Scaling in the AI Era with PagerDuty CEO Jennifer Tejada

11 Dec 2025 · 47 min

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Village Global Podcast: Episode Summary

Episode Title

Scaling in the AI Era with PagerDuty CEO Jennifer Tejada

Host

  • Ben Casnocha (Partner at Village Global)

Guest

  • Jennifer Tejada (CEO of PagerDuty)

Episode Overview

In this episode, Jennifer Tejada shares her insights on scaling businesses in the fast-paced AI landscape, drawing from her experience at PagerDuty, which serves over 30,000 customers globally. The episode includes a masterclass on the impact of AI on enterprise sales, followed by feedback sessions with four AI-focused startup founders.

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Key Takeaways

The Changing Enterprise Sentiment

  • Shift in Mindset: Customers have transitioned from a "fear of missing out" (FOMO) to a "fear of getting in" (FOGI) regarding AI adoption.
  • Psychological Barriers: Concerns over security, resilience, and managing people transitions are prevalent among enterprise customers.

Understanding Customer Personas

  • Targeting Different Personas: It is crucial to understand what different personas (CIOs, developers, CMOs) value in order to tailor conversations and solutions appropriately.
  • Customer Success: Know what contributes to a customer's success and how your product can either promote or hinder that success.

Pricing Strategy

  • Strategic Pricing: Pricing should be seen as a strategic foundation tied to the value realized by the customer, rather than a mere tactical mechanism.
  • Consumption-Based Models: While these models are popular, predictability matters more than novelty for enterprise clients.

Embracing Transparency

  • Customer Expectations: Transparency in pricing and service usage is becoming a standard expectation. Customers prefer clear instrumentation of their consumption and costs.

Rapid AI Transformation

  • AI's Disruption: The pace of change attributed to AI is faster than previous technological transformations, necessitating new approaches to business operations.
  • Adaptability: Companies that embrace change and experiment with new operational methods will gain competitive advantages.

Building a Support Network

  • CEO Community: Establishing a network of fellow CEOs is essential for navigating unique challenges and pressures of the role. Engaging with this community fosters mentorship and support.

Managing People Transitions

  • Psychological Considerations: Transitioning employees to work alongside AI should be handled with care; asking individuals to replace themselves is counterproductive. Focus on enabling staff to add value in new ways.

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Detailed Discussion Points

Importance of Customer Discovery

  • Discovery Process: Emphasizes the significance of thorough discovery in sales processes. Sales teams often rush to close deals, neglecting to deeply understand customer needs and contexts.

Creating Urgency in Sales

  • Overcoming Fear: Strategies to create urgency in sales processes amidst a culture of fear in enterprise organizations by emphasizing value rather than simply pushing for acquisition.

Founders Feedback Session Several AI-native startup founders presented their businesses, including:

  1. Dani (Jam): A tool to streamline software debugging.
  2. Key Insight: Focus on removing bottlenecks in developer processes and enhancing collaboration across teams.
  1. Matt (Aerox): An AI marketing platform.
  2. Key Insight: Emphasizes the importance of creating content that adds value to LLMs for better online visibility.
  1. Sean (StepWork): Automation for internal processes without APIs.
  2. Key Insight: Emphasizes the need for seamless automation that mimics human behavior for efficiency.
  1. Sherwood (Sazabi): AI-native observability platform.
  2. Key Insight: Focus on simplifying observability through log-based monitoring to enhance DevOps efficiency.

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Final Thoughts

  • The Role of Self-Awareness and Humility: Successful partnerships, especially between founders and executives, require clarity in expectations and a willingness to engage in constructive debates.
  • Continuous Adaptation: In the rapidly evolving landscape of AI, businesses must continuously adapt their strategies, offerings, and engagement methods to remain competitive.

Closing Jennifer Tejada's insights provide valuable guidance for leaders navigating the complexities of scaling in the AI era, emphasizing the importance of understanding customer needs, pricing strategies, and the power of community support.

For more information about this episode, visit [Village Global](http://www.villageglobal.com/) and subscribe for updates.

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Transcript

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0:00Hey, everybody. This is Ben Kesnoka, co-founder and partner at Village Global Global, a network-driven venture firm. And this is our podcast, where we go deep on all things business and technology with world-leading experts.

0:21Good afternoon, good evening, wherever you are dialing in. I'm Ben Casnoka, partner here at Village Global, and we're delighted to have Jen Tejada, who's CEO of PagerDuty. Many of you know PagerDuty. She's helped scale the company from a promising little startup to now, of course, a public company, 30 ,000 plus customers around the world. And she's also an LP here at Village Global. Our plan for the next 55 minutes or so is Jen and I are going to chat for about 20 minutes on the state of pager duty, the impact of AI, maybe some tips and tricks on how each of us can accelerate our go-to-market and sales motions.

0:53Then we're going to shift and invite four successive founders to join the conversation one by one. They'll each have five or six minutes to talk about what they're working on, show a quick demo, solicit some input and reactions from Jen. And then we'll wrap up. So, Jen, welcome. Thanks for doing this. Thank you. Thanks so much for having me. So let's start just to orient everyone and level set. Tell us the state of PagerDuty today. What's the current product offering and scale for those who aren't aware? I mean, there's really never been a more exciting time to be a PagerDuty. I always say to people like, when you're the CEO, there's no getting promoted.

