Building Maz: Inside the Strategy Behind Ninety’s AI Tool

Mark Abbott

[0:00:05]

Hey, tj. 

TJ Kneale

[0:00:07]

Hey, Mark. How are you?

Mark Abbott

[0:00:09]

I'm doing great, man. I've been looking forward to this for way too long. How long have you been with us now?

TJ Kneale

[0:00:19]

Just over a year and a half, I believe.

Mark Abbott

[0:00:20]

So 18 plus months.

TJ Kneale

[0:00:23]

That's right.

Mark Abbott

[0:00:24]

And you were brought in for a very specific purpose. Could you share with our audience what we brought you in to help us do? Because I think it's pretty cool work that you're doing.

TJ Kneale

[0:00:33]

Yeah. So I don't know if our audience is familiar with the term mas short, short for Maslow, and Maslow's Hierarchy of Needs, which is the name that you had given a long, long time ago, a decade ago, more to.

Mark Abbott

[0:00:50]

Yeah, it was Jarvis back in 2012. And then we thought we couldn't get away with Jarvis. It was with two Rs. And so we. We switched to. Actually, we switched to Henriks and then we switched to Maz. But in hindsight, we could have done Jarvis. So that would have been kind of cool. But anyway, it's all good.

TJ Kneale

[0:01:10]

But in any case, the AI personality that you had envisioned for a long, long time to make an integral part of the 90 experience, and it would.

Mark Abbott

[0:01:21]

Be great if you would sort of share a little bit of your background, because, you know, I think it's super cool background, but that's me. I think others will as well.

TJ Kneale

[0:01:30]

So I'll share the Twitter version and we can dig in if you want to dig in further. I do have a bit of an unusual background for somebody in the tech industry. I spent 24 years in the US Navy, so I was a fighter pilot, a test pilot, and then on into product management for the Navy. So when I left there, I was leading a $6 billion portfolio of software, avionics, and modeling and simulation products for the F35 program, which many people won't know, but that's a new fighter that we're buying. And that was awesome, but also, like, super frustrating to be stuck inside one of the world's largest bureaucracies. So the other threat to pull on. My background is around innovation, which is kind of a tired word, but it sort of does the trick. I spent a year at Autodesk as a fellow on their strategic innovation team, where I did a bunch of work on human machine collaboration. After I left the Navy, went to work for a company called Alpha in Barcelona. Alpha is Telefonica's Moonshot factory. So think like Google X would be the closest analog, using radical new tech to create social impact. I was the head of Moonshot Launch. There but most of what I worked on was an AI tutor and that was super interesting work. It was out of that that I was introduced to the co founder of my last company and we went out and raised a couple million in venture capital to unlock the world's cognitive surplus in the workplace. And so really the past, you know, five years before joining 90 was really all focused on this intersection of the future of learning and the future of work. So when we were introduced and I heard about your vision for MAS and got to dig in a little deeper to how we might be able to help folks learn and succeed in workplace environment was really, really exciting and exciting to, to come on board to help turn that into reality.

Mark Abbott

[0:03:29]

Yeah. And, and another, I think there's several cool parts to our story that you didn't get into. One of the things that I kind of think is cool is not only, you know, is, is your background kind of unusual in terms of, you know, jet fighter pilot and then, you know, going into the procurement and then et cetera, et cetera. But if you go back to high school, right, your background wasn't traditional jet fighter pilot background, is that fair to say?

TJ Kneale

[0:03:59]

Oh, well, I don't know. I guess there's a, a stereotype as fighter of fighter pilots as, as jocks.

Mark Abbott

[0:04:06]

Yeah.

TJ Kneale

[0:04:07]

And I did play football in high school, but I also was very active in drama and music, so did a lot of plays and show choir and that sort of thing as well.

Mark Abbott

[0:04:16]

Yeah. And I think the thing about that, that I've come to deeply appreciate about you is sort of the, the humanistic side of you.

Mark Abbott

[0:04:29]

Right.

Mark Abbott

[0:04:30]

And, and the approach that you've taken since day one in terms of, you know, building the team and just sort of the, the deep belief in, in, in the importance of a strong culture and leadership and coaching and we'll just call it the, which once again, you know, I'm not from the military. We do have our stereotypes.

Mark Abbott

[0:04:52]

Right.

