Episode 1: When Work Outgrows the Organization

AI is changing what work is, but most organizations still rely on job descriptions, structures, and leadership practices built for a less fluid world.

In the first episode of The Edge of Now, Jason Averbook and Jess Von Bank examine why people increasingly contribute across functions while organizations continue to keep them in boxes. They discuss the growing value of organizational context, the difference between routine and frontier problems, and what happens when companies invest in AI without redesigning the work around it.

The capabilities already exist. The harder question is whether leaders are prepared to organize around outcomes, expand human potential, and build organizations that learn as quickly as work changes.

Listen to the conversation and consider what your organization may already have outgrown.

Highlights:

• Why “What do you want to do next?” may be more useful than asking what someone wants to be
• What cross-functional AI use reveals about the changing nature of work
• Why broad learning may be becoming more valuable than narrow expertise
• How outdated job descriptions quietly constrain organizational value
• Why organizational context may matter more than model selection
• What companies should document before introducing agentic workflows
• The difference between routine, complex, and frontier problems
• Why advanced AI should be reserved for questions requiring genuine discovery
• What separates AI investment from meaningful work redesign
• Why leadership may be the greatest barrier to becoming AI-native

About the Hosts

Jason Averbook

Jason Averbook has spent more than 30 years shaping HR technology and workforce transformation. His career includes leadership roles at PeopleSoft and Ceridian, co-founding and leading Knowledge Infusion from 2005 to 2012, serving as CEO of The Marcus Buckingham Company, and co-founding and leading Leapgen from 2018 to 2023. After serving as Mercer’s Global HR Transformation Leader, he co-founded Now to Next to help leaders prepare people and organizations for an AI-shaped world

Jess Von Bank
Jess Von Bank brings more than 20 years of experience across recruiting, talent strategy, employer branding, HR technology, and workforce transformation. She began as a recruiting practitioner before moving into leadership roles focused on bringing workforce solutions to market, including global HR transformation and technology advisory work at Mercer. She is now co-founder of Now to Next, where she combines industry expertise, community building, storytelling, and a human-centered perspective on change.

Stay Connected:

Jason Averbook
LinkedIn: https://www.linkedin.com/in/jasonaverbook/
X: https://x.com/jasonaverbook
Substack: https://jasonaverbook.substack.com/

Jess Von Bank
LinkedIn: https://www.linkedin.com/in/jessvonbank/
X: https://x.com/jessvonbank
Substack: https://jessvonbank.substack.com/

Now to Next
Website: https://nowtonext.ai/

Transcript

SPEAKER_01 0:01

Hi Jess, how are you?

SPEAKER_02 0:03

I'm good, Jason. How are you?

SPEAKER_01 0:05

I'm so excited. We're finally starting this podcast together.

SPEAKER_02 0:11

Do you know what it took for me not to say Happy Friday just now?

SPEAKER_01 0:14

I know. We've been talking about this for so long, and we've had so many people ask us about it that I'm so glad that we're finally starting it.

SPEAKER_02 0:22

I honestly can't believe people want to hear us yap more than we already do.

SPEAKER_01 0:28

Well, I think yap is an interesting word, right?

SPEAKER_02 0:33

I think people want to hear Do you mean rap or yap?

SPEAKER_01 0:36

Rap or rap.

SPEAKER_02 0:37

Oh, we could do both. This could be the yap and rap show.

SPEAKER_01 0:42

Well, let's talk about the name.

SPEAKER_02 0:45

Yes, what we actually are.

SPEAKER_01 0:46

Edge of Now. The Edge of Now.

SPEAKER_02 0:50

I love it. I love it. It goes with well, it goes with a couple of things. I love that a few years ago we stopped saying future of work and we said it's it's happening. It's right now. It's the now of work. We have a now of work community. We called our business now to next. Um and when we talked about this podcast and what we wanted to talk more, the fact that we needed a little more time and space to talk about things. Uh, I loved the edge of now. It's all coming together, Jason. The plan.

SPEAKER_01 1:22

It really is. It's amazing how that happens. It takes a lot of planning, right?

SPEAKER_02 1:28

Totally. Yes.

SPEAKER_01 1:29

But it's also been fun building this together with the community. And I'm so glad that uh this podcast is just another way to reach that broad, broad community. So I'm excited.

SPEAKER_02 1:43

I think uh who would our contenders be? I think like the the Scott Galloways and Kara Swishers of the world.

SPEAKER_01 1:52

Well, I was gonna that one of my leadoff questions for you kind of before was like, if you were going to design a podcast, who would you design a podcast after? And that might be where you were headed with this.

