Enablement Is Predictive or It's Waste

Machine-generated transcript from the episode video. Speaker labels are not included and some names and product terms may be transcribed phonetically.

[0:00] I've learned that the best founders are always selling. Welcome to the GTM Vault podcast hosted by Rick Kleta. We uncover the strategies, the pivots, and the breakthroughs turning startups into giants. Let's crack open the vault and find out how. Today on GTM Vault, I'm joined by Christina Brady, CEO and co-founder of Luster, a groundbreaking platform redefining how go to market teams learn, practice, and perform. With over 18 years in SAS sales and 13 years in executive leadership, Christina has built a reputation as one of the most creative and people first operators in B2B tech. From leading high growth sales orgs at Groupon, Glass Door and Speckit to serving as chief strategy officer and president at sales assembly. She spent her career helping revenue teams scale better, faster, and smarter. At Luster, she's pioneering a new category called predictive enablement, a skill proficiency mapping engine that uses AI to diagnose where reps are likely to

[1:10] make revenue impacting mistakes before they happen. and prescribes tailored coaching to prevent them. In this episode, we explore how Christina is transforming enablement from reactive to proactive, what predictive enablement means for the next generation of GTM teams, and how creativity, improv, and empathy make AIdriven leadership more human. Christina, you spent nearly two decades building and leading revenue teams. what inspired you to start Luster and how did that idea evolve from your time at sales assembly and speck it? Yeah. Um, thank you so much for having me. And I I love this question because I think like so many things, my inspiration came from needing to solve a problem that I had as a sales rep, as a sales leader, as a trainer, as an executive, as an operator, and then also wanting to take advantage of this massive opportunity to shift the way that go to market teams produce revenue. Right? Right. And so the problem that I felt no matter what seat I sat in in go to market and as you just went through so kindly I've sat in a lot of them. There's this one really really consistent problem that I felt

[2:21] that there was no tool or service or person to solve. And it's this idea that we make our customers collateral damage to our inability to be able to predict when a skill deficiency is about to erode revenue until it's too late. Right? We get on a call with a customer, we make mistakes that should be avoidable. It erodess our revenue and then we reactively try to figure out why did we make that mistake? How can we avoid making it again? And it just sends the entire go to market team into this tail spin. And so that reactive nature but also the missing data layer of what is the actual proficiency and readiness of my team to do their job. Those gaps drove me absolutely nuts. And I searched for years for a tool or a service or a person, a miracle that would actually help to solve for that. And one didn't exist. And so I sort of stumbled into this idea through piecing together the gaps that led to a lack of performance across the people that I've coached, the people I've trained, and all of the companies that I've also overseen.

[3:18] What problem did you see in traditional in what Let me repeat that. Sorry, this is going to be edited, by the way. So feel free to if you Yeah. What problem did you see in traditional enablement that made you believe predictive was the missing layer? Yeah. Yeah, I mean it's going the opposite of predictive and proactive and the reactive nature of it. So traditional enablement one, you have a few select group of brilliant individuals that are trying to serve a very very large crowd in multiple different roles and what they have to do is basically find the lowest hanging fruit or the common denominator. Where are the majority of people right now struggling? Um and can we deploy a solution or a training to help as many people as possible? And so it winds up falling into this one-sizefits-all type of training. And so you feel like we're consistently training our team. We take the whole team off the floor. We do a big training. Everyone does a knowledge check and then they go and they do their job and then revenue impacting mistakes and revenue erosion continues to happen and we're confused as to why. And so then we say more training, more enablement and it still doesn't solve the problem. And so traditional enablement is doing that, right? They're trying to look at what is the common denominator. Where do the most people need assistance? And then the other problem with that is the way that they

[4:30] uncover who actually needs help is by simply asking people, right? They go and they ask people, "What do you think are the deficiencies in your team? What do you think are your deficiencies?" Um, and that's also inherently ineffective is asking people to self-identify their own diagnosis as an artist and former improv performer. Now, how has creativity shaped the way you build and lead in the SAS world? Creativity is everything especially when you are building a company in a brand new category. Creativity is the problems that we are solving are not new. We are not solving brand new problems. I actually don't think that anybody is solving brand new problems but we're solving them in very very different ways. And that is the root and the crux of overall creativity right like we have things that we have to solve that we've had to solve for ages but can we do those in a very very new and very very different way. And so creativity comes into play when we say hey this age-old problem that hasn't been solved properly we're trying to solve that how do we think outside the box not just with the solution that we provide but even as we're going and iterating and building creativity is a huge part of what we are doing and trying to say let's not say no to that idea let's let's exist for a moment as