1:26So you have to reinvent yourself and find growth opportunities in disrupting the business, disrupting yourself, finding new paths to growth, finding new markets, solving new problems. And, you know, I think as somebody who's been in this industry for a number of decades now, we really have just never seen a transformation or like the tectonic shift that we're seeing with AI move so fast. You know, I was around for the smartphone transition. It was the year of mobile for 10 years, right? Cloud, you talk to any of the cloud providers, they'd tell you there's still a long way to go in cloud adoption.

2:03That's not a mature market in their view. But the AI transformation is just happening so fast. You know, we're seeing such a different pace and velocity of change. And it makes for some uncomfortable moments, you know, because a lot of the old playbooks that you would throw at some of these business challenges don't apply. But at the same time, it makes for really exciting moments. I was in town hall yesterday and I said to my employees, like, there's no limit on your capacity if you figure out how to deploy AI against some of the challenges and opportunities you're trying to address. So in this world where we needed a new person and our new skill set to do something, like, that's really not the case anymore.

2:43If you learn how to leverage these tools in your daily work. You know, the second thing is like the way we operate and run businesses is being entirely disrupted and people don't like change. And so, you know, the people who are willing to embrace change and be open to new ways of doing things are going to be more successful faster than the people who aren't. That's simply the case. When you talk to enterprise customers today who are AI curious, there's some mandate coming down from the board that they need to embark on digital transformation or implement AI or whatever. What are the kind of core anxieties that you hear from your customer base?

3:20What are the key misconceptions that they harbor about the potential of AI or where the pitfalls may lie? What are you hearing from your customer base? And remember, the folks joined today are mostly a lot of early stage AI native startups who are selling into enterprise and are always trying to work with these customers and figure out a solution that can work for them. And they're complicated, these customers, these big enterprises, right? I mean, I don't think you can ever underestimate how many layers there are to that onion in a large enterprise. And I also think one thing that continues to hold true is that the aspect or the view on this set of challenges and opportunities is very different based on the persona, right?

4:02So you're going to have a very different conversation with a CIO than you're going to have with a developer than you're going to have with the head of infrastructure versus the chief marketing officer or the chief customer officer or someone in middle management, right? So you've got to know what your starting point is and really try and understand before you even have a conversation. What is this persona, this person really care about? What gets them promoted? What gets them fired? You know, and then you can get a sense of like where their anxiety is going to come from. But I would say, one, we're kind of seeing this shift from fear of missing out.

4:36Like I got to be doing something. I got to be saying something. I got to have an agent to fear of getting in. what if I do this and I do it poorly wrong or it's too expensive or I can't do it or fear of screwing up, which is like, what if it goes really badly and it destroys business trust, it destroys financial capacity, et cetera. So there is a lot of fear and uncertainty because we just don't have experience with something that's moving at this scale and at this speed. And so that's natural, but fear is good, right? Like I'm a skier, right? And if you stand over the top of a cliff and look down a crevice and you don't have any fear, you're going to do really stupid things.

5:23You need to figure out how to help your customer sort of harness that fear into, well, what, you know, what would happen if I could solve these problems that you're worried about, right? So start to be part of their solution and harness that fear. But things that people are worried about are the things you're worried about. Security. How do I make sure this new AI investment that I'm deploying is going to be resilient and not cause more problems than solutions, right? They're worried about people. How do I manage the people transition? And I see people learning the hard way, asking folks who do the work today to employ AI to replace themselves.

6:05like psychologically that's just not a prospect that's going to manifest itself quickly and so sometimes thinking about how you organize to get that work done it's got to be different so you have to have that conversation at the right level and then at the level of the people that you know may find that the work they do today is no longer necessarily sari because a platform can do it or the i can do it you have to help them transition to where they can add value in the future yeah Yeah. And let me just pause one there, John, because I think you're making a couple of good points that I want to make sure I understand them.

6:37So the first is you're saying across the enterprise today, with respect to AI opportunities, there might have been a sort of psychological evolution from we must get in, we're fear of missing out. We've got to be there. We've got to be talking about it. We're everywhere. Right. And then we've shifted perhaps to a fear of getting in. So from fear of missing out to fear of getting in and worried about unintended consequences, et cetera. And that's important, I guess, for everyone sailing to the enterprise with an AI product today. If what you're saying is true, at least in some organizations, having a sales strategy that aligns with a customer that might be fearful rather than just raw, unbridled excitement.

7:19So that's one point that's, I think, really interesting. The second thing. I'd put a pin on that point, Ben, because in the old days when we were small, I would hear us say, well, we're developers building for developers, so we know who our customers are. And I would have to remind my team that the development team at Morgan Stanley is working on different things with different constraints than the development team at a Silicon Valley startup, right? So yes, it's true. You're all developers, but the problem set is different. The regulatory environment is different. The scale is different, et cetera.

7:49So you have to know, you have to meet your customers where they're at in enterprise. And they're not likely to be at the same place you are. Even a person in this, your VP of infrastructure and a fortune 50 company's VP of infrastructure are not in the same place. Yeah. Got it. And then, okay, makes sense. And then in terms of this very interesting dynamic of, Hey, we have a product that will allow you to, you know, eliminate these three human jobs or make more efficient these five people. it is a funny sort of tactical sales question of if that's the value prop of your product and you're talking to the human on the other side of the table who will be directly impacted how are they going to take that they're probably not going to be a rational assessor of your product so is your sales advice you have to be talking basically one or two levels up in the organization to someone that has that broader view on ROI for sure my sales advice is that you have to align with the executive or the leader who owns the end, the lagging indicator, the end output.