SPEAKER_02 2:05

Um, so I wish I listened to more podcasts, but I do have a handful of go-tos. Uh my favorites are always interview style. Now that you ask me that, I guess I probably know this. My favorites are um interview style, meaning somebody has a chance to really breathe into the conversation. It's not too rapid fire, it's not too long, but it's definitely not short. I think I think I'm suffering from sort of like this rapid fire of content online. Uh, and I I blame all the platforms with algorithms who like demand so much content to like stay active in the algorithm. Uh I tend to prefer a slow, thoughtful conversation. Um, and so I guess that's interview style. I mean, Oprah has a great podcast where she doesn't talk very much at all. She's sort of a famous talker. She does a lot of listening. I love Scott Galloway and Karis Wisher because of their banter. There's a lot of back and forth. They have great yin and yang. I think of us uh kind of the same way. I love Nicholas Thompson's podcast, the most interesting interesting thing in AI because he talks to super smart people and really knows how to probe because he's a subject matter expert as well. So his probing interview style is really, really good. Uh yeah, I mean, those are just a handful of favorites. What about you?

SPEAKER_01 3:36

Yeah, you know, I have such an eclectic taste, I guess, when it comes to this. Like, believe it or not, like I do believe it or not, we're lined when it comes to Pivot. I'm a big fan of Kara Swisher and Scott Galloway, even though I will say sometimes we're gonna work on this. We're gonna make sure it doesn't sound exactly the same all the time.

unknown 4:00

Right?

SPEAKER_01 4:01

Right. Because sometimes you can be like, oh man, they're talking about that again, oh man, they're talking about that again, oh man, they're talking about that again. Uh, I'm a huge fan of um the all-in podcast. Now, one of the things we're gonna do with this podcast is we're not gonna get political. Okay. As much as we can not get political in a world of politics where it drives everything. So the all-in podcast tends to get a little political at times, which is where I'm sure I turned some people off when I said it, but I do like the style. I love Smartless. Do you listen to Smartless?

SPEAKER_02 4:34

I think I've caught an episode.

SPEAKER_01 4:36

Yeah, where they have like a mystery guest on and they introduce the mystery guest. Um, that's always fun. I'm just looking at my list. Uh, I love on purpose with Jay Shetty. It's a good one. Uh and the last one I'm gonna throw out is I love the diary of a CEO.

SPEAKER_02 4:55

Oh, that is a good one. I love podcasts I can watch.

SPEAKER_01 4:59

Uh and well, that's why we're recording this, right? Yes.

SPEAKER_02 5:03

Yes.

SPEAKER_01 5:03

Uh, you know, and and we're both in the same city as we're filming this, and you're no sleeves, of course, and I've got like long sleeves on and all that other stuff. You know, the diary of a CEO uh podcast, and one of the things I just want to throw out about it, like right now, the what episode that's on there is the vitamin D expert. The supplement world is giving the wrong advice. And a lot of people that think about the diary of a CEO podcast wouldn't think that they'd be talking about that. So give that one a chance, just for everyone listening. D-O-A-C, Diary of a CEO.

SPEAKER_02 5:37

Yep.

SPEAKER_01 5:38

I love it. So, what we're going to do, you guys, as part of this podcast is we've kind of broken it up into four chunks. Okay. Now, the four chunks could be three chunks, they could be two chunks, they could turn into seven chunks, but we're going to start with four chunks. Okay. And the four chunks are A, the signals. What are the signals that we saw this week that we want to talk about and we want to bring to light in this discussion? B, dive into one of them really deep. The Hughes, what we're going to call the real story. And that real story is, you know, probably a little back and forth, maybe some tension, maybe some debate, healthy debate about one of them. The third one we're going to dive into is the human question, which is how this is affecting humanity. And it's a really key component of this podcast in a world that's to me filled with too many technical AI podcasts right now. We're going to talk about the impact of AI, but the human side of AI. And then lastly, kind of the edge. One or two predictions for the upcoming week.

SPEAKER_02 6:55

Ooh, for the upcoming week. Wow.

SPEAKER_01 6:58

Yeah, like we're this is the mode that we're going to be. I mean, well, sure, we'll do our end of the year show and all that stuff, and we can make predictions for the next year. But like just something that you think is going to be important to watch in the next week.

SPEAKER_02 7:12

Yeah. Cool. Yeah. Yes. You know, I feel I feel like there's a lot of pressure to keep up with. Like when you say in the week, uh, do you ever take a week off, Jason, and then feel like you missed so, so much? But that's all that that could be your edge. Totally. It's just taking a week off. What people feel is sort of a sense of the pace of things and the timeliness of things. Um, but also like just kind of understanding what's real and relevant in the moment while things are happening.

SPEAKER_01 7:46

And and the other thing that we're going to be doing with this, you guys, is we really want this to be something that you become, this is going to sound corny, but friends with us. So we want to take this on the road. We want to do it live at conferences, we want to do it in your organizations, etc., etc. So we're probably get a little personal at times too. Um, you know, talking about the impact on our kids and our families, as I really believe it's the best way to tie a lot of these things together.

SPEAKER_02 8:15

I love it. So let's start.

SPEAKER_01 8:19

Let's start with the first one that I think is a really important signal. Now, Jess, when we I every week we're going to introduce some signals. You might just pass. You might say, that's way too controversial. I don't want to talk about it. Or you might say, you know what, I don't know anything about that. And I might say to you, I don't know anything about that. So we don't always have to comment on it. But to me, they're just important signals to be watching.

SPEAKER_02 8:45

Perfect.