Mark Abbott

[0:04:54]

But yeah, I think it's, it's a part of, you know what I'll say. This is the unique tapestry associated with TJ Neal. And the second part of the story is that a very dear friend of mine who's actually on our board is also a dear friend of yours. And that's how we got introduced. Right. Rob Toomey, who's the co founder and president of, I can never remember he's president or CEO along with Carly's wife, but the two of them run type coach, which is what we believe is the premier sort of personality communications based, you know, system that Leans into the Jung, sort of the Hume, the Jung, Myers Briggs type ology. You know, Rob's been a super close friend of mine since 2012 and, and you guys met in Barcelona when you were there and, and became pretty strong friends as well. So we, so Rob introduced us and we pretty much started to align on what we thought AI could do. You obviously had your money where your mouth was several points prior to that. And so it was a pretty swift sort of meeting of the minds and meeting of the mission. And as you said, now it's been over 18 months and one of the things that, you know, I think that, you know, you and I have been deeply aligned on is, and I want to go here now is, you know, it's been 18 months and AI has been, you know, a thing for, you know, like people talking about it in terms of the product side of the, of, of software and of course, just generally in terms of society. Since Chat GBT came out in, you know, in late 23, you came on, you know, literally at the end of 23. We were hired right at the end of 23. And I don't think when we hired you, I'm trying to think through this. I don't even think ChatGPT was very. Well, it wasn't like a big thing, you know, where everybody was aware of it. So, you know, we started down this path together and unlike a lot of people and companies that we've seen over the last 18 months, you know, we've been focusing on trying to figure out how to do this right as opposed to putting something into the world. So I'd love for you to sort of talk about sort of the, the whole, you know, sort of thinking through how to do this well, coming onto the team, thinking about all the implications, the human side of the implications, the delivery side of the implications, dealing with, you know, the pressure of trying to do something in the marketplace. But also, you know, one of the things we talk about all the time is, you know, we deeply believe we need to build high trust relationships with all of our customers. And so putting something out and just, you know, and, you know, sort of something like this, something of this, in my opinion, importance and power was something that neither you nor I ever took lightly.

TJ Kneale

[0:08:18]

Yeah, you know, it's true with the rise of ChatGPT, GPT3 and subsequent models that there was this kind of gold rush mentality in the product tech space where everybody was just slapping AI in whether it belonged there or not. And it made for a lot of really, I think, terrible Customer experiences. And I think if, if you think about the, like, the Gartner hype cycle, that as a nation, we're probably somewhere in between the, the peak of inflated expectations. And I forget what the valley is after the valley of disillusionment, the trough of illusion meant. And I think that as individuals, where we are on that slope is greatly influenced by the kinds of product interactions that we've had. And folks that have interacted with a lot of these sort of inappropriate uses of AI are way down in the trough of disillusionment. So, you know, my take has always been that nobody cares about AI in product. They just care about doing the thing that they came there to do. And if AI helps them do that thing better, faster, more effectively, then it's great that it's there. But they don't care about the AI. They just care about the outcomes. And that's where we started the conversation is how, you know, what are people here to do and how do we help them do that thing better? And that's been the, you know, the guiding principle, if you will, of, of our, our implication or our integration of, of AI throughout. Yeah.

Mark Abbott

[0:09:47]

And I think that, you know, part of the area where there's been really super in a healthy tension and I, and I, and I mean this in all sincerity, and I'd love you to be obviously sincere about it as well, is I think, you know, when you, when you first came on, I dumped my vision on you, right? And this is where I think, you know, where it's going to go. This is how I think it can help across all these different tools and, and, and, and disciplines that I think great companies should be, you know, should be taking advantage of. And so we had this big vision and then it was like, and, you know, the story I always share internally is, you know, I want that we all have a sense for where things are going, and most in particular, because I want to avoid what I like to refer to as the Animal House scene, where all the, you know, the band gets taken into the, into the, into the dead end alley and everybody's trombones break and so just align on the vision, align on where this is going, and then, you know, work our way back to what makes sense given where the technology is. And then where you, you know, you've been really strong and, and focused is now, okay, so this is, this is, this is where we want to go. This is what we can do right now or where the technology is capable of helping us. Now the question is, what's the what are the first two or three things that we think can be most powerful in terms of leveraging, you know, the capabilities of the technology. So if you wouldn't mind, I think it'd be cool for you to sort of share, you know, the little bit of the journey that you've had going from, okay, here's this crazy founders vision right now. What's the. What's the smart thing for us to do? And in particular, I think maybe leaning into a little bit of the, you know, sort of the vision versus pragmatic side of introd, you know, incorporating technology of this capability into a platform.