8:47So in our case, we often speak to either the CTO who owns customer-facing applications, customer-facing agents, or the head of that digital business that owns that P &L. Because at the end of the day for them, it's not just that the infrastructure, the ecosystem is not working correctly. It's that their end customer didn't have the experience that was expected, and they're losing transaction velocity. They're having shopping cart abandonment. They're seeing revenue impacted by a technical failure. And that's a very different conversation than I can show you hard cost savings by automating your network operations center.

9:24You can see the difference and you can see why I can build a champion in line of business that then can help me move the needle in the IT organization. So you just sort of have to work the ecosystem. Now, if we've shifted from FOMO to FOGI, And I guess we've just, I don't know if we've just invented that acronym in real time here, but if so, that's a great legacy for all of us. If we've shifted from FOMO to FOGI, then it raises fear of getting in. It raises this kind of evergreen question that all startups and probably all even companies at PagerDuty scale struggle with, which is how do you create urgency in a sales process to get these enterprise buyers to lean in, right?

9:58If there's actually kind of a fear orientation or a nervousness, that's usually cause for bureaucratic process. Let's do it. Let's triple check. Let's do another review. Let's think about it. What have you learned over these years and what advice do you find yourself giving to early stage entrepreneurs and sales teams as they're meeting with customers to accelerate a go-to-market motion? There is no substitute for discovery. And I think when sales teams are in a hurry or founders are in a hurry, I don't see this so much with founders tend to be so curious and they're constantly trying to understand the problem.

10:31But sales teams want the fastest way to get to the money. And so they often will skip the discovery, make assumptions, and then get stuck later on in the process in a different stage of an opportunity. And so really trying to standardize and structure discovery and teach your salespeople and your customer success people how to really understand where the customer is. Because there are some parts of the team, like a lot of enterprise organizations now have dedicated AI teams, and their only job is to support AI adoption in the business. And they're going to move a lot faster than somebody who is maybe protecting their empire or their domain.

11:09So finding the right places to have that conversation is a big part of the discovery process. And in enterprise, one of the things I've learned is, you know, if you rely too heavily on assumptions and patterns, you will miss opportunity because every enterprise looks a little different. And our reps who have been the most successful in the early days are the ones that really walk the halls, really understand what makes the organization tick. really know who actually has power and influence and who doesn't, as opposed to making assumptions about who has power, budget, and influence. Yeah, it's a powerful reminder.

11:42It is the case, isn't it, that as people, especially if they have some early success, early momentum, you begin to kind of ossify around a worldview or a set of assumptions, as you say, about what customers want. And this idea that you have to revisit those assumptions routinely, tune in to what the prospect you're talking to today, what do they really want? What are their pain points? in the drive for urgency, we can forget that sort of basic first step sometimes. 100, 100%. And it's especially more important now because the sands are shifting faster. So like even the playbook that worked for you two years ago may not work for you this year, right?

12:21Even the playbook that worked for you at this customer two quarters ago may not work because one of the other things we're seeing is these organizations are changing and evolving so rapidly, leadership's moving around. You know, headcount is compressing because of layoffs, like people are moving around. So there's a lot more thrash in enterprise teams than there was maybe four or five years ago. And so also just staying in touch with what's happening in that company requires a lot more effort. But at the same time, there are AI tools that can help you do it. Kind of, it reminds me, I believe there's been studies done in like, you know, doctor effectiveness and the patient doctor relationship.

12:58And, you know, most patients, when they go and see their healthcare provider walk out and report that they did not feel listened to or heard by their doctor, right? Because there's this incentive to churn through these appointments as quickly as possible. And that doctors that just take a little bit more time to listen, find that they are dealing then with patients who are much more compliant in accepting the recommendations, right? Like when, if the doctor listens first and then says, okay, you need to take these two pieces of medicine, the patient's much more likely to say, okay, I'll do that versus pushback.

13:25And so being heard is a huge psychological unlock for people. It's a huge foundation to partnership. So most of my conversations when I'm talking to executives in our customer base, whether it's now or nine years ago when we were small, have been, you know, please give me feedback on what you're hearing from your teams, what you think about our products and services, and what I can do to help you get more value from what you've already bought. Yeah, that's great. We had a question come in from a founder, Jonathan from Ursula, who wanted to ask you, Jen, how did you structure early partnerships or pilot programs at PagerDuty before perhaps without overcommitting on product capabilities you hadn't built yet?

14:08Like, how do you think about the roadmap and what's to come and wanting to close sort of early pilots and maybe a little bit of vaporware that's part of all the enterprise sales processes without overcommitting? How do you think about that? We have the opposite problem. We've never been good at vaporware. We're like founded in resilience engineering. So I kind of had the opposite issue here, but I've seen the problem that you describe. And, you know, what I would say is be really clear with a customer as to whether they're part of an early design partnership or whether they are part of, you know, being an early customer in your generally available product.