[5:39] if we are going to build every single thing that we think of how would we do that who would use it what does it look like in living almost in this world of kind of yes and which I learned learned from my years in improv. What was the early founder journey like going from an idea to a funded category defining product? Uh it was wild. It has been um a wild journey. I I will say that I'm having the absolute time of my life. I get the opportunity to not only build a legendary product that is going to fundamentally change go to market as we know, but I also get to build a company that in in my opinion is doing things as close to the right way. And I say that with parenthesis as possible because there's a lot of different ways to cut a pie, but but in this case, I want to build a company that takes care of people. I want to build a company with an amazing culture. I want to build a company where people feel like they can learn and they can grow. And I want to correct a lot of also the ills of my past that I've experienced at previous organizations. And so I would say the founder journey has been brilliant. It's been terrifying. It's been stepping into the unknown. Overarchingly over all of that though, it's absolutely been incredible. And I certainly am not doing this alone. Without my incredible team

[6:48] that I have with me, there's no way that I would have been able to do all of this. And so my biggest thing is the founder journey. They say that it's it's solo and it's lonely. But if you surround yourself with brilliant people, it doesn't have to be. You said to practice without a diagnosis is revenue malpractice. What does that mean on practical GTM teams? Yeah, that's right. So you think of this idea of what is medical malpractice, right? medical malpractice would be if I walked into your office as a doctor and the doctor said, "What do you think your diagnosis is?" And you said, "Well, I'm guessing that it's XYZ." And the doctor said, "Okay, what I'm going to do is I'm going to ask every patient that I have today what they think their diagnosis is." And then based on the most popular answer, we'll just treat all of you as if you have that. Right? That would be absolute medical malpractice. But that's the way that go to market teams actually ask their team and do proficiency mapping exercises. They ask them what they think their deficiencies are. They take previous conversations and they subjectively listen to those to try and identify without any data what they think. Again, all subjective is actually wrong. And then they treat the entire team. Now, I've trained over 30,000 revenue professionals in my entire career. I have yet to find one that is like, I'm actually very aware of the uh proficiency gaps that I have and exactly what I have to do to go and uplevel myself to the peak of performance.

[8:04] Right? So asking somebody what they think their deficiencies are and then putting together an entire training plan around that. The same way the medical malpractice is to diagnose without any kind of testing or prognosis. That's the same way revenue malpractice is to train an entire team without any accurate layer of data to really understand the objective proficiency and readiness of every individual person and go to market. How does predictive enablement defer from the AI roleplay tools and training platforms that have existed for years? Yeah, if you take any point solution that's a training tool, right? An AI roleplay would fall into that category, right? We have an AI roleplay tool. They're point solutions. They're medicinal. What does that mean? It means they come at the very very end of the journey. In order for me to do any kind of training, and let's use AI roleplay since that is sort of the the topic of the conversation. In order for me to AI roleplay, I have to understand what are my deficiencies? Where are they about to erode revenue? What do I need to practice and why? Any point solution like any a roleplay tool is going to build you somewhat realistic simulations for you to practice but without a way to actually diagnose the skill proficiency

[9:11] and then help you prioritize what you're practicing by predicting revenue erosion based on your deficiencies. Then what are you practicing? And it sort of brings me back to you know when when I was a kid I was a musician and whenever my mom would tell me to just practice I would practice whatever I wanted to and I actually wouldn't improve at all. I would just practice random pieces of music. I try to get through the 30 minutes of practice, but when I knew that I had a competition coming up, I knew exactly what I needed to practice and why, and I knew what perfect sounded like. And when I knew what to practice and why, and it was time based, now I would actually nail that piece of music and I would improve as a musician. It's the same way for point solutions versus a predictive enablement tool. If you just have a point solution AI roleplay tool and people are using that, I'm sure they're practicing, but are they practicing based on their own deficiencies? Are they practicing based on actual calls? they're about to make a mistake. Probably not. And so you're going to get a lot of people practicing and not a lot of improvement in the metrics. So it's only part of the solution that comes at the very end of uncovering and diagnosing deficiencies and then helping to prioritize and predict revenue erosion.

