Billy Riggs (00:32)
Welcome, welcome, welcome to Rewiring the American Edge, where we explore automation, innovation, and the things that are reshaping the future. I'm Billy Riggs and I'm here with Vipul Vyas And I want to start with a little thought experiment.

imagining that we're arriving at work tomorrow and discovering that our company, maybe my university, they hired a hundred new employees with no office, no healthcare, no payroll, no onboarding, and they're working 24 hours a day to make our lives better. They never sleep, they're multilingual, and they

can do large-scale tasks and routine work happening within our organization all the time. And of course, that sounds ridiculous. How can you scale up an organization like that? that's increasingly realistic. And

I don't think most people realize it's happening. And unlike previous revolutions that our society has gone through from a work standpoint, this one is invisible without factories or assembly lines. Of course, there's not tons of giant physical infrastructure; Now we can talk digital infrastructure, but just software taking on more and more responsibilities and mission-oriented responsibilities. So

our goal is to talk about that today, about how we are transitioning from talking about AI as a tool to something different, a worker, a teammate. And so we're gonna call today's episode Agents Are Among Us. And hopefully, I think by the end of the conversation with Vip and I, I think you'll realize that agents are all around us.

perhaps not as nefarious as Agent Smith from The Matrix. so let's get started Vip, what's the first place to start.

Vipul Vyas (02:31)
That's I don't think that's new actually. This is just sort of a culmination of what's been going on in other ways for a really long time, for the past quarter century or more?

I don't think there's a lack of problems to try to go off and solve. The rate of absorption is going to be dictated also by how fast people in organizations can

consume the stuff or adapt to it or absorb it in general.

Billy Riggs (02:58)
Yeah, so when we compare what's happened in the past with the advent of the web, what we're seeing here with the advent of AI agents is, the web was a static availability for your business, but this potentially when you're thinking about regular office work, the ability to do the work of an organization.

in the absence of hiring a physical a physical individual is the somewhat is somewhat novel, right? I mean this is not the this type of automation is is a bit different than than rolling out a web rolling out a a PayPal store or rolling out an an eBay store.

Vipul Vyas (03:42)
I don't know. I mean, it was is a combine that basically look farm employment, agriculture employment was eighty plus percent of the economy a hundred twenty years ago. And now it's like five what, seven at most, maybe five percent. I mean the biggest worry that people are I think grappling with is farm workers became

Billy Riggs (03:44)
Yeah.

Vipul Vyas (04:09)
factory workers became knowledge workers and there was this natural progression of what you're gonna use humans for from just muscle to brains. And if this stuff comes along and the brain squart isn't needed, maybe even the muscle isn't either because you got robots, the question is what's there left for us to do? That's that's the real insecurity. right is is what what

Billy Riggs (04:18)
Mm-hmm.

Well, maybe we go ahead. Yeah, sorry.

Vipul Vyas (04:35)
what comparative advantage do we have over these things we've created and you know in in general as a as a person. and I think that's fair, but I think at the moment there's a lot of stuff just there's still a mountain of drudgery that we hire people to do. And that mountain still is being worked down.

Billy Riggs (04:44)
Right.

Vipul Vyas (05:03)
We had people who, I don't know how many years ago, maybe decades ago, but if you want someone to lay a foundation or make you a pool, they they broke out a shovel, right? And started digging. Now you have a backhoe and that job's done, in half a day or less. And th that's because the drudgery of having to dig out all that dirt and move it, take it off the site, all that, etcetera.

Billy Riggs (05:13)
Mm-hmm.

Vipul Vyas (05:28)
was just just drudgery. There's no real creative value add there. But it did employ people. There's people who, that's that's what they did. But and now in the white collar environment, there's a whole similarly, there's a whole bunch of just drudgery. and so I think that's gonna get addressed first before anyone's like and I know people are saying, well there's like job loss and

Billy Riggs (05:30)
Uh-huh.

Mm-hmm.

Mm-hmm.