14:42I think the truth is always on your side here. There's nothing worse than having maybe an exaggeration catch up with you in the form of disappointment with the customer. And it leads to churn. It leads to bad word of mouth. It leads to a lot of things that are much more damaging than just being honest up front and having sort of clear design elements around what is early design, what is generally available. But I also think you can really drive time-based milestones within your organization around how long are we willing to be in early design? Because sometimes I think the mindset of best efforts leads to these early design programs bleeding on forever.

15:25And that just makes them incredibly expensive, poorly controlled experiments. One last question for me, then we'll bring up the founders. So, Jen, you did not found PedroDuty. you joined as CEO and you've done an incredible job scaling the org since you're joining. How do you, what advice do you give founders who are contemplating bringing on, you know, a seasoned exec, maybe to replace themselves as CEO potentially, but even just to fill out an exec team, to be a partner, to be a COO, to be a president alongside them in the journey, what has to be true for a partnership between the original founder and a hired exec to be successful?

16:01Yeah. In any partnership, I think it's incredibly important to very early days and then often on an ongoing basis to have clear expectations on who owns what, who's going to do what. And so in the case of if you were contemplating bringing on an experienced executive as a CEO, no experienced executive worth their salt is going to consider a role where they don't have autonomy to design and lead and operate the business, right? And so oftentimes what I'll see founders do is say, I really want a new CEO, but I'm going to keep finance and product. And an experienced CEO is going to say, that's not a CEO job, no thank you, right?

16:44If you're looking for experienced executives, I think there has to be a lot of intellectual honesty and self-awareness on the part of the founder on what do they know and understand that is unique to the leadership team, where they spike and where they will add a lot of value. What does an experienced executive bring that they know and understand that fills a gap and complements the founder? And how do those two things interplay? Where it tends to come unstuck is when one or the other believes their knowledge and expertise overrides the other person's vision and ideas and that they're not open to having a healthy debate and agreeing to disagree sometimes, right?

17:31But it starts with the foundation of what are the expectations around what you own and what you have decision rights on, what I own and what I have decision rights on. And I'd also say that it requires a lot of humility. I mean, if I had come in and said, I've been at this forever long and I know how to fix all the things that you did, imagine the defense mechanism that's going to automatically deploy. And likewise. And sorry, because we're going to bring Danny up in a sec, but I strongly agree this is self-awareness on both the part of the founder and the exec and then a humility from all parties.

18:06And I think self-awareness often in short supply, humility often in short supply. It's no wonder why a lot of these hires don't work out inside companies. It's a testament to you and the founders of Pajudry that's been such a successful partnership. Let's spotlight Danny, Sheila, Jen. What we're going to do now is five or six minutes per founder, and they'll tell you what they're working on. maybe a couple of questions that you can screen share if you want, Dani, and show the product, and then we'll move on to the next person. So Dani, take it away. Introduce yourself. Hey, everyone. Hey, Jen.

18:33I'm Dani. Very happy page duty customer, mostly because we have no incidents. I'm just kidding. So we started Jam to make software a lot faster to develop. And the bottleneck that we were focused on is how do we make it so that every time a customer has some sort of issue or there's some sort of incident or something has gone wrong, that an engineer can spend time fixing it instead of just trying to figure out how to replicate this issue. So let me show you what we've built. I have here a web application that has bugs on purpose, like this upgrade flow doesn't work. But luckily, I have a really great way to record it for engineers.

19:10I can just share what just happened. It captured what is on the screen. It automatically reduces PII. It grabs everything from the console logs, network requests, AI writes a description, all the repro steps with timestamps for the engineer. You can send it to a ticket. And essentially what the engineer gets is a perfect bug report on the other end. And so you get all the session details, console logs, network requests, and you can send it to an AI to debug it for you. And so what we hear from customers that use it is, you know, before Jam, like something would go wrong and then they would like hop in a screen share.

19:45The PM would get a lot of questions. The customer would have to get questions. And after Jam, something goes wrong, an engineer hears about it, and then it just gets fixed, you know, move on. And so this has been live for three years. A quarter of a million people used it last month to debug almost 800 ,000 issues. It's growing. It's crazy. And then we started to think, well, what if you don't have to report a bug at all? And that's what I'm so excited to show you. We built a product called Please Fix, which allows anyone when they're just looking at the site, if they see something that they want to fix, to not even have to ask an engineer to do it.

20:19They can just fix it themselves. Like they can fix copy or they can change some styles. They can also use AI to change more complex styles. Like I can just say, make this hero section look more like Apple. And an AI will actually look at the page, think about it and do it for me. And when I'm happy with all these changes, it's so easy. I just click publish to GitHub. I'll show you in a second. Okay. I don't love this great background, but I love everything else.

20:56And I don't love the shadow either, but it's really easy to just edit. You can just edit in line like you would edit a Figma. And when you're happy with your changes, you can create a PR. And so I think the change that I'm personally very excited about and very interested to hear your take on is in the past, when someone wanted to see something that they wanted to fix, it would have to be like communicated through product, bubbled up to engineering, prioritized. And in the future, I think everyone is becoming a product builder. And this is uncomfortable for engineers, and it's actually uncomfortable for everyone.

21:28But I think in the future, everyone is going to be an extended part of the engineering team. Everyone is going to be on the product team. I love it. I mean, what I really like about it is you've disrupted the entire workflow and attacked the problem differently. And so AI is a great enabler to that, but it's actually the way you've deconstructed the problem that I think is so ingenious. And the other thing that I like about it is it's kind of hard to argue that this isn't a better, faster workflow. I think for enterprises, one question that they will have on their mind that could potentially become an obstacle or a barrier and excuse is how does this interact with my change controls?