SPEAKER_01 8:47

So the first one the first one ties back to a substack that I wrote this morning that you probably didn't read.

SPEAKER_02 8:54

I haven't read it yet. I'm so sorry. I was working on further content.

SPEAKER_01 8:58

That's okay. But it was all about this concept of we all have to go back to school.

SPEAKER_02 9:03

I did see the headline.

SPEAKER_01 9:05

And that there isn't like a you go to school and then you're done learning, then you go to work and you just do your work. Like it over 30 years. That we live in this world now where everyone is schooling, working, and education and learning is an ongoing thing. And that as we think about the world today and what's required of it, this concept of a broad ongoing education may be more important than a north-south vertical education.

SPEAKER_02 9:42

Yeah. Oh, this is a good one. Okay, so no joke, just two days ago, Saturday, I was driving, I was in between softball games uh with one of my kids, and I had two of her friends.

SPEAKER_01 9:56

I heard you almost got kicked out of a softball game. Is that true?

SPEAKER_02 9:59

That is a true statement.

SPEAKER_01 10:01

Different statement, different story, different time.

SPEAKER_02 10:03

I'll tell that story another time. That is a first time for me, by the way. I'm not the type of parent who normally lunges uh for the fence to dispute what's happening on the field. Uh anyway, different story, different time. Uh, but we had a long enough break in between games. I had Kenna and a couple of friends in the car, and we made a dash for frozen yogurt because it was so, so, so hot. Uh, and one of Kenna's friends, Ashley, asked her, I know, like there was a sometimes you get really good car conversation as a parent, right, Jason? Uh Ashley said, Kenna, what do you want to be when you grow up? Like randomly. And Kenna said, I have no idea. She was sort of like scoffed at the question. I have no idea. And I thought about that and I just shut up as a parent does when there's a good conversation happening in the car and you don't want to like ruin the flow of that. But in my head, I realized what I didn't like about that question, what I loved about her answer. And I actually thought to myself, I think every time I want to ask that question, I'll say, What do you want to do next? What do you think you might want to do next? It is way too far out for young people to think about what they want to do when they grow up. And I know plenty of adults still trying to figure out what they want to do to feel fulfilled and purpose-driven and happy and all of that stuff.

SPEAKER_01 11:26

I think that's really I think that's really good. Like, what do you want to do next? I like that. Just next. Like just Yeah, and and the next is tied to what you just did now.

unknown 11:38

Right.

SPEAKER_01 11:39

Sorry, try to tie our now to next together. But you know what I mean? Like, we don't know what exactly what that means.

SPEAKER_02 11:44

Don't like I feel like I could ask you, what do you want to do next? And you would have some, you know, like anybody of any age, any point in their career, it doesn't matter whether you've transitioned careers, uh, if you've been in the same space your whole career, like everybody probably has something that they might say, gosh, I wish I could do this. I think for young people and early career people, um, it's especially important to give a little bit of birth, a wide birth to figure out number one, we don't know what jobs are going to look like. Number two, skills have a half-life of almost nothing anymore. Um, and I do think the most competitive organizations of the future will be learning organizations. They will have cultures, a leadership mindset, lots of psychological safety and permission for people to always be developing, always and self-developing as much as organizationally developing. I think it has to be top-down and bottom-up. I have to have hunger, drive, curiosity, and space permission, you know, freedom to sort of learn, make mistakes, get new skills, keep refining my skills. And the organization has to give me some direction for what might be most valuable and important to achieving business outcomes. Both of those hand in hand, uh, I think is the most powerful thing organizations can be thinking about enabling right now.

SPEAKER_01 13:13

And and you know what I think is really interesting, Jess, and we'll put this in the this is why this is signal number one, because I read this fascinating piece early this morning. Um, it was a a study done by OpenAI, their economic research group, that was called uh work at the frontier. And the thing that I found f most interesting about this is that out of all chat GPT inquiries done at work, almost 50% are done outside of the domain where the person actually works.

SPEAKER_02 13:51

Ah, I was dying to see how you were going to finish that. Interesting. Interesting. So what does that mean to you?

SPEAKER_01 14:00

Well, it just means people are working more, like I've said for about the last year, east-west instead of north-south. Like they're not just working deep in a domain where they already know what they're doing, they're having to go across the the domains. Uh, and we'll put a link in the study um into the show notes where you can actually see how they're going across. But I mean, for example, if I take a look at engineering, you know, 53%. But engineering, they spend 4% of their time in customer experience, 4% of their time in design, 9% in finance, 4% in legal, 20% in marketing, and 2% in sales.

SPEAKER_02 14:42

Wow. Wow, wow, wow, wow. Look at all the skill sets in one person. One yeah.

SPEAKER_01 14:49

So it just it kind of meet for me when we're thinking about the preparation, back to this first signal that I wrote about this morning. The more broad that you can be to understand how to use humanities or human skills, which we'll talk about in a second, uh, the better I think we're gonna be, you know, as quote unquote prepared for work.

SPEAKER_02 15:11

You know, I I don't know.