TJ Kneale

[0:11:57]

Yeah. Yeah. So, you know, one of the things that I learned as the. As the head of Moonshot launch at Alpha was, you know, we had these. We created these visions that were almost by definition, at least 10 years of work to get to that thing where, you know, future casting, building a desirable future, and then. And then back casting to wait, what do we actually. How do we start? And what's the roadmap to get there? And so I was working with this team of ideators, which is very, you know, expansive and fun. But then my job was like, okay, well, what do we actually build? Who do I hire? What's the first thing that I deliver? And, you know, one of the first lessons I learned was that a societal problem is different than an individual's problem and something they're willing to pay for. And so sometimes the first step in deciding where you're going is figuring out how to translate that big vision that solves a problem for society into a real pain that a customer has right now that they're actually trying to solve. And so for 90, I think we were very well aligned on the Moonshot vision of creating a career mentor for somebody that can take an individual throughout their career, build with them along the way, steer their business in the right direction. It takes a while to build that technology, but, boy, right now, when people come to 90 and, you know, I'm excited that we've got this new draft rock functionality in Maz out to our customers, one of the hardest things that they do is look at all these blank spaces in our app and try to figure out how to fill them in. And that's the real work that they're there to do, is figure out what are my quarterly goals, how do I come up with that, how do I make sure that I actually achieve it? Because what we see is people write some stuff down, but then they don't achieve it because they weren't well thought out. They didn't go through the right process. And so this is a great application as a first step. It's a real problem that our users have. And we can leverage what AI is good at, which is acting as a thought partner, keeping the user in the thought leader position and helping them walk through as a foil perhaps for, you know, their worst instincts to just blast through something and drop it into the app and move on. And we've seen that that's really, really effective. Getting lots of great feedback right away. And I will say that in terms of a first step, another reason that this is good is it allows us to focus on a very specific use case, which means that we can apply our opinionated framework for how to do things in a very effective way. If we try to do it everywhere, all at once, often very difficult, but in a narrow use case, we can be very effective. And so we can build up a collection of those tools that apply our principles so that we are bringing that opinionated framework which is one of our biggest values to our customers.

Mark Abbott

[0:14:55]

Yeah, as I shared with you before we got on to recording this, I was literally coaching a client today and it was my first time, you know, having Matt help us in session. And, and, and, and honestly, and I say this like, you know, almost with a little bit of embarrassment, it was asking better questions than I typically do, you know, and, and, and, and it, you know, it was Claire asking great clarifying questions.

Mark Abbott

[0:15:31]

Right.

Mark Abbott

[0:15:32]

I think. And, and, and, and once you start to go down like, oh, if it could help here, if it could help here, but you know, just the simple thing of, of let's just make sure, you know, you rock smart, right. And, and, and for those of you, you know, at home who know all about smart, right, I'm going to share with you that we've actually tweaked it. Right. So it's, you know, it's an acronym, right. So it's specific, measurable, attainable, relevant and, and timely. And we've switched the R up to return on investment.

Mark Abbott

[0:16:05]

Right.

Mark Abbott

[0:16:05]

So, you know, make it specific. What exactly is the end goal? Make it measurable.

Mark Abbott

[0:16:11]

Right.

Mark Abbott

[0:16:11]

How can you measure that? It's generating, you know, the value that you think it can generate. Make it attainable, obviously, let's just make sure that this is actually something that can be done given whatever, you know, constraints are out there, whatever roadblocks are out there. And it actually does a really good job of asking about is this attainable?

Mark Abbott

[0:16:29]

Right.

Mark Abbott

[0:16:30]

It asks that second and that third order question, which sometimes people just blow right by right. It doesn't ask right now because we haven't taught it what we do, right? It doesn't ask for, okay, now you know, you know, how are you gonna, what's, what's your sense for the return on investment, right? And then obviously in terms of timely, what is gonna, how, how long is it going to take and what are you going to get done? And then it, you know, it immediately asks, you know, some more questions, but then it immediately delivers, you know, a set of milestones and, and the answers around what, you know, what smart looks like. And then the next thing that this just came to me today, so I'm feeding this to you, right, live here, right, Is you know, we not only at 90, we don't just do rock smart, but we make sure everybody's thought about the racy, right? Who's responsible, right, for helping us get things done. Those are usually with the face and it's the milestone. Then who's accountable? Who's accountable for bringing this rock to close and making sure that rock actually gener generates the value that we were looking for. Who should be consulted, who should be informed, right? And making sure that you know that you're not ending up with what the heck did you guys do? Why did you do this? Why didn't you involve me?

Mark Abbott

[0:17:43]

Right?

Mark Abbott

[0:17:44]

And so, you know, you can immediately see already and maz helping us with rocks. It's how old now?

TJ Kneale

[0:17:50]

We had a proof of concept a quarter ish ago.

Mark Abbott

[0:17:53]

Yeah.

TJ Kneale

[0:17:53]

So this quarter, we've been using it.

Mark Abbott

[0:17:55]

Yeah, yeah. So this quarter, it's in ga. But you can see like, you can immediately see, oh, this is awesome. And now, right, this is the next thing to do. And this is the next thing to do, right. Make sure that as an example that people are, you know, those are in those who you deem to be have, need, need to consult, make sure that they're signing off. I will consult. And by the way, it's going to require this many hours and yes, I will do this or yes, I want to be informed. And then when the rock is done, you know, you hit done. And it's like, well, you know, maybe there's a two step in that. Was it done?