22:13And particularly in highly regulated industries like financial services, where the idea that somebody could just change something from somewhere in the business would make them really nervous. And I'm sure you've got an answer for that. Yeah. And which is, it just pushes to get, and it's the same change controls you've always had. Got it. Got it. I love it. Dani, tell us, and by the way, Dani, if you could stop sharing your screen for a sec, just so we can see the full size. Again, awesome. Tell us, looking forward over the next like six to 12 months, what are you most excited about in terms of how, especially AI is enabling your product roadmap?

22:48We talked to a lot of engineering leaders. We talked to a lot of leaders of support, product design, marketing teams. they are all rolling out cursor licenses for their entire teams. They're feeling very forward-looking when they buy the licenses. And then, you know, actually the licenses don't get used. And the reason is there's a huge delta between having cursor and actually being able to use it because you need to run a local dev environment. You need to maintain your local dev environment. You need to use Git. It's kind of out of the skill set of most non-engineers. And so the thing that I'm very excited about is I believe that at every company, everyone needs a please fix seat.

23:21It's the in-between a cursor and actually a Figma. It's the non-engineer way to actually contribute and make the dream real. And we love reducing toil for human beings. And a lot of this stuff that you're attacking here is really frustrating, paper-cut-like toil, right? So I love that. Is it true, Dani? I hadn't seen stats on the cursor utilization question. Obviously, the ARR growth and customer pace is massive. but is this anecdotal or have you seen data on just like low utilization after people implement cursor? Oh, I think in cursors, like customer base, it's probably mostly engineers. There's probably a very high utilization rate.

24:02When we talk to our customers and they are trying to roll out cursor to their design team or cursor to their customer support team who are on the front line of hearing about fixes, those utilization rates are extremely low. It's the code assistant for everybody else. Yeah. Yeah. Interesting. Okay. Danny, we'll appreciate the demo. Thanks for joining us. And we'll bring Matt Hamill on from Aerox. Hey Matt, do you want to introduce yourself and tell us what you're working on? Yeah. Hey everyone. I'm Matt, one of the co-founders of Aerox. Really great to meet you all. Thank you, Jennifer. Thank you, Ben and Village team.

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24:36I have couple slides that I can walk through. Cool. Can you see my screen? Yep. Awesome. All right. So we are Aerox. We are the AI marketing platform that the best brands in the world use to take action and win this emerging new channel, broadly defined as AI search, historically known as SEO or organic growth, but we'll refer to it as AI search as we go through this. For those who aren't aware of it, the way that you get your brand to show up online without paying for it has changed pretty dramatically over the last really like six to nine months as consumers have started using ChatGBT as both a supplement and a complement to traditional Google search.

25:24And Google has actually changed the way that they surface results to its users. The simplest explanation and biggest delta in how you used to grow your business organically to what's needed to do that now is that in the old world, an SEO team, an organic growth team could rely on reorganizing information either already on their site or already on the web in order to drive eyeballs, clicks, and conversions to their site. In a world with instant synthesis that LLMs provide and the new formats that Google via AI overviews and AI mode, and then the way that ChatGPT, Perplexity et al work, really the only way that you as a content marketer, as an organic growth team can drive meaningful visibility and therefore revenue from organic is to create content on your website and off your website that adds meaningful information gain to the models.

26:23And we call this frontier knowledge, basically information that LLMs are not trained on or don't have available in their inference set that answer one or more user questions. So this was always a part of SEO, but it was unfortunately a much smaller part. And this is actually at the core of the problem that we solve for marketing teams. there's a sort of emerging stack of how organizations are thinking about solving this problem the first bounce the ball was really around really leadership teams marketing wanting to know you know what is my number how am i showing up in chat gbp and other surfaces the conversation has really quickly changed to really what can i do about it that's where we started, we spent the last two years figuring out how to create and optimize content and internal knowledge that you can then turn into information that gets you cited, both in traditional Google search.

27:20What are like the couple of key pieces of advice you give if you have a whole corporate thought leadership that's historically been SEO optimized? How do you convert that to be optimized for ChatGPT or whatever? Yeah, there's three ways to do it. But if you have existing content, or three kind of components of refreshing your existing content, one is structural. So is the page and the content structured on it designed to be read by LLMs? That's probably the most straightforward and I would say the least brand risky element of what we do. The second is the depth of content. So is the content on your site actually answering the longer tail queries and conversations that people are having with Chatshubut?

28:00In the old world, you'd ask Google kind of like one thing. Now you're having 40, 50, 100 line dialogues back and forth with the model. And so whether it's your product page or a blog post or a product listing, if you're an e-com, the ability to have really rich FAQs and contextual information to answer those, you know, the 14th and 15th back and forth with ChatGPT is the depth. All right, just to plug, because I think that's really interesting. So yeah, because historically in enterprise software, there'd be like 20 FAQs. In the new era, you need like 2000 FAQs structured in Q &A format, right?

28:33For easy ingestion. Yeah. Structured in Q &A format or sort of like written in a way that can be picked up and synthesized by the LM. So there's some fairly technical. Sorry to interrupt, Matt, if you might just turn off screen share, but then Jen, do you want to react just to the general category? How are you thinking about thought leadership at PagerDuty these days in the AI age? Yeah. I mean, I think one of the things that we're seeing evolving is the way companies need to operate has to change and it has to change fast. And so a lot of the old tenants that supported DevOps or even digital ops no longer really hold true because they're very people-centric, right?

