PeopleTech on the Edge | Ep. 01: Driving Product Innovation With AI in the HR Tech Market

Driving product innovation with AI in the HR Tech market

The integration of artificial intelligence (AI) is significantly reshaping the operational landscape for small businesses, a topic recently explored by Zack Johnson and Nathan Shapiro of Paychex.

Their discussion centered on AI's practical applications in enhancing user experience through advanced analytics and the emergence of sophisticated digital "knowledge agents" capable of providing nuanced insights. The conversation also addressed the critical challenges of building trust in AI solutions and navigating complex data models, highlighting the profound and multifaceted influence of AI on the contemporary small business environment and evolving workforce dynamics.

In this episode:

• Host, Zack Johnson, General Manager, Embedded Analytics, Visier

• Guest, Nathan Shapiro, Head of Product, UX, and Architecture, Paychex

Episode transcript:

Zack Johnson
Hello everyone, I'm Zack Johnson, GM of the Embedded Analytics business at Visier. Welcome to PeopleTech on the Edge. This is our chance to come together and learn about how technology is shaping the future of management, the future of work, and of course the future of the people in HR experience across companies big and small. Today, I'm joined with a very special guest, Nathan Shapiro from Paychex. Nathan, how are you?

Nathan Shapiro
Good, good to see you, Zack. Thanks for having me.

Zack Johnson
It's good to see you too. I'm glad you let me rope you into this. We're going to have some fun today. So real quick, just tell me who you are, what do you do, and where are you focusing your time these days?

Nathan Shapiro
Good. Yeah, absolutely. So I work at Paychex. We're an HCM provider, primarily in the US, but with a bit of a global presence, serving 750,000 businesses. So I had a product architecture and user experience here. a lot of areas being impacted by AI these days. So a lot of AI focus and really focusing on how we bridge the AI growth with the user experience and change the way people work.

Zack Johnson
I'm really excited to dig on those topics. There's so much to talk about and it's crazy how fast things are happening. But before we get in, just so the audience understands where your thinking is coming from in the context for what you're working on, can you just share a little bit about your journey? What made you choose this area to focus on? How did you wind up running product for 750,000 businesses? That's wild.

Nathan Shapiro
Yeah, it's a fun journey. I've actually been a paychecks for a little over 20 years now. So I started as a software developer right out of college. Wish I had AI tools back then, cause I wrote some pretty bad code. Don't worry. It's all gone. It's not in production anymore. But I was good at finding solutions to problems. So kind of made the jump into product back in 2014 as we looked to move towards more platforms and really away from just products and starting to build out our strategies around integrations and APIs and single sign-on and analytics and reporting. Just kind of kept growing that. So it's been a fun product journey, starting with a real tech focus and continuing to grow that out. And just really trying to push the boundaries of how people work and bringing solutions to small businesses and mid-sized businesses that historically would have just been reserved for large enterprises.

Zack Johnson
Amazing and I know it's something you're deeply passionate about. I'm deeply passionate too. Having run a small business, having been a Paychex customer once upon a blue moon. What's it like working at that level of scale? Like that's hundreds of thousands of companies. That's like people's lives. Like what's that like?

Nathan Shapiro
Yeah, yeah, it's pretty cool. Like when you stop for a second and think about the reach of what we do, that I think sometimes as product people we forget about, like we get caught up in just the customer and some of the commercials sometimes. And when you kind of put that lens on not just your users, but the broader reach you have, like, you know, I go back to a story all the time during COVID when I was at the pediatrician with my kids and hearing about how they were impacted by not being able to get access to solutions that we were offering and you start to think about hundreds of thousands of businesses and then the reach they have, it's pretty rewarding, I gotta be honest.

Zack Johnson
It's amazing. mean, I think like, you know what's funny when people think analytics or AI or reporting people, like their brains just go to like giant corporations, like super specialized roles. And so for me, one of the things that's most exciting is like, I think about like, you know, coffee shops, restaurants, like places that, you know, it's people running real businesses end to end and they need that help too. And so it's really cool you're able to work on that and make that happen. So you brought up AI right off the bat. What are you excited about around AI and what it means for small businesses?

Nathan Shapiro
There's a lot. So I think when I look at AI and how it can help us deliver solutions, but even more so just how it helps people and changes the way they work, which is obviously a huge part of the Workforce Edge and what you guys are focused on. But when I think about small business owners and the consolidation of responsibilities, where they're the CEO, the CFO, the CIO, the CHRO, and the ability to be an expert in all those fields and how difficult that is when trying to run a business and where AI can step in to make you an expert in the moment and streamline things. Like that's really cool. Like I know you and I have talked before around how we view analytics and how it can marry the office of the CFO and the CHRO that that ability to get support, but also AI to help you figure out what questions are you not asking and how are you not thinking about it? Like that's super, super powerful because that time to competency.

