#127 How to build an AI-ready GTM org for 2027

Janis Zech: Hello, and welcome to another episode of the RevOps Lab podcast. I'm actually alone today. Philipp is at an engineering off-site with all our 10x engineers that are building great stuff at Weflow. But, yeah, super excited about our guests today. We're here with... or I am here with Lonny Sternberg. I hope I pronounced this correctly. Lonny, welcome to the RevOps Lab.

Lonny Sternberg: Thanks so much for having me. Happy to be here. I'm glad we were able to connect and get scheduled. Super super excited. I'm looking forward to today's content.

Janis Zech: Yeah. Same here. I mean, we've known each other for a while. You've done a lot of awesome stuff. So, yeah, maybe if you could do a quick intro, and then we jump right into our topic of today.

Lonny Sternberg: Yeah, most definitely. So over the last thirteen plus years, I've been leading, you know, revenue operations, go to market operations, specifically focusing on engineering scalable revenue engines for high growth, you know, B2B SaaS companies and technology service companies. Most of my career has been focused, or I should say spans across, you know, zero to one, up listing to NASDAQ, and then, you know, all the way from VC to PE backed organizations and three fifty million plus scale. So super excited to talk about the era that we're in today and what's necessary to build the clarity and the loop systems to maximize AI and create, you know, durable, predictable growth engines.

Janis Zech: Yeah. Super excited. I mean, it's a very timely topic. I think, you know, our topic for today is essentially, you know, a RevOps operating thesis that you've been, you know, I think developing over the years, right, where I think we are, you know, faced with a lot of challenges these days. Right? Like, everybody wants AI, and everybody wants it yesterday. And at the same time they wanna, you know, reduce the budget for RevOps and, you know, while you upscale yourself into, you know, how do you do the whole transition. So I think it's a very challenging time for RevOps right now and at the same time, I think, you know, we had that last week, you know, on the podcast, like probably RevOps is well positioned to, you know, also grow into C level positions given the skill set and the abilities we all have. So I think today's topic is essentially kind of how do you drive clarity with a clear operating thesis that spans across governance, context, and systems that help essentially feed a loop where you essentially come out and you build that, you know, durable, predictable, repeatable engine. But, you know, I think the challenge really, like, that's really, really hard to do. And I think, you know, I think jumping into just building agents on top of poor input data is really challenging. So I think, you know, like, this is me going broad, and now, you know, over to you, Lonny. I'm curious. Right? Like, you basically thought of a loop. So curious, like, if you could maybe high level explain what you mean with that and what you mean with that topic, and then we jump into each of the different areas.

Lonny Sternberg: Yeah. Most definitely. So I think as, you know, the revenue operations, and especially just business today has continued to evolve, it's been about people, process, systems in a lot of ways, or from an analogy standpoint, and we're in this position, I think, where it's not becoming about as much about focus or time, but it's really creating clarity. And now that we've removed a lot of the blockers, if you will, and AI is unlocking these components, going back to and considering the basics and creating a loop system where we really consistently can create a framework and a thesis that is governed by having clear definitions, articulated definitions, and operating cadence and rhythm through systems and a context layer that we're creating throughout the organization in which everybody knows what to do when the playbooks are working and what to do when the playbooks are not working. So I like to think about number one, governance as it's not a set of rules or controls, but it's a common framework or a common set of definitions. It's a common way of doing things that you know within the team, whether it be forecasting calls, customer success, playbooks, analyzing data, shared definitions from ARR, ACV to how maybe different departments may bring the numbers and reporting to the tables. If everybody is consistent and there's that governance framework, then there is not a lack of clarity — which clarity is gonna offer rewards, but when there is ambiguity, it's definitely gonna create a punishment. So I think that creates speed. Governance is gonna get speed and it's gonna get people in a position where they know what to do when things aren't working the right way. That's kind of the spot number one. Two, really looking at creating that context layer. I'm a big subscriber of having that data foundation layer, it be your CRM or other systems of records, then together combining that first party data and that third party data to get your knowledge layer plus that governance to create that overall contextual layer, and then flowing the information in and through the different points and parts of infrastructure, which I know you see each day.

Janis Zech: Yeah. It's funny you say that because I actually, you know, posted last Friday about the hottest job in RevOps is to create the context data layer. And I don't know why, but it completely blew up and, you know, it became, like, viral. So, you know, if you have any ideas, please reach out. You know, ping me on LinkedIn. No. Just joking. So that's, like, governance, context. What's the third?