Mark Abbott

[0:18:30]

Right?

Mark Abbott

[0:18:31]

Were the people consulted? Consultant. Were the people who were informed informed?

Mark Abbott

[0:18:34]

Right.

Mark Abbott

[0:18:35]

Were the people that, you know, ultimately were responsible? Did you actually call them out in the beginning? So I mean, you know, I just sat there today with my client and we're sitting there going, geez, right? We just had this, okay, now it can do this. Now I can do this because it has access to obviously all these humans in the platform. So, you know, it's, it's funny because we look at that as, it's actually, I look at it as the second thing we've done with mas.

Mark Abbott

[0:19:00]

Right.

Mark Abbott

[0:19:00]

Because I also think maybe. Is it. Are we in beta or are we in GA with, with the, with the meeting prep stuff?

TJ Kneale

[0:19:09]

The meeting prep functionality is in beta. Yeah. And we should also not forget the onboarding companion.

Mark Abbott

[0:19:14]

And the onboarding companion. Right. So we have NAS inserted, helping with three different aspects of the, you know, helping our clients, you know, turn their visions into reality and helping them understand what's working and what's not working. But yes, we have three different efforts underway. Two are in ga, one is in beta. And, and what's fascinating is, is sort of taking this crawl, walk, run approach you've done. You know, it enables you to, to, to like you could, you could see. And I, I don't know if the answer is going to be right, but, but I could see us spending some, some quality time just, you know, sort of going to phase one, phase two, phase three. You know, in terms of just what the rocks can do. The meeting stuff is super cool because, you know, it helps you. It says, hey, you know, your meeting's coming up tomorrow. You may want to take a look at these KPIs because, you know, they're off track as an example or hey, you know, there's a number of things going on with your rocks that are, that look like they're going off tracks or hey, there's certain issues and then once you. To connect, you know, the entire plat. Everybody's in meetings. Maz is seeing across the meetings, it's seeing across the KPIs, it's seeing across the issues list, it's seeing across the, the rock progress. It's seeing across what's, what's working, what's on track versus off track in terms of milestones, you know, I mean, you can just. Right, just right there between meetings, Onboarding companion and rocks. It's pretty powerful. And this is just like the very beginning of, you know, proceeding towards the vision. So as someone who's sitting in the seat of pain in, in theory, right, in terms of having to deliver all this and having some crazy visionary going, why aren't you, why aren't you progressing forward? What's your, what's, what's sort of been your, you know, now 18 months and what, what are the, you know, what are the things you, you appreciate today that about trying to do something like this that you, you know, probably didn't fully appreciate 18 months ago.

TJ Kneale

[0:21:25]

Well, you know, it's, it's interesting. I'll say. The, you know, the very first thing that we, we started doing or we started out to do with MAS was this onboarding companion. And my hypothesis was that our customers were going to want help with theory for business operating system work, how do I do this, why is it important, etc. But to test that theory, I put a button in the interface that said, what should I do next? I don't know if you remember this, Mark. Yeah, we got lots of clicks on it which validated the theory. They wanted to know what to do next. But then the questions they asked were about what do I do in the app? Like how do I schedule a meeting? And so we had to. First of all, I'm glad we did that test because our hypothesis was, was wrong, at least in scope. But when we shifted toward that, like those answers were very, very deterministic, very discreet. Step one, step two, step three, and it has to be right or else it's useless. And force fitting generative AI into that solution. Because we had already started down the path of creating this generative AI agent, it took us a long time to make that work. It was a little bit off center from the best use case for it, generative AI. When we shifted to something like the Draft Rocks functionality that we were talking about, boy, it's spot on. It does just what AI is really good at doing. It can synthesize, it can take that information about what are the company's annual goals and does this advance you toward them, for example, and we were able to generate that functionality in really just a few weeks. Now, getting it into the interface and making sure it works from a technical standpoint beyond the AI, that takes a bit more time. But I guess what I'm getting to is what was surprising in that is that when you've made the use case correct, matching the technology, what it's good at with what the user really needs in order to do well, there's a really an acceleration that happens there. So yes, having gotten some really wonderful feedback that proves out our hypothesis about this Draft Rocks functionality, we can apply that same type of approach to things like building a scorecard or building a VTO or building an accountability chart. And when we can start to build that out really quickly, I think going forward. So lots of great validation from our customers that we're going down the right path and that this is useful and lots of validation from the team that this is so much easier to build because we're using it the right way. So I think that we're set to accelerate from here.