29:10And now you're orchestrating people, machines, agents, et cetera. And so there is a big opportunity to own territory in terms of how the ecosystem is going to transition, but there's also a ton of noise. Everybody has an agent. Everybody has an agent suite. So cutting through is really hard. And then making that transition quickly from traditional SEO, you know, but like you want, it's not about people navigating it anymore. It's about how does, how does the information get to people through the new channels that they're going to get it? And I think it's a tough problem. How do you help? How do you help unstick people from doing things the way they've always done it?

29:52Because it's scary. Yeah, we actually, we've, we've sort of built the right system to operate this channel in the kind of like future world that I that what I was describing, we call that process or that kind of set of jobs to be done content engineering. It's one part internal context minding. So finding the like sources of frontier knowledge that I mentioned, it's one One part, stakeholder management, getting brand, PMM, legal compliance product on board with content that you're going to expose to still human users, but also agents. And then one part, taste and actually being able to kind of like write well and build the logic of how you talk about the brand into workflows.

30:34The unfortunate or the challenging part is that set of skills doesn't exist natively in most, as this is true of other elements of kind of like AI first teams, right? It doesn't naturally exist natively in some teams in some cases. And so we've invested a ton in enablement. We have a recurring two-week live cohort course, a very similar to the way that Clay has kind of like redesigned go-to-market engineering. We're doing the same thing for content marketing and kind of like SEO type processes. But yeah, it's a constant challenge. I'm sorry to let us move to the next person, but I think what you've just underscored a key point, which was Jen was covered at the Grove this week, a lot by a lot of these hyperscale CEOs, which is can people who currently do a job reinvent themselves to do the new job?

31:16And in this domain, can marketers today, content marketers reinvent themselves for this new chapter that Matt, you're describing. And I suppose some will be able to, some won't, but tools like Aerox are certainly, you know, driving that frontier forward. So Matt, thank you for joining us. And let's bring on Sean from Stepwork. Sean, you can take yourself off mute and introduce yourself. Perfect. Hello, everyone. I also have a couple slides that I can just quickly share. Okay. Cool. So really kind of what we're trying to focus on in StepWork is how everyone kind of thinks about automations today.

31:54And in the first slide, Jen, I know you were on the board at UiPath for a couple of years, so I don't need to educate you on RPA and how all that works. But really, there's been like this big evolution in how automation works at companies where you kind of have these traditional players that really pioneered automation at companies where they're automating lots of back office processes and so forth. But the challenge with these kind of traditional methods is you need a lot of consultants. It can take weeks and months to build these processes just because there's a lot of code involved and you need a lot of technical people to build these.

32:27Then came kind of the wave of now API-based automations. Zapier was kind of like the big one that really kicked it off, but there's now been kind of vertically focused ones or ones that are kind of more DIY. And this is kind of where plugging into APIs is really powerful. And you can plug it into LLMs and use things like MCP and so forth. But the reality is not the entire world has APIs. There's lots of things that where APIs just don't exist, whether it's an internal tool or the API does exist, but the parameter doesn't exist, or you're only automating one sliver of your actual process. So really what we've actually done is we've used things like Vision LLMs and actually built the process kind of end-to-end, where we will literally do your exact expense audit in your existing Google Worksheet and actually do this entire process end-to-end.

33:20So to really emphasize what we're doing, we're literally mimicking the exact human behavior that you would do at an organization of logging into the applications, taking screenshots if this is your activity as an IT person, collecting all the user data, uploading the CSVs, and everything that you see have happened in the first two demo videos is real flows that are actually live in customer environments right now. So rather than just automating one sliver of the process, we've literally automated the entire process end to end. And that's really where the power comes into play. Everything that you see on the bottom of these applications, these are very popular applications, but a lot of them just don't have APIs to like automatically provision this user.

34:04One of the big ones is like plot code. Danny mentioned cursor, like everyone's manually provisioning cursor and then trying to figure out if people are using it and then like manually removing it. And it becomes this like juggling act that IT has to do. So the real question that you probably have is like, how do we actually create these processes or these workflows? So what the user just does is they actually just record their existing process of what they do. And then we built kind of the engine and infrastructure to actually build these flows for them. We actually test them at really high volume.

34:37And then we support all of their existing login. So everything that you see is also happening locally. So we're able to touch super sensitive information that like$100 billion enterprise wouldn't want to tell us who are offboarding. But everything is stored locally. So we can do it with really high percentage accuracy. And it's really ends off experience. And Sean, let me just stop you there for a second. Jen, do you want to react or questions on what he's building? Yeah, I think it's really interesting because again, this is a lot of toil. And by the way, I think I spent a 10th of my life logging into things.

35:07So if there were things that I didn't have to do anymore, that would create capacity for me to do higher value work. And when you say that it's local, I actually think that's really smart. And a lot of our highly regulated customers are really concerned about access to their data. And when you see an automation capability like this, you wonder what bad actors would be able to do with this kind of hyper automation at scale. So I think security is going to be a really important part. Demonstrating the security and resilience of your platform would be really important. It's like you don't like to hear when Okta gets hacked.