[10:14] What data signals does Luster use to anticipate performance gaps and how do you prevent teams from becoming overmated? Yeah. Uh overation is not a good thing. So we'll kind of start there. Overa automation can also replace tasks that should be done by humans because there's not a lot of thought put behind that. Teams need to do an exercise of what should be automated, what should be human, and what should be some sort of a hybrid between those two things. And I think that conversation is often not happening enough amongst gotom market teams. Um, and so that's the first thing is like how how do we not overly automate the way to properly function a tool like this is one how do we actually look at the qualitative and quantitative skills that are important. So that's one data point, right? Is qualitatively based on your role, the company that you're at your tenure, where based on every qualitative skill are currently measuring in terms of your proficiency.

[11:05] Then you look at quantitative skills, right? Where based on your quantitative skills are you in terms of your proficiency? And again, that's contextual to every single role. So the first thing that we do is we diagnose the entire team with a skill proficiency map through a combination of customuilt boot camp roleplay and then previous customer conversations. After we build basically a custom measurement tool for you and your organization, the next thing that we're looking at is various different data points to help inform the system. What kind of content is in your CMS that we should surface in front of people? What kinds of calls do you have on your calendar? Who's on those calls? And based on those types of calls, what stage they are? What's the size of the deal? What's the industry? We can now look at your skill proficiency map to identify where erosion is about to take place. We can use CRM data to help to identify who are the people on the call and what are those titles and what are those industries. Uh we can also use CRM data to help tie the ROI and the performance of the tool. Right? We're actually able to say that when people deploy X skills properly at the right time, it increases revenue by X amount.

[12:05] So high level we're taking call recording data, LMS data, CMS data, calendar data, and CRM data to all come together to create a solution that's operating in the background and allowing the human being who's in that role to operate and function at their best. So again, it comes down to automating the right things. What are the early use cases where customers are seeing the biggest impact? Yeah, there's three main ones that people are using Lustra for right now where we're seeing really, really measured results. So use case number one is hiring, onboarding and ramp. So previous to something like Luster, we have to hire people based on all subjective measurement. What was their past performance? Do we know them? How did they do in the interview? How they do in their presentation? Maybe you do some sort of a roleplay where you have the people at the organization role playing with them and then we hire them. And then we take the next 3 months to three years to determine if we actually made a good hire. Uh versus with Luster, you're able to actually get an objective proficiency map on a candidate before you even hire them. So you can then determine if they're walking in the door with the skills that they need to actually succeed in their role at the tenure that they have. Um and then then that naturally leads into onboarding which is now how do we do customized onboarding for every single new hire. So while they're going through their very

[13:15] typical company onboarding and learning about the product and the company and the vision and their benefits, Luster is then plugging in very individually based on their skill deficiencies that we've already measured to help them get to revenue faster. And so again, there's that mix of what are the people doing, what is the automation doing to get an individual ready to actually perform. And with those hiring and onboarding use cases, we've seen a 50% reduction in ramp time as defined by I'm now hired and now I've closed my first deal. The second big use case that we've seen is any kind of certification use case. Your company just rolled out a brand new product, maybe a new talk track, maybe you changed your sales process or your sales methodology. Maybe you did a big training and you want to make sure that the entire team is actually heard and ingrained the training before they go and start having customer conversations. With the certification use case, you take any training that you do, you upload that into Lester and then we create a couple of essentially certification or test simulations with a variety of different personas that you sell to that will actually say, "Hey, Christina went to this training. We can actually now prove whether she's absorbed that and is ready to perform that with actual customers or not." Uh and then the third one is the everboarding use case which is regardless of your tenure or role within

[14:26] the organization. Luster is consistently measuring your skill proficiency. It's then taking that proficiency and looking at the actual customer interactions that you have scheduled on your calendar, proactively predicting where you're about to make a revenue impacting mistake on your actual customer calls and then prescribing the customuilt solution just for you to not make those mistakes in the first place. Whether that be AI roleplay, training, human coaching, AI coaching, that prescription is based on where are you about to step in mud. So those are the three main areas that we're able to see real measured revenue results. Many GTM leaders are excited but skeptical about AI in enablement. What's your honest take? Where is AI already delivering real value and where is it still hype? Uh they should be skeptical. I actually think that revenue leaders should be skeptical of all AI and they should ask a lot of questions because there's a couple of different ways that AI products are being built today. Um, and some of them are really wonderful and really responsible and some of them are really really irresponsible because this industry is moving so quickly. It also means that a lot of founders who are building companies right now are saying we have to move really really quickly which then sometimes leads to a we will build something and fix it later. And when you get your entire organization