Zack Johnson (04:54)
Really?

Nathan Shapiro (05:07)
But also the confidence in your decisions to make the right decisions for your business, for your workforce, whatever it might be. That's really exciting when I think about that kind of that small business market and what it can do.

Zack Johnson (05:19)
It's pretty cool. I mean, like, I love the idea of like the finance piece and the people piece, right? Cause like, I remember being that user and just trying to figure out like, why is my, why is this amount of money coming out of my bank account? Like, where's it going? Like how many months do I have left to live? And like, you're kind of reliant on all these different service providers to help you. And every day is existential. And so every little bit of intelligence, and I think like the ease of use that AI can offer through its various interfaces. I think AI is going to be maybe the most exciting thing to ever happen in small business. I'm really quite passionate about it.

Nathan Shapiro (05:55)
Yeah, and we'll even look at some of the deep research models and how, like even a small business owner looking to shop for tech that's not traditionally in a spot where you're RFIs out to big companies or otherwise and can get so lost in that Reddit rabbit hole. Like the ability to go and have AI help you do that research to figure out what's the right solution for me in a very short timeframe. I mean, I used AI to figure out how to fill out my March Madness brackets and auction values for my fantasy baseball draft in the last couple of weeks, right? So there's like serious, serious power that can supercharge everybody and how they work, but small business owners especially.

Zack Johnson (06:28)
Right? Totally. Yeah, and so speaking of that, Like everybody, we're all at various stages of like, comfort around technical adoption. And we're all in various stages of following the AI journey. And I know you get to be pretty bleeding edge on it. Started with Chappots, and now everybody's talking about agents and agentic AI. So like, how do you think digital agents are gonna work with humans in the small business context? Like, what do you see happening here that... is exciting for you and challenging.

Nathan Shapiro (07:13)
Yeah, I think it's a fascinating time as a practitioner in UX, right? When you think about it, I think so many people are making agents synonymous with conversational interface, and it's really not. And that's where we challenge ourselves of thinking about agents, but how do agents interact in a variety of ways? That can be an agent sitting behind an email inbox. That can be an agent talking to you. That can be a traditional GUI you know, I think a lot of people jump on Satya's message of like, is dead and misinterpret what he really means there and so we really think about what are those multi-channel and multi-interface experiences and how do we use agents to design those that fit the way people work and not just, you know, I think the other assumption sometimes is, well, some people just like to chat and some people just like to use voice, but it's so much in the moment.

Like, you know, for me, it varies quite a bit. Like there's times that I love using voice to control something and talk to an agent or an application. There's other times where it just doesn't work. Like, I need it to be something that's not audible for my surroundings. So that's like really fun when we kind of poke at that and kind of play with those ideas from a UX perspective to think about in the flow of work and kind of different interoperability models there.

Zack Johnson (08:35)
So when you think about that, if you don't mind just going just one level deeper, can you make that real for me with a moment? The voice versus text piece, how do you think about that as you're conceptualizing the product experience?

Nathan Shapiro (08:49)
So let me ask it back to you. So if you called me today and you were trying to give me your payroll data, because you just don't, you you're not there, you don't want to key it in, you want to give me a bunch of payroll values, and I'm an agent that you're talking to, if I came back to you and said, hey, would you rather just send me a file with that and I'll go ahead and process it, and then I can let you know if there's anything that needs to be corrected, like those types of journeys, right, where you're not locked into a singular pathway.

Like what works the best for you? Like those are the kinds of things we think about where an agent designed well can have different interfaces on top of it. And so those can work well together.

Zack Johnson (09:30)
That's helpful for me. You know what's funny? One of the things I'm curious if you agree, disagree, or understand it better, because you probably understand it better, is I'm finding like I'm experiencing way more pebble in the shoe moments with technology now with really powerful AI tech than I did before, right? So like the limitations of Siri are stark when I'm able to talk and have a conversation with chat GPT version whatever right and so I think about like, know those transition moments You're on the phone with an agent or like you're taking what do you say the other day? You're taking the train into work You're not gonna want to talk through your payroll data on the train in front of other people But as soon as you get the office that might change right like those Transition moments become really important and that's that's like that's hard to get right

Nathan Shapiro (10:27)
It is, think, but I think things are evolving so fast that it's making easier to get it right when we realize we need to get it right. Like not everything has to be defined upfront. And that's like the exciting part is how fast things are iterating and moving. And also like what we're seeing with this boom with AI is the level of crowdsourced innovation that's occurring is way beyond the engineering community. Right? Like when, when have you had technology before that you could go and ask it? What, what am I not asking you to do?