Vipul Vyas (05:54)
This and that already. I think a lot of that is actually from overhiring during the pandemic. I I think, and there's some, don't get me wrong, some automation that the AI is driving that obviates and needs for certain jobs, like some analyst positions and whatnot. But I don't know, and people saying engineers aren't really need anymore. I I think in each engineer is becoming more productive. And so you can do more with less, but

Billy Riggs (06:00)
Yeah, yeah.

Vipul Vyas (06:20)
I I'm not a hundred percent sure if people thought to the fact that there's no engineering department anywhere, I don't think, that says, you know what? I've I've done everything I was supposed to do. I'm give me more. I mean, yeah, it's typically, I mean, they're they have a mountain of years worth of backlog that they can never get to and perpetually they're always, talking about the proverbial line of everything above the line makes it in, everything below the line.

Billy Riggs (06:33)
Yeah, yeah. I'm done for the day.

Vipul Vyas (06:48)
is pushed off for another day or never never addressed. And so I think you typically what you can do, what you can actually accomplish, is really just the part of the iceberg that's sticking out of the water. And the mountain of requests and p things that people want actually to get done is massive. And so at least at the moment. And so there's a big backlog that I don't think people in I mean AIMS will help eat eat into that, at least for the foreseeable future, I think.

That's likely where the energy will go.

Billy Riggs (07:18)
Yeah.

Well when you you we think about and and of course like in my area with with automated driving, we we've long thought that like driving and particularly gig work, those type of jobs aren't the most don't carry the most physical dignity, then use the word drudgery. And maybe using that form of automation to replace that type of work is kind of a nice parallel. But maybe when we're starting to talk about

Agents in the workplace that do white-collar work or can replace some white-collar drudgery. what do we what exact maybe we step back for the sake of my our power listener, my mother, and we kind of define maybe we can define what exactly we're talking about with an agent

Define an agent for me for the lay audience?

Vipul Vyas (08:08)
It's in a piece of code. we don't have to get any more technical in terms of is it a markdown file or this or that? But it's basically a piece of software that can be created by almost anyone, anywhere, that can handle complex tasks that involve analysis and generative creative.

Billy Riggs (08:10)
Mm-hmm.

Vipul Vyas (08:32)
output from text to pictures to spreadsheets to images to virtually anything that's rendered digitally today and it can do potentially more in the physical world in the future. But I think the simplest analog is blue collar workers who were displaced by automation way before, cheaper labor overseas, came along or at least in parallel. So

The Detroit Autoworker that used to put the the side panel assembly on was displaced or augmented by the robot that grabbed the assembly, bolted it on the chassis, welded it on, and pushed it down the the line. That robot is no different than the agent.

If you want to call them a robot to make make it cleaner analogy, that's fine. Then the robot or agent that essentially is told, go give me a equity analyst report on this company, with the purpose of seeing if it's an ideal MA target. Right? Which that so you're automating that.

Billy Riggs (09:41)
Yeah. Yeah. And I think that's a

yeah, that's a important distinction because I think there's there's a bit of confusion around this. There's a bit of confusion around this in that most some people who may be familiar with AI assistance may be familiar with Claude or Chat GPT or other assistance that they're using and

asking a question and getting an answer, but we're really talking about an interactive model that's different where an agent doesn't just answer the question, it's a goal of pursuit. And it's really transforming a task and accomplishing a mission. I think that's what you're describing in the prompt that you just said is that it's not just a a conversation that there are there are sequence of tasks that yield an output. So it's

It's research, analysis, communication, and decision support, but it's also the execution piece. And and I think that's something that that yeah, sorry, go ahead.

Vipul Vyas (10:38)
I don't know if we can Yeah, I d

I don't know. I look the the robot in the factory line had a mission to bolt this piece of metal to this other piece of metal successfully. And it was very prescribed and and def narrowly def seemingly narrowly defined. This seems much more ambiguous, but it's the same conceptually, the same idea, I think. And you could have a s you could say a series of robots act as a

single agent of today, and agents work in concert. And again, like if you want to just call it a robot to make it easier to understand, that's fine. It's it's basically software robot. And but again, I know I go, this is a sort of an extension combination of a significant leap, don't get me wrong, to what we've had with the the web for some time. Like the ability to let you purchase, to let you interact,

Billy Riggs (11:07)
Mm-hmm.