Mark Abbott

[0:23:59]

A lot of people these days are talking about agents right through, up and down and throughout the company. You know, Maz in one regard could be seen as an individual agent, but actually I'm curious because you and I haven't caught up on this lately. It feels like every six months or so we, you know, we stand back and look at the vision, the vision paper, our, you know, sort of our, the phases that we thought we were going to go through in order to, to build Maz out. Do you think of Maz now as a singular helper or do you see Maz as sort of a steward of a bunch of agents that are helping, you know, with, in with that are helping on very discreet tasks?

TJ Kneale

[0:24:50]

Yeah. My hope is that over time our users will. The fact that we've built an agentic architecture with a bunch of different bits and pieces that are purpose built for a specific task, I hope that's completely transparent to our users. All they know is that when they ask a question, they get the right answer when they ask for help on something, they get the right kind of help when they're trying to ideate on something to get the right kind of feedback. The truth is that we have built an agentic architecture and we've built purpose built solutions behind that interface. But eventually it's not, we're not there yet. Eventually it will just be a single interface that allows users to do what they're trying to do as they're trying to do it. And all the rest of it is just tech stuff that happens in the background, invisible to our users at this point in time.

Mark Abbott

[0:25:37]

Our original vision was that there would be, you know, basically on a multi agentic, you know, background and obviously our goal is for the IT to feel like a singular, singular entity that that one's dealing with and but it does feel, it does feel like what we thought made sense. Even actually before you came on board.

Mark Abbott

[0:26:03]

Right.

Mark Abbott

[0:26:04]

Because we had the division, I don't want to say it four or five years ago and I, and, and I should say I think I've shared this with before publicly. You the idea behind that. Well, I said it earlier.

Mark Abbott

[0:26:15]

Right.

Mark Abbott

[0:26:15]

The I Jarvis was developed as an idea for, you know, for what the platform in 2012.

Mark Abbott

[0:26:22]

Right.

Mark Abbott

[0:26:22]

So we, you know, that we, we knew this was going to happen. It was just a question where the technology, when the technology would kept up to catch up to the vision and, and, and, and in my, in my world, and this is easy for me to say, who's not an engineer, right? Not a, not, not a data scientist, not, you know, nothing along these lines. My view is that the power of AI today is absolutely capable of addressing all the things that was in the original vision. I mean AI is advanced to the place where we have to obviously have to execute. You need obviously a lot of talented people on the team. But the technology has evolved to the place where the original vision can be delivered. It's my opinion, curious as yours, but I believe the original vision for what we could accomplish here, forget about, you know, the cost and the associated power, but the basic technology has evolved to the place where we can turn our vision into reality right now. Which is super cool. If you agree.

TJ Kneale

[0:27:40]

I think it's probably true. I would add some clarifying statements. Perhaps the original vision imagines a technology that always gets the right answer. The current generative A technology is not that. Yeah, it is, it is probabilistic. It will sometimes go off the rails. However, when we choose the right application for our users and we purpose build guardrails for that application and we keep in general the user in the thought leadership position and AI in the thought partner position. The fact that it might only be an 80% solution is not a problem. In fact, it's a feature. I showed an example of using AI to summarize a retrospective that my team had done and the summary added some points that weren't actually discussed because it was wrong in, in an interesting way, in a context where it was okay and we were still thinking about it, it actually drove additional thoughts.

Mark Abbott

[0:29:01]

Right.

TJ Kneale

[0:29:01]

It drove us to solutions that we wouldn't have otherwise come up with on our own. And so I would say that the technology will continue to improve and by the time that, you know, we have, have built enough to intersect with that, we will absolutely have achieved the vision that we've set out to achieve. But in the meantime, where the technology is now is super, super useful and certainly it's got way more to offer than we can keep up with, if that makes sense.

Mark Abbott

[0:29:28]

Yeah, it's funny, I know, and I hate to argue with you.

Mark Abbott

[0:29:33]

Right.

Mark Abbott

[0:29:34]

But the vision was never to deliver the right answer because I don't think there is a right answer.

Mark Abbott

[0:29:42]

Right.

Mark Abbott

[0:29:43]

I think the vision is to help us think right. And, and, and to make you more self aware of some of the, you know, some of the complexity associated with, and this is my brain, right. But, but it's just like what what mass does today in terms of helping you think about, okay, what are the roadblocks?

Mark Abbott

[0:30:02]

Right?

Mark Abbott

[0:30:03]

What are the, what are the KPIs, what are the measurables?

Mark Abbott

[0:30:06]

Right?

Mark Abbott

[0:30:06]

Who are the people that you need to be, need to be involved in this process? Right? Do they have the resources, the time?

Mark Abbott

[0:30:11]

Right?

Mark Abbott

[0:30:13]

Do they, are they, do they have the competencies required?

Mark Abbott

[0:30:15]

Right.