Lonny Sternberg: So systems and rhythm. And I think systems, a lot of the times, focus on like, well, what's the tech stack or what's the system of record? But I think systems is a collection of all of the different processes that helps individuals, and especially in the era of AI, that we can carry out the context layer for each person independently when they need it, as they need it. And then followed by the rhythm, of course, the rhythm of the business, you know. We can talk about that from the lens of, you know, deal review, forecast, going to OpCos or any type of board meetings, etcetera, in addition to just calling the forecast for the quarter or the respective annual planning.

Janis Zech: Yeah. Yeah. I love that. So, basically, just to repeat, right, like, have governance, context, systems, which is essentially not just the technical systems, but a set of processes and then the rhythm, the cadence of the business, you know, quarterly, annually, monthly, weekly. Right? Like, and being, you know, essentially laying that out. Maybe let's jump a bit into the governance piece, right? Like, obviously, this is important in general, right? I think we've all been in these situations where kind of marketing had a different definition than sales of what is the sales qualified opportunity or, you know, you have too many amount fields that govern ARR and maybe bookings. Right? So I think we've all lived there. So it's like super crucial. Obviously, when you now throw agents into the mix that maybe don't sit in the meetings and listen to everything that we say. Right? It might become even more important. Like, curious. Like, can you elaborate a bit more on the governance piece? Like, you know, what do you think is crucial? What are some common gaps that you're seeing now?

Lonny Sternberg: Yeah, so I think that, this is something that, you know, most recently and throughout the last six months has been something that's been critical on my plate, when we're looking at what are the core go to market metrics within the business that are needed to measure repeatedly month over month to help us identify what we're going to invest in or divest in. And traditionally, if you think about the reporting structure and the different verticals of the business, there's often situations in which folks are kind of — everyone brings the wrong numbers to the meeting and says, no, this is the conversion rate from MQL to SQL or, nope, the contribution of pipeline from sales versus marketing is X versus Z. I think just that governance layer there of making sure that we're very, very clear on the most basic things of what is the arithmetic, what is the formula that we go into measuring these things, centralizing the ability so everyone can see what's going on at all times so the individuals that need to improve or move the output of the number see the same thing that, for example, myself and my team in RevOps has seen, but also that we're in charge or we're giving that governance layer for the right department to bring in and say, I am standardizing, I'm reporting on it. I pressure tested this. So we're all making those decisions consistently. So this is commonly coming up in organizations, I think, across, you know, when it comes to the forecast, when it comes to annualized planning, quota allocation modeling, coverage, etcetera, and just a consistent thing such as those basics and then, you know, having a clear understanding of who's bringing what, where do we capture the data, how is it calculated, and then who's accountable for it. Sounds super basic, but I think that is one example of that governance layer where it just plays critical. Now, putting fast forward, right, from the basics to AI, if you have an agentic atmosphere and you have an agent talking to another agent or you're utilizing this information or some MCP layer and you're connecting and going and scraping and going through this information and calculating it, that's when it becomes even more critical because it's not going back and saying, well, we calculated this way. What did you guys do? How is that working over there? But it's now automated, so it's either an acceleration of something that's very thoughtful or it accelerates a disaster.

Janis Zech: Yeah. Yeah. I think that's such a good call because what we are seeing a lot is that suddenly everybody's a data analyst with Claude. And so, you know, like... because they have access to the MCP and they can write some prompts. Right? Like, they come up with their own metrics and their own measurement and then suddenly, right, like, RevOps is tasked with, hey, you know, I have this reality, a second leader has this reality, and the third leader has this reality. If you don't have that governance framework in place, these guardrails on the definitions, the documentation, right, that essentially feeds into those, you know, self built projects. Right? Like, then, yeah, it's a... there's a lot of time spent on discussing what's real and what's not. And it's like... Yeah. I think we've all been there. We've all done that. And it's funny because, like, it's almost like history repeats itself, right?

Lonny Sternberg: Yeah. Most definitely. I mean, that's what's interesting. I find myself just reflecting on this conversation that we're having right now. It's we fast forward significantly into an era of autonomy and agents and automation and, you know, are we feeding efficiency to get more customer time and create value, or are we trying to optimize for a reduction in cost to then accelerate the benefit of the P and L? Or is it a tertiary which is, hey, we're gonna create more value and then as time goes on, that tail will start to present itself where we're optimizing for the P and L. And it's almost like going back to the basics never hurts, but getting those rules of the road down to then accelerate and automate, it's interesting. Also, while you were speaking, the other thing that came to mind is not only everybody's an analyst, but everybody now has a very strong, grounded opinion on how it should work. Or this is what it should do and this is why. So I think that, you know, it's this cycle that we're in where it's, you know, you can't replace the human — I think it's incredibly important that you have to have that rigor and that understanding and that just experience that you can interpret the situation and I think make the decisioning, not just, you know, build the workflow.

