speaker-0: Welcome to Author Hour. Today we are here with authors Rold Van Wick and Joan Smith, who alongside author Jared Zogby wrote Competing at Machine Speed: How the Agentic Era Enables Commerce to Become the Central Nervous System of the Modern Enterprise, which is out October 27th. Rold and Joan, welcome to Author Hour.
speaker-1: Thank you. Thanks, Lex.
speaker-0: So let's dive right in and actually start with the title. What does it actually mean for a company to compete at machine speed? And why can't most big consumer brands do it well today?
speaker-1: I'll I can start. I think the title just it comes from and the simplest answer is I think the market now moves faster than most companies can compete in. That's the simplest answer. And we started seeing this already, I would say, years ago as we got into this business. And I think it's just been accelerated with the new advent of all the new technology, especially AI technology coming in. mentioning is big brands have been around a long time and they aren't built for agility with that with the current technology infrastructure and and coming in as AI comes in, they're just not built for the pace that the world is moving today in that way. They're large. Think of them like a cruise ship, right? They've got lots of products and lots of people and lots of structure to make all that work. And so agility is sort of at the other end of that. Mm.
speaker-0: So the book opens with a small, almost funny example. So there's a food brand whose products kept showing up next to pet food in search results because the listing never said that the food was for humans. One word fixed that. How is that story the essence of the whole book?
speaker-1: I okay, I think that th what's interesting is you have to take a couple of steps back and realize a lot of these companies to advertise anything, say online or in e-commerce was a new thing at one stage. And I think they haven't really adapted to, I would argue, to what it takes to to win in that space. So from the outside it looks very simple that there was a miss, you know, a simple word missing in a description or they haven't updated a particular page. But historically companies have looked at digital commerce as putting their catalogue online. And the focus has been on the TV and the print and the the retail partnerships and the kind of the traditional channels. So as as ridiculous as it sounds, it's actually quite common to to to discover that that really big brands are like in the wrong category or on the wrong kind of digital shelf. So I think for us it's a metaphor for where a company's focus is. And the moment a lot of companies are still focusing on the the traditional channels and winning in these traditional shelves where w we would argue that a lot of the consumers and you know an audience has moved on. So something as simple as not having being in the right category or missing a couple of keywords in your Amazon description sounds so obvious to us, but it it's it's a it's a legacy problem for not being For not taking that space seriously, more than anything else. And and and now you can't afford to make one mistake because besides your traditional competitors, you have a whole new generation of competitors that are just born on these platforms and will absolutely, you know, annihilate you if you make, you know, one wrong move. To bring what Roll's saying to life, take a couple of steps back and remember that the way we cure way as consumers got products and services where we walked in a store. And when you walked in the store, you would clearly know that the food on the aisle was in was human or pet because you were in the pet aisle or you were in the human aisle. And when we're in a digital world, those aisles don't exist. It doesn't it's not the same. And so not having something updated the way Rolde's mentioning, thinking of it as your catalog, you're still assuming that you're in the pet food aisle or the human food aisle. And and the digital world, it's all blurred.
speaker-0: So such a tiny little oversight, not prioritizing the right thing changes your entire digital catalog. So competing at machine speed argues that the way people shop has split in two. There's the invisible automatic buying on one side and the discovery as entertainment on the other. Walk us through that split and explain why it's such a problem for some of these big heritage brands.
speaker-1: I think it's even th that's two splits I think we touched on, but I think the the big divide is you know, we always talk about the difference between shopping and buying. And that also just came in, I would argue, overnight in in the case of people still brands still assume people are walking through the supermarket aisles, as Joan is mentioning, and kind of discovering brands or knowing where the the their regular brands are. But I think what we are seeing now is, you know, COVID kind of fast forwarded how we buy. products online, how products get delivered. the most powerful thing probably is the buy again. You have your existing set order on a lot of these retailers and you just click buy again. So you're not even looking at new products or trying a new product. So and then you now have a gen tech shopping. So you have agents, you know, looking for deals, price points, features who don't get moved by emotional content or beautiful language. They're looking for specifications for ingredients and things like that. So it is a massive change in how we are speaking to people, how we are trying to get them to buy our products, how we're trying to tell stories from a brand perspective. And also how we're trying to introduce something and even introduce discovery, which was such a simple thing before, because you would just display it, on on on the on the shelf. So the the big fundamental split is you might have two Audiences now. You have an audience, the human audience, and then you have an agentic audience that is looking for something completely different, but it's the same product. Yeah, and then the shopping part, the discovery part, that's become entertainment as well. If you look at influencers and all the social media channels, a lot of times that's where our generations are our younger generations are discovering things because we're not walking through stores as much anymore. And with the number of products online, it becomes A lot of choice, right? To scroll through lots and lots of products. So we turn to influencers or our friends or trusted channels to recommend things for us. And so that becomes a bit of entertainment. And that's how you're finding things on the shelving side. But then the buying side, some of those, as Rose mentions, I mean, I don't know how many listeners will have their, you know, their paper products on buy again. It just shows up at your house, but to that end. If the even your favorite brand that you buy, if they introduce a new version or with some upgraded features, you wouldn't know. You would just keep buying the same one unless they discontinued it, which is a whole other issue that can happen to the for the brands, in that you might have discontinued a skew and replaced it with another skew, but now it's in somebody's cart as by again as the old skew and the skew doesn't exist. Yeah. So you can actually lose customers that way as well.
speaker-0: Wow. So the book does have some interesting math. Thinking about on the brand side, a mid-sized company with 2,000 or so products across 10 retailers has to make over a million optimization decisions a year, about one every six or so minutes for a 50 person team, which is a crazy word problem. It feels like I'm in math class, but What are all of those decisions? And and what happens when a brand just can't quite keep up?
speaker-1: I I'm not gonna list all the dissent
speaker-0: Yeah, yeah.