Mark Abbott

[0:30:16]

You know, asking, to me, asking the right questions is actually from my point of view, that's, that's the real, that's the real important thing, frankly, if it gave you the answers, everybody stop thinking. And now all of a sudden, I think we're running into a different issue.

Mark Abbott

[0:30:35]

Right?

Mark Abbott

[0:30:36]

But so, yeah, to me it's always been about, okay, so these are frameworks that help you think about, you know, it's like, you know, EOS has the, you know, get it wanted capacity thing for, you know, does a person have what it takes to sit in the seat? Obviously there's the, you know, the whole bigger picture around right seat, right. Right person, right seat. Some of the frameworks around structure first, people second. Right. Just, just respecting those frameworks and helping people think through how to genuinely respect the power of the framework.

Mark Abbott

[0:31:07]

Right.

Mark Abbott

[0:31:07]

And you know, back to, I've said it a thousand times, maybe, maybe hundreds of thousands of times, right? You know, the map is not the territory.

Mark Abbott

[0:31:16]

Right.

Mark Abbott

[0:31:16]

The map is just, this is just a, and heuristic that can help us think, that can help us, you know, decide how we want to go from here to there. But yeah, I just, you know, I, I, I, I, I don't want it to end up, you know, I don't want Mazda end up telling people what to do, obviously.

Mark Abbott

[0:31:36]

Right.

Mark Abbott

[0:31:36]

I don't think you do either.

Mark Abbott

[0:31:38]

Right.

Mark Abbott

[0:31:38]

But, but, but, you know, being able to ask good questions and then the other thing in which, which to is, you know, one of the reasons I love software and I love technology and, and, and I, and I say this kind of cheeky is, you know, I mean, I, I've been a subscriber to OpenAI almost, you know, since it became public and you know, God knows how many notices I've gotten from it that, you know, that, you know, it's down or there's an issue or whatever. I mean, it's all the time, right. And so I actually, you know, back to bugs versus features. I actually like the fact that it's not perfect. I like the fact that, you know, we can push on delivering value without having to, having to be perfect. Because, you know, if even though, you know, not and I Almost don't want to say this, but, you know, but, you know, you try to have your offering up 99.9999% of the time.

Mark Abbott

[0:32:45]

Right?

Mark Abbott

[0:32:46]

But the reality is that everybody knows that there are issues, and they're okay with those issues because the work that's being done to progress, the power, the value of the platform is work that's being applauded as opposed to expecting perfection. Thankfully, we're not subject to expecting perfection by our customers, by the coaches. And, and so, you know, I like it not being perfect. I like it being better at asking questions. You know, I like, like, you just talked about the fact that, you know, if you're just assuming that the answer is right, you're actually missing. It's just a tool.

Mark Abbott

[0:33:30]

Right.

Mark Abbott

[0:33:31]

You're misusing the tool.

Mark Abbott

[0:33:32]

Right.

Mark Abbott

[0:33:33]

You're giving the tool more. You're giving the tool credit for things you shouldn't be giving the tool for. It almost keeps those who are, in my opinion, who, you know, maybe, you know, would love to just, you know, just have it. Give them answers and have them stop thinking, you know, it's, it's. It's sufficiently insufficient that it's kind of, you know, you know, don't, don't go there.

Mark Abbott

[0:34:00]

Right?

Mark Abbott

[0:34:00]

Don't, don't assume perfection. But, you know, do sit there and say, oh, you know, that's a great question, or, yeah, I'm glad you asked me the following question. Or the following question. The following question. So, you know, once again, getting back to. I think it's in, you know, I think that, that generally speaking, and we all know there's a, There's a whole story behind that phrase at 90, but generally speaking, I think that its capabilities right now are, you know, pretty, pretty incredible.

TJ Kneale

[0:34:34]

You know, Pablo Picasso once said, computers are useless. They can only give us answers. And I think it's just such a great quote because what's important is asking the right questions. But I think that with generative AI, we can, we can flip that around. And in fact, what we've built MAZ to do is act kind of like a Socratic tutor and ask you the right questions. And that's the value that MAS brings to the table within our opinionated framework, it asks you the right questions for you to develop the right answers.

Mark Abbott

[0:35:10]

Yeah, And I think, you know, one of the things that, you know, you know, I've been focused on for years and years is back to asking the right questions is, you know, our vision is that NAS not only helps the senior leadership team, obviously ask the right questions and helps the senior leadership team sort of execute on their priorities. Helps the senior leadership team understand what's working and what's not working within the organization, but ultimately.

Mark Abbott

[0:35:45]

Right.