Mm-hmm.

Vipul Vyas (11:31)
and find product that you want, suggest product you might like, let you select it, maybe even select the options for it, put it in the cart and check out is a form of automation as well. This is simply just progression. And so I think and so the the question is and there it has implications, like this progression can go very, very far. And that's what the it's but ultimately it's a it's on the same spectrum.

And ⁓ the fact that that spectrum can go out, the question, I think is like if you have this line that goes out like this of of automation from the shovel to the backhoe to the factory robot to websites to this, et cetera, then there's a intersection point where this stuff exceeds human capability where you can just do more than the average person because in in a few ways it's very d different as that.

Billy Riggs (11:59)
Yeah.

Vipul Vyas (12:25)
A human is basing their judgment, their actions, even their emotions, based on their personal lived experience. And the agent is able to harness a huge universe of different people's lived experience. It can aggregate that. So it can almost bring in the wisdom of millions of people and make decisions based on that. Because you now

Billy Riggs (12:47)
Right, right.

Vipul Vyas (12:52)
taken lived experiences and commoditize them. So that which is the wisdom. And then you have a an ability to execute against that using, logic. And that's the part that's very hard for a human to frankly compete with.

Billy Riggs (12:56)
Mm-hmm.

Vipul Vyas (13:11)
ultimately someone has to decide what it is that that thing is gonna do. There's there's an ultimate point of accountability. Well yeah, what's what is what is the mission? You know, I think you said like this has a mission like that's someone has to decide. And I don't know if there's a I think maybe Jeff Bezos may have said the same, but I I tend to agree that there's not a l there's an infinite number of problems to solve.

Billy Riggs (13:15)
Right. Yeah, what what's the output? Yeah.

Mm-hmm. Yeah, and I think that we will still have an infinite number of problems despite these advances. But I think when we if we look to brass tax and of kind of the stuff we're talking about, I mean a couple of examples that that have come up to me recently and and and folks are aware I took a each year I take twenty to thirty students to Belgium, the Netherlands, sometimes Germany to do

Vipul Vyas (13:36)
And we don't seem to be doing a great job of solving them.

Billy Riggs (14:03)
research consulting and it's an international immersion course and many times we do quick strategy assessments. But what I saw when I took the students this year was that their their pattern of work had changed. Now in the past years that when Canva and some of these tools were coming online, they yes, they integrated some AI to do image generation or to do discrete tasks within the process flow. But

using, for example, Gamma and Nobook LLM, and they the students were able for real very quick strategy studies to bring in research reports, transcripts, presentations, and to really provide strategic advice in a much more lean and agile way than I've ever seen before, and and of a much higher quality than what I've seen before. And that doesn't that didn't

mean that they didn't have the formative knowledge to start off with. But it meant that they were giving the software the parameters to to work to achieve the mission of delivering, for example, strategy for the the Dutch government, strategy for an automated vehicle company that's operating in Belgium. And I think this is this is really potentially

something that accelerates solutions. And you said there's an infinite amount problems. You know, we were able to provide solutions and creative ideas, and the ideas came from the humans, but they they were executed by deep analysis from some of these tools. And I for me, I find that I find that revolutionary.

from a work process standpoint. And I know Viple, you and I have texted back and forth about last week. We're seeing the same thing in software development, right? I mean, I I I my brother sends me an app a day these days that he's spending up to and he's vibe coding them. He's he's writing, testing, debugging and documenting code in minutes in a way that that used to take multiple teams hours.

And it's I mean, again, th there are many there are many things that we can do to make our lives more convenient, but I see it as transformative because taking your idea to action and implementation just got a lot faster. And I find that I find that incredible.

Vipul Vyas (16:20)
Well you

Yeah. I mean you basically if you can think it you can probably build it. If you can conceive it, you can probably make it. So that just means there's gonna be a lot bigger pol it the the there's a few big structural things I think are going on. One is you used to like to build a a car cost effectively. cars used to be handmade. I think Rolls Royce's still are Aston Martin, so they're literally handcrafted.