speaker-1: but it's a lot. But I just but to take a step back, it is like just keeping your page refreshed, as they say in in in digital commerce, to refresh your page with you know, updated content, even seasonal, even picking up on trends or or or you know promotions or even that alone takes a lot of work. And even as much as a lot of these systems are are automated, I think what we touch on is Just doing the right job today is is a near impossible job. And now you have so much more information and so many more signals telling you what you could potentially change or adapt or you know what categories you need to be in or new categories that have started. So I think the the point we were trying to make in that, you know, that chapter is l or that section is literally that you will you do need s a new kind of operating model or a new way of thinking to just even manage what you have. Never mind Trying something new. The biggest challenge we would see in the past is sitting in these meetings with these brands, and in our previous lives as consultants is even if they knew that a piece of content needed to be updated, the time it takes to get that information across to the content team, you know, to the the Amazon team or the Walmart team, whatever, it still takes too long. It's just the way that these companies are designed, you know, the silos and the gaps and the nature of things. So Even if things are working really, really well and you have all the clear instructions, it is becoming an impossible task just to manage as it is. And and that's everything from keeping the product description updated, updating the content, refreshing the the the the the shelf, the partnerships, all of that. And the problem is when consumers are seeing old content, you know, especially when it comes to cultural cultural relative products and it's you it's winter and you're seeing people sitting outside or it's a it's a it's a product that is not known for a certain market or all those things count. And the really, really good companies are the ones that are constantly keeping this stuff updated, constantly measuring and constantly testing. So but again, this is all new. You know, this is stuff that kind of came in so fast into these companies that are built and structured to produce large amounts of traditional assets, TV ads, print, outdoor, even social. And traditionally they've treated digital channels as they put a bit of content out there. This is not necessarily the most premium content that they always have the budget for. And they kind of forget about it. And you come across these pages and in some cases these pages haven't been refreshed in six months or sometimes up to a year. And then, you know, you're dealing with, you know, all the challenger brands that come in and are refreshing the pages all the time. reading the market, updating the descriptions, seeing what works, A B testing. It becomes a basically this battleground where, these companies born on Amazon this morning are cutting into these really, really age old brands because they're just way more nimble and way more aggressive, you know, on these shelves or digital shelves. Yeah. So you can imagine from a perspective of the larger brands, they have a team that probably doesn't that doesn't have necessarily the breath to handle everything that Rold is is outlining. So what you find them doing is like anybody, you focus on the things that have the most pain. So you focus on your large or the most gain to that. mean to say it better more accurately. So you focus on your larger brands, right? The ones that make or break the portfolio, the ones where you know that, you know, are are moving the most product or are you most successful or most customers need and want them. And you kind of let the other ones Maybe take care of themselves or to World's point, you maybe touch every six months or or whatnot, 'cause that's about all you can manage to do with the size of the breath of the tea that you have.
speaker-0: A lot of companies would listen to this and think that the answer is add more AI. You call that the augmentation trap. Can you explain what you guys mean by that?
speaker-1: I think it's an infrastructure play, meaning companies are not designed to work together traditionally. And I don't mean that as a as a as a swipe or a a s what do you say swipe? I mean that in a way that they've built these incredibly disciplined teams that are doing incredible jobs and very skilled. And there's an assumption that AI is just going to make everything easier and faster. So the fact that before AI you would see a signal And on the market that you wanted to act on, and it took six months to get that signal to the right team, AI is not gonna make necessarily gonna fix that overnight. That is how the teams are built, the structured and everything. I think AI can make teams more connected, but AI is not gonna solve your problems. I think the the way I look at it is I think there's an an infrastructure change that needs to happen in how teams are designed, you know, how companies work together. And then bringing in, the power of AI and the power of a genetic thinking, that'll make it so much easier because you can go and look at a large amount of data very, very quickly and you can process insights much faster and you can look at hidden tension much quicker. But if a team is not structured or a company is not structured to work together and to ha to to to take in those signals and do something with it, I don't think AI is gonna you're gonna flick the switch and AI is gonna gonna gonna solve it. And I think what we are seeing is I think it might even fast forward a lot of your dysfunction if you just bring it in as a tool versus redesigning how you work together. Mm-hmm.
speaker-0: It's like speeding up a a broken process just gives you a faster broken process, right?
speaker-1: Yeah, it's done look, it's done wonders for for for content, especially from a brand perspective, because content is traditionally very expensive but it's where brand brands always want to save money. But from an operations perspective and how companies are designed, I think if it is well designed, it could could potentially be the the new glue of a company because the way that information can travel th through an organization. But it's adding you know, if you add more lanes to to a road, it they've it's been proven not to reduce traffic. But it just creates more cars versus building faster trains and investing in in better infrastructure. And I think it's a very similar situation. We are seeing that companies are just looking at AI's more lanes and just thinking it's going to reduce traffic, where it really needs a a rethink in how the company's actually structured and how the teams are connected. There's an example we use in the book. We call it the Yellow Pages moment. And it illustrates what World is saying really, really well. So back when digital first came online, Yellow Pages, if for all the listeners who may be younger, were big old books, right? And when digital first happened, the Yellow Pages started to digitize their book. So they took the book and were putting the book online. They weren't doing what they felt they needed to do. And Similar and right around the same time, Google was coming into play. Google didn't put a book online, Google changed how we search for things. And so the yellow pages never got to a better way of doing things. They kind of fell into this trap of they augmented, they made what they had better, but it didn't actually solve the problem. So slightly different, but it's it's essentially what Rolde is saying that these companies sometimes have broken processes or they have gaps in processes that are filled by humans that no one knows about. Or a really common thing is they have different incentives and and goals that they're trying to achieve between different teams, which makes it really hard for those teams to work together as one cohesive unit because they're trying to achieve different things. That works in a world where everything is siloed. Channels are siloed, but when you start to bring things together as our the pace of the world is happening now, that becomes harder and harder to
speaker-0: In the book, you lay out something you call an agentic commerce operating system, a system that senses, decides, and acts on its own inside limits that humans set. In plain terms, what does that actually look like running inside of a company?
speaker-1: I'll give my version and then Joan can give her can contradict my version. But no, I mean I mean she comes more of a transformation background. Mine's more my background's more creative. So the
speaker-0: Okay.
speaker-1: way I look at it and and and my take on it is it is about working s smarter together. And I think you there are things that took us six months that are not taking us seconds. To give you an example, like we can if we are seeing a a a signal in a in a in in a reviews or ratings reviews. For example, that everyone's talking about the community or the the users, the customers are all talking about comfort in a particular shoe, but all the advertising and the marketing is around grip. The speed in which we are discovering that messaging and the speed in which we can get that signal to the right content team, brand team, innovation team, AI makes that so much more faster and more effective. The operating system, I would argue, is how are you designed to all work together? Because traditionally those signals aren't flowing very well. There's gaps, there's silos, you know, there's politics. So the the the the idea of building a better operating system is essentially like it is an infrastructure play where how do we go from seeing something and putting it into practice as fast as possible that could not only affect making the content better and talk about, you know, grip instead of comfort more. vice versa, but actually make a better product, shoot a better commercial, launch a better promotion. But at the same time, the speed in which we can now build a genetic system that are constantly looking at the market all the time and measuring and filtering out the noise, finding the the the hidden tensions that could impact things, the speed in which that signal can travel, can be vetted, can be approved, you know, can can be put into the right hands. That all is gonna require a humans working together in a in a in a in a much better way, but powered by, you know, an intelligence system, kind of an intelligence layer, an AI powered system that can give you more faster and more effectively. But if you're not connected and the company's not aligned well with with with a aligned operating system, then all that kind of just becomes meaningless. Mm-hmm. Yeah, so and I agree with everything Roll just said. So But my background is transformation. So if I've often thought about it as, you know, we we we purchase tools to make tasks easier. But that tool sits there and waits until you have to do that task and then you engage the tool. A system is actually operating all the time, whether that be a technology system or a human and technology system, which is what we're talking about when we talk about the agentech system. If I'm going to give an analogy, if you start looking at today where airline travel has gone and the and the pace and the number of flights that come in and out of an airport in a day, you would you would actually probably be pretty worried if you felt that humans and a couple of spreadsheets were managing all of that. There are systems that help manage to make sure that there are collisions in air and everything's timed appropriately. So now bring that back to any company, combinations of technology with humans in the oversight or above it, paying attention and making sure that as with the with AI being out the layer of intelligence, they can make decisions, they can actually take action as those signals are connected. They can move it further and enable the humans to do more. The humans are then over it providing their judgment. And making sure that they are discerning right decisions, wrong decisions, or adding in all those things that the technology might not know, but they're able to handle a lot more if it's orchestrated as a whole operating system. It requires a big change. It's a, you know, we would use the business terms of operating model or organizational design, all of that comes into play, plus incentives, plus teams, plus the roles, what people do for a living also. has to change in order for all that to to come into play and to be seamless.