Mark Abbott

[0:35:45]

The big idea here is that. Is that we're building a platform that can help people from the top to the bottom side of the organization in terms of, you know, not just, you know, getting their rocks, you know, complete, not just in terms of making sure that, you know, progress is being made in their seat or within their team or across their department or that the progress that's being made is coherent in that, you know, you don't have one department doing all this stuff. And yeah, it's got great progress, but by the way, it's just, you know, it's just made everybody else's jobs miserable and so they couldn't do their job. Obviously, that's not. Not the kind of, you know, healthy organization. We're trying to help people figure out how to build. But, you know, but ultimately it's helping people have, you know, great quarterly conversations. Helping people leaders have, you know, have hard conversations where they need to take place. Helping leaders, you know, become better and better at leading and coaching and understanding, you know, that if there's someone who's struggling, chances are that's on you as a leader, not on the employee. Because a. You hired them. And if you think that. Well, no, I actually. They were given to me. Well, no, right. Whether you realize it or not, you know, when someone comes onto your team or you take over a team, you are basically going through a hiring process.

Mark Abbott

[0:37:14]

Right.

Mark Abbott

[0:37:15]

And because what we teach is you should never have anybody on your team that you don't want to lead right now, once you agree to lead them and. And to be their coach now it's on you right now. You need to help them understand what a level performance looks like, what it means to get an A for the quarter means to get an A for the year.

Mark Abbott

[0:37:33]

Right.

Mark Abbott

[0:37:34]

And. And coach them up. And so, you know, part of the. The vision originally and always has been that, you know, really about helping people thrive in organizations, helping people build great organizations is, we know that, you know, as. As goes to people, so goes the company. Right? You can't have a great company filled with, you know, with either incompetent people or people who just don't, like, want to be there or people who don't like the mission. And so ultimately, just helping people, you know, helping companies become better and better at helping, you know, individuals thrive. And it's hard, right? I mean, we're going through a hard period right now in terms of, you know, what's the, what's, what's the social contract between the company and the, and the individuals. It has, you know, things, the power of AI starts to come across and so we, so it isn't easy, but the reality is we're trying to figure out how to help people, you know, build great companies up and down across the organization, helping them be great leaders, helping them be great coaches, helping them see what's real.

Mark Abbott

[0:38:41]

Right.

Mark Abbott

[0:38:42]

And it's not a small task that we've taken on here, but I, it's all about execution for us, in my opinion. The technology's here, right. For what we think it needs to be doing. And it's a lot, there's a lot of, a lot of it's about execution. If not, it's all about execution. But, but I, you know, I, I'm very optimistic and I'm curious sort of, you know, you know, how you feel sitting in the seat now that's responsible for helping us do this very important work. You know, what do you, what, what is it that, you know, you know, I don't want to say keeps you up at night, but you know, for you right now, what are the things that, are the lenses that you tend to look at a lot of decisions you're making now?

TJ Kneale

[0:39:41]

Yeah, yeah. You know, I'm so encouraged by the customer feedback that we're getting from what we've released so far that I really like. The biggest thing is how can we go faster? How can we deliver more value to more people sooner? You know, in the process of doing that, I do want to make sure that we main, that we're true to our core principles and what we teach. I want to ensure that we respect our customers data and their data privacy. So we want to take enough time to make sure that we get these critical pieces right and not just deliver stuff because we can. But, but boy, yeah, I think because our hypothesis of value seems so aligned with the feedback that we're getting. The biggest thing keeping me up at night is just how can we do more of it?

Mark Abbott

[0:40:45]

As we come to a close, you and I in the beginning, in sort of thinking about what we wanted to talk about during this conversation, you know, a thing that we told our clients is that, you know, the way we run the organization is we, we, we have this five quarter view. We have a sense for what we just did. We said we were going to do these things. How'd we do? We have a thing that we have the things that we're working on right now and we share those with our clients because, you know, we're getting requests all the time, right. I mean, you know, you know, what is it, 20 to 30 a day? I mean, it's, maybe I'm, I may be under, understating it, right? But they're, you know, they're like, well, can you give us this? Can you give us this? Can you give us this? Can you give us this? When's this going to happen?

Mark Abbott

[0:41:35]

Right?

Mark Abbott

[0:41:36]

And so, and you know, and we have, you know, well over a quarter of a million people who are using it all the time.

Mark Abbott

[0:41:44]

Right.

Mark Abbott

[0:41:44]

We've got 18, 000 companies now, now, you know, running on the platform. And, and you know, what we've, what we've said to our clients is we'll, we'll let them know what's happening this quarter and then, you know, every month we give them an update, if not a release. Then once a quarter we give them the big reveal of hopefully there's something really cool we built and that we can share. And then we're also letting them know what's going to come out the next quarter and give them a sense for what's going to come out over the following quarters. You know, there's a lot of that we're doing in terms of integrations and people are super, you know, super anxious for us to build a lot of integrations out. There's a lot of really cool things we're doing on the data front and obviously now on the AI front, not wanting to get us in trouble in terms of having people have expectations. But, you know, what's, you know, what do you see us working on over the, you know, between now and the rest of the year that you think you're comfortable sort of talking a little bit about.