Billy Riggs (16:28)
Yeah.

Vipul Vyas (16:50)
But you really can't cost effectively scale. So you had to have a lot of capital to create a factory to make things at scale so that you can

Have a market for a product that is reasonably priced. Right. And similarly with software, you had to go off and you had to aggregate a team, a bunch of engineers to be able to pull together the code that would be necessary to launch a specific piece of software. Now you could do that with a fraction of the number of resources.

Which is one of the reasons these SaaS stocks were under so much pressure for a while. Do you buy this off the shelf piece of software or do you build it yourself because you can't? Now, I think there's some tension there. You know, when HTML was was something everyone was learning, twenty something years ago, you could build your own website. But nowadays people just would like if they're gonna build your own they're if they're gonna have an e commerce site, they'll just get like Shopify or something like that. They don't typically go out and

completely. Even the biggest some of the biggest companies just use things off the shelf. Yeah. Yeah.

Billy Riggs (17:54)
Right. They plug and play Stripe, he plug and play Paddle.

There's so there there's many tools out there to integrate with your with your with your WordPress, with with anything. So and there's there's also open source platforms too for content management. So

Vipul Vyas (18:03)
Right. So so I just don't think

so I think this notion of everyone's gonna build everything themselves is probably not quite right. And we've seen this this sort of come and kind of happen before because ultimately people just don't want to own like so say you build your own piece of code, then now you have to maintain it, you have to you've all of a sudden become the developer and product manager for this thing. Which, you know, is that really what you want to do?

I d I don't think so. So that I think for s

Billy Riggs (18:32)
Yeah. But the counterpoint there, Vipul,

a lot of developers for a long time made their their bread and butter, for example, you know, for someone that would do up a wordpress template for somebody that was going to use a CMS. But now you could vibe code your own WordPress template, download that and execute it on your own server.

And you could do all that in a matter of minutes and, mimic the highest design website out there that somebody spent twenty, thirty thousand dollars on five years ago.

Vipul Vyas (19:02)
Yeah. So what's the implication of that? Means there can be more of that, right? That's w what what you're describing is there used to be lots of friction in getting things done. Now there's just less friction. So you can argue that there'll be fewer jobs or you can argue that more will happen.

Billy Riggs (19:17)
Yeah, and so that's an interesting, I mean I so that's why, I know you weren't as energized about my idea of the digital workforce, because you said, like, we saw this happen with the advent of the the website. But with my introductory thought experiment, that now you can just prop up this small army of of minions, this small army of people or not people, agents that can help you spend less time organizing data.

And more time making decisions that can help you spend less time searching around and more time interpreting and designing. And I think that's really where it doesn't lower the need for expertise, it actually increases the need for expertise and particularly for deep thinking. And that's where I mean I would be interested, if you can go with me on the journey and call it a digital workforce, what do you think?

It means for the future of what people are doing, but also how we educate people for what they're gonna do in the future.

Vipul Vyas (20:13)
I think critical thinking is gonna become even more important to degree. And I think someone who's a philosophy major is probably maybe even potentially more valuable than someone who's a, applied science or engineering major. Maybe. I think the combination is actually where things get really interesting. But there's no pushback against the idea of having these digital minions, if you will. I think that's

happening, people are making it but I don't look at these things as that radically different than my Roomba, which is just removing something that wasn't that high value a task anyway.

Billy Riggs (20:49)
Well

Roomba probably not the best example,

Vipul Vyas (20:51)
well thanks to

the I guess it was the FTC or who, but yeah, the they've kind of gone to the toilet. But the point there is that these things are taking away tasks that probably were repetitive, ⁓ had some degree of pattern, at least for now. and even the ones that aren't, even the ones that are higher thinking.

Billy Riggs (21:06)
Mm-hmm.

Yeah.