Janis Zech: Yeah. Yeah. Okay. Let's assume we, you know, did a... we set up great governance infrastructure for the company. Everybody's aligned. The docs are there. They're not duplicated. They feed not only the human discussion and workflows, but also the agents. Right? Like, let's talk a little bit about context. Right? And, I mean, maybe just, you know, to share, you know, some of these experiences we're seeing from talking to hundreds of our customers and, you know, people in the space. Right? Like, I think there's a, you know, like, there's a strong need to invest in, you know, data capture, unification, and context, you know, mapping towards some sort of system of truth, which typically and governance layer that typically sits within, you know, the CRM layer. And then that essentially, you know, is the input to essentially then use AI to automate a lot of the, you know, workflows that humans are doing. But I think the interesting piece here is that you actually need to use AI to, you know, automate the context capture because otherwise, it just doesn't happen. I think we've all lived through this over the last fifteen years. Right? Like, I mean, you know, I... I'm also under the strong opinion that reps shouldn't update the CRM. It's just tedious work, which everybody hates. I mean, who loves manual data entry? Nobody loves it. Right? But I'm curious, what are some pitfalls you're seeing on the context layer? What are the things that you think is important to get into a place where you can actually really excel at that loop?

Lonny Sternberg: Yeah, so I think that, I mean, all of these are fairly broad, but I think they're gonna resonate independently with each listener, each user, each operator in their respective business. I think one is when we think about context, I think about it by breaking it down. It's gonna be different for every business. So I think first is like, who's my audience and who's my user, and who is the stakeholder inside of this loop system at that time, and do they have the context that they need and that they care about? Are they thinking about the right pieces of information or the right processes, the right steps? So I think the context can change based on the applicability. If we use an example specifically of, if it's — you mentioned the auto capture and if we talk about competitive intelligence, if we talk about putting in MEDDIC, SPICED, MEDDPICC — I think that is another gateway to having the right context layer. And then I think how we surface the insights and the information going back to that governance, right, and those shared definitions, the shared use cases, and the applicability of the approach at that time, that's when we start to say, are we surfacing the right information to the right people at the right time so the right conversations happen in the room when they need to be happening? So I think really surfacing the context around what do they care about and what do they need, and how do we surface that information so it's available when they need it rather than always being mapped back to like, I've gotta start or stop a process or stop and go get that. So it could be the context layer of preparing for a call. It could be the context layer of reacting real time in the call. It could be the context layer to how to overcome, you know, objections, etcetera. So I think we're seeing this place in time where how can I get access to that real time all the time, which I think will take us in the conversation down the road a little bit of laying a headless and what is the gateway now that we're accessing this context? So in summary, to kind of wrap it up, it's really like how can you leverage the framework plus AI and the information at your fingertips to create your own business context layer of like how your business operates and what actually moves the needle inside of the business. I think what ultimately, first and foremost, has to be there's people who gotta understand how it actually operates and how does it monetize and how do you create value for the end user.

Janis Zech: Yeah. I love that. I love that. And especially this aspect of, like, I think we're going from kind of system of record, system of intelligence, and kind of to, like, orchestration of essentially, you know, agentic and human workflows. Right? And I think RevOps is playing, you know, a key role there where, like, yeah, essentially those contexts is different in the situation you're in and I think remembering that. And then also, like, ideally, you know, not building it around the process, but building around where the people live and where they spend their time and when they need it. And I think... right? So this is actually a great segue maybe into kind of the processes and systems side of things. Right? Like... because, obviously, you know, like, there's some, you know, key systems that govern certain processes, right, like, that essentially are in context of the context. I don't know if you can say that in English, but...

Lonny Sternberg: Sure. Sure. Sure. Sure. We're getting really deep into the weeds.

Janis Zech: Yeah. Yeah. It's like, oh my god, where are we going?

Lonny Sternberg: Yeah. I was just gonna say, I think in your world, it's like, if you take a step back and you think about it from the landscape and the lens in which, you know, when you're talking to a client, it's saying, hey, do you guys have the governance? Do you have shared definitions in common? Do you know where all this information is being collected? How is it being retrieved? Who needs it, when do they need it, and then what's the gateway in which they're gonna access it? And then is there an actual rhythm?