SPEAKER_01 15:13

By the way, think about I'm sorry to interrupt you. Think about all of the challenges that causes, though, like job descriptions, uh competencies, uh, skills and things like that. I mean, it requires someone to be either very good at using tools, which is I think for sure, but then how do you know what question to ask next means you have to think about being broad enough cross-discipline.

SPEAKER_02 15:48

Oh, okay, there's so much in that. I I don't know if you know, Jason, how many times I tell this story, because I don't think I've ever told it to you. Uh, but sometimes when I talk about the role that I played at LeapGen, which was the prior consultancy, um I joined after you were already um off and running, but you asked me, I don't remember how I don't think you asked me to be a CMO or asked me to be the, you know, mar like you, but the word marketing was definitely used. And I definitely remember my response. I'm not a trained marketer. I acted surprised, confused, like, what? I'm not a trained marketer. And you said, I don't need a trained marketer, I need a storyteller. And you needed business outcomes, often espoused by a CMO. Like, so, so, like what you asked for were business outcomes. And the lever you needed pulled was storytelling, and you saw someone who could bring that to the table. Who cares what was on my resume, what I had done previously, it would not have been captured exactly in my resume, but you knew me. I told that story all the time because then it took a while after that. People naturally now thought that I had a title or like the I don't and I and I still say, no, I've never really been a CMO or a marketer really in my life, but I have been an industry storyteller for a long, long time. Um, and I think that's how people need to I so job descriptions unfortunately are lagging behind what the market is actually doing and how jobs are disrupting themselves, which is sort of ironic because it's one of the first things we rushed for with AI. But all we're using AI for is to perfect job descriptions as written, uh, instead of using them to be a little bit more intellectual and intuitive and to suss out like what the actual capabilities are that would produce the business outcomes and how you might look for a person like that. Unfortunately, we're still using stupid job descriptions and stupid resumes. And yes, I'm using that word on purpose, meaning lack of a little bit more intelligence, which would be a huge opportunity in this moment.

SPEAKER_01 18:04

So, just the other thing I found interesting since you brought it up is that if you look across this, and I'm if you look across this, and I by the way, for those of you watching on YouTube or wherever you watch, I hope this is valuable that you can see it. Look at the job that is got the biggest bubbles all the way down from top to bottom. So left to right would be the occupation, right, or excuse me, top to bottom would be the traditional task. And look at marketing 26, 28, 20, 25, 23, 36, 29. All that's saying or showing is that the ability to still tell stories, like you just talked about, is uh a huge part of every occupation.

SPEAKER_02 18:54

Yeah. Because store because storytelling is connecting the dots, which is understanding context and applying some reasoning and some lived experience and pulling a thread through the story to help somebody arrive at a conclusion. Like think about the art of storytelling. That is, I think it's the number one skill right now. Yes, in the AI era, don't think of storytelling as drafting language. That's what Jen AI started doing for us a few years ago. And it's not all that artful. It can be, but it's actually quite, I mean, we we know what it is. It's just sequencing and predicting and putting things together that make mathematical sense. The actual human critical thinking ability here is distilling insights and understanding what you're consuming and why it matters and applying it in new context and under and then translating. We've talked about translation, Jason, a number of times. Translating back to the business why to care, if to care about this and why. That is, I mean, humans sort of need to reimagine their own uh value in this thread. It's actually more important than ever. You just have to think about how AI is assisting you, not you assisting it.

SPEAKER_01 20:22

You know, and I think I think that for me, this study is probably like one of the clearest signals yet that AI isn't just changing how we work, it's changing what work is. Does that make sense? I mean, it it it's like tasks are moving across traditional boundaries.

SPEAKER_02 20:44

Yeah.

SPEAKER_01 20:45

We can't keep static job descriptions. And I think that like the leaders who are uh AI native, let's just call them that, are gonna organize around outcomes and orchestration, not titles.

SPEAKER_02 21:00

Yes.

SPEAKER_01 21:00

So, you know, all that being said, I think it's about people creating more value. It's not about people doing more jobs. And I think that to me, that's the highlight of this one study that we'll put out there is that you know, jobs are becoming a really fluid collection of capabilities rather than fixed roles.

SPEAKER_02 21:24

I think that's accurate, but a little bit wishful thinking yet. I have yet to see a bunch of job descriptions do away with themselves and be replaced with something better.

SPEAKER_01 21:38

I ever say that I didn't say it was I didn't say that it's a good thing. I think that's what happened. Here's what I'm trying to say. The job descriptions haven't caught up yet, but the fact that those inquiries are happening the way they're happening is proof that the work has changed.

SPEAKER_02 21:55

Yes. It's proof the work has changed and needs to change. Now, all of the artifacts and infrastructure of how we operationalize work need to catch up really, really fast because your inability to catch up to that reality is literal value. It's it's like leaving the window open with the air conditioning on. You're just letting all that value out your business windows because people are wanting to capture value and realize impact differently than they are, but your systems aren't designed to help them do that. And if they're not, that's that's total friction.