Vipul Vyas (21:12)
They actually serve more as an anvil than anything else. There's something that you use to beat your ideas up with as opposed to wholesale repla no, so I think people do wholesale replace. Like I think if you want to get some kind of basic report on, like, if you gotta write a report or book report on the on a particular book, you could probably just have ChatGPT do it. But if you want to do a good novel, new creative thing, what you're doing is actually saying, you know, look, in the past, let me put it this way.

Billy Riggs (21:16)
Yeah.

Vipul Vyas (21:41)
Hmm, back years and years ago, right? Before there were so there were software word processors, like Word, and people can't even imagine this, I'm sure some people. But you literally had to get a blank sheet of paper, put it into a typewriter, and start typing. Mechanically, literally, levers were hitting it against

wood pulp and then your thoughts were gonna render from your brain onto that piece of paper through a mechanical mechanism. And you know if you screwed up you used whiteout or something if anyone remembers what that is or you ripped out the paper and you started over right and and you did this and you went over until you got all your thoughts out. And there was massive friction in doing that of getting this stuff out and out of your head. And then

You got word processors and now you could edit, you could replace, you could copy paste, you could do all kinds of you could format all kinds of wonderful things. Right. So that removed a different degree of drudgery. But you still had to go to the library. And back in the day you had to take your index card and you had to write the source and then the quotation, and you had a whole box of whole yeah.

Billy Riggs (22:54)
⁓ I ⁓ I am that old, Bipple. Yeah, I remember doing the you had the index cards and you're going and looking

for your sources. Oh my gosh.

Vipul Vyas (23:03)
Yeah. And you quit the quote or the piece of evidence and all these index cards and you had a whole potential index card box of index cards of all the research you'd done. And that was your you you felt like you were doing real work 'cause you did all this research. You hit the library.

Billy Riggs (23:16)
I remember the first

stats class that I took and we had to do everything by hand in a blue book. So all the the entire equation. And so may maybe I bring that up to say because I teach stats, and you and I have taught the same course before, but I transitioned this class. You know, I've always felt like that my students who are

Vipul Vyas (23:24)
yeah, yeah.

Billy Riggs (23:40)
urban planning or public administration students, only a small fraction of them will learn to code. Only a small fraction of them will learn Python or a script that allows them to work in some of the the the to work with some of the most fancy schmancy statistical software. Or they pay, a boatload of money to go buy SPSS or some one of these other packages. But now

The way I teach stats is actually loading Python scripts into LLMs, parameterizing them, and having the students run the scripts, knowing the statistical output they want, and and being able to assess it and then compare it to: hey, here's an Excel output, here's a here's a Python script run through an LLM. Compare those outputs and by and large.

Sometimes they're not the same. Why? Because of the way, for example, the the script is entered or the way that rounding occurs. But it's a really effective way of it, it's a very effective way of teaching statistics in a new way. And yet, what do we say to the people that say, well, is it important that we understand the actual equation?

Is it is it important that we actually understand the details of how to calculate it by hand in today's day and age? You know, is it important that that that fundamental function may be that fundamental gap in knowledge? There may be a fundamental gap in knowledge, and yet the student knows how to get to the solution with the tools of today's society. And I I don't know the answer for that.

Vipul Vyas (25:18)
Well what I was going before is that you know you went to those the I was giving the index card example and now the person who's doing the research can just use the internet, which that was a that was a big leap. Like you don't have to go to the stacks anymore, the library and pull out a bunch of microfiche and you know s through. stuff. Right. Like like you like you like

Billy Riggs (25:35)
and everybody was angry, you're like, You didn't go to the stacks. You you found this on Google

Scholar and it must be incomplete as a result.