And what, what more could you do for me? Like it, like, you know what I mean? Like it's so easy now. And what's happening is then instead of traditional methods of like, we need to go talk to users and we need to do generative research and co-design. Like users are just being very expressive about those types of things. So there's this massive like crowdsourcing of innovation that we can capitalize on to like learn and come up with new ideas that otherwise I think we just never would have thought of in a product context, even, even when getting customer feedback.

Zack Johnson (11:27)
And so what are some of the unique challenges you face making data work in these new interfaces? Because one of the things that I think is really fascinating is how do I do a task, automate a task, take an action, right? But then there's also give me a better way of doing things, help me understand what happened, help me understand why happened. And a lot of the things I know you work on marry the two. And that has some really unique challenges and opportunities.

Nathan Shapiro (11:54)
Yeah, we, I'm going to answer and then I'm going to ask it right back to you. So the, ⁓ what we've found is everything we've done with AI and we've been on our AI journey for well over a decade, but around building trust, right? With anybody that's going to interact with AI transparency, explainability. And that's something we focused a lot on is like, how do you not bury somebody who just wants confidence in what's being provided to them in, you know, the, the nuts and bolts of data science or otherwise. so historically we've done that well, but when we talk about some of those different interaction models, where does that actually fit? If I'm talking, do I really want an explanation? And there's this inherent trust when you're talking to a person a lot of times where people feel like, well, I'm talking to a real person, so I'm trusting the answers and the accuracy. And when you take all of that knowledge and even when you build great AI,

There's that, there's not that level of confidence there. ⁓ so that, like, that's something I'm not going to tell you. We haven't solved yet. Like we've done some really cool things, but it's, it's a big area for exploration for us is where do we, where do we build up to where people have a bit more inherent trust, versus where are we bringing in explainability and everything else? ⁓ and so, you know, there's a, there's a lot happening in that space with a lot of AI providers today.

Nathan Shapiro (13:21)
But like we balance that and a lot of it's around like trying to limit cognitive overload, right? Without it being too limited So which is a big part of everything we've done in design practices and everything for a long time So how about it Visier? Like how do you think about that and then personally? How do you think about it?

Zack Johnson (13:39)
Thank you for asking and thanks for your perspective, right? I do love like, know, marrying some of the things we talked about before like super large-scale you have a user who has to be a master of a whole bunch of things and then you have like this rapidly changing tech expectation etc. It makes for amazing opportunities and cool challenges. I think for us like there are a couple things we're really focused on that are really cool problems that are like

I don't know, some of the coolest things we ever thought we could work on and now it's now, right? And so I think one of them is just like, you're seeing a difference emerge between what I would call like an automation agent and like a knowledge agent, right? And so most of the early agentic announcements and releases, they're very much like automation agents. It's how do I go and make a bunch of tasks happen, right? Like, how do I set up my pay runs? How do I do like an automated check on each one? Like,

How do I go hire a thousand people? How do I go have something post online for me? It kind of reminds me of like, this then that, but like with a whole, with broader reach, higher quality, and you don't need to necessarily flowchart the whole thing, but there's still a lot of flowchart apps. What we're seeing though is the power of multiple applications of AI, whether using an LLM for translation or you're taking a machine learning model and like, bringing that to the forefront to explain why and what's gonna happen. There's this knowledge agent that's emerging where it's like, what should I do? What's the best way to solve this problem? How do I think about how many people I could hire? When do I open up a new site? Should I take out a loan?

Those are really tricky questions that also require orchestration. It also requires querying data from multiple places. It also requires... training against a knowledge and there's an element of workflow, but each question's different. And I think one of the things that's really interesting is like, as consumers, we have access to these frontier models that have been trained against like the whole web. And then you can throw like 200,000 tokens at it and kind of bend it a little bit. But in the enterprise or in the small business, so much of that context is locked behind. stores. And so a big thing we're focused on is how do you unlock that context, whether it's data, whether it's structured data, unstructured knowledge, what have you. But then it's how do you make sure that to your point it's trusted, it's accurate, right? Like, because the fun thing about AI is it will make some stuff up to try and give you the right answer. And if you're not like laser focused in the details, you can make them, especially with people data, make a big mistake. And so

That knowledge agent opportunity is really compelling to us. I think there's a place in it in small businesses and large businesses, but it's how do you bring that to life, safeguarding and having contextual structure around that data.

