions, whatever you want to call them, with their roles fundamentally shifting at the same time, I imagine just even managing relationships with these people becomes more complex.

Speaker B: Absolutely. And that's one of those things where we have joked before, and I think a lot of folks in the AI space have gone through this, where customers on the one hand are more invested than ever in your product, which is an incredible feeling as a csm. Right. Every CSM has their horror stories in the past of clawing for every little bit of engagement. That's not the challenge anymore. Customers are highly interested, but they are now. Rather than in the past where they were picking a vendor for a category and doing it. The nature of AI tools and the pressure that they feel for outcomes and the way that AI tools can both complement each other and compete with each other. Customers are now at a point where oftentimes they're evaluating every tool for every use case. They'll have multiple in their tech stack. And then they're not just picking a tool, they're evaluating each tool for each use case to see which is best. Which is suddenly causing like you're having to lead through that as a CSM for every use case. Right. It's not like great, it purchased, uh, classic old, you know, kind of work. Auto example purchased us for integration and automation. We know that that's what they're using for integration and automation. Great. We're good there. Obviously we need to fight for value. Obviously we need to continue to expand to do all those things. But there's often not like competing with another platform that does the exact same thing until like an unseating kind of play. AI. That's not the case. They'll have us and a number of other tools that they're trying to use at the same time that they're comparing for every use case along the way. So CSMs have to be able to guide customers through that and how they think about it.

Speaker A: Yeah. So kind of going back to something we talked about at the very top of the episode, which was not every CSM role is created equally when we're looking backwards. I would say the same thing is true when we're looking forwards. Like not every CSM role at uh, a startup or not every CSM role at an enterprise is the same. We all know this. It's highly dependent on the team and the culture and the industry and the customers and this and that. What would you say given everything you just shared about how AI really like changes the CSM's role? Like who would not thrive or enjoy a CSM role where they are selling or implementing AI products?

Speaker B: Somebody who needs a really overly clear defined playbook and where they're going and something really mature. Because here's the spoiler, like no matter how well developed different products in this space are right now the whole market is in its infancy and booming and growing quick. Nobody has fully figured this out. Everybody who joins this space is joining some form of a startup, no matter how big or small the company is. One of my favorite definitions of a startup that I heard this is from a talk given at Google of all places back in 2010 that is extremely applicable and I think is where most AI companies are today. And that quote was that a startup has nothing to do with company stage and size. A startup is a human institution that's designed to deliver a new product or service under conditions of extreme uncertainty. And that is where every AI company is right now. So a CSM who needs the stability of like a well rounded place that's delivering on a really established motion will likely not thrive at a, at a role like this and won't enjoy to be clear. And that's why one of the things that's also stood out from a hiring profile perspective. It's funny, I think there used to be this, this kind of mentality of you would go from small startup to big company and then, okay, big company logos were what was most appealing in a background. Candidly, we're in a place now where startup background and experience is more valued than it's ever been for csms because it shows that they know how to adapt, they know how to work in a ambiguous environment, they know how to roll with an evolving company and product which every AI, uh, company and product is right now.

Speaker A: I'm glad you pointed that out, because I do think that it's been ingrained in all of us forever, that when someone is looking at your resume, they're looking at the companies you worked at. And if they don't recognize any of them, then they're certainly not picking you. But that might be the case for some hiring teams based on their needs. But especially for folks who are excited about AI and feel like, I want to work for the top AI companies, they might not care that you've been at big logos. They want. They need people who are, like you said, used to environments where there's a lot of ambiguity, there's a lot of question marks, there's a lot of creativity, we'll call it. But that startup experience is more and more valuable if you want to work in the AI space, is what you're saying.

Speaker B: Exactly. That's exactly right.

Speaker A: I'm, um, feeling like the theme of this conversation, and we certainly did not come into this with a theme in mind, but what I'm getting from it is AI is equally good and equally challenging from the candidate side. We talked about how it can make prepping for interviews so much easier, so much faster, so much more effective. But it's also raised the bar. Same thing with being a CSM in the AI space. It can be incredibly exciting and complex, and your customers want to talk to you, and they're so excited and engaged. But there's also this complexity to it. So it really is a balance of, I don't want to say good and bad, because nothing is, you know, good or bad. It's just.

Speaker B: And that's why I've described it to folks as. It's the tension. It's not like a balance, because I think a balance, we. It's funny balance. I think we. We all hear and we think equilibrium. We think this, like, Zen state that we get to. And that's not the. And I found it true is tension is the word I've come to. Right. It's this tension that, uh, on the one hand, I can be more effective than I've ever been before. And that's incredible. The other end of that tension that is pulling just as hard in the opposite direction is I now have to be better than I ever have before. And so that's true for me as a leader for the csms on my org and for candidates in the hiring process.

Speaker A: I really like that tension. I think that's a great way to sum up everything we talked about is like you might be feeling pulled to use AI, you might be feeling pulled to not use AI, but at the end of the day it doesn't really matter because once you start using it there's going to be a new tension. So I think that's a really nice way to kind of sum it all up.