speaker-0: One of the things I did want to ask, and we are touching on this so perfectly when we're talking about human and system working together. And Joan, your analogy made that perfectly clear with the whole judgment piece. But just to just to hone in on it a little bit more, the obvious worry here is that if machines are making these calls, what's left for people to do? So what's the line between what you hand the system and what must never leave human hands?
speaker-1: think from a creative perspective, I'm more positive about the fact that we can use our best thinkers and best creatives and best ideas. If we can remove the people from having to, you know, do all the the processing work, you could you could argue, like the amount of research that's required, the amount of information that needs to be absorbed and what the market is the thousands and millions of signals that a that a marketplace is giving us on a daily basis. Traditionally not that long ago, that required, we used to call it machine learning, but extensive systems and a lot of people, a lot of analytics teams and and and that, you know, especially data analytics to find interesting insights and opportunities. If the the fact that AI can now take that, process that, and actually then give us better briefs, better insights. better instructions for people to do what they do best. And it's to be creative, to bring a sense of taste, a bit of, you know, I call it happy accidents, a bit of magic and and creativity. I think this idea that that, you know, the robots are gonna replace the the thinking and and the creative, sure, but we are we've seen the result of that. You know, we see what that stuff looks like and and and it's obviously gonna get better. But I think the companies that that that That reward their best people with the best, insights and the best briefs and the best strategy are going to see really, in my opinion, better work because you want your best people to do what they love doing. And I think traditionally, a lot of these big companies, you know, we've spent a lot of time working on on on a lot of information that is not always delivering the best results. So I I I I I'm I'm excited from a creative perspective because I think From what I've seen is I'm getting smarter directions, smarter insights, you know, and and and and smarter, you know, literally smarter briefs than I did before. Yeah, so Roland is touching on the soul of the brand, right? The soul of the brand remains with humans. The the AI can never have that soul. It can't innovate on that soul in the same way. If you now extrapolate that out a little broader across the organization. Over the last fifteen years or so as digital became, digital came onto the the playing field probably twenty years now, something happened in sort of the the skill profile of most most corporate employees or corporate workers, corporate executives. And you have a think of a T, the letter T. Mm-hmm. You have a broad sense of understanding your your craft. whichever area you're in, whether you're in finance or whether you're in marketing or whatnot, you understand your craft and you understand what your role, what the job is. But then that bottom of the T, that that became a a way of developing depth because as digital came into play, channels came into play and you needed to learn how to how to be deep in those channels, how to execute in those channels. So if you now give some of that to the AI system, those People who are spending their days operating, doing a lot of those doing, they become the orchestrators. So that broadness of the T still stays. And it becomes really important that they understand a lot about their product portfolio and all the factors that there's plenty of signals that can be put into the AI, but if we're real, there's factors that come up every day within a company that the AI wouldn't know. And there might be a reason you would not want. An action to be taken on a particular product because of a corporate goal or because of an earnings announcement or because of a weather anomaly that you're expecting next week. And the AI won't necessarily know all of those things. So the human's role really becomes that discernment and judgment layer of being able to look at something and say, do we really want to do that? Is that the right thing to be doing? And it becomes important that they know less about the depth of how to do that. Although they still need to understand how it happens to make sure that the technology isn't isn't missing something, isn't not seeing something. Hmm. I think what's interesting is we now have the first generation of graduates or kids coming out of the system that are going to be AI fluent. I think the first gut reaction that we saw with a lot of companies was obviously firing, retrenching, laying off a lot of people. And I We saw a lot of junior level skills being removed and it was kind of the technology that was you know was was great if you had an expertise because it was this like support system, it's a rewarded expertise and it was really difficult to enter the market. But I think the the the opposite is is is kind of about to happen as we see this new generation coming in where people that have gotten used to being able to do a lot more than they are capable of and have only known to do it that way. the knowing that they have a a claw design or a you know chat GPT or an agent that they've built that can actually process in an a lot of information or go through a lot of you know signals and data, but still focus on what you know what what they love doing and what what you know makes humans what who they are, like innovation, the creativity, the skill and So I think there's a we w I feel like every f every week we tend to try to do an assessment of what AI's done this week to our to our industry, you know, to technology. And it's like it's it's and it's it's it's true and it's it's needed and obviously it's warranted, but at the same time there's also a s a a cycle I think that's about to happen where the the ease in which we've now gotten used to kind of having this this engine next to us. And working with it. And like Joan said, it's the I think s systematic thinking and understanding that systems have always been around, but I think what AI has done is really brought it in into the foreground. Like this living, breathing entity that is focused on constantly looking, improving, you know, if it's guided in the right way, if it's structured in the right way. So I think the old way was kind of thinking this thing comes in, it's gonna fast forward replace. But pretty soon I think it that's pretty much how a company will be structured. it'll have this kind of brain, this entity, this, this this this system that it's not gonna be that weird or that scary if you've already been using versions of it as you're coming coming into it. And I think if the focus is to make the work better, make the product better, to innovate, to make the messaging, the storytelling better, it becomes a reward rather than a a like a f a fear factor i in a way.
speaker-0: Right. And it does go back to that guidance, whether it's that creative guidance like you were talking about, administrative guidance, it's still you you're saying orchestrating, like you are orchestrating the system. You're still in charge of the nuance and the judgment. And so that makes it really interesting to see how the two human and system can come together.
speaker-1: Yeah, and I think you're gonna see more of that title that Joan mentioned. You're gonna see more people being referred to as orchestrators, as kind of as as conductors and being comfortable in in in being multiversed in in in in you know different skills and not being so siloed because I think the the price big brands are paying or big companies are paying is becoming too good at singular thinking. Now we're not seeing the results of it where The modern infrastructure is a lot more fluid, a lot more flexible and a kind of a lot more easier to adapt, you know, and what's happening.
speaker-0: Yeah. Very reactive. Yeah. So thinking about the book as a whole, who did you most want to reach with this book and what do you want them to do differently on Monday morning?
speaker-1: So our, our core audience, obviously the the book is written very specifically in the product space. So consumer goods and products companies. And we are ti it was written for larger companies. So our core and and specific audience is any executive in that from the finance through the brand, through the marketing, the senior executives who are making those day-to-day decisions about how to apply AI, where to put things. And how they are competing and winning in the marketplace in terms of their own goals as a company. Board members, same thing. But I also feel it's the book is really applicable to any anyone in in the corporate world who's trying to trying to build their own roles, build their teams and trying to figure out how the heck do we get more of our product to market to the customers who really want to. Purchase it. How do we find them? And how do we keep that product in their hands at the pace that those customers want it? And this is a really the book is built on principles. We didn't build it on employ these capabilities and do X tomorrow because the world of AI is still new. It's still emerging and it's changing really fast. So we built it on these principles that still require people to, they're going to have to consider through. How would I apply that? What does that mean within my company? How would I create this kind of system? Even though we've given you a roadmap for it or blueprint for it, we haven't given you a step-by-step employee technology X today. So it actually applies to, in my opinion, to any executive as well as anyone coming out of school right now. If you're coming out of school and you're going to go into the corporate world, this is a really good book to really challenge your thinking about how do you how would you design the What's the operating system in the future? Mm.