[15:40] bought into an AI tool and you're sharing data with that and most of that tool is vaporware and it's going to fix it later. That's a big problem for your org. It's also a big problem from a security standpoint. So you can have AI tooling that is essentially a GPT wrapper. A lot of point solutions are a glorified GPT wrapper. Meaning there's a user interface that they've custom built that's sitting right on top of chat GPT. When you're doing that and there's not a lot of custom coding, you can build product really really fast. It's product that's going to break if you squint at it too hard, but you can build really, really quickly and you can give the impression of being a really robust tool, even though you've only been in the market for six months or a year, right? Or you have a solution that is powered off of a large language model, but the majority is customcoded, which gives you more control over that product and a more customized experience and a more safe and secure experience for your customers. Those companies are typically building a little bit slower, right? So, they look like they're further behind.

[16:36] they don't have as much product. And so there's this very, very weird thing going on in the AI market where I think enablement professionals, sales leaders, any AI tool that you're looking to buy, you have to ask the questions around the underlying infrastructure and make sure that you're not accidentally buying a wrapper that you could probably have an engineer on your team build by themselves. How do you design AIdriven systems that still leave room for human intuition, mentorship, and creativity? Yeah, everything comes back to what is the problem that we're solving and who is best to solve that. So the metaphor that I use cuz my brain works in metaphors is if you consider marathon running and in most cases the inspirational thing about marathon running is the fact that the people are persevering and getting through that. I don't think anybody wants to see an AI marathon, right? Where a bunch of bots are just like running around on a track.

[17:20] Like there's nothing inspirational or fun about that. So you think about a marathon running where I don't want the AI to replace the human in that, right? I don't want to build an AI that can run the best marathon ever. That doesn't make any sense. But I might want to use AI to build a really good treadmill. Um, and so it's thinking about how do I use AI as almost a gym or a mechanism to help human beings do what they should be doing. Let's look at a go to market example of where I think that we're going to see more AI automation and where I think that we should versus what some other folks might be thinking. So I think that we're going to see a lot more AI automation at the top of the funnel in terms of sales processes. For years and years and years, sales reps have been slamming their head against the wall trying to figure out like, how do I open up a conversation with a prospect? Is it 8 million emails? Is it personalization? Do I send them cupcakes? Do I message them on LinkedIn?

[18:10] Do I drop into their right? There's all of this of how do I actually open the door? And then there's when the doors open, how do I have a really wonderful advisory, consultative based conversation with my prospect to actually lead to a close? I don't think that any human being wants to talk to a robot for that second piece, right? Like I don't think people want to have a robot that is leading them through the entire process when they're buying something meaningful. But top offunnel, I do think there's a lot of opportunity to automate top of funnel, which is not where there's a lot of brilliance. There's a lot of slamming the head against the wall. So it's a lot of that, right? What is the problem that we're having? What is the right solution? And most importantly, what's going to delight our customers? Because if we don't think about how the customers of our companies want to interact with us, we're going to make mistakes that are going to be customer impacting. What does the human AI collaboration look like inside Luster today from product design to customer engagement?

[19:03] Yeah, we utilize a lot of different forms of agentic and generative AI especially for a lot of the menial tasks that we know a human being could do but that a human being doesn't need to do. A lot of that is things like automating reporting pulling together different collections and subsets of data even down to writing some really really minor code. One of our use cases for AI internally is when we have customers that want things like custom reporting or custom dashboarding versus having a human being sitting there running the same reports. We can build an agent for a customer that will customize their reports the way that they want them and deliver them so that our CSMs are not buried in those data sets but actually talking through the story and helping customers to adopt the product. And so our take on it is kind of exactly what I'm talking about, right? We have the capability to use AI to do a lot of the administrative work that requires a lot of precision that a human being is probably not the best person for. Right?