Nathan Shapiro (16:52)
It's I love that. And one of the things, so when we look at ourselves as paychecks in the scale, but not only the scale, but like 50 years as experts, 50 plus years as experts in the field, like that's where we kind of see where our biggest assets to help small and mid-sized businesses are, like all of that knowledge and expertise, all of the data and the scale of the data we have and building AI solutions. And so that like,

Nathan Shapiro (17:18)
That's really powerful, especially for a small business that just otherwise wouldn't have any access to that. And if they did, they're probably off buying something that's commercialized that they're questioning the validity and how much they can trust it. When, when you think about the scale of data to help with modeling and decision support. And then the other piece I look at is where do we take the expertise that's like expert knowledge that's humans today and start to incorporate that into agents to then let those humans become even bigger experts and expand that domain knowledge and keep going that way.

Like this is even since we launched our chatbot in 2018, like this has been a big fundamental thing of how do our experts view bots and agents as complimentary, not competing with them as we free them up to be even broader experts. And like that's something we're constantly working through, but also using AI and agents to support the experts to become better or whether it's our sellers, right? Being able to not have to go through time to competency to learn about all of our products and services all the time and memorize that, or know exactly where am I going to go for this asset, but like to have an assistant there. We talk about, we call it digital companionship, and it may sound a little clippy like at times, but it's really, how do I have that ever present, ever present technology sidekick?

And really what we're talking about with this proliferation of agents, is this just army of sidekicks, right? That know how to work with each other, but have the right boundaries around them for security and privacy reasons and everything else. And like something that's really fun that I know we've kind of bounced around together is like, what is that agent ecosystem look like and that orchestration, you know, and how is that going to evolve? But it's like, it's exciting when you just stop to think about the potential.

Zack Johnson (19:07)
I mean some of the work that you're doing right now is just like it's transformative. How are you thinking about this? Because isn't, I mean one of the unique things about Paychex is you work with every domain of company, right? Like across all of them. Like is that challenging? Is that exciting? Like what's it like to have so much depth and breadth of type of company you're working with?

Nathan Shapiro (19:29)
Yeah, it's both, right? you know, there's times where you sit there and you're like, man, I wish I could just compartmentalize to this like micro segment. But having that breadth, you start to see commonalities. Like lot of what we've seen historically is many businesses oftentimes express that they feel like they're unique and there's nobody like them. But then you start to use data and the great equalizer and all of a sudden, personally this happens to us, right? Like, I'm unique, I'm different. And all of a sudden you see something where you go, actually I'm not too dissimilar from that person or that role or whatever it might be. And so that's where that scale becomes awesome because you start to like benchmark yourself against people that really do compare to you. But like where we're getting with data and AI, you start to draw correlations that might not otherwise be obvious because

You know, I think back to a lot of like initial benchmarking and turnover benchmarking. And it's like very much what, what size of company you are, what industry is your NAICS code say you're in. And you got companies that are like, well, yeah, I classify there, but like I'm a startup tech company, right? Like that's where I, and so you start to see those trends and the more data we have, the easier it is to connect those dots in ways that might not be obvious to somebody that's working off a partial data set.

Zack Johnson (20:48)
Totally. mean, the ability to tailor experience, to tailor recommendation, to tailor insight based on the not just like who you are and the data around you, but the way that you experience the solution and the service. It's just an unbelievable opportunity.

Did you have like a magical aha moment with AI that made you be like, my God, I can't wait to bring this to our customers?

Nathan Shapiro (21:20)
Yeah, it's, I think what, there's a couple and actually I'll talk about our kind of journey to V, right? Cause I think it's a good one. We had a moment probably 10 years ago where we were trying to analyze and go through data and dig through spreadsheets and put things into Power BI and like everywhere else. And we always had this view of like, wouldn't it just be cool to have a conversational interface into analytics and not have to be a BI expert. And, you know, there was some things starting to emerge out there, but they really, you had to like speak like a business intelligence application, right? It just wasn't intuitive. And so we started playing around and experimenting with that. And then we actually ran some projects with, we sometimes partner with universities to sponsor senior projects. And we gave a team of data science and UX students a challenge to say,

Nathan Shapiro (22:18)
Here's what we want to do. Go play around with this. And they built some pretty cool stuff. But to do that at scale, across the breadth of HCM data and the scale of what we're talking about on client size and everything was still a challenge. And to continue to innovate on that and let things learn, it was very traditional in terms of how some of that was being looked at.

