Inspired with Alexa von Tobel
00:17:55 · May Habib
[00:17:55] S0: Yeah. So Writer wins in AI when there are two or three requirements that a company has. When a use case requires high precision, high quality, high consistency and reliability. Right? People choose Writer. A lot of these use cases tend to be front office, tend to be sales and marketing. Right? If you are now really semi automating the way a wealth advisor communicates to a client after they have a sit down meeting, right? Everybody records calls now. We've got a great CRM. It's captured everything. But really being able to understand what does Alexa need? What are Alexa's financial goals? How do I bring the best of what I know about Alexa with really what my organized knows about Alexa. Right? A a lot of what we do is make explicit what the organization knows implicitly, but doesn't apply consistently. And the thing with other AI tools is you can go ask Copilot or ChatGPT, you know, the same question asked 50 different ways by 50 different people, and you will get, you know, 48 or 49 slightly different answers. And that's just not... That doesn't pass the bar, right, in these regulated industries. And so in healthcare, in financial services, in CPG, there are millions of use cases like this, right? Micro use cases. But they all really ladder up to better high end customer support, customer service. They all ladder up into making relationship selling much more productive, much more consistent, better user outcomes, better company outcomes. And so much of the front office is really calcified into these systems of record that don't talk to each other and produce, like, pretty rigid business rules. But so much of this type of selling is dependent on unstructured information, unstructured know how. Right? And the beauty of AgenTik AI is it's really good at the unstructured. And so, you know, we really shine in these kinds of use cases. Most of our customers are in highly regulated industries. But we've got a lot of technology customers too. Microsoft, Salesforce, Nvidia, HubSpot, Qualcomm. Lots of folks who build their own AI use Writer in front office because a much more scalable solution. Because if you are now going to automate something, if you're gonna gentify something, you've gotta be pretty certain that the guardrails are there, right, for you to get the kind of outcome that you need. One of
00:20:58 · Alexa von Tobel, May Habib
[00:20:58] S1: the things I wanna give you a compliment on, which is Writer has built an incredible reputation on responsible autonomy, creating agents that act independently but remain really aligned to a company's values and compliance. I was Chief Digital Officer at Northwestern Mutual of Mass and Financial Firm, so when Yeah, you talk about [00:21:15] S0: they're also a customer. [00:21:16] S1: Yes. So when you talk about, you know, how much it matters that you can trust these autonomous agents to stay on brand, stay on brand values. Talk a little bit about how you've maintained trust at scale, because that's something... Obviously, you're ten years in, so you've had a lot of time, but that's a really hard thing to get, right, and to thread that needle, May. How have you done that?
00:21:42 · May Habib
[00:21:42] S0: Yeah. You know, the the way that we... I I kinda wanna answer your question in a meta way, because we're having, like, a philosophical Yeah. Love it. Let's do it. You know, like, a lot of the the trust we build is by not trying to do anything else other than make these customers successful. Right? If you look at the hyperscalers, you know, they're really trying to sell compute. And the, you know, labs have become full stack, but they're really still LLM API companies. You know, our ability to go in and say, we are the only full stack player that is not trying to do anything else means we can say, look, this 10 step process that you have to do this thing doesn't make sense anymore. We're not gonna just shift and lift it to AI. It really should look more like three steps. Right? And a lot of that is really questioning the assumptions around business process and org design and the calcification of legacy systems. Right? And so think of the question you just asked around brand and compliance. We can bake that in from the very first draft, but your compliance officer has to be Gabe. Right? Your brand team that may actually report to a different leader than digital, we see that all the time, right, has to be able to sit at the same. And so, you know, our technology forces a conversation because it is built in a way that agentically all the systems are talking to each other now, right? Like these silos don't exist in Writer. In natural language, you can get the guardrails to talk to the best practices, to talk to the customer data, to talk to the brand brain. Which means people need to now make decisions on how to operate more effectively and really get on the same page as to their goals. And I think the way we've built trust over time is to really never be selling anything beyond that, and to challenge the customer the way that we challenge ourselves. Sometimes our account teams are like, May, did you just kind of yell at a customer? I'm like, no, it's not yelling. I promise you they appreciate it. And the customer does come back and say, thank you for challenging me. Like, I kinda needed that kick in the pants, you know? And we do, like, that's, we we ask people to really question their assumptions. Like, what assumptions about your industry do you take for law that actually aren't? And, you know, we are looking for radical partners. Right?
00:24:19 · May Habib, Alexa von Tobel
People who are really willing to rethink their business, reinvent around AI versus sprinkle a little on top. May, one of the [00:24:27] S1: things that you're really talking to, and I I really wanna double click on it, which is there was so much surface area you could cover with Writer. At the end of the day, you're building agentic AI that can do things like write front office facing emails. You're you're focusing on companies that are heavy in compliance, health care, financial services. That's a lot of service area already. And one of the things you just said, which is that you guys have been maniacally focused about doing nothing other than that, And you even talked about some of these big companies, the very successful ones are calcified, and and their technology, in many cases, are decades old. Fifty years, seventy five years, eight... A hundred years. Northwestern Mutual, hundred and sixty years. Steadily, what you're saying is that your maniacal focus has just been this compounding benefit of trust because you are only promising to do one thing and do it extremely well with companies that probably are a little reticent to adopt AI because it's so new and they cannot afford to fail. How do you maintain focus? Because there's so much surface area you guys could cover, and I know how bright and ambitious you are personally. How do you keep everybody focused? What are your tricks on that?
00:25:47 · May Habib
[00:25:47] S0: Yeah. I mean, we we we... We're a we're a horizontal platform. Right? And so a customer, if they've got engineers and they're a sophisticated player, we've got the enablement. And people tell us all the time, like, I learned in an hour what had taken me weeks to do in Copilot studio. Right? We we get that a lot. But when we're selling to the Fortune 500, not everybody's got the engineering team that, you know, the creme de la creme financial services companies have. Especially in CPG and retail, like, a lot of these teams are badged to SIs. Right? And so we need to be able to make it very easy for the businesses' most technical people. So these might be data analysts, data scientists, to be able to really configure and customize and connect on their own without a lot of engineering support. And so, you know, we've been very user friendly both for technology heavy users and savvy users as well as, you know, your sophisticated business operations person from day one with a focus on front of office. And by being able to like really focus on front of office, we can get the customer to value in those first three to six months and we spread from there. And the first couple years really was like Wild West from a use case perspective, right? Like we said, okay, regulated industries is who cares the most about reliability and consistency at scale? Like AI slop, by the way, bothers everybody. But like inside of the Fortune 500, AI slop like gets people fired, right, in a way that just doesn't happen in other industries. So the focus on front office use cases has really been a result of like go to market focus versus platform focus. Like we are still a pretty horizontal platform. People use us for back office and finance and HR all the time. But in terms of, like, what we're trying to get a customer to do in the first ninety days and, you know, what connectors we're trying to hook up, which users we're trying to onboard, You know, there's a very strong sales and marketing bias.
00:28:04 · Alexa von Tobel
[00:28:04] S1: I wanna transition for the sake of time a little bit to where the world is headed. And again, like, you have been a thought leader in the category. You've been in this category for over a decade. And again, one thing I didn't even get to give you a nod to. You build your own foundational model, just like truly the the technical chops and the forward thinking that you have had have proven to be quite strong. Where is the world headed in your mind? And just give us a sense if we wake up in 2035, what does the world look like because of AI in your mind?