AI and the Implications for your Organization’s Operating System

AI is forcing organizations to rethink how they operate. In this insightful conversation, Dave West and Yuval Yeret discuss the emerging need for a new organizational “operating system” that integrates AI into strategy, structure, and execution. They highlight the role of product thinking, OKRs, and continuous improvement in turning AI from hype into real business value.

Transcript

Speaker 1  0:00  
Welcome to the scrum.org community Podcast, the podcast from the home of Scrum. In this podcast, agile experts, including professional scrum trainers and other industry thought leaders, share their stories and experiences. We also explore hot topics in our space with thought provoking, challenging, energetic discussions. We hope you enjoy this episode.

Dave West  0:24  
Hello and welcome to the scrum.org community podcast. I'm your host, Dave West, CEO here@scrum.org and in today's podcast, we're talking about AI and the implication for your organization's operating system. Okay, let me just give you a little bit of background. So recently, there was a stat that I saw that AI projects are failing at about 95% meaning, because it's very important to define a meaning here, meaning that that people are spending money on AI and not seeing the value afterwards, you know. And so that's understandable. It's very new technology. It's certainly not well understood yet, right? But this led to a very interesting conversation with a colleague, friend of mine, Yuval, who's also going to be on this podcast. I'll introduce him in a moment about what does that mean? You know why? What's happening? Is there a problem with organizations ability to take this technology and deploy it? Is it something to do with the technology? Is it etc, etc? And that conversation was quite interesting, so I thought I would try to repeat some of that conversation today in our podcast, because I think this is actually really interesting topic. So I'm very lucky that Yuval wasn't busy on this Friday afternoon, and I persuaded him to come and join us on today's podcast. I've got Yuval, Yvette, you know, you may know him. PST, safe fellow, Kanban leader, what's interesting about Yuval. And the reason why I was even talking to him about this was he's really interested in transforming how organizations operate, to be more empirical, to be more inspect, adapt, transform, kind of oriented. And that's kind of his thing. So that's why I started talking to him and asked that question. And that's where this conversation. Welcome to the podcast.

Yuval Yeret  2:22  
Yuval, thank you, Dave, glad to be here again.

Dave West  2:27  
Yeah, it's, it's interesting, because you've done a lot of research on operating systems and and that the whole thing really around how organizations operate. You know, both at really large, boring, no, don't say boring, more traditional companies and much smaller, more dynamic companies. You know, some of our listeners may have listened to the dyno therapeutics conversation, which you were heavily involved in, in their transformation and the like. So I guess the heart of this question that kicked all of this office you've got, we've got AI, and particularly generative AI and llms. And now we're getting these agent, these agent kind of mechanisms coming into the into the market, chat, GPT, we've got LMS. So the question is, what is the implications for organizations operating systems of this new technology?

Yuval Yeret  3:27  
So I look at it as a convergence of a couple of things. You mentioned dyno. So maybe a bit of a background how I backed into this world of company level operating systems. You know, whatever you call it, that that's the way I think about it. In some of the organizations that I work with, Dyno was one example. We realized that in order to really move the needle on the strategic growth that the organization needs. You need to go beyond just the product organization. You improve the product organization, you level up your agility, and you see the constraint is elsewhere. It's in marketing or bringing in the right partners or making the onboarding experience work great. So we saw opportunities to leverage the same ideas that we use to accelerate and bring more value and create better outcomes inside the technology organization, in people, operations, in finance, in marketing, in partner success, in the interaction between these different groups, because a lot of strategic value comes from the interaction. So that's how I got into into this space I encountered Dino was using. Some flavor of the Entrepreneurial Operating System, Eos, which afterwards I learned was pretty popular in, you know, the world of scale ups and mid market companies, sometimes companies that have nothing to do with technology, or very little to do with technology, as a way to bring some sense, you know, some discipline into organizations as they scale, to let founders to help founders scale their organization. To come back to the what's going on with AI conversation. I think AI is one example where organizations without the right operating system, without the right approach, are struggling to get the value out of it. And you can see the two levels go ahead.

Dave West  5:55  
Dave, no, I was just going to quickly say because a lot of AI adoption from looking a little bit more details at that that that number is being done outside traditional IT organizations, it's being done in sales, marketing, legal, etc, and they're taking this technology and saying, Oh, can I, can I build a bar, build something that quickly reviews contracts, and they build something, and and, and it works, and then they realize it doesn't work quite as well as they thought it worked. And then they're like, oh, that's unsuccessful. That wasn't quite what, what I wanted. So, so I just wanted to, you know, I that's what I'm seeing anyway. So that probably has an implication,

Yuval Yeret  6:39  
right? Yeah. I mean, if you look at it, you were talking about those numbers, and I have deja vu, because we both know what. You know, the cost report says about the success rates of IT projects success from the perspective of, do they complete on on budget, on time? Do they deliver the scope, and then, you know, later on, after we improve that and create, you know, better feature factories, we started to look at, are they delivering outcomes? Is there evidence that those successful projects, that minority of successful projects, are they actually moving the needle for the business? And we've gone a long way in it towards creating more value for our business. I don't think we're anywhere close to, you know, the Nirvana of being customer centric, outcome focused, empirical evidence based, product organizations in it, or in technology in most organizations. But when you start to look beyond the people that have been exposed to these ideas, it's like the Stone Age. It's, you know, a similar challenge of, there's this new technology, there's this new opportunity. It's very tempting to spend your time on LLM geekery, and, you know, trying to make sure that the data is clean, and talking about legal aspects all of the time. But very few people talk about, why are we doing this? What's the business purpose for this? And even those disciplined organizations are running AI adoption as a project, and we've learned what are the problems with treating complex initiatives, strategic initiatives, as a project? We've learned that focusing on scope, even if you deliver that scope, doesn't necessarily deliver the value so So

Dave West  8:46  
ultimately, the sort of premise is because EOS and the like or most operating systems that that are being used by organizations would treat AI like they would treat, oh, we need to build a new building. We need to, you know, run an event. We need to it literally, is a defined scoped sort of like it's a project. And what fundamentally that that when your operating system has this concept of projects within it as a mechanism for driving change and driving everything then, then, that isn't necessarily the most successful orientation for AI, right?