And it was boxed into great, I've got data that's for reporting analytics and I can guess questions about it. And so, you know, when we started working with you and looking at V and understanding the vision for where you see that going, complimented with our vision to your point of unstructured data, right? How am I, how am I taking turnover data or risk of exit data for my workforce and the broader market and my own policy information to actually get better insights?

That was the moment where it was like, wow, this could be so much bigger than even what we were thinking about, which was like kill traditional BI. And like that was like an awesome moment as we kind of saw ourselves coalesce on like a shared vision there that's moving pretty fast. So that for like small mid enterprise businesses, you know, advisory service companies, like there's, there's really awesome things there within the context of, you know, the domain we're in.

Zack Johnson (23:42)
Thank you for the shout out and I'm glad that you had that experience when you were playing with it. And it's crazy because like, you know, some of the, one of the greater level technology problems has been ask a question, give me an answer, right? I mean, from a Visier perspective, that's what we've been working on for years and years and years, which is like, well, let's create the exhaustive list of questions. And then it's like, well, what if you have a question, what if you don't know how to ask the question, right? Which is really the V piece. I think it's funny for me as a user, like I've worked in analytics for a long time. I'm not an analytical person. Like I'm totally an intuition guy. I'm a fly by the seat of my pants. Like I love the people side. But I know that there's value. And for me, my goal has always been like, how do you marry the two? Right?

Because what's awesome is we take intuition, you back it up with data, you make really great decisions with lots of momentum. And one of the biggest barriers, I think, to be I helping like the person doing the work, not just an analyst is you have to learn a data model. And I think learning a data model is really tough because if you're a small business owner or you're in a mid-sized business and have 50 people in your department or whatever, you don't have time to click around and figure out what something was classified as. And so being able to ask a question and have something translate like the SQL model for you is really powerful. And so I'm glad that that seems to be working.

Nathan Shapiro (25:07)
Let me ask a question back to you on your aha moment, but in a personal context, not a professional context with AI.

Zack Johnson (25:13)
Oh man, that's a great question. So for me, actually had one recently, because you'd have the first like, hey, can you do me this in iambic pantameter? And I'm like, oh my God, that's like structurally so difficult to do. But the one for me was actually, it was like financial planning and like what to do around a mortgage, right? I find sometimes when you talk to an expert, there's this like, am I asking a smart question? Am I asking too many questions? Like, how much does this cost? Right? How much time do we have? Like you're not.

Helping you're not explaining this to me. Like I'm not a Financial planner like you are and so it was crazy was just um working with some of the new reasoning models like how ridiculously high quality like like Whether it's like tax planning What are either or scenarios like I find sometimes like? The it's hard to ask fact questions Which is why we've spent so much time like creating that like contextual data model where you can but the

How should I think about two approaches to a problem and the pros and cons? It's so good. And so I have this moment of like, you know, I learned more in maybe an hour of just like texting and talking than I did in like 10 years of conventional financial wisdom. And I was like, in an unlocked understanding. And so that's to me, like when I think about doing that as like a business operator or as a manager, like, whoa, it's gonna supercharge people, like absolutely supercharge people. And I think for small businesses, my goal would be keep people in business longer, help people grow better, right? Because that's the, it really is existential. If you're a giant corporation, you you've got the luxury of time and credit, right? Small, medium businesses, it's a knife fight every day.

Nathan Shapiro (26:54)
The, that, that's interesting. You know, it's like, it triggers the thought of, like, let's think, let's go to a small business owner, right? Who's just running, right? Trying to keep the lights on, run the business, grow the business, kind of having to pick where they want to invest that, that extra time. Cause there's not a lot of it. And like, you think about the future of agents that are just working for you asynchronously and are proactive that are like going and doing all that exploration of where you have opportunity.

Nathan Shapiro (27:23)
Like that, like that's awesome, right? Like if you, if you actually can put those to work for you where you've got an agent that's thinking about workforce planning and whether that's an opportunity for you or condensing like suppliers or otherwise, like that, that's pretty awesome. If you think about what that can do when you've got this team that's off working for you, that's this unbelievably scalable team that has access to all the information out there. Like that gets pretty exciting when you just think about the future of work and running and growing a business.

Zack Johnson (27:56)
I mean, totally. And that's like the whole reason why we started this podcast actually. Like, because if you think about it, like all these aspects of business and running an organization, whether it's a business or it's like a, you know, a nonprofit or whatever, it's all interconnected, right? Like, should you open a new location? Where? How should you finance it? How many people do you need to keep it open? What hours should you operate? Like, should you, should you outsource something or, or, or do it in house? Like,

They're all questions that touch your workforce and they touch your expenses and they touch your customers. in over the past 30 or 40 years, technology has made it easier to do each of those pieces siloed. But now technology is gonna make it possible to think about how those are interconnected. And to me, people, that's like the hub of the wheel.