speaker-0: It's good thought exercise.
speaker-1: Yeah, I for me it's just been the years of s sitting in meetings with with clients, initially with brands with with my advertising background, then I kind of became an accidental consultant. That's you know where I met Jared and Joan and and and seeing how companies have we I mean we use commerce I think as a you know as a kind of the the maybe as the the the the the th the main theme, but essentially it is a it's a business transformation that's needed in how companies, operate. But what was so interesting about commerce is that it came in into the world in a way that clients and we saw businesses going, why should we care about this? we we know how to do things. We've been doing things like this forever. It works. What are you talking about? why pay attention to Amazon? and then it became COVID had a big impact. It was a jump start into taking a world very seriously that was ignored. I came in from the from the brand perspective, just trying to tell tell clients you need to take this space seriously. It's a canvas where there are there's a buy button. This is very unique. We've never had a canvas with a buy button. we've done storytelling over here and we did that over there. And then it became like, well, who's doing it? And we quickly need to do it, and then it's gonna fade away. As COVID goes away and then it became, and then it became like help us. And then AI just fast tracked it in that sense. So it is something we've seen happen over the years and it's taken on different forms. And I think for me the book is just it it's a it's a great framework to look at your business and to kind of assess your business and using examples of what we've seen and and examples of how companies have have approach the space and also just the incredible opportunity if you do it right. Because every single thing that's written now is a threat to to to companies. I think if you turn it around, they all become opportunities. We've never ever had this much information that we are are able to look at when it comes to people telling us what they like, what they're buying, what they think about, what they care about, on just on a one single product page. The amount of energy a single product page generates around one face cream is just incredible. And it just to treat it as a you know as an online catalog is is is is ludicrous. And then never mind two thousand, twenty thousand, thirty thousand. And you know, and making it work on Amazon is different to making it work on Walmart and just making it work on you know Target or Team, or you name it. So you have this insane world that has just appeared and it's giving brands and and companies, so many signals. And if you are structurally ready and prepared to to to see it and and and and react to it, it's it's giving you incredible information and opportunity to to to play in the market. So yeah, I s I s I think to Joan's point, I think anyone in business that's selling something would find it useful. But it is, I think the it it came from like a a corporate executive, you know position that's dealing and fighting these battles on on a on a on a on a daily basis and giving someone a a structure to look at their own company and look at a a way to, take on these challenges of of of what's coming and what's happening.
speaker-0: One thing both of you just touched on and we've discussed throughout this entire episode is how fast moving this world really is. So I wanna know what was the hardest part of turning something so fast moving, so new every single week into a book?
speaker-1: Don't look at the news as you as you as you I think Claude went through five updates.
speaker-0: Yeah. Yeah. Keep your head down. Yeah.
speaker-1: As as we were. But I mean I it it's look it's a we use it the the term agentic and obviously we we we we we we we use it as a way we which you can structure, but at the end of the day it's a business. It's a business transformation book. It's it's how companies are structured and work together and look at commerce as this as the nucleus. So in that sense it was you know, we we had written versions of this over the years. in in in different I would say in different thought leadership pieces and presentations. So the the core of how we look at companies and businesses haven't changed. I think weaving in the immense impact that is happening now was obviously you know there was a a a need to to get it out because it is happening so quickly.
speaker-0: Yeah. it's those principles that Joan was talking about where the principles do remain the same. It's just different technological applications, right?
speaker-1: Also don't underestimate how slow companies are to change. So as much as we were racing, you know, against this this technology updating itself every day, it is still surprising how structured and set in the ways of s some of the biggest companies in the world are. Mm-hmm. And they they they do pay a price for it because the new upstarts that are coming in are coming in so aggressive. So there is an element of understanding how upset the the the the industry still is and that how it that does require a new thinking. A new approach. Yeah, we were privileged to have been watching this pattern start to emerge for years as we worked through it. So that able that enabled us to make a shift, I think even as we were writing world, we we started to go down a path of making the blueprint into a guidebook and putting here's what you should do. And as we were doing that, Claude was updating the AI models everywhere. We're updating so darn quick and we realized that's there's lots of other books that'll give you the ham to on on on that, that that's not going to serve because it's going to be changed before we would even publish. So we we pulled it back and looked at the patterns that we'd seen for years. And went to this idea of the principles and this is a blueprint, an architectural blueprint that we're hopeful that executives are gonna look and apply to their company. We would be so thrilled if on Monday morning somebody read the book and looked at it and said, I wanna now see how does my company do against this? How does my team do against that part of the book? And actually apply the blueprint out and use it as a guide to figure out how they should be changing or what's the right formula for them.
speaker-0: One thing I really find interesting about competing at machine speed is the book has three authors, but it speaks in a single voice. What did it take for the three of you to reach that endpoint?
speaker-1: we all come from such different backgrounds. And I will credit Accenture for that for the way they bring interesting people, clearly very interesting people, together. And that's and I think the idea that we worked in teams, but we came from such different backgrounds. And I think from my side, being creative, you know, Jared has an incredible background in systems and technology and Joan transformation and but I think the single voice came from like we've always worked with single visions in in teams, and when you come in to to help a company transform or or evolve, there has to be a single focus. And that was the I I I would say the approach in that sense is how do we bring our different skill sets and things into this space and seeing it from different angles. And and yeah, and I think we have had so many conversations in the past that we I would say agreed on where we see things going. Hm.
speaker-0: That shared finish line, yeah.
speaker-1: Not always. We spent a lot of time. A lot mostly, yeah. Yeah, we spent a lot we spent a lot of time on the outline and really aligning that we were all we all aligned to the architecture of how we were gonna write the book. And that that consensus is Raul was saying, because we were all used to a single vision on a team, it was easy for us to get into that mode with each other. That is not to say we didn't have some really good conversations along the way as we Maybe, one when we we didn't agree on a unified vision and and then we just navigated to find it and then then the writing just flowed from there and it was easy it was easier to turn it into a single voice.
speaker-0: So where can people find the book and how can they keep up with you?
speaker-1: I think the book is out on the twenty seventh of October. I think it's on Amazon already for pre-order. So it'll be available on Amazon and I think all all other books, major booksellers. And then we have a a URL competing at machinespeed.com that'll have all the links. We also have a machine version that we've uploaded so you can feed that to your robot. It'll make it much sm make it much smarter. And then myself and Jared is we've actually founded a company called ACOS Labs. So if you go to acoslabs.ai, the the book's link is on there and all there's also some more information about the process and the the thinking that we've been talking about. Yep. And then I'm same you can find me on LinkedIn or via my own my own website, jopsmith.com.