So is it gonna be weeks one through four, five through eight, and eight through twelve of a quarter? And the context layer, just going back to that for a second, is going to build as that time bound meter keeps going. And then you're gonna start over and keep going with that loop. But I think, to your point, it's like, what's that pane of glass, or where do you want people to live, and how do you want them to interact, how do you want them to gather information and then really share it back so then they can end up having the collection of it together and the next move to be made?

Janis Zech: Yeah. And I think, like, I mean, just, you know, sharing some experiences here. Right? Like, I think, you know, if you think about the individual contributors, right, like, it's typically a high end of users that you're building for. And so wherever they live, whether that's Slack or Teams or Meet or Zoom or in their car or in their email, right, they don't want to change. And you don't want them to change it. Right? So, like, you want the tool that essentially captures context from wherever they are automatically in the background so that they don't need to change. Because I think change management, right, like, yes, we are in the age of AI, but change management is still very, very hard. And so, like, right, like, you know, it's different if you then maybe run your forecast motion where... anyways, most of the people already have a spreadsheet. They might have a report, and they jump between different areas. Right? And it's painful actually to do that. So you much rather have a unified dashboard that, you know, centralizes your deal intelligence, roll up forecast, and maybe, you know, your pipe analytics and coverage and, you know, pipe gen, you know, metrics into one layer. Right? So I think there's things, but then you're talking about maybe CRO plus, you know, ten people compared to, you know, maybe like a hundred people across AEs and CSMs. If you think about, like, maybe a hundred twenty people, you know, like a go to market organization. Right? So obviously driving change for twenty leaders is very different compared to the ICs. And I think that's like something to, I think, keep in mind here when thinking about like context capture and then also, you know, like, the systems and the way you essentially design these processes. And I think, you know, you mentioned MEDDIC, so I just bring it up, you know. Like, that's your favorite. It is the best example of this where, you know, I think if you ask a rep, you know, how do you like MEDDPICC or MEDDIC? They hate it. And the reason they hate it is because they feel like they just have to do more work. Right. And, you know, and like, it doesn't... and they don't get anything back. Right? And so I think this is a great example where it makes so much sense to run something like this if you run deals like MEDDIC. But it's not that the people really need to run it that way and then the managers need to coach reps against MEDDIC or MEDDPICC or whatever methodology you're using. But it's less about, like, you know, the data entry task, which everybody kind of hates. And then, you know, they do it on the side on a Friday and it's like, you know, it takes an hour and, you know, it doesn't make them any more productive. And I think that's like a great example where often this goes wrong and AI can help for sure. Right? And like, I get that there's, you know, different schools of thought where like, you know, you should think about these things and I agree with some of that. But, like, I think generally speaking, right, like, yeah, just interesting, like, observations from, you know, many different, you know, setups we've been seeing over the years.

Lonny Sternberg: I think you mentioned two critical things that — I shouldn't say nobody, but it's often not in the post and it's not being talked about and it's not commonly discussed — that is, it's not new. It's change management, and I think it's also the management enforcement, if you will. You can call it enforcement, you can call it enablement, you can call it management coaching, but if you really think about all of these things, you know, like philosophically, academically can be planned and thought and written, but if it's not taught and shared and the objective, you know, through management is not coached and followed up on, a lot of it is just gonna fall through the cracks. And it just doesn't happen without change management and it could be influenced with or without authority. And to your point, it's a twenty person organization versus one hundred and twenty. It could be a company that's domestic or international, global, etcetera. And all of those requirements are different, but I think going back to just consistency, you know, and that framework that we started the conversation with really boils down to just grounding in the coaching, you know, and the enablement and management enforcement in a way that's empowering, not disciplinary, but empowering as to like how to use it, why does it matter, and how it can help you.

Janis Zech: How it can help you. Super important, right? Like, what's a good rhythm cadence for you? I mean, what are some of the learnings you've seen there over the years? I think it's such an important topic. We actually had a full episode on just cadence.

Lonny Sternberg: Oh, really?

Janis Zech: Like, yeah. Yeah. Like, a year ago or so. And we went through, like, what is a very typical kind of cadence that people run. But, yeah, curious what you've seen, what are kind of do's and don'ts in terms of rhythm cadence running a business.