And so it's so exciting, you know, the work that you're doing is going to accelerate this shift for so many American workers. It's unbelievable. It's really, really impressive work.

Nathan Shapiro (28:52)
Mm-hmm. So I'm ask you question back on that and the future of the workforce. So we'll go to the people side now because there's a lot, think historically we've seen in businesses a consolidation of multiple responsibilities on an employee because I can't really hire half a person. And so how do we get the return? And that idea of like that skills transformation, but also the fractional employee.

Like, do you see, and the reach through technology, as opposed to, can only employ somebody by having them sit in my office and take up the seat and people don't want to be part-time. What do you see as that impending change with like the workforce, the skills dynamic, the fractional employee?

Zack Johnson (29:50)
I mean, first off, thanks for asking, because I think about this stuff all the time. But I think a couple of things are going to be true. So the first is it will hit different sizes of the market differently. The way a large enterprise is going to approach this challenge and the opportunities of automation and AI is going to be very different than how I think it's going to manifest in small medium business, just because there's different financial goals. There's different ways that companies are measured.

Goals that they seek, right? I do think, speaking for like your, the scale of your world, the leverage that you're gonna get from one additional hire now is amazing. And so I do think like, if each person brings with them a swarm of agents that can work on a whole bunch of things, every person you add is just so creative. So I think in a lot of ways, like it could really stimulate a lot of growth.

When it comes to fractional employees, think you're gonna see people develop if you think about like kind of like the Freelance economy and like having like a specialized thing that you get you go and help people with I think they're gonna be really really cool models to like rent out and extend that capability So right now if you're selling your time one-to-one you can only work with so many customers if you can take your expertise and duplicate it and leave it behind Almost like every individual could potentially be its own tech company in a lot of ways

And so I do think it's gonna be a really exciting model. I think in some ways it might mirror the creator economy. If you look at like what's happened with professional YouTubing and like all that stuff, like we're gonna have some people who just master this and wind up with like, you know, huge reach. Like I sort of think about it like, think about how much money has been spent at work to set up like your operational cadence. Like what metrics do you track? Like what meetings do you have? Like what do you look at? You're gonna be able to take that with you, right? Or rent that out, or like follow it on LinkedIn from somebody and subscribe for 100 bucks a month. Like, I think it's gonna be a whole new economy of value created with the new technology that's coming. That would be my prediction. What do you think?

Nathan Shapiro (32:06)
Nice. I like it. I'm not sure, to be honest yet. Like I'm fascinated when I think about this in that, you know, we're going to have, we're going to have laggards and we're going to have people that are ready to go. And I think we'll probably find employers are pretty diverse in how they view the opportunity. So I think you're going to see probably some models that evolve that align a bit more to the traditional staffing agency type of a model where I've got access to somebody for jobs to be done instead of a full time. But when you, I like your perspective because you layer in the technology aspect of me as a professional and what I could do to scale my services and abilities.

I think there is a massive opportunity for the dynamic to change. you just, I mean, look at the, like at the P E market and a lot of these companies right now and what they're accomplishing with a very small number of people and how productive they're getting by using AI. It's there's a lot there. I think now we've got to counterbalance it with the vendor consolidation that's happening in the market. Right. And so, which is also exciting, especially for somebody like us based on.

Zack Johnson (33:21)
Yeah. Totally. Yeah, someone like you, totally exciting. Absolutely.

Nathan Shapiro (33:28)
So it's just very interesting to just kind of watch how that's going to evolve and where aspiration is going to get out ahead of reality. But also where reality and where we see some fast movers are going to just fly by aspiration when it comes to some of this.

Zack Johnson (33:44)
You know, it's fascinating, right? Because you're right, you can move super fast with technology. I the last three months of software news has been all about the AI first companies that are hitting the 10 mil, 15 mil, 100 mil milestones with small teams. But one of the unique things is it takes years to mean decades to build the distribution and scale that you have as a platform, right? You can't just create that overnight. You have to build those trust and relationships with people on their worst days running their business, like it takes forever. And so I do think you have a very unique opportunity to like not only just be a leader, but also elevate others and partner and be able to bring that tech to so many. I do have a question for you. So very exciting time, lots of changes in the market. You've had an amazing career and huge impact as a product leader and innovator.

What advice would you give to the next generation or maybe the first, know, they're in their first few years of product management or engineering leadership, like, what advice would you give them for navigating this crazy exciting time?