speaker-0: Perfect. Thank you, Rold and Joan. We cannot wait for people to get their hands on competing at machine speed. Thank you both for coming on Author Hour.
speaker-1: Thank you. Thanks, Lex.
speaker-0: So let's dive right in and actually start with the title. What does it actually mean for a company to compete at machine speed? And why can't most big consumer brands do it well today?
speaker-1: I'll I can start. I think the title just it comes from and the simplest answer is I think the market now moves faster than most companies can compete in. That's the simplest answer. And we started seeing this already, I would say, years ago as we got into this business. And I think it's just been accelerated with the new advent of all the new technology, especially AI technology coming in. mentioning is big brands have been around a long time and they aren't built for agility with that with the current technology infrastructure and and coming in as AI comes in, they're just not built for the pace that the world is moving today in that way. They're large. Think of them like a cruise ship, right? They've got lots of products and lots of people and lots of structure to make all that work. And so agility is sort of at the other end of that. Mm.
speaker-0: So the book opens with a small, almost funny example. So there's a food brand whose products kept showing up next to pet food in search results because the listing never said that the food was for humans. One word fixed that. How is that story the essence of the whole book?
speaker-1: I okay, I think that th what's interesting is you have to take a couple of steps back and realize a lot of these companies to advertise anything, say online or in e-commerce was a new thing at one stage. And I think they haven't really adapted to, I would argue, to what it takes to to win in that space. So from the outside it looks very simple that there was a miss, you know, a simple word missing in a description or they haven't updated a particular page. But historically companies have looked at digital commerce as putting their catalogue online. And the focus has been on the TV and the print and the the retail partnerships and the kind of the traditional channels. So as as ridiculous as it sounds, it's actually quite common to to to discover that that really big brands are like in the wrong category or on the wrong kind of digital shelf. So I think for us it's a metaphor for where a company's focus is. And the moment a lot of companies are still focusing on the the traditional channels and winning in these traditional shelves where w we would argue that a lot of the consumers and you know an audience has moved on. So something as simple as not having being in the right category or missing a couple of keywords in your Amazon description sounds so obvious to us, but it it's it's a it's a legacy problem for not being For not taking that space seriously, more than anything else. And and and now you can't afford to make one mistake because besides your traditional competitors, you have a whole new generation of competitors that are just born on these platforms and will absolutely, you know, annihilate you if you make, you know, one wrong move. To bring what Roll's saying to life, take a couple of steps back and remember that the way we cure way as consumers got products and services where we walked in a store. And when you walked in the store, you would clearly know that the food on the aisle was in was human or pet because you were in the pet aisle or you were in the human aisle. And when we're in a digital world, those aisles don't exist. It doesn't it's not the same. And so not having something updated the way Rolde's mentioning, thinking of it as your catalog, you're still assuming that you're in the pet food aisle or the human food aisle. And and the digital world, it's all blurred.
speaker-0: So such a tiny little oversight, not prioritizing the right thing changes your entire digital catalog. So competing at machine speed argues that the way people shop has split in two. There's the invisible automatic buying on one side and the discovery as entertainment on the other. Walk us through that split and explain why it's such a problem for some of these big heritage brands.
speaker-1: I think it's even th that's two splits I think we touched on, but I think the the big divide is you know, we always talk about the difference between shopping and buying. And that also just came in, I would argue, overnight in in the case of people still brands still assume people are walking through the supermarket aisles, as Joan is mentioning, and kind of discovering brands or knowing where the the their regular brands are. But I think what we are seeing now is, you know, COVID kind of fast forwarded how we buy. products online, how products get delivered. the most powerful thing probably is the buy again. You have your existing set order on a lot of these retailers and you just click buy again. So you're not even looking at new products or trying a new product. So and then you now have a gen tech shopping. So you have agents, you know, looking for deals, price points, features who don't get moved by emotional content or beautiful language. They're looking for specifications for ingredients and things like that. So it is a massive change in how we are speaking to people, how we are trying to get them to buy our products, how we're trying to tell stories from a brand perspective. And also how we're trying to introduce something and even introduce discovery, which was such a simple thing before, because you would just display it, on on on the on the shelf. So the the big fundamental split is you might have two Audiences now. You have an audience, the human audience, and then you have an agentic audience that is looking for something completely different, but it's the same product. Yeah, and then the shopping part, the discovery part, that's become entertainment as well. If you look at influencers and all the social media channels, a lot of times that's where our generations are our younger generations are discovering things because we're not walking through stores as much anymore. And with the number of products online, it becomes A lot of choice, right? To scroll through lots and lots of products. So we turn to influencers or our friends or trusted channels to recommend things for us. And so that becomes a bit of entertainment. And that's how you're finding things on the shelving side. But then the buying side, some of those, as Rose mentions, I mean, I don't know how many listeners will have their, you know, their paper products on buy again. It just shows up at your house, but to that end. If the even your favorite brand that you buy, if they introduce a new version or with some upgraded features, you wouldn't know. You would just keep buying the same one unless they discontinued it, which is a whole other issue that can happen to the for the brands, in that you might have discontinued a skew and replaced it with another skew, but now it's in somebody's cart as by again as the old skew and the skew doesn't exist. Yeah. So you can actually lose customers that way as well.
speaker-0: Wow. So the book does have some interesting math. Thinking about on the brand side, a mid-sized company with 2,000 or so products across 10 retailers has to make over a million optimization decisions a year, about one every six or so minutes for a 50 person team, which is a crazy word problem. It feels like I'm in math class, but What are all of those decisions? And and what happens when a brand just can't quite keep up?
speaker-1: I I'm not gonna list all the dissent
speaker-0: Yeah, yeah.
speaker-1: but it's a lot. But I just but to take a step back, it is like just keeping your page refreshed, as they say in in in digital commerce, to refresh your page with you know, updated content, even seasonal, even picking up on trends or or or you know promotions or even that alone takes a lot of work. And even as much as a lot of these systems are are automated, I think what we touch on is Just doing the right job today is is a near impossible job. And now you have so much more information and so many more signals telling you what you could potentially change or adapt or you know what categories you need to be in or new categories that have started. So I think the the point we were trying to make in that, you know, that chapter is l or that section is literally that you will you do need s a new kind of operating model or a new way of thinking to just even manage what you have. Never mind Trying something new. The biggest challenge we would see in the past is sitting in these meetings with these brands, and in our previous lives as consultants is even if they knew that a piece of content needed to be updated, the time it takes to get that information across to the content team, you know, to the the Amazon team or the Walmart team, whatever, it still takes too long. It's just the way that these companies are designed, you know, the silos and the gaps and the nature of things. So Even if things are working really, really well and you have all the clear instructions, it is becoming an impossible task just to manage as it is. And and that's everything from keeping the product description updated, updating the content, refreshing the the the the the shelf, the partnerships, all of that. And the problem is when consumers are seeing old content, you know, especially when it comes to cultural cultural relative products and it's you it's winter and you're seeing people sitting outside or it's a it's a it's a product that is not known for a certain market or all those things count. And the really, really good companies are the ones that are constantly keeping this stuff updated, constantly measuring and constantly testing. So but again, this is all new. You know, this is stuff that kind of came in so fast into these companies that are built and structured to produce large amounts of traditional assets, TV ads, print, outdoor, even social. And traditionally they've treated digital channels as they put a bit of content out there. This is not necessarily the most premium content that they always have the budget for. And they kind of forget about it. And you come across these pages and in some cases these pages haven't been refreshed in six months or sometimes up to a year. And then, you know, you're dealing with, you know, all the challenger brands that come in and are refreshing the pages all the time. reading the market, updating the descriptions, seeing what works, A B testing. It becomes a basically this battleground where, these companies born on Amazon this morning are cutting into these really, really age old brands because they're just way more nimble and way more aggressive, you know, on these shelves or digital shelves. Yeah. So you can imagine from a perspective of the larger brands, they have a team that probably doesn't that doesn't have necessarily the breath to handle everything that Rold is is outlining. So what you find them doing is like anybody, you focus on the things that have the most pain. So you focus on your large or the most gain to that. mean to say it better more accurately. So you focus on your larger brands, right? The ones that make or break the portfolio, the ones where you know that, you know, are are moving the most product or are you most successful or most customers need and want them. And you kind of let the other ones Maybe take care of themselves or to World's point, you maybe touch every six months or or whatnot, 'cause that's about all you can manage to do with the size of the breath of the tea that you have.