[19:55] Human beings inherently make errors and make mistakes. But what human beings are really good at doing is connecting with other people and thinking creatively. AI is not creative. Like it's not AI is not creative. Computers are not creative. Creativity does not exist amongst a machine. Um, and so how do we bring that creativity and let people shine with that and let AI do the tasks that are meant to be more administrative and much more uh forward- facing? What advice would you give revenue leaders trying to modernize enablement with AI but feeling overwhelmed by data or tech complexity? Yeah, stop taking demos with so many tools until you know what every single one of them is going to solve. Um, I've talked to a lot of revenue leaders who, and I get it, like I get it. Building an AI company, right? There's a lot of revenue leaders. I talked to one the other day and he's like, I'm just taking a demo with every single AI company that I can find because I'm fascinated by it.

[20:43] And I'm like, that's great. One, you have a lot of time on your hands, but two, you get lost in what am I trying to solve with this time? Why am I shopping for an AI tool with this? Is it out of morbid curiosity? Is there a problem that I'm trying to solve? Is it some element of I don't know why I'm doing this? Like, what is the reason why you are shopping for different forms of AI? And are you doing it in a silo? Because this is the other big problem that's happening with AI tooling right now is you have almost every single person in a goto market organization from the BDRs all the way up to the CRO that are taking multiple hours out of the day or the week to look at tools. And so you could potentially have 60, 100, 200, however big your organization is of people who are all looking at different AI tools and all making different suggestions. And I saw this at an organization that I was advising. All of the reps were looking at various different tools to solve the same problem. And all of them were very loud and noisy about which one they were using and wanted to use. And candidly, it was a mess. Everyone's using different tools because most AI tools, you can use them for free for a little bit. Also, be careful with those because you can leak your company's data by using a free AI tool that's not approved by uh your security team. So, there's just there's a lot of risk there.

[21:52] As a firsttime founder and longtime sales leader, how do you balance being visionary with staying grounded in execution? This is where relying on my team is very very important. I very naturally am a vision person. I'm a big picture person. I see 10 years ahead and where I want to go. And what is not one of my strong suits naturally is saying now what is every single maniacal step that we have to do in order to get there and what are the milestones? Can I do that exercise? Absolutely. Does it come naturally to me? No. And so when I'm looking at who I surround myself with, I firmly believe in hiring people that are smarter than me and hiring people that are filling the gaps that I have. Right? So if I know that I'm not a big picture or that I am a big picture thinker, but each of those little steps are not my strong suit, then I was very lucky to bring in my co-founder and my VP of ops who are my executive team. And both of them are very good at saying that's an amazing vision. Here's exactly how we get there. And then it becomes a conversation amongst the executive team of the steps that we take and the milestones that we're going to hit. So for me personally, this is one where I

[23:01] don't believe in doing things alone and by yourself because I don't think that you can build a great company that way. So how I use the people around me as resources is huge. You've been vocal about building culture through trust, accountability, and mentorship. What does that look like in a remote first startup? Yeah. Um, one is finding every opportunity that I can to connect with all of my employees. So, that's big. Whether that be in regular all hands, regular one-on- ones, for as long as I can do that, I will continue to because I want to understand who are the people that are working at this organization. What kind of brain power do I have and all elements of that? And are we really listening to people and getting all of the different brilliance and expertise that exists? So, that's one piece of it. And then the other piece of it is hiring people and trusting them to do their job. and also making sure that they understand the impact that they're making at the organization. So I believe in not just telling people like, hey, great job, but why did you do a great job? What did you do that was really, really good? What can we learn from that? And so for me, it really is just seeing people and showing that I care about them personally as far as what's appropriate for an organization, right?

[24:07] Because you don't want to go into the realm of we're a company, we're family, right? But you spend a lot of time at work, objectively more time working in your younger years than you do not working. And so how I can make this a delightful experience full of growth for my employees is is actually one of the most important things to me. How do you keep team energy and creativity high while pioneering a new category and raising capital? Yeah. Um it's hard and again it relies me to rely on the people who are here. While I was raising our recent round that we just announced, I was running all of go to market. I was running all of revenue. I was running marketing and then I was being a CEO and overseeing things like the product and the engineering team at the CEO level, overseeing things operationally, working on hiring and all of the roadmapping. And so me doing all of that, I couldn't possibly do all of that well. No one human being could. Um, and so during that time, it just came down to if somebody had an incredible idea or if somebody wanted to talk through a new or different way to build the product or evolve the product, it came to listening to my people when they had ideas and again making them feel empowered that they do have a voice here. And there's a lot of channels that you can do that for us. We have different Slack channels