Nathan Shapiro (34:55)
Yeah. A couple of things. One, I think you actually kind of just teed it up really well, which is like, don't fall into if you build it, they will come. Like you can build awesome stuff and no one will ever see it. So like you got to understand as you're thinking and putting out product, like how are you actually going to get that in the hands of people? And there's a million ways to solve that, but like you just got to think about that because like the best idea can just fall flat.

Nathan Shapiro (35:25)
But then solve real problems. you know, like you and I have talked a lot about our approach to AI and the practical application of AI. And so it has to be an outside end viewpoint. Like you may come up with this, this idea, but then you got to really look at it and say, it solve a real world problem? And that, ⁓ I actually find a lot of product leaders struggle with that. Like they, ⁓ actually I was just reading an article a week last week around the role of design, right? And design having a seat at the C-suite table now and is design ready for it. And I was talking to my team about it because like design is the mentality and the approach to design. doesn't mean UX designer. And so bringing that design mentality, which is all about like identify problems, like real user problems, figure out what needs to be solved, how to solve it. Like you just have to take that look at it. Cause otherwise you're just building to an idea rather than something that's gonna solve a real problem. I feel like if you just kind of like ground yourself in that, like you can be fine at product. Like just do it, like figure it out, do it and go and have conviction.

Zack Johnson (36:35)
It's awesome advice. I mean, you know, it does remind me like I said the creator comedy thing before but like, you know film used to be like you needed a studio You needed a $75,000 camera. You needed an editing room with scissors, you know what I mean? And like now you can anybody can create and that creates um So much opportunity to get started but also the fundamentals are still the same great story, right? You need distribution you have to find an audience like it takes craft and perspective. And so I love what you're saying there, which is like, hey, yes, you have something that can code for you and create an app on the fly, which is amazing. It opens up possibilities. But you've got to solve real problems. You have to still think really thoughtfully about your user and how do they want to experience the world. Those principles don't go away. They're just maybe how you bring them to life changes a little bit. That's really powerful. Thank you.

Nathan Shapiro (37:30)
So if we rewind to young Zack, like thinking about his future, what are you gonna be when you grow up? I'm guessing you weren't sitting there at five years old thinking you wanted to sit on a podcast with me today. But if you rewind it back knowing what the tech that's out there now and if it was around back then, what would that have changed in terms of kind of how you viewed where you wanted to go and what you wanted to do, like ultimately as a career and a profession?

Zack Johnson (37:35)
Thank my god, that's such an awesome question and I'm gonna try and give you an answer now. I'm gonna think about it. I'm probably write you an email with my thoughts. I'm gonna give you the chat GPT answer and then I have to do the deep research answer like with some time, right? I think I love experience. I'll tell you the thing I've been really excited because I went to school for film. I went up working in music, right? And then I stumbled upon upon like how organizations work. Like it was really kind of a weird like trip and fall and like, oh, this thing's cool. I think but what I love is experience, right? Like if you think about business, all business really is is you have a problem yourself and then you put it through the lens of experience, which is like, set an expectation for how it's going to be solved. And do I meet that? The example we use a lot at Visier and my team and everyone's so sick of hearing this is if you go to a five star hotel and someone doesn't come and take your bags, you're like, am I welcome here? If you go to a movie theater and someone comes to take your bag, you're wondering if you're being robbed, right? It's the exact same thing, right? It's the exact same thing.

But because one of them has the context of this experience, it's like, the expectation are like a wild, jarring thing you'd never want to have happen. And if you look at business, business when it competes, like establishes these conventions. Like everyone knows what a fast casual restaurant's like now. Everybody knows what budget airfare's like now, right? Like, and I think when I started building software, the stuff I wanted to work on was so esoteric, like measuring social networks between employees figuring out if pay is fair, like those kinds of problems. So I had to start super large, high enterprise, like some of the biggest companies in world who had money for this, who had specialized people to even think about these problems. We'd have to be able to spend the time to get that data, and we'd have to spend the time to then deliver and present our results and figure out how it would be used. was like, there was no, the application experience was like the tiniest piece of the solution.

Do you think if I had the tools I had now, and I stumbled on some of this stuff that I stumbled on, the ability to create an experience for the day to day, right? you, the moment that matter, like you come into work, open your laptop and what happens? Where you walk into a meeting, you sit down and what happens? I think I could have started 18 years ago building those experiences where now I feel like I'm finally really getting to it. And so, that's really exciting for me today, but that's some of the stuff I've always been most passionate about, is how do you create that moment? Yeah, and I probably would have made a bunch of AI movies. So that's my answer. How about you? What would yours be?