SPEAKER_01 22:32

And just that is a perfect lead-in to our kind of signal and deep dive number two. So you know one of my favorite authors on X is Aaron Levy.

SPEAKER_00 22:46

Mm-hmm.

SPEAKER_01 22:47

Do you know Aaron? You know Aaron, right? Aaron's the CEO of Box.com.

SPEAKER_02 22:51

Yes. I think you've sent me a head or two.

SPEAKER_01 22:54

I'm sorry?

SPEAKER_02 22:55

I think you've sent me a headline or two from Aaron.

SPEAKER_01 22:59

Random texts in the middle of the night. So so for those of you that don't follow Aaron, Aaron's at Levy, L-E-V-I-E on X. Um, and for those of you that don't use X, um You can still see headlines. Yeah, you can still see headlines, yes, and we'll talk about it. But one of the things that Aaron said uh in in a in a tweet or an X, whatever I'm supposed to call it over the weekend, is the battle in AI is shaping up to be a battle for context. Context. And the way he talked about it, he said enterprise AI advantage is shifting away from models and towards context. And defining context as the combination of governance, knowledge, domain expertise, tools, and workflows. And and I think that it's really, really interesting to think of context is bigger than knowledge. Because in the past we've just like captured our knowledge databases, but when we think of context, it's all of the rules, it's how work works and things like that. And I think that that's a part of what you were just saying that hasn't caught up yet to that is that thousand percent. And and I go ahead. Sorry.

SPEAKER_02 24:20

Oh my gosh. Okay, so I guess it was in March because I was there for Women's History Month. GE had me come out, GE Appliances had me come out for Women's History Month doing some AI stuff. Uh and I'll never forget one of their most senior engineering people leaders in the room. Uh, I was going on and on about AI, pretty mixed audience, but as an organization, very AI forward, very innovative uh in all parts of their business, how solution, you know, how uh appliances work, how customer experiences are designed, how things actually get made on factory floors. Uh, and one of their most senior engineering talents raised her hand and said, I'm getting pretty worried that no one around here is actually going to know how work works anymore. And what she's talking about is literal documentation. Literal documentation for several reasons. Number one, how does this thing actually get done so that you can map it and multiply it and automate it and let agents take it and run with it. Also for auditability and traceability, which is accountability, all of the things, you know. And it was such a it was such an interesting thing to say. Of course, we know this is like the year of agents. Like if last year wasn't, this year definitely is. And I think that's such a wise thing to say from a business process and governance perspective. You probably have no business playing around with agents if you haven't fully documented how work works in your organization and what and what that gives you, when you can literally document how things happen, you before you automate anything, you should interrogate it to see if it's still worthy and and should be happening that way, and refine it and optimize it before you push it into agentic workflows and full automation. Mo I don't know about you, Jason. Most organizations are not close enough to this yet.

SPEAKER_01 26:25

No, I uh and once again, uh, you know, what you've heard me say a fool with a tool is still a fool, blah, blah, blah, blah, blah. I mean, I I and we'll talk about tools just because we have a lot of listeners who, you know, who care about tools. We'll talk about tools in a second. But I I I I think that this is really, really important when we start to think about what is context. You know, so we've talked about in the first signal, work changing. In the second signal, we're talking about this concept of context. And if I continue to go down the bad look or the the line here of the discussion, it's AI natives aren't just giving agents better context. They're building systems where every interaction strengthens the context for the next employee, the next team, and the next agent. And and I think that's really interesting. When I was reading this, I jotted that down because for me, I was like, like for the tacit knowledge thing is still a huge problem. Tribal knowledge, walking out the door, entry-level jobs, not being defined, etc., etc. If we're thinking contextually right about this, I'm context expands and gets stronger every day. Does that make sense? And I'm not just doing automation, I'm really doing amplification and augmentation of the context of a company. And which is all of those things we talked about knowledge, expertise, tools, workflows. That's the competitive differentiator. And I think that going forward, we will spend a lot less time talking about which model and a lot more time talking about how are we building capabilities that drive human performance on an ongoing basis through context.

SPEAKER_02 28:28

I love that. I love that. And so what you're talking about is sort of like sense making and anticipating. It's kind of I how do I say this?

SPEAKER_01 28:38

I I mean there are it's compounding judgment.

SPEAKER_02 28:41

Yes. So if you have a fully documented workflow that you've pushed the way of documentation of automation, the workflow itself should be able to tell you or tell itself really that step wasn't necessary, or we never should perform that step, or that's not a value-adding step. So cut it. And it would self-optimize itself. And of, and yes, there need to be kick outs for you know, permission and validation and like, is this correct? Like, yes, do all of the, you know, the necessary kick outs and loop back in so that you can validate that you're doing a good and correct thing. That's just test and refine, test and refine. But a workflow should be able to do that to itself. You can't get there unless you've documented and sort of interrogated what a good workflow is. And then it should almost like self-clean, it's like a self-cleaning oven. Yes, yes, yes. I don't know about that.