Lonny Sternberg: I think that one of the biggest things I think that is continuously compounding is that folks are looking at the rituals, if you will, and the cadences of, you know, like if there's a weekly forecast or a biweekly forecast. You know, if you think of the quarter as, you know, those weeks one through four, you know, what am I doing weeks one through four that's different than, you know, five through eight and, you know, nine through twelve, etcetera. It's really looking at it as like a tactical checkpoint versus thinking about what's the end state and then backing into it with an account plan and just thinking through like, what do I really need to achieve? And then through the context layers that we're talking about building, those are the signals of like what it's telling you and what it's showing, which really should be an input of how you're gonna spend your time day over day and week over week. So I think the critical failure points, if you will, that consistently over the course of my career that presents itself is it's a checkbox or a task versus just trying to look at it like as an independent player and holistically just saying, I want to be here in, you know, three months. How do I back into it? Here's all of my inputs. Here's the information. Here's how it's conceptually changing over time. And then looking at it as, you know, you're gathering data and you're reviewing and you're altering your plan a little bit as the time goes on. But it's just not looking at it as like a checkpoint or a task to do, but more of an orchestration of collecting information and then changing my decisioning based on, like, kind of a thesis and a framework.

Janis Zech: Yeah. I love that. I mean, I think especially, like, how you allocate time. Right? So, like, you might see, oh, we're short on pipeline, we need to spend more time on that. You know, we may have a few deals that are, you know, very, very important, and we need to close them. We may need to fly there. Right? Like... so almost like a cockpit where you can then kind of have full visibility into the reality, and you can course correct and, you know, adjust. Yeah. Which, you know, gives, like, more flexibility than, hey, you know, this is, like, you know, the weekly rhythm that a lot of companies are maybe thinking of.

Lonny Sternberg: I could assume — I mean, once you build your plan for the year, like, your plan is, for the most part, baked. And you're like, okay, this is the plan. This is what we've committed to. This is what we reported to the board or our stakeholders, constituents, etcetera. And you have to continue to execute against that plan. Once you're in the quarter, like, you know, your value proposition isn't changing overnight, right? Your marketing material is not changing overnight. So what do you really ultimately have control of? Like, your values, your velocity, and really volume. And depending on where you're in the quarter and how the business monetizes, your volume might always be baked too just based on respective timelines to achieve into a place in which you drop into the sales funnel with a sales qualified opportunity. So I think collecting this information and then saying how, to your point, do I spend my time to then pull these two to maybe three levers to then exit, you know, where we plan on being. And then the rest of the academics and the framework and everything we're discussing from, you know, the context to the rhythm to the processes to, you know, the governance layer is really just how to keep us in a position where we know what to do when it's not lining up.

Janis Zech: Yeah. Well, I love that. So final question for you.

Lonny Sternberg: Yes.

Janis Zech: What's an unpopular opinion about RevOps you have?

Lonny Sternberg: Oh, man. An unpopular opinion. I think an unpopular opinion — it could be opinion or kind of interpretation, but, yeah — you guys are just there to kinda calculate it and get the data put together and put all the reporting and kinda tell us where we're at. I think that is still kind of the age old kind of challenge that is not — I want to say it's starting to change because companies are really adopting, putting RevOps in the centralized function, if you will, to be a force multiplier. But I think that's kind of the thing that allows me to participate early on versus after something has happened.

Yeah. Not having to... I mean, fix it or clean it up versus like be part of the decision criteria that leads to the result versus after the result is pretty much like a foregone conclusion, pull back in to then say, why did this happen?

Janis Zech: Yeah. Yeah. Yeah.

Yeah. I think... I hope it's changing, but I know it's not for everybody listening here. And I think, you know, we've been, like, putting a lot of content out on that, you know, like, how do you become more strategic? How do you have, you know, kind of more say? And, like, the reality is, like, in some setups, it's just very, very difficult to get there. Like, it, you know, definitely worth trying, but, like, yeah, I fully agree. I think that's like... yeah, I think that's another, you know, harsh reality in RevOps for many many folks for sure. But I think it is shifting.

Lonny Sternberg: Definitely. I mean, I think, you know, the last fourteen to fifteen months, I think we've seen a big shift. And it's gonna continue to shift. Just the amount of, I think, job postings, discussion points, you know, where should the function sit, how does the function influence and or govern AI, having a consolidation of agentic workflows versus just everyone being scattered all over the place. I also think there's plenty of organizations that are starting to build their business thesis on how they're going to, you know, pretty much orchestration as a service in a way, whether it be, you know, a platform or influential processes. But I think it is shifting, but I still think that's kind of the ultimate departmental dream is to be that force multiplier versus kind of like a reactionary tool.

Janis Zech: Yep. Love it. Love it. Lonny, thank you so much. This was awesome. I really enjoyed it.

Lonny Sternberg: My pleasure. And I'm sure we'll have you back one day. Yeah. Thank you so much. Thanks for having me.