[25:20] where there's different categories and any employee can pop into any of those and say like, "Hey, I have a great idea." And they instantly get attention. It gets tracked somewhere. And so, especially in a remote world, it's where is everybody marching, where are we crossing over, and then what are we owning on our own and making sure that we're all aware of the plan that we have. What lessons have you learned about fundraising as a female founder in B2B tech? Fundraising is difficult no matter what. And I think fundraising in this landscape is also difficult. Really similar to sales, it's all about relationships. And the biggest thing for me is really really early on when I was fundraising, I got really really discouraged because I was just hearing a lot of nos and I didn't know what to expect because it was my first time going through this journey. And one of the things that surprised me is as a two decade long salesperson, when somebody would say no to me to buying the product that I was selling, it never felt personal to me. Never felt personal, right? I was like, "Hey, I get it. You don't have the budget. You don't want to solve this problem. You don't like the product. Well, I didn't build it, right?

[26:18] It's not my problem." So like I never took it personally. I was disappointed but it never felt like a personal hit. When you're a founder of a company of a product that you generated in your mind and that you are building and you have a venture capitalist who is saying I don't believe in your vision. I'm not going to give you any money. It's really hard not to take that personally. And that caught me off guard was how personal it felt. But the reality is it's not personal. It also does come down to business. And what I learned very early on is the reason I was getting nos was actually my fault. It was the story that I was telling. I had never pitched to a VC before. I had never done that. So, I'm selling to VCs the same way that I sell to customers. And it really is a very, very different way to talk about the product and talk about the roadmap. And I'll actually say our company underwent a huge evolution even in the product and how we were building it based on the conversations I was having during fundraising when I was trying to figure out how do I talk to this individual about the large vision but also where we are. I had a bunch of light bulb moments of like, oh my gosh, you know what we should build? like it gave me actually ideas of what we should build. And so we're fundamentally better for that journey. And now as we go on to raise our series A, our series B, I feel so much more prepared mentally and emotionally for that. But also, I look forward to it in a very, very different way. So early on, if this is your first time doing it, it's going to be

[27:31] emotional. You're going to hear a lot of nos. It's going to feel personal. Sometimes it is, sometimes it isn't. Just keep going. There is one of you and there's thousands and thousands and thousands of people who can invest. So for every no generate four new conversations and that to me is the way that I sort of stayed ahead of kind of the dark cloud that came early on. What's the biggest mind shift at shift GTM leaders need to make to prepare for predictive systems? Yeah. Um the first is all of the time that is spent being reactive feels like a part of the job. I'm actually seeing a lot of go to market leaders that are almost resistant to the idea of predictive technology when it's actually in practice. Right? The idea of predictive technology is the technology is going to listen to every single customer interaction. It's going to grade that interaction that interaction based on your rubric of success and then it's going to spit out a playbook for you to go and engage with your people to improve revenue. When I say that to a revenue leader, when I say I can tell you every revenue impacting mistake that your team is about to make this week and then I can stop them from making those mistakes and prove readiness for a conversation, they go that's that doesn't sound real. That sounds incredible. And I go, "Yeah, well that's exactly what we do. That's what we are doing." And then we get in there and they go, "Yeah, well our sales leaders

[28:43] are still listening to all of the calls and they're still right." So they kind of go back to this reactive because it feels like a part of the job. It feels like part of my job as a manager is to go listen to 800 gong or chorus calls in the course of a week and manually grade all of them and tear through and try to identify what's going on with my team. And so getting teams to let go of some of those activities that are not generating revenue and instead say I'm going to give you the playbook that you need to go execute on in whatever way you see fit that's going to improve the readiness of your team. We are about to uplevel sales leadership massively all go to market leadership massively into their executive brain and keep them out of menial tasks that are really dragging them down and pulling them away from being able to do what they should be doing which is spending time with their team coaching their team and really understanding the readiness of their team and scaling it and so that resistance to let go of ways that didn't work of the past change is difficult even good change and so that's the massage that we kind of have to do how will AI reshape the roles of sales enablement and revenue leadership in the next 3 to 5 years.