SPEAKER_01 29:37

Well, I say, yes, yes, yes, but I've never used a self-cleaning oven. So that's maybe not the right thing for me. But it gets stronger every time. Like it, it it's sensing, you know, and this is where to me, in the past, with all these systems, if we wanted to change a workflow, we'd have to put in a ticket, go to IT, et cetera, et cetera. Now, as a manager or a leader, you know, if I'm looking at an expense report, I saw this, uh, I saw this in a vendor demo yesterday with Darwin Box, who was showing me some other new capabilities. And I was like, you know, like they were showing, like, hey, in the future, if a user doesn't need to see eight things and they just need to see one, they say that once and it automatically adjusts.

SPEAKER_02 30:22

Yeah.

SPEAKER_01 30:23

And I think that it if you think about all of the flows that we do, whether it be an applicant moving along faster, an expense report getting paid faster, like all of the that's sitting waiting for approvals along the way. I think that this concept of this concept of compounding context is really, really a huge signal for for all of us. And it's gonna change the way it I I've said this for the last three years. Instead of us learning how to use a computer, it's a computer learning how to work with us. Oh my gosh. Who we are, what we are, et cetera, et cetera. And I think this is a huge signal towards that.

SPEAKER_02 31:10

So I'm gonna add to what I said. I'm gonna I'm gonna yes and myself right now, if that's a thing. Earlier, I said the most competitive organizations of the future are learning organizations, and I was referring to your workforce, investing in sort of the time, skills, resources, permission for them to be a constantly developing asset on their own behalf. I would add a learning organization in terms of self-optimizing, self-learning, self-correcting uh your own documented workflows, everything that, I mean, that's the benefit of technology. Technology is documentation of how things are happening, of business processes and workflows. Uh, and if you can get that in a self-learning, self-cleaning oven mode, uh, that then that means your organization is constantly evolving and adapting on its own behalf without humans constantly having to push buttons and say next, next, next.

SPEAKER_01 32:09

I totally agree. Uh, so for me, that's something to really watch. That's another signal. And I say when, you know, when we say edge of now, one of the things I love about it is like it's not a signal for next year.

SPEAKER_02 32:23

Yeah.

SPEAKER_01 32:24

It's a signal for now. And I'd love for you guys to bring it into the work that you guys are doing every single day. So just the third signal, third and final signal, and we've added, we've already started to mess up our format because the signal and our real story have come together. But I Satya Nadella, one of my favorite people to listen speak. Favorite people to speak, can't speak like me. He can speak much better than me.

SPEAKER_02 32:54

I've never heard him live. I quote him often. You've never heard him live? No. I've got.

SPEAKER_01 33:01

Oh my gosh. Well, so I was listening to a podcast last night on the treadmill, and one of the things that he said, which I just loved, and I hope that listeners take this away. Uh we should not be using frontier models for non-frontier problems. Oh, oh, that's so good. And I loved it because it's like at first to me, it kind of sounded like a tech discussion, but then it turned into like, don't spend premium tokens on routine work. And are we really thinking about frontier problems or are we really thinking about just like little uh workflows? And it got me thinking deep into this whole concept of tokens and et cetera, et cetera, et cetera, to the point of like are we training anyone on that? Yeah. You know what I mean? Like, you know, internally in our small company, we're like, oh, we're out of tokens, we're out of tokens, we're of tokens, you know, and I probably did something stupid like, hey, can you look at this email and tell me what's missing from it to make sure that I wrote it in a way that I didn't miss something? That's not a frontier problem. No, but I probably use a very expensive frontier model to solve it and therefore cost us tokens. Does that make sense? Yeah, I think it's really, really important that all of us, when we understand these models, we start to think about um, you know, before we route the model, we route the problem and start to say, like, what is the problem that we're trying to solve? And it got me thinking, kind of like, for us, like in your head, what would be an example of a frontier problem? I'm putting you on the spot.

SPEAKER_02 35:00

Well, I don't know if I can name her or name this organization. One of our very good friends is leading AI transformation at a very impressive healthcare organization. And I'm aware of the fact that they blew through their budget for AI tools, handing out licenses like candy, and had to like literally call timeout, time out, what have we done with all of this tool investment so far? Please tell me it's not just drafting PowerPoint decks, which it was. Everybody's just creating a bunch of artifacts of work that aren't really themselves moving the needle on anything instead of, and I'm sure they were doing other amazing things as well. But frontier problems are uh, you know, discovering new disease interventions.

SPEAKER_01 35:53

Yeah. So oh my God.

SPEAKER_00 35:54

Oh my god.

SPEAKER_01 35:55

So sorry. I so really quickly, I I tried that exercise myself, and I had much more time to think about it than you did. Okay. And this is why sometimes I do I'm on the treadmill for 45 minutes. I plan to be on the treadmill for 45 minutes, and all of a sudden I'm on it for two hours because I'm st I can't get something out of my head. So here's what I jotted down. Sorry for those of you uh on the video because you're gonna see me reading off of a scrappy piece of paper. I said routine problems have we know the answers to. Does that make sense? Like routine problems we're just trying to do faster. Yes. Complex problems have kind of known methods. But frontier problems require us to discover both the answer and the method.