35:41Like I wouldn't want to hear that somebody who has access to all my login methodology has a leakage issue. Yeah. Yeah. Yeah. So we already got approved at like a company that is very similar to Databricks, but we'll not say the horrible name, but we're like, as long as we pass that security review or this type of product, we are very like confident and everything kind of was set up natively to be done locally. So you only get the service accounts that you want. It's not actually your own credentials. So it's a very like common setup that they do. Something that I believe in that I think is important for all leaders is you should only be as confident in your security as you were the last day you were secure?

36:20Because every day there is somebody trying to attack your environment or soften your resilience or make life hard for you. And they're getting much more sophisticated. Yeah. Yeah. We honestly, probably half of the kind of execs that we sell into are CISOs. So we kind of, it's like a double whammy where we get validated by them and then we just automate their process for user access reviews. So that's one of the pitiful ones too. But yeah, I think the only last slide I had here was just on really the amount of use cases that kind of can explode now that like you're not reliant on APIs. The traditional way that people try to think about automations is, okay, do they have integration?

37:00Do they have an API? Can we build this? And maybe an AI team comes in to kind of build these things. But if the API doesn't exist, it kind of goes back to, okay, well, we'll do part of it automated and then the rest will kind of process. process. So the way that we think about it is like, if you record your hour long process, even for things like FedRAM compliance that we're doing for organizations, it's like the end to end process. What's your monetization model? Yeah. So we do consumption based. So we do on the number of steps that are actually being done, almost like a direct comparison to labor in the market.

37:32So the best way we do it is like, do you want to pay someone to do this on your team? Probably not. This is not enjoyable work of copying and pasting and clicking things. And this is the best work to automate that is like hyper repetitive. So most ICs love giving us the screen recording because they're like, do this. I do not want to do this ever again. So if you do this, I will be very happy. Well, Sean, by copying and pasting and clicking things you've just described, it feels like most of my days. So I guess there'll be automation soon for all of us. That's the future economy. Sean, thank you for joining us and for those thoughts.

38:02And last, but certainly not least, she will bring on Sherwood Callaway and Sherwood will have you introduce yourself and tell us what you working on? Yeah, thank you, Ben. Thank you, Jennifer. Really excited to be here. Excited about the opportunity. I am the founder of a company called Sazabi. Sazabi is an AI native observability platform. So you can think of it like a data dog or a century, but rebuilt from the ground up with AI and also built to be used by AI. I think a lot of us probably already agree with the premise that AI has completely changed the way that we do software development. And a lot of organizations, especially mid-market and down-market, you'll see AI is writing like 90 % of code today.

38:39And as a result, devs, they can ship these huge changes in minutes or hours. And, you know, sort of, as we all know, I think that when you move fast, like you tend to break things. And so there's this explosion of software and also a proportional explosion in bugs and outages. So Sazabi is addressing this problem with a pretty radically different approach to observability. So for one, we only deal with logs. Traditionally, observability, there are of three types of pillars or types of telemetry, logs, metrics, and traces. We are able to just leverage logs and that gives you enough of the information for the AI to actually root cause real issues and understand the state of the system.

39:16And it also simplifies a lot of the rest of the platform. We also don't allow users to do structured queries on their telemetry. So instead of being able to go into the dashboard and do lots of different searches over these tables of logs and construct these sort of SQL-like queries, we force users to actually just communicate with our agent, which has access to all of their underlying salinity. And then finally, we have a pretty novel approach to monitoring that involves just an agentic anomaly detection. So you no longer need to create and manage and triage all of these manual alerts. And we'll let Jen react to that, but just one more thing.

39:49What's a key go-to-market or product challenge that you're reflecting on as you look ahead? One of them is pricing. I think that AI makes pricing complicated and it's both an opportunity and a challenge. Traditionally for a observability platform or a tool like a log management solution, you would charge based on ingestion and indexing. I think that is a model that we could pursue and it's one that we're seriously considering, but there's also inference cost and outcomes-based pricing that we can investigate. And I think that actually unlocks some really big opportunities for a new tool like us.

40:20I'm so glad you mentioned this because Jen, a lot of founders are asking questions about pricing these days and sort of the AIR. How are you thinking about it at Pave to Duty? What advice would you offer? Pricing is hard. I think one, you have to approach pricing as not a tactical enabler of monetizing your business, but as a strategic foundation for how you communicate your value. An example is in the world of seat-based pricing, where you're starting to automate more and more of the things that people did, you become more and more distanced from the value you create by just counting seats. Right.

40:51And so the market right now doesn't like seat based pricing. They like consumption based pricing. But the challenge with consumption based pricing and we here in the market, our customers are like, can you help me reduce my observability spend because it's out of control and I can't deal with the unpredictability. I can't if I wasn't writing a 30 million dollar check for monitoring, what could I be building? right and so I think that it really starts with where are the unit economics for the customer that denote value they achieve through your platform start with value realization and then make sure that whatever pricing metrics you choose those are tied back to value realization so it's fun to talk about outcomes but if there's any negotiation on what truly was an outcome you enabled the customer to achieve or that they could achieve on their own they're not going to pay you for it.

41:41So the other thing I would say is that the simpler it can be, the better. And then build the instrumentation in your product to make their consumption or their investment transparent. Nobody likes surprises, right? Like predictability is everything for people who are trying to manage margins, manage gross margin, manage their OPEX, et cetera. So a lot of times we build these pricing models and the customer's like, how do I know if I do this? How do I control it, et cetera? And some companies don't want their customers to understand the price engineering because they want to get them hooked, right?