speaker-0: A lot of companies would listen to this and think that the answer is add more AI. You call that the augmentation trap. Can you explain what you guys mean by that?
speaker-1: I think it's an infrastructure play, meaning companies are not designed to work together traditionally. And I don't mean that as a as a as a swipe or a a s what do you say swipe? I mean that in a way that they've built these incredibly disciplined teams that are doing incredible jobs and very skilled. And there's an assumption that AI is just going to make everything easier and faster. So the fact that before AI you would see a signal And on the market that you wanted to act on, and it took six months to get that signal to the right team, AI is not gonna make necessarily gonna fix that overnight. That is how the teams are built, the structured and everything. I think AI can make teams more connected, but AI is not gonna solve your problems. I think the the way I look at it is I think there's an an infrastructure change that needs to happen in how teams are designed, you know, how companies work together. And then bringing in, the power of AI and the power of a genetic thinking, that'll make it so much easier because you can go and look at a large amount of data very, very quickly and you can process insights much faster and you can look at hidden tension much quicker. But if a team is not structured or a company is not structured to work together and to ha to to to take in those signals and do something with it, I don't think AI is gonna you're gonna flick the switch and AI is gonna gonna gonna solve it. And I think what we are seeing is I think it might even fast forward a lot of your dysfunction if you just bring it in as a tool versus redesigning how you work together. Mm-hmm.
speaker-0: It's like speeding up a a broken process just gives you a faster broken process, right?
speaker-1: Yeah, it's done look, it's done wonders for for for content, especially from a brand perspective, because content is traditionally very expensive but it's where brand brands always want to save money. But from an operations perspective and how companies are designed, I think if it is well designed, it could could potentially be the the new glue of a company because the way that information can travel th through an organization. But it's adding you know, if you add more lanes to to a road, it they've it's been proven not to reduce traffic. But it just creates more cars versus building faster trains and investing in in better infrastructure. And I think it's a very similar situation. We are seeing that companies are just looking at AI's more lanes and just thinking it's going to reduce traffic, where it really needs a a rethink in how the company's actually structured and how the teams are connected. There's an example we use in the book. We call it the Yellow Pages moment. And it illustrates what World is saying really, really well. So back when digital first came online, Yellow Pages, if for all the listeners who may be younger, were big old books, right? And when digital first happened, the Yellow Pages started to digitize their book. So they took the book and were putting the book online. They weren't doing what they felt they needed to do. And Similar and right around the same time, Google was coming into play. Google didn't put a book online, Google changed how we search for things. And so the yellow pages never got to a better way of doing things. They kind of fell into this trap of they augmented, they made what they had better, but it didn't actually solve the problem. So slightly different, but it's it's essentially what Rolde is saying that these companies sometimes have broken processes or they have gaps in processes that are filled by humans that no one knows about. Or a really common thing is they have different incentives and and goals that they're trying to achieve between different teams, which makes it really hard for those teams to work together as one cohesive unit because they're trying to achieve different things. That works in a world where everything is siloed. Channels are siloed, but when you start to bring things together as our the pace of the world is happening now, that becomes harder and harder to
speaker-0: In the book, you lay out something you call an agentic commerce operating system, a system that senses, decides, and acts on its own inside limits that humans set. In plain terms, what does that actually look like running inside of a company?
speaker-1: I'll give my version and then Joan can give her can contradict my version. But no, I mean I mean she comes more of a transformation background. Mine's more my background's more creative. So the
speaker-0: Okay.
speaker-1: way I look at it and and and my take on it is it is about working s smarter together. And I think you there are things that took us six months that are not taking us seconds. To give you an example, like we can if we are seeing a a a signal in a in a in in a reviews or ratings reviews. For example, that everyone's talking about the community or the the users, the customers are all talking about comfort in a particular shoe, but all the advertising and the marketing is around grip. The speed in which we are discovering that messaging and the speed in which we can get that signal to the right content team, brand team, innovation team, AI makes that so much more faster and more effective. The operating system, I would argue, is how are you designed to all work together? Because traditionally those signals aren't flowing very well. There's gaps, there's silos, you know, there's politics. So the the the the idea of building a better operating system is essentially like it is an infrastructure play where how do we go from seeing something and putting it into practice as fast as possible that could not only affect making the content better and talk about, you know, grip instead of comfort more. vice versa, but actually make a better product, shoot a better commercial, launch a better promotion. But at the same time, the speed in which we can now build a genetic system that are constantly looking at the market all the time and measuring and filtering out the noise, finding the the the hidden tensions that could impact things, the speed in which that signal can travel, can be vetted, can be approved, you know, can can be put into the right hands. That all is gonna require a humans working together in a in a in a in a much better way, but powered by, you know, an intelligence system, kind of an intelligence layer, an AI powered system that can give you more faster and more effectively. But if you're not connected and the company's not aligned well with with with a aligned operating system, then all that kind of just becomes meaningless. Mm-hmm. Yeah, so and I agree with everything Roll just said. So But my background is transformation. So if I've often thought about it as, you know, we we we purchase tools to make tasks easier. But that tool sits there and waits until you have to do that task and then you engage the tool. A system is actually operating all the time, whether that be a technology system or a human and technology system, which is what we're talking about when we talk about the agentech system. If I'm going to give an analogy, if you start looking at today where airline travel has gone and the and the pace and the number of flights that come in and out of an airport in a day, you would you would actually probably be pretty worried if you felt that humans and a couple of spreadsheets were managing all of that. There are systems that help manage to make sure that there are collisions in air and everything's timed appropriately. So now bring that back to any company, combinations of technology with humans in the oversight or above it, paying attention and making sure that as with the with AI being out the layer of intelligence, they can make decisions, they can actually take action as those signals are connected. They can move it further and enable the humans to do more. The humans are then over it providing their judgment. And making sure that they are discerning right decisions, wrong decisions, or adding in all those things that the technology might not know, but they're able to handle a lot more if it's orchestrated as a whole operating system. It requires a big change. It's a, you know, we would use the business terms of operating model or organizational design, all of that comes into play, plus incentives, plus teams, plus the roles, what people do for a living also. has to change in order for all that to to come into play and to be seamless.