Vipul Vyas (25:41)
Right. Yeah, like you cheated somehow, right? And so then,

you've got internet now you're going one step further where it's actually pulling this stuff for you. And there's a there's a selection bias. it could be potentially not pulling all the right things. So you have to have the right prompting to say, no, I want you to look here, here, and here and make sure you don't disclude this, this, and this. and so but it but it but just think about that. The amount of research you can do now is massively more

than it was before and you're gonna be much much more productive. Now, do you need to understand the basics of research and I I would say that if you need to replace the learning of how do you capture citations correctly, I remember that was a big thing. You gotta make your citations just perfect. With do these citations hold merit? So I think that's a more useful thing to do. I mean you're basically teaching people

how to use microfiche, how to use the library, how to use, the the card catalog. There's a lot of things you had to learn that were just not that ultimately important to the end. There was a lot of waste in the process. And now what you can do is replace that encumbrance, that that knowledge that you had to have just to mechanically pull something off. Take that brain space and use it for something more valuable, which is the power of discernment.

Which you were having to teach as well, but it was having to compete for attention with a lot of things. Now, so the the key is is to know that that is what you have to compensate with. That just because it's easier to do doesn't necessarily mean it's the best you can actually produce unless you have these other skills that are probably in this context more valuable. Look, knowing how to use microfiche, not that it was some, amazing skill or anything, but

It was important to know how to use it and being savvy with how to like navigate those those tools was was valuable. But it's not I mean, that's not that's you don't need to know that now and you shouldn't know it. And it's a waste of time and effort if you do, one it so the point there being that now the things you have to know really well are just evolved, and that's always happening. That's always happening.

Billy Riggs (27:57)
Mm-hmm. Mm-hmm. Yeah, it's

a it's and I think that's maybe what it w makes this this moment in time the same as well as different and that we're it we're not automating physical labor, it's portions of cognitive labor. And that and that's a yeah, and so you would say it's cognitive burden.

Vipul Vyas (28:12)
Yeah, yeah. And it's not even the it's not even the most useful cognitive labor. Like even if I was doing that.

Billy Riggs (28:19)
So when the example that you had here, and it's like, why did you need to spend brain space on operating the microfish when it actually wasn't the intellectual labor that you were trying to do? You were trying to do research and yet finding that article that you were looking for in the microfish.

was incredible and and if folks haven't played around with micro I remember looking through newspaper newspaper articles as a researcher in grad school and going through this and scanning up and down and it's it microfish was not easy to operate. and so

Vipul Vyas (28:44)
yeah.

had to zoom in and out and you had to like scroll

around and sh yeah. It was like you had to like have like joystick this dexterity to even be successful with it.

Billy Riggs (29:01)
Now is it a hockey stick, is it a straight line? Probably more a hockey stick, but for me I've been thinking a lot about all these books we read.

teaching entrepreneurship, teaching management about the lean organization and also Clayton Christensen's innovative dilemma and thinking about no matter if you're a government organization or your private organization, your big or small company.

How did I think it changes perhaps the way that you manage your organization? And I I'd be curious about that because I think it requires you to be even more agile. And I'd be curious your thoughts about what it means for this idea of the innovators dilemma, for example, relating to failing fast.

And it's interesting because we are at a moment where you've never been able to fail faster. And you've never been able to faster go towards finding, product market fit. And very interesting, right? I mean, I think for your organization, you can become more of an organization of experimentation to where you're better able to match products with customer needs

Vipul Vyas (29:53)
That's all true.

Billy Riggs (30:07)
today even better than a year ago. What do you think?

Vipul Vyas (30:10)
I think that's true. I think that's right. I think that it's really cheap to stand something up and see if there's any takers. It's really cheap to come up with a marketing strategy. It's cheap to promote something. It's cheap to iterate on it. And so that's all true. wow.

Billy Riggs (30:26)
Yeah.

Well, what

would you advise then organizations? Because you know, I hear lots of narratives. And I was in Switzerland two weeks ago and there was there's some chatter about some of these automation projects to make them much bigger and to scale them larger. And I've been thinking about this the other way around is that if they're experiments, maybe they need to be smaller.

So that they actually can yeah, so they can be more agile.

Vipul Vyas (30:51)
You're right, in my opinion. In my opinion.