SPEAKER_02 36:48

Oh, I love that.

SPEAKER_01 36:50

Does that make sense? Because I was like, how do I break this down? So I was like, okay, in science and medicine, it's it's identifying a treatment for a rare disease, like you said. Yeah. In engineering, it's designing a system that must operate safely in conditions that have never been tested. So does that make sense? It it in in in in thinking about creative work, it's like a new product category rather than improving an existing product. So not just not improving a product, but a new product category that probably doesn't have a vocabulary yet. Does that make sense? I think those are frontier problems. And I I I mean, I I sorry, I guess you can tell how excited I get because I can't talk. Like, I don't even think we've scratched the surface on thinking. I think there are people that are, but on true frontier problems and these models, like these new models, when everyone's real excited, like, do you know there's been eight models released in the last three days? Like, yeah, they're all frontier models and they're all really expensive, and they should only be used for frontier problems. Is that's my personal take.

SPEAKER_02 38:01

Totally. I actually I had this moment yesterday. There's a mom I follow on Instagram, and she's the mother of a disabled child, and she shares his journey, and it's beautiful, and uh, and she posts stuff uh because she has a very rare disease. Uh, and so a lot of the stuff she's experiencing, she's sort of alone in trying to figure something out, or you know, there's she doesn't have a big community of people to follow herself. So she just puts herself out there for people to help, and you know, and she has like this little custom walker, literally custom, because he's a little guy and he needs it to operate a certain way to help him get over a curb, you know, to do certain things. So it's totally custom engineered. And she posted something yesterday, or you know, whenever I saw it yesterday, that said, could somebody help me figure out how to carry his walker? Because he doesn't always need it or want it. Uh, and we like him to be able to walk on his own when he can and wants to. And this thing is heavy for me to lug around and like, you know, could somebody figure out how to like maybe I could wear it like a backpack? And I literally had this thought, I wonder if she put that thing in nano banana to see if it could like possibly like, you know, and I like I combed the comments, like, is anybody helping this? And of course, there were lots of like engineering people, like, take this to a machine shop and ask them to do this thing and whatever, and like everything was, and I was like, this that's a frontier problem right there. I wish we could help come up with new novel solutions for for things that are hard to crack on our own. Don't like I totally drafting email, like no shade to that doesn't mean we shouldn't use AI for that. No shade to to to the other stuff. It's just not the big opportunity. It's not the big opportunity.

SPEAKER_01 39:47

Yeah. No, completely agree. So when we think about the week, and once again, we're recording these earlier in the week. We're gonna post them a little bit later in the week. But if you think about these three signals that we talked about, and you had to try to wrap them up into one message.

SPEAKER_02 40:08

Yeah.

SPEAKER_01 40:09

Any ideas?

SPEAKER_02 40:10

Well, so last week, I know this was a little bit reactive, you sent me, I don't think it was the jobs report, but there was something about unemployment claims.

SPEAKER_01 40:19

Um I think I said I probably sent you the thing that more people were out of the workforce than ever before.

SPEAKER_02 40:27

Yes. Or not. Well, so it was okay, so it was this one. There's a report that said first-time unemployment first-time unemployment claims dropped, uh, and uh continuing unemployment claims also low. And so if I were to interpret that headline, we're in sort of this stalled out sort of phase. Low hire, low fire. Okay. Low hire, low fire phase of the employment market. And the other thing that I think we're missing here, like I feel like there should be a dot, dot, dot on there. We're not seeing very many net new AI jobs, meaning jobs drafted for what comes next. We're seeing not a lot of new jobs, new jobs, period, replacement jobs, not a lot of employment and first-time or continuing unemployment claims. I like when I read reports like this, I see a stalled-out job market. Employers are holding off. They're still making AI investments, but they're making investments in AI tooling and technology, not in AI forward people. We're not redirect, we're not redesigning jobs yet to keep up or to create value out of the actual AI technology investments we're making. We're in this stalled-out sort of in-between. I think that, and this isn't a next week prediction. I wish it would happen as soon as next week. I think in the months to come, we'll see a little bit of catch up in the actual jobs of the future, meaning what an AI forward organization who is redesigning work believes that it now needs from a human capability standpoint to operate in that environment. I still see old jobs or no jobs, um, which is which tells me it's a it's a lagging employment market.

SPEAKER_01 42:25

Yeah, and I and I totally I so first of all, Jess, I totally agree with you. I want to argue with you, but I can't on that. Um, I I totally agree with you. I do think that it's not spread equal. And I do think there are going to be organizations that are gonna leapfrog very, very fast other organizations who are. I I think there's AI native.

SPEAKER_02 42:46

You saw so then there's also the Ravellio Labs and Ramp study.

SPEAKER_00 42:50

Yeah.

SPEAKER_02 42:51

There are, and again, it's such a micro slice of the industry, but there are jobs who, or I'm sorry, there are employers, organizations who are investing heavily in AI technologies, tools, you know, strategies, and they're hiring more people because of it. So we're also seeing that, that is very much an edge case. Those are very bleeding edge, first mover organizations. I guess so. I guess what I'm saying is I think we're gonna see a little bit more catch up uh and a few more organizations going that way.