TJ Kneale

[0:42:51]

Sure.

Mark Abbott

[0:42:52]

On film.

TJ Kneale

[0:42:53]

Yeah, sure. So, you know, hopefully this podcast will last a long, long time and so it may become dated. So I would encourage folks to go to our product Updates page on 9io to go find the specifics, whatever the latest is. But I will say this, we've had great success with the Draft Rocks functionality, with the meeting prep functionality. So we are leaning into more, you know, purpose built, specific agents around things like how do you build out a scorecard, how do you build out an accountability chart as we get integrations, as you mentioned, we'll be able to do things like summarize your meetings for you personally, for you, based on your personality and your role and your goals for that quarter or year. We'll be able to look into your scorecard and your KPIs and identify trends and anomalies. So that sort of data based things. And as we get out into the end of the year and early next, we I think are approaching the, the area where we've got a sufficient number of, if you considered each of those agents, purpose built things a skill, we got a sufficient, you know, kind of a critical mass of skills that we can unify that into a general purpose interface where folks can ask for whatever they want and it will all come out in that, in that one place. Yeah, so that's the, the big picture view. But again, check out the product updates page for the latest.

Mark Abbott

[0:44:08]

Now. It's a great point. And then the other thing I would, I would add, which is, you know, people have been asking for mobile for a long time and we finally, you know, and I'm, I'm the guilty party. I was like, you know, you can't do everything. So they've been asking for mobile for a long time. We now have mobile out there and you know, I'm looking forward to the day where, you know, we can just, you can say, hey, you know, what's going on here? And, and MAS will give you a pretty good, good summary of, of what's working and what's not working and things you might, when I look into a little bit more closely. But it's, you know, it's very exciting, number one. Number two, I, you know, I want to thank you for your leadership. You know, I literally said probably five times today with my client that I'm the most patient, impatient person I know. And what I mean by that is there's stuff we just wanted to do. Literally like we've wanted to work on this since 2012. It's crazy to think about that, right? But, but you know, it just takes time to, to do this work. And, and I, and I deeply respect and appreciate you and the team's commitment to, you know, being super thoughtful about what it is we're doing, how we do it, where we're going, making sure that it all makes sense. And I'm just looking forward to continuously sort of delighting our clients with how we can reduce the friction associated with going all the way from an idea to an ipo. Because it's hard.

Mark Abbott

[0:46:00]

Right?

Mark Abbott

[0:46:01]

And, and so, you know, a lot of times, you know, a founder or CEO is like, you know, I just have this gut that something's not working and for, you know, to get to a place, you know, certainly I think you know, next year right, where you can say, hey, you know, I've just got this concern. Is it well placed or is it, you know, am I just like being silly because I watch some stupid news program? So looking forward to just reducing the level of, degree of difficulty associated with building great companies and, and the anxiety associated with not seeing things that you know, you should be able to see because I, I think the, the path in front of us is, is definitely, you know, we, yeah, I hate to say Will, right. I'm a karma guy, but there's, you know, I, I can't see why we won't be able to help people become better and better at mastering the fundamentals of building a great company. And you and your team are a huge part of us delivering on that promise. So thank you.

TJ Kneale

[0:47:08]

Well, thank you. It's very gracious. Thanks for having me on the show and really just grateful to be a part of the team and have the opportunity to help companies build great businesses and actually make them work. I think it's really important work and really glad to be a part of it.

Mark Abbott

[0:47:23]

Yeah, we love small and mid sized businesses. We think they're pretty crucial for having a healthy society. So I think we're all, you know, you hate to, you know, it's it people don't like founders who have a mission, but I think, you know, and a company that has a mission where I, I think we all believe strongly in what we're trying to do. So once again just, just, just thank you and the team and I'm looking forward to, maybe we'll end up doing this, you know, every, I don't know, it's three months but every six months or so we just sort of revisit what's going on and, and so, you know, we can help people, you know, appreciate sort of the practical side of this technology. Feel like I'm rambling here when I say this but you know, I have a, I belong to a group that's as I, you know, I belong to abundance360 and one of my, I don't know if I think they're, they're called forums or groups or you know, has, I'm very, very, very successful, very smart guy. And he's like, I, I just don't see, you know, why people think AI is delivering any value. And I'm like, ah, I, I, you know, we do. And so I've started to show him and talk about what we're doing and I think he's starting to come around a little bit. But, but I think it's, I, you know, I think it's a game changer and, and delighted to be involved in an industry that, that, you know, gets to hopefully do tremendous good with it. So thank you again.

TJ Kneale

[0:48:49]

Thanks, Mark.