Yeah, I mean, I would actually go the other direction and say there's the whole, continuous improvement mantra of the Japanese of, doing the same thing a little bit better every time. And that's really where this can play a role is like empower employees to automate their own tasks to make their own lives easier by using these tools.

come up with their own solutions. And I think you'll get them to because they know their job function better than anyone else's, and they know what things that they hate doing and what things are of little value that are annoying. And so that's what you'll see is that they will start to automate away the unimportant stuff by and large. So the salesperson will automate away the

process of keeping the CRM system up to date. The account management person will automate away the research need to get ready for a quarterly business review. and so that'll just diffusely happen across, and you're gonna get much more productive because look, big projects just mean big risk, mean big risk of failure, which means big cost.

Billy Riggs (32:01)
Mm-hmm.

Vipul Vyas (32:02)
I think that's that's probably a very European way of thinking and just

Billy Riggs (32:07)
I think this is where

one of the things that we need to be training managers to do is to allow their subordinates to take risks and allow them time to experiment and hopefully with increased increased productivity gains. But then I think it's also goes with some of these basic tenets of the innovators' dilemma.

When you have experimentation, you push it down to the grassroots. And when you do that, it percolates up. The successful tools percolate up and can be si and can reveal themselves and be systematized. Exactly.

Vipul Vyas (32:37)
Mm-hmm. Yeah, they all reveal themselves.

Yeah,

I think that's right. They become the things that need to be more broadly adopted. And then those are the things that you double down on. And you essentially create a a fail fast factory internally that reveals what it is that you need to, you know, abandon and what you need to double down on. I think this is this this is right. Like if I'm i the other thing is just that by doing that you get people

culturally acclimated to this stuff so it's not scary. They're less resistant because if they feel like it's going to help them directly, and they're allowed to let it help them directly, their adoption in general is going to be higher versus if it's coming upon high. So say, look, you have these tools, you have access to them, use You know, the the biggest thing you can do is probably say, Look, you gotta do something. You gotta do any something. You have to anything, but you can't do nothing.

I know I don't care if it basically helps you just do status reports or whatever. You know, I'm just making something up, but you can't not do anything. And but that's the starting point. Like if you just it's almost like defeats the purpose of tackling some kind of big project, at least initially. Because the whole point is this isn't stuff that can be pushed to the edge. That's the whole value, is you can push this to the edge and let the edge tell you what is relevant, what's not, versus

Billy Riggs (33:35)
Mm-hmm, mm-hmm.

Vipul Vyas (34:05)
The opposite where you're kind of saying, you know, you're re centralizing 'cause and you're doing that 'cause that's what you know. That's what's worked. And that's what you historically needed is to have scale by having things in the middle to say, the only way I can get projects done is by having lots of people coordinate something because that's what you need to pull something off. So it's the same old mindset reasserting itself. Like, I gotta do something centralized because that's the only way things get done, and that's because you need so many resources when it

Billy Riggs (34:13)
Mm-hmm.

Vipul Vyas (34:33)
completely misses the point around. No, you actually don't.

Billy Riggs (34:36)
Well, so

maybe just to wrap up, we know, I think we we've talked about a lot of the advantages but what are some risks that we need to be aware of going forward?

Vipul Vyas (34:44)
⁓

Short to intermediate term dislocation. because it takes time for the world to adjust and there's a human cost to that adjustment. And that's can be less than trivial so society's job in general is to manage that dislocation and transition. And be flexible enough to respond as things evolve because you're not gonna be able to predict it

fully.

Billy Riggs (35:07)
Yeah. And I think it also doesn't

Vipul Vyas (35:09)
Same thing with same thing with the organizations.

all the all the way all the way up.

Billy Riggs (35:14)
And I think I acknowledging that we are in a technological revolution. That these tools are among us, but if managers allow their subordinates to experiment, it will yield dividends. And I think that's where we are. We're at a moment in time where

we have to adapt, but we can see new levels of productivity if we don't contract our organizations, but we allow our organizations to use the tools and embed them and systematize them to revolutionize the future of work.

Vipul Vyas (35:47)
Agreed.

Billy Riggs (35:48)
So yeah, well this has been a great conversation, Vival. I hope everybody has enjoyed this episode. these agents are among us. The race is already underway. Thanks for joining us on Rewiring the American Edge.