speaker-0: One of the things I did want to ask, and we are touching on this so perfectly when we're talking about human and system working together. And Joan, your analogy made that perfectly clear with the whole judgment piece. But just to just to hone in on it a little bit more, the obvious worry here is that if machines are making these calls, what's left for people to do? So what's the line between what you hand the system and what must never leave human hands?
speaker-1: think from a creative perspective, I'm more positive about the fact that we can use our best thinkers and best creatives and best ideas. If we can remove the people from having to, you know, do all the the processing work, you could you could argue, like the amount of research that's required, the amount of information that needs to be absorbed and what the market is the thousands and millions of signals that a that a marketplace is giving us on a daily basis. Traditionally not that long ago, that required, we used to call it machine learning, but extensive systems and a lot of people, a lot of analytics teams and and and that, you know, especially data analytics to find interesting insights and opportunities. If the the fact that AI can now take that, process that, and actually then give us better briefs, better insights. better instructions for people to do what they do best. And it's to be creative, to bring a sense of taste, a bit of, you know, I call it happy accidents, a bit of magic and and creativity. I think this idea that that, you know, the robots are gonna replace the the thinking and and the creative, sure, but we are we've seen the result of that. You know, we see what that stuff looks like and and and it's obviously gonna get better. But I think the companies that that that That reward their best people with the best, insights and the best briefs and the best strategy are going to see really, in my opinion, better work because you want your best people to do what they love doing. And I think traditionally, a lot of these big companies, you know, we've spent a lot of time working on on on a lot of information that is not always delivering the best results. So I I I I I'm I'm excited from a creative perspective because I think From what I've seen is I'm getting smarter directions, smarter insights, you know, and and and and smarter, you know, literally smarter briefs than I did before. Yeah, so Roland is touching on the soul of the brand, right? The soul of the brand remains with humans. The the AI can never have that soul. It can't innovate on that soul in the same way. If you now extrapolate that out a little broader across the organization. Over the last fifteen years or so as digital became, digital came onto the the playing field probably twenty years now, something happened in sort of the the skill profile of most most corporate employees or corporate workers, corporate executives. And you have a think of a T, the letter T. Mm-hmm. You have a broad sense of understanding your your craft. whichever area you're in, whether you're in finance or whether you're in marketing or whatnot, you understand your craft and you understand what your role, what the job is. But then that bottom of the T, that that became a a way of developing depth because as digital came into play, channels came into play and you needed to learn how to how to be deep in those channels, how to execute in those channels. So if you now give some of that to the AI system, those People who are spending their days operating, doing a lot of those doing, they become the orchestrators. So that broadness of the T still stays. And it becomes really important that they understand a lot about their product portfolio and all the factors that there's plenty of signals that can be put into the AI, but if we're real, there's factors that come up every day within a company that the AI wouldn't know. And there might be a reason you would not want. An action to be taken on a particular product because of a corporate goal or because of an earnings announcement or because of a weather anomaly that you're expecting next week. And the AI won't necessarily know all of those things. So the human's role really becomes that discernment and judgment layer of being able to look at something and say, do we really want to do that? Is that the right thing to be doing? And it becomes important that they know less about the depth of how to do that. Although they still need to understand how it happens to make sure that the technology isn't isn't missing something, isn't not seeing something. Hmm. I think what's interesting is we now have the first generation of graduates or kids coming out of the system that are going to be AI fluent. I think the first gut reaction that we saw with a lot of companies was obviously firing, retrenching, laying off a lot of people. And I We saw a lot of junior level skills being removed and it was kind of the technology that was you know was was great if you had an expertise because it was this like support system, it's a rewarded expertise and it was really difficult to enter the market. But I think the the the opposite is is is kind of about to happen as we see this new generation coming in where people that have gotten used to being able to do a lot more than they are capable of and have only known to do it that way. the knowing that they have a a claw design or a you know chat GPT or an agent that they've built that can actually process in an a lot of information or go through a lot of you know signals and data, but still focus on what you know what what they love doing and what what you know makes humans what who they are, like innovation, the creativity, the skill and So I think there's a we w I feel like every f every week we tend to try to do an assessment of what AI's done this week to our to our industry, you know, to technology. And it's like it's it's and it's it's it's true and it's it's needed and obviously it's warranted, but at the same time there's also a s a a cycle I think that's about to happen where the the ease in which we've now gotten used to kind of having this this engine next to us. And working with it. And like Joan said, it's the I think s systematic thinking and understanding that systems have always been around, but I think what AI has done is really brought it in into the foreground. Like this living, breathing entity that is focused on constantly looking, improving, you know, if it's guided in the right way, if it's structured in the right way. So I think the old way was kind of thinking this thing comes in, it's gonna fast forward replace. But pretty soon I think it that's pretty much how a company will be structured. it'll have this kind of brain, this entity, this, this this this system that it's not gonna be that weird or that scary if you've already been using versions of it as you're coming coming into it. And I think if the focus is to make the work better, make the product better, to innovate, to make the messaging, the storytelling better, it becomes a reward rather than a a like a f a fear factor i in a way.
speaker-0: Right. And it does go back to that guidance, whether it's that creative guidance like you were talking about, administrative guidance, it's still you you're saying orchestrating, like you are orchestrating the system. You're still in charge of the nuance and the judgment. And so that makes it really interesting to see how the two human and system can come together.
speaker-1: Yeah, and I think you're gonna see more of that title that Joan mentioned. You're gonna see more people being referred to as orchestrators, as kind of as as conductors and being comfortable in in in being multiversed in in in in you know different skills and not being so siloed because I think the the price big brands are paying or big companies are paying is becoming too good at singular thinking. Now we're not seeing the results of it where The modern infrastructure is a lot more fluid, a lot more flexible and a kind of a lot more easier to adapt, you know, and what's happening.
speaker-0: Yeah. Very reactive. Yeah. So thinking about the book as a whole, who did you most want to reach with this book and what do you want them to do differently on Monday morning?
speaker-1: So our, our core audience, obviously the the book is written very specifically in the product space. So consumer goods and products companies. And we are ti it was written for larger companies. So our core and and specific audience is any executive in that from the finance through the brand, through the marketing, the senior executives who are making those day-to-day decisions about how to apply AI, where to put things. And how they are competing and winning in the marketplace in terms of their own goals as a company. Board members, same thing. But I also feel it's the book is really applicable to any anyone in in the corporate world who's trying to trying to build their own roles, build their teams and trying to figure out how the heck do we get more of our product to market to the customers who really want to. Purchase it. How do we find them? And how do we keep that product in their hands at the pace that those customers want it? And this is a really the book is built on principles. We didn't build it on employ these capabilities and do X tomorrow because the world of AI is still new. It's still emerging and it's changing really fast. So we built it on these principles that still require people to, they're going to have to consider through. How would I apply that? What does that mean within my company? How would I create this kind of system? Even though we've given you a roadmap for it or blueprint for it, we haven't given you a step-by-step employee technology X today. So it actually applies to, in my opinion, to any executive as well as anyone coming out of school right now. If you're coming out of school and you're going to go into the corporate world, this is a really good book to really challenge your thinking about how do you how would you design the What's the operating system in the future? Mm.