[29:47] The biggest thing is the kind of data that we'll be able to have that we haven't had before. Being able to operate from an objective data layer that actually tells us so specifically for every individual whether or not they're ready to do their job and then actually bringing them to readiness without people having to lift a finger. The future of that is understanding and being able to embrace that new layer of data which again I think kind of like what we talked about there's going to be some resistance there. AI can do a lot of really really cool things. But when you look at the kind of real new unseen revenue intelligence that is starting to hit the market right now, especially being led by Luster with predictive enablement, it is a change. It is brand new. I've been hearing for a decade about like predictive revenue, predictive intelligence, predictive this. And none of it was actually predicting anything. All of it was a lot of guesswork, right? there was guesswork because none of it was actually rooted in any kind of a diagnostic of your go-to market team. And so I think new data is going to solve a lot of problems but I think new data can also create a lot of friction.

[30:49] If predictive enablement works as intended, what does the world of GTM look like in 2030? Yeah. Um I think that we see attrition rates for organizations go way down. I think that we see the success rates and the way that companies can scale go way up. I think that we see the ability for companies to build new product and launch new product and test new product massively goes up. I think that we see managers having to spend a lot less time doing things like, you know, PIPS and managing uh employees up and out. I think that we see a lot of leaders that are no longer stuck in that lower level of how they manage out bad unfit talent and instead they're not bringing them into the organization in the first place. I think that we go from a world where it takes on average 9 to 18 months realistically to be able to ramp a brand new rep to cutting that far more than a world where somebody can be ready to do their job and producing revenue with the kinds of automation and training that we have in 3 to four months, right? And so I think we are about to lock into a new level of speed for go to market organizations and I think also a new level of on the qualitative side fulfillment with role. What luster does is it helps you to really identify if

[31:58] you are ready for the job that you are doing. If you have the skills that you need, where your gaps are, and if you really are a right fit. So many people take jobs as guesswork. Right? I think this is going to be a good fit. I think it's going to look good. And then once they start working there, they realize, shoot, I'm in the wrong job for me. What do I do? How do we eliminate that and actually improve the human experience at work as well? Yeah. And especially with AI going more mainstream, it seems like it's going to lead to a massive headcount reduction across most GTM teams, if not all. And so, um, in in that kind of a world. Okay, cool. I lost my train, I thought. But, um, move on to the next one. You're doing great. Great. You're What's that you talking about? Like, uh, like is AI going to shrink the size of teams?

[32:45] Yeah. Yeah. Yeah. Yeah. I'd love to get your take on that. Yeah, the answer is maybe. You don't think so? Teams are well, it depends, right? There is a lot of bloat because again, we go back to what traditionally happens if we focus first on scaling specifically B2B tech organizations, but but I think this also is a little bit more broad. You raise a lot of money, you're doing really, really well. And what do you do? You hire and go to market, right? We hire, we scale, we go from there. And so I think that there's a lot of irresponsible hiring that happens and then a lot of irresponsible firing that happens to rightsize that. I think that we can get a lot more of that right especially with tools like Luster. Will companies overall smaller? Maybe. Will people shift in their responsibilities? Probably. So I think one of two things is going to happen. So when I say maybe it's yeah maybe teams will be smaller or maybe people will just be doing different things. I think 10 years from now you're not going to see massive BDR SDR inbound teams that are answering form fills and making cold call. Like I actually don't think that we're going to see that. But I do think that sales teams and specialized different types of account executive and solution consultant and solution engineer and client success manager.

[33:54] Like I think those roles are going to be redefined and so much more important in an organization. I think AI is going to cover kind of the front of funnel and the end of funnel. And I think we're actually going to see a growth of people midfunnel and an evolution of the types of roles that they have because of the support by AI. In that world, if your company's cooking, you could actually have a bigger team than you did before because they're actually doing well and they're producing and it's more people that are creating more revenue. So, it's a maybe. It depends. And what's your take on the convergence of revenue generating functions into a singular revenue department? Does that seem like a potential future? It's going to be my answer again of maybe. I don't believe that there is a one-sizefits-all to how a company infrastructure should be built. I really don't. The same way that if you say, "Hey, come be an account manager at my company." Account manager could mean five very, very different things depending on how it's defined at that particular organization and what their roles and responsibilities actually are.