SPEAKER_01 43:23

Totally agree. And my, excuse me, my edge, which has got me choked up yet excited, is about leadership. Because I actually think that there's a new brand of leadership, and I've been writing about it quite a bit on X called AI native leadership. And I think AI native leadership to me is the thing that I'm gonna talk more about probably on this podcast than anything else. Because the only thing that's stopping what you're starting to talk about is leadership.

SPEAKER_00 43:59

Yeah. There's

SPEAKER_01 44:00

Nothing else stopping it. There's no government compliance issues. Like, why are people not being invited to meetings where the work goes east-west instead of north-south? As jobs are becoming more porous, we keep people in boxes. That's a leadership issue.

SPEAKER_02 44:19

Completely. There's nothing that needs to be invented, technology or otherwise, for you to become this kind of organization. It all exists.

SPEAKER_01 44:30

Right. I think that instead I think we've got the same thing about most leaders are still thinking of AI as task automation instead of human expansion. And you know, I I I would I did a huge keynote for an all-employee meeting this week. And I'm like, leader. And I then I did a separate breakout session for leaders. I said, leaders, you have to model this.

SPEAKER_02 44:55

Yeah.

SPEAKER_01 44:55

Like this is not about task expansion or task automation. It's about human amplification and human expansion. And the more that you can bring people along on that journey with you, in an as an AI native leader, which I I hope everyone listening to this becomes, whether you're a little kid that wants to lead your little pack of people in a different way, and saying, guys, AI isn't something that's burning more water, even though it is. Let's think about how we use it to help us all get better. Or, you know, whether we're an 80-year-old thinking about planning something, and oh, wouldn't it be cool if we created an image? Yeah, but wouldn't it be even cooler if we talked about how to keep a discussion going after our little meeting for an event where we created an image and said, let's uh make the humanity stronger. And I think that you and I talk about this a lot. Not human plus machine, not human human minus machine, not human versus machine, human times machine. Or like the new human variable work we're starting around HX. Like that human times machine with humans still at the helm is where this is all that's our now. That's the now it is now. It's gotta be the edge.

SPEAKER_02 46:27

So as you were describing that, I can't help but think of like everything is new and novel until it's not, right? Like we don't say generative AI anymore, it's just AI. I don't think we'll say AI native leader when we don't need to anymore. When you go shopping for a new house, you don't say, I'd like one with electricity, please. We sort of assume it's gonna come wired.

SPEAKER_01 46:47

You're so right. You're so uh now that you say that, you're so right. Like I I would never say like the mouse native leader as someone who's really good at using a mouse.

SPEAKER_02 46:56

Uh it's still new and novel. So we'll say it until we don't have to, and then it will just become core and implicit to our thinking. But for now, it's not. And that's kind of the whole point. It this has to become core and native to your thinking. So so I guess new and novel gets replaced by native. And until that happens, uh, we have to state it explicitly. Just like I said in 2025, I said, I don't think I've ever heard people use the word human, like in defense of ourselves, right? To fight for our own relevance more than I did in 2025, because it all of a sudden seemed necessary to define human because everything felt like human versus AI. It's not human versus AI, but all we were just getting used to new language.

SPEAKER_01 47:43

Do you remember in my book in 2018 where I said stop calling users users and said call them humans?

SPEAKER_02 47:48

I think I just quoted that in a in my LinkedIn post today. Stop saying users. Like I'm having we're having to say that all over again because we're doing it all over again for different reasons. Now it's users and agents, human agents versus AI agents. Like, oh my goodness.

SPEAKER_01 48:07

Okay. So, Jess, this was an amazing first episode. I love doing this. I can't wait to do this weekly with you. Yeah. Uh, do you want to thank our sponsors? Oh man, we're so many sponsors.

SPEAKER_02 48:20

I'd like to thank Bailey, who I made lunch for before we began. My second daughter, who walked in our background as we began. No, I don't know. Who would we like to thank?

SPEAKER_01 48:32

No, I don't want to thank anyone. I just want to say I hope well, I want to thank people for listening. A. And B, if you found any value in this, what is it that they say? Like, please share, uh, like us, uh, give us a star, uh, give us a thumbs up. But most importantly, I hope that you can use this as inspiration and education for what you do, whatever it is.

SPEAKER_02 48:58

I think they have our new intro or outro, Jason. You just reminded me when speaking of Bailey and Kenna, when they wanted to be famous YouTubers, and I let them create a like a private YouTube channel. And they I have a video, I'm gonna find it now, where they said, like and subscribe and smash that like button. And I have like 20 outtakes of them. Smash that like button. Yeah, do all that. Sharing is caring.

SPEAKER_01 49:25

Thank you guys so much for joining. First episode we're gonna do this weekly. Like us. I mean, don't like us. Like it, uh, give us feedback. Um, and yeah, smash the like button and uh we'll see you all soon.

SPEAKER_02 49:41

Thanks, everybody.

SPEAKER_01 49:42

Have a good one. Bye.