42:19But that transparency is becoming an expectation. It's so funny you mentioned that. I think that if you were to go to the data log storage or congestion log management solution pricing page, that's how it would feel. You would need to be a rocket scientist in order to accurately predict your bill there. But I know that we're short on time. So I do want to share a quick demo. This is the Sazabi platform. We've been working on this for just about three months. So you'll see it's already looks like pretty significantly different from a tool like Datadog, which would have tons of modules and dashboards and blinking lights.

42:49I've got a few prepared queries, example queries that a user might ask. And so you can imagine being a developer and wanting to just understand what the state of the application is. So you might ask a query like this, how is the app doing today? Do you see any issues? And then our agent's going to begin searching some of your log data. This is all log data that's been sent to us through our OpenTelemetry compatible log ingestion and storage system. So just like Datadog, you can send your logs to us via basically any method that's available in any programming language, any logging library. You can see here in the response, it's able to diagnose and investigate the different services in our application.

43:27It looks like things are pretty healthy today. We also have a generative UI component. So our vision here is that the AI will begin actually illustrating the system to you using elements like time series, tables, pie charts, other components that you would see in a traditional observability platform, but doing it dynamically, sort of like using progressive disclosure to bring the most relevant part or the most relevant information into the foreground as you do an investigation. I can search for recent errors.

44:10This one looks like a kind of gnarly one. It's a thread not found. It's able to describe it to me. I will have to stop you there just given time, but that is super cool. I actually haven't seen that demo before. I love the cleanliness of the interface and the simplicity of it. You can imagine how DevOps is going to change a lot in the coming months and years because of that. Sherwood, thank you very much for joining us. And Jen, one last question for you before we wrap in the Village Global spirit. every great CEO requires a village to get to where they want to go. Who is somebody in your life or career outside of family that's been instrumental in your career success?

44:41And what did they teach you? I have a posse of other CEOs, retired CEOs, sitting CEOs, who I rely on a daily, weekly basis to compare notes, commiserate, empathize, just feeling a connection. You know, there's an old saying that it's lonely at the top and only a CEO understands truly what that means for another CEO. There are a lot of things as a CEO that you can't tell your family, you can't tell your board, you're not ready to tell your board or wherever the case may be. And I think having a village of people that are in a very similar position under the same pressures, but also with the same privilege and opportunity really makes a difference.

45:29And so right before COVID, I invited a bunch of other public SaaS CEOs over to my house for dinner. And that became a weekly SaaS connect during the pandemic, which has resulted in lifelong friendships and peer mentorship. And so there really isn't one person I can name, but there are many that have emerged. I mean, Zach Nelson, who was the longtime CEO of NetSuite is on our board, I'm very close to Mark Mader or Hayden or Yamini Rangan and HubSpot. Like these were all relationships that were built from having a set of common problems, but also being willing to make the two-way investment. Like you don't go to that community to just get support.

46:09You invest in that community yourself on a daily basis. And we're all available on a 24 by seven. You need something. It's time sensitive. You text any one of us and there's an understanding that we'll be right on the phone with you. Well, thank you so much. That's a lovely note to end on very much in the spirit of everything we're trying to do here with your support and your investment, helping enable Danny and Matt and Sean and Sherwood and everyone to be building in the future. So, Jen, thank you for your time. We really appreciate it. Thank you, villagers, for joining us. And we'll see you next time.

46:37Well, thank you to all of the founders. It was so inspiring. And thanks, Ben. I appreciate being part of this community as well. So have a great day, everybody. Thanks so much for listening to the Village Global Podcast. You can check us out online at villageglobal.vc. We'd love to hear from you, your feedback, your ideas, your inspirations. You can email us at hello at villageglobal.vc.

From the publisher
Jennifer Tejada is CEO of PagerDuty, a public company serving 30,000+ customers worldwide. She joined Village Global GP Ben Casnocha for a masterclass on scaling in the AI era, followed by live feedback sessions with four founders building AI-native companies.

Takeaways:
  • Enterprise sentiment has shifted from “fear of missing out” to “fear of getting in.” Customers are anxious about security, resilience, and managing the people transition.
  • Know what gets your customer promoted and what gets them fired. Different personas care about different things. A CIO has different anxieties than a developer or CMO.
  • Pricing is a strategic foundation, not a tactical enabler. Start with value realization for the customer, then build pricing metrics that tie back to that value. Consumption-based models are popular, but predictability matters more than novelty.
  • Transparency is becoming an expectation. Customers want instrumentation in your product that makes their consumption and costs visible. Nobody likes surprises when managing margins.
  • The AI transformation is moving faster than any previous shift. Old playbooks don't always apply. The people willing to embrace change and experiment with new ways of operating will win faster.
  • Build your CEO village. Having a trusted network of other CEOs who understand the unique pressures of the role makes all the difference. Invest in that community on a daily basis.
  • Psychology matters in people transitions. Asking employees to use AI to replace themselves won't work. Think differently about how you organize to get work done while helping people transition to where they can add value.

Thanks for listening — if you like what you hear, please review us on your favorite podcast platform. Check us out on the web at www.villageglobal.com or get in touch with us on X @villageglobal.

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