speaker-0: It's good thought exercise.
speaker-1: Yeah, I for me it's just been the years of s sitting in meetings with with clients, initially with brands with with my advertising background, then I kind of became an accidental consultant. That's you know where I met Jared and Joan and and and seeing how companies have we I mean we use commerce I think as a you know as a kind of the the maybe as the the the the the th the main theme, but essentially it is a it's a business transformation that's needed in how companies, operate. But what was so interesting about commerce is that it came in into the world in a way that clients and we saw businesses going, why should we care about this? we we know how to do things. We've been doing things like this forever. It works. What are you talking about? why pay attention to Amazon? and then it became COVID had a big impact. It was a jump start into taking a world very seriously that was ignored. I came in from the from the brand perspective, just trying to tell tell clients you need to take this space seriously. It's a canvas where there are there's a buy button. This is very unique. We've never had a canvas with a buy button. we've done storytelling over here and we did that over there. And then it became like, well, who's doing it? And we quickly need to do it, and then it's gonna fade away. As COVID goes away and then it became, and then it became like help us. And then AI just fast tracked it in that sense. So it is something we've seen happen over the years and it's taken on different forms. And I think for me the book is just it it's a it's a great framework to look at your business and to kind of assess your business and using examples of what we've seen and and examples of how companies have have approach the space and also just the incredible opportunity if you do it right. Because every single thing that's written now is a threat to to to companies. I think if you turn it around, they all become opportunities. We've never ever had this much information that we are are able to look at when it comes to people telling us what they like, what they're buying, what they think about, what they care about, on just on a one single product page. The amount of energy a single product page generates around one face cream is just incredible. And it just to treat it as a you know as an online catalog is is is is ludicrous. And then never mind two thousand, twenty thousand, thirty thousand. And you know, and making it work on Amazon is different to making it work on Walmart and just making it work on you know Target or Team, or you name it. So you have this insane world that has just appeared and it's giving brands and and companies, so many signals. And if you are structurally ready and prepared to to to see it and and and and react to it, it's it's giving you incredible information and opportunity to to to play in the market. So yeah, I s I s I think to Joan's point, I think anyone in business that's selling something would find it useful. But it is, I think the it it came from like a a corporate executive, you know position that's dealing and fighting these battles on on a on a on a on a daily basis and giving someone a a structure to look at their own company and look at a a way to, take on these challenges of of of what's coming and what's happening.
speaker-0: One thing both of you just touched on and we've discussed throughout this entire episode is how fast moving this world really is. So I wanna know what was the hardest part of turning something so fast moving, so new every single week into a book?
speaker-1: Don't look at the news as you as you as you I think Claude went through five updates.
speaker-0: Yeah. Yeah. Keep your head down. Yeah.
speaker-1: As as we were. But I mean I it it's look it's a we use it the the term agentic and obviously we we we we we we we use it as a way we which you can structure, but at the end of the day it's a business. It's a business transformation book. It's it's how companies are structured and work together and look at commerce as this as the nucleus. So in that sense it was you know, we we had written versions of this over the years. in in in different I would say in different thought leadership pieces and presentations. So the the core of how we look at companies and businesses haven't changed. I think weaving in the immense impact that is happening now was obviously you know there was a a a need to to get it out because it is happening so quickly.
speaker-0: Yeah. it's those principles that Joan was talking about where the principles do remain the same. It's just different technological applications, right?
speaker-1: Also don't underestimate how slow companies are to change. So as much as we were racing, you know, against this this technology updating itself every day, it is still surprising how structured and set in the ways of s some of the biggest companies in the world are. Mm-hmm. And they they they do pay a price for it because the new upstarts that are coming in are coming in so aggressive. So there is an element of understanding how upset the the the the industry still is and that how it that does require a new thinking. A new approach. Yeah, we were privileged to have been watching this pattern start to emerge for years as we worked through it. So that able that enabled us to make a shift, I think even as we were writing world, we we started to go down a path of making the blueprint into a guidebook and putting here's what you should do. And as we were doing that, Claude was updating the AI models everywhere. We're updating so darn quick and we realized that's there's lots of other books that'll give you the ham to on on on that, that that's not going to serve because it's going to be changed before we would even publish. So we we pulled it back and looked at the patterns that we'd seen for years. And went to this idea of the principles and this is a blueprint, an architectural blueprint that we're hopeful that executives are gonna look and apply to their company. We would be so thrilled if on Monday morning somebody read the book and looked at it and said, I wanna now see how does my company do against this? How does my team do against that part of the book? And actually apply the blueprint out and use it as a guide to figure out how they should be changing or what's the right formula for them.
speaker-0: One thing I really find interesting about competing at machine speed is the book has three authors, but it speaks in a single voice. What did it take for the three of you to reach that endpoint?
speaker-1: we all come from such different backgrounds. And I will credit Accenture for that for the way they bring interesting people, clearly very interesting people, together. And that's and I think the idea that we worked in teams, but we came from such different backgrounds. And I think from my side, being creative, you know, Jared has an incredible background in systems and technology and Joan transformation and but I think the single voice came from like we've always worked with single visions in in teams, and when you come in to to help a company transform or or evolve, there has to be a single focus. And that was the I I I would say the approach in that sense is how do we bring our different skill sets and things into this space and seeing it from different angles. And and yeah, and I think we have had so many conversations in the past that we I would say agreed on where we see things going. Hm.
speaker-0: That shared finish line, yeah.
speaker-1: Not always. We spent a lot of time. A lot mostly, yeah. Yeah, we spent a lot we spent a lot of time on the outline and really aligning that we were all we all aligned to the architecture of how we were gonna write the book. And that that consensus is Raul was saying, because we were all used to a single vision on a team, it was easy for us to get into that mode with each other. That is not to say we didn't have some really good conversations along the way as we Maybe, one when we we didn't agree on a unified vision and and then we just navigated to find it and then then the writing just flowed from there and it was easy it was easier to turn it into a single voice.
speaker-0: So where can people find the book and how can they keep up with you?
speaker-1: I think the book is out on the twenty seventh of October. I think it's on Amazon already for pre-order. So it'll be available on Amazon and I think all all other books, major booksellers. And then we have a a URL competing at machinespeed.com that'll have all the links. We also have a machine version that we've uploaded so you can feed that to your robot. It'll make it much sm make it much smarter. And then myself and Jared is we've actually founded a company called ACOS Labs. So if you go to acoslabs.ai, the the book's link is on there and all there's also some more information about the process and the the thinking that we've been talking about. Yep. And then I'm same you can find me on LinkedIn or via my own my own website, jopsmith.com.
speaker-0: Perfect. Thank you, Rold and Joan. We cannot wait for people to get their hands on competing at machine speed. Thank you both for coming on Author Hour.