Nathan Shapiro (40:51)
Nice. Uh, so in truth, I never actually thought about this question. It kind of popped my head. So I figured I'd put you on the hot seat. um, you know, I think probably thinking about where I'm at, the tools, how I leverage them and like my youth, I want to be a professional baseball player. And when I think back about like my progress and the access I had to get better and learn.

Zack Johnson (41:01)
Good question. Yeah, I loved it. I loved it. Thank you.

Nathan Shapiro (41:24)
Was pretty much what coaches I had access to. And now, like I coach now. And so I probably would have actually gone down a path in coaching much earlier in my career because what I can do with AI to get new ideas, help me get better as a coach, use it to analyze players where I have a good eye for things. And like, that was my thing was like when I was a kid.

Nathan Shapiro (41:51)
I was always trying to figure out what I was doing wrong, but I didn't have the tools. I didn't have anything to break that down. It wasn't even easy to record. And I think now, thinking back, I would have leveraged it so much growing up, striving for that moonshot of could I get good enough? And I still would have fallen short. I'll tell you that right now. But I think it would have put me on that path of realizing, holy cow, what I tried to do for myself, I could do for others and be an unbelievable coach that has access to all of these tools where it doesn't just have to be how do you coach. I think that moment would have probably hit back then. But like it was very much just, what do you know and can you teach it? Like, you know it back then, so.

Zack Johnson (42:36)
The education aspect's wild. Actually, if you don't mind, I've had a, that made me think, there's a crazy product experience I'm enjoying right now. Have you heard of this product called CARV? C-A-R-V. So I live in Vancouver, which means I get to ski a lot, which is fun, but I'm not very good at skiing, because I started when I was like 30, and they made, there's this product that came out a few years ago that's like sensors for your boots.

And it took like a quantum leap when the AI tech really took off. And so it was my Christmas present this past Christmas. And it literally tracks like your edging similarity and your weight distribution, all these things. And then in real time, it sets goals for you. And like the same way you like pick up a Ringland Sonic, you know, like you're playing with Sonic on NES or something, it'll like ping when you nail a turn. And so I'm maybe like 12 or 13 ski days in on being actively coached on form. And I can't afford a good ski coach to follow me every time I ski. That's crazy. I'm not on a high school ski team, or I'm not Olympian bound. But I'm getting better every single session. And it's crazy because it's patient, it's personal, it's dynamic. And so when you're talking about the baseball one, that is going to permeate everything.

Think like you read Dante's Inferno for the first time. don't need to, like, you'll get explained the context in the way that you need to hear it. And so I am, I sometimes struggle between AI optimism and pessimism, right? The thing that makes me really optimistic is those curated experiences. And I'm experiencing what you just described as the wish one, it's really cool.

Nathan Shapiro (44:19)
That's awesome. it's the speed at which it can process and occur that helps with that challenge of lack of proximity. Because even if you had somebody really recording and you were to, after a run, go and look at that analysis, sure, you'd get a little bit of progress out of it. But you're getting it in the exact moment within milliseconds that you don't have to try to correlate to memory. And so.

Like that and the compute power and everything else, like how it can happen. It's just going to accelerate the learning and advancement for people in a lot of these things. Like I just think about videos that I show my players and I can see them like they're 10 years old and they're trying to process. Well, I did that 30 seconds ago. What did it feel like? And he struggled to do that. Whereas in the moment when you've got that reinforcement and the learning and also learning behaviors and what's the best way to, to coach in this moment to this individual.

Like, it's pretty wild where it's gonna get to.

Zack Johnson (45:20)
It's amazing. And I mean, like to tie it back to the people tech at work, right? Like that coaching in real time, that help making decisions in real time, the accessibility of that to businesses of all shapes and sizes with that curated experience. Like, it's an exciting time and you're doing work that's going to help a lot of people now. I'm really, I'm glad to be in your orbit.

Nathan Shapiro (45:44)
I appreciate it. It's been an awesome partnership and even better just the ability to get together and share the thought leadership and ideate and challenge each other. We love that. We thrive on it. So it's been great.

Zack Johnson (45:58)
Absolutely. Well, thank you. Thank you so much for spending time with me. Is there anything else you'd want to share with the audience before we sign off?

Nathan Shapiro (46:04)
No, just everybody get out there and listen, listen to this whole series. And it's awesome. Like just let people jam out on tech and AI and everything else.

Zack Johnson (46:14)
Thank you, Nathan. Hope to have you back soon.

Nathan Shapiro (46:16)
All right, man, appreciate it, thank you.