Speaker B: And the one thing I would say as an encouraging bit there, and it's funny because you, you alluded to it earlier in the conversation when you said started something with a very CSM answer. The best CSMs are primed to thrive in this environment because they have always, if they've been worth their salt as a CSM over the years, have always been operating from a perspective of it's outcomes first.

Speaker A: Mhm.

Speaker B: The outcomes that matter. And I think that a CSM that is truly internalized that not just when it comes to how they talk to a customer, but how they approach their job is the best person who is most primed to use AI because it will stop them from doing the thing where they use AI to actually get a worse outcome than the like old way they used to do. It will also stop them from just doing things the old way and getting the same if not worse outcomes than their peers now because their peers are using other tools. And so having that bias towards what's going to allow this to be the best possible outcome is what will serve folks in this time.

Speaker A: You know, I was going to ask as a last question, what's one last piece of advice that you have? But uh, I think that the perfect piece of advice is just. Yeah, a lot of what we're talking about might seem overwhelming and complex and confusing and it's always changing. And how do we know what hiring managers want to see? And at the end of the day, focus on outcomes. That's what your brain has been trained to do in all your time in cs. Just keep doing that and everything else will fall into place.

Speaker B: And the only other thing that I would add as a final piece of advice on top of that would be, and this is the most cliche part, but it is so true, is just get your hands dirty.

Speaker A: Mhm.

Speaker B: It will feel hard until you start doing it. And it's like any new muscle, it will feel stretching at first when you go to the gym and you start working out this new AI muscle that you haven't worked out before. But as you use it over time, suddenly that gets stronger and it is no longer as uncomfortable. And so truly it is one of those areas where I always tell folks Just get your hands dirty with it, because the only way out is through. And it will feel uncomfortable and awkward until you start doing it, until you start using it. And once you do, you're able to push past that.

Speaker A: That's a great piece of advice, because I think for a lot of people who are hesitant to use AI right now, it's almost the perfectionism that gets in the way. Like, how can I. How can I catch up? I'm already so far behind, and things are always changing. And you're kind of reminding folks, like, you're never gonna be perfect. Just get your hands dirty, just get in there, and eventually you will get to where you need to go. But if you continue to just wait and be hesitant, then you're never gonna make progress.

Speaker B: And that's why what I said about my team is just as true for candidates, which is it's the direction, not the starting point, that matters.

Speaker A: Yep.

Speaker B: You will not be as fluent day one as the person who's been doing this for a year at, uh, an AI native startup. And that's by design. That's part of the process. But directionally, if you're growing in it, you'll be able to hold your own.

Speaker A: This has been so insightful. I know that I learned a lot, and truthfully, I try to make every episode relevant to anyone and everyone in customer success, and I know that that's impossible, but I think this might be the episode where we finally nailed that. I think anyone listening to this, no matter what position they're in, what their goals are, how long they've been in cs, what their strengths or weaknesses are, I think I can confidently say that everyone listening to this is going to get something valuable out of it, if not many valuable things out of it. So, again, I can't thank you enough for coming on and, uh, just sharing so much and being such an open book.

Speaker B: Always a pleasure to chat, Carly.

Speaker A: Okay, so here is what I am hoping you walk away from this podcast episode with with Dan said many things that really stuck with me, but one that really stands out is this overall theme that AI is not necessarily good or bad for your career. It is, however, going to create tension. It's, on the one hand, going to make you more effective than you ever have been. It's going to make you more efficient than you ever have been. And where that tension comes into play is, at the exact same time, it's also raising the bar in terms of expectations. So it's making you better. It's also raising expectations for you to be better. So what I took away from this conversation is we shouldn't fear AI without also celebrating it. And we shouldn't celebrate it without also being realistic about how it is changing our role. So I think it's okay to fall on either end of the spectrum, but I think at the end of the day, like, AI is neutral. It's both good and it's bad. I also think a really great takeaway is the only way through all of this change, all of these changes in expectations, in the way we operate, all of this overwhelm that comes with AI is just keep doing the same thing you've been doing this whole time that you've been in cs. Focus on your outcomes. AI is not going to ever get rid of that. It's not going to replace it. The people who are quote unquote winning with AI right now are the ones who are laser focused on delivering outcomes, whether that be outcomes for their companies in terms of their performance or outcomes for their customers. And they're using AI to help them, um, get more outcomes or get to outcomes faster. As long as you remain outcome focused, you will be fine. And then lastly, I would say stop waiting to feel fully ready to embrace AI. It's time now. If you haven't yet, you've got to get your hands dirty. And just by getting your hands a little bit dirty, like you're doing enough. So don't feel like you have to be an expert and do everything tomorrow. You don't. You just have to start. Last note I'll lead you on is if you are job searching right now and you're feeling this tension like the bar keeps moving and you can't keep up with what hiring teams actually want. That's what my team is here for. This is what we do all day, every day. At this point, We've helped over 1200 customer success professionals from entry level to director level land roles. On average, they're securing offers within 2.9 months. So just about 90 days. If you want our help, shoot me a DM on LinkedIn or you can always apply@cearlyagar.com apply. We always put the application in the show notes. Huge thanks to Dan for coming on. I hope you all enjoyed this conversation as much as I did and I'll catch you in the next one.