[34:51] So, I do believe in aligning different orgs together. Like one of the things that I believe in is having an operational org that all rolls up to a single operational piece of that. I believe in having individuals who are responsible for all revenue. I believe in having individuals that are responsible for product and those are cross functional leaders. And that's also very very different. Then there's also another way that you can say you build companies which is you know marketing and every single role in marketing rolls up to one person whether it's a BDR or it's an operator or it's a PMM like they all roll up to somebody in marketing versus you can say hey the operator in marketing would roll up to the operating team the BDRs would go to sales right so there's different ways that you can slice that I would say what is your product who are you selling to what kind of infrastructure do you actually need what kind of tooling do you actually need and what leaders do you actually need I actually think that the irresponsible hiring and go to market is in two places. It's for top offunnel BDRs and SDRs. We hire those way too quickly. Um, and we make people collateral damage. But then also we hire leaders way too quickly. We hire executive leaders. People are so itching to bring in a VP of sales, a VP of CS, a CRO, and you're like, do we even need that function right now? And so, uh, that one is another big maybe.

[36:04] Beyond revenue metrics, what cultural or human outcomes are you hoping Lester drives for teams? I mean one of the things in one of the areas that we are defining is this element of revenue impacting mistakes and avoidance of revenue impacting mistakes. Um which is a new you could call it a metric right but it's every time I get in a conversation depending on what stage of the sales process I am in I'm either taking my skills off the shelf and I'm succeeding in advancing that deal forward or I'm making a revenue impacting mistake by missing a trigger, a question, a yellow light, something that that customer said and so I make a revenue impacting mistake. I don't ask the right question. I don't advance in the right way. I don't multi thread properly. I don't fully understand all of the risk. It could be a myriad of different things. And so, a non-revenue metric that Luster is looking at is how many revenue impacting mistakes can we measure and avoid. It's so saying, "Hey, you would have made these mistakes on this call based on your proficiency and calls that look exactly the same, but we got ahead of that and brought you to proficiency on that call." And then when you had that call, you didn't make those mistakes. Right? So how many areas of potential landmine stepping are we avoiding before we get there? So that's one. Another one would be actually being

[37:11] able to measure skill proficiency increase separate from revenue. Right? So we look at proficiency often tied to revenue. If I'm doing well at hitting my goal, then you assume I have great proficiency, which is not always true. Uh and then vice versa. If I'm not hitting my goal, you assume that I have a problem um or that I'm deficient in my role. Um and those assumptions are almost always inherently wrong. And so how do we measure skill proficiency separate from revenue as a predictive layer that tells us when we're going to perform versus not? And so a stat that we have through Luster is teams that are using Luster for at least 20 minutes a week are increasing their skill proficiency by 38% in four to six weeks. Right? And so how can we actually measure that lift in your proficiency and then predict where that's about to impact the revenue? So it's separating out a couple of those things.

[37:58] I'd like to move on to the rapid fire section of the pod now. one GTM metric that deserves more attention in 2025. I'm going to get hate for this one, but attribution. And what I mean by that is I think that it's a garbage metric and it needs to be re-evaluated. And I think that go to market teams spend all day fighting over attribution. And it's rapid fire. So I'll leave it there, but we all need to stop choking each other over attribution. Hardest but most valuable lesson you've learned as a founder? Don't do it alone. Most underrated role in modern GTM or PMM. A book framework or creative discipline that shaped how you lead. Radical Cander is is a really really good one. I know it's rapid fire, but I'll say a second one. It's Who Moved My Cheese? Those two books like fundamentally changed the way that I think about work. In one sentence, the future of enablement is predictive.

[38:50] Christina, thanks for joining me and for showing us what it looks like to build a company that fuses AI innovation with human empathy. From scaling teams at Groupon, Glass Door and Specket to now leading Luster's predictive enablement movement. Your journey proves that great GTM leadership starts with clarity, creativity, and conviction. If this episode helped you reimagine how learning, leadership, and AI intersect inside modern GTM systems, subscribe to the GTM vault. Share it with your team and join us next time as we unpack how today's operators are designing the next era of go to market growth from zero to one and beyond. Great. That was awesome. You did. You did.

[39:33] Thank you. Tech founders and VCs careers lessons GTM