Yuval Yeret  9:35  
Yes, but I'd argue that it's not just AI. I'd argue that if you look at based on what I've seen, okay, my experience is, whenever I look at the challenges that companies are really facing, their strategic challenges, what keeps their CEO C level management team up at night? Is tackling those challenges, developing their organization, working on growth, whether it's a, you know, a mom and pop shop, whether it's a scale up company, whether it's a mid market, or whether it's the enterprises those challenges, regardless of whether they are product development challenges, or company development challenges are complex. There's a lot that is unknown, a lot that is uncertain. There are bets. There are bets on if we build this new standard operating procedure, if we build this new process, if we give people chat GPT. If we do this, if we do that, will people want to use it? Is it something that is worth our investment in it? Is it even feasible to achieve this? A lot of the time our focus is too much on is it possible to achieve this, or even let's just assume it is. Let's build a plan and let's deploy it, and we're not thinking about the human aspects. We're not thinking about our organization as an organ, as a living thing. We're not really, you know, making the assumption that we don't know that we need to balance championing and, you know, focusing on something with being skeptics, it's not in the interest of leadership teams to be skeptics about their strategic initiatives.

Dave West  11:28  
No, I definitely have unfortunately fallen for that myself. Yes, unfortunately, but I just want to take it back. So what we found with with Scrum in particular, was that product orientation, meaning that when an organization aligns, invests and has this sort of product mindset around the capabilities that support or are the business as it were, let's not use the word support because it's so commingled. It's almost like they are that that product mindset, coupled with the investments and the structures and the empowerment, etc, provides a mechanism to ultimately deal with that complexity, because it it gives con continuous context, as it were, is that? Now I probably waffled on and used all sorts of bizarre words there, but, but at the heart of it, product is the right paradigm, right we've found, and is that true for these organizations wrestling with AI?

Yuval Yeret  12:43  
I think it is. I'm not sure that. I'm pretty sure that these organizations are not thinking about it as product. But if you think about the challenges that, let's say, a mid market company faces or a scale up faces, there's running the operation, running the customer factory, running marketing, bringing people through the funnel, fulfillment, serving them whatever it is that you do. It's can be a professional service. It can be a dental clinic, an architectural firm. It can be a product company that you know the software as a service that onboards, activates these people. We need to make sure that they use the product that they're happily using, that they don't churn the other end, that they refer other people that the flywheel is spinning, that's running the operation. But just you constantly need to think about, how do I spin the flywheel faster you you need to continue to develop the organization. And developing the organization is go through developing a product that will, you know, make the developing a product that will serve our customers, our external customers better and also developing the company so that people inside the company, our internal customers or constituents, can do a better job serving our customers and operating this customer factory. So I do think the product, the product model, the product metaphor works, because once you start to see these key business processes as products, and you have people that own their effectiveness at creating outcomes, you start to think about, how do I develop them? How do we get the organization to to a mode where they think this way is an interesting challenge.

Dave West  14:46  
And the the thing that's also interesting about the product paradigm, so yeah, an organization could think about the capabilities that it uses to serve the customers and the products itself. It. Provides as all products, meaning, you know, a help desk could be a product. The you know, sales and marketing would be a product and and you can think of the capabilities of an organization around that. The benefit of that is that it you treat, you have a roadmap, how you're improving it, how you're going to change it. You also know how much you're investing in it, which is something I definitely as a small business, when I was at task top that just making decisions about where we invested. You know, do we invest in a help desk? Do we instead invest in more software engineers? Do we invest in was actually really hard. I mean, it was, it was at that moment of crisis, we made a decision and hired somebody or spent some money. It was very, not very strategic. The benefit of approaching this from a product paradigm is you get that strategic nurse, because you've basically decided where you're putting your money, and then you can review how that's going and then you can make changes based on that. So, so, so there's something very compelling about that. The other thing that's really interesting about the product paradigm is in the context of AI, the most successful uses personally, of AI that I've had, and where I bound the problem, meaning, I provide a consistent context. I pick the right model. I you know, the AI engine knows the boundaries, and the solution that comes out from the AI engine is very different when, when, when it hasn't got those boundaries. You know, we're actually, interestingly, using AI on some thought leadership, around some, some of the, some of the ideas that we're building around products. So now it's getting very complicated. So and by binding that, by actually saying, This is what we mean, this is, this is the boundary, it's made it a lot more successful. So that's another compelling reason to start thinking about your business in that sort of product paradigm as well. In AI, does that? Does that make sense? Is that what you've seen as well?

Yuval Yeret  17:12  
Yuval, yes, I think about it as context development. So your the context, the additional information that you provide the AI engine when you're working with it on anything is crucial. I've seen that I've I spend a lot of time. I spend more time developing the context for my AI usage than the actual prompts, and it's improved my personal AI effectiveness dramatically. Yeah, so, and if you look at how I do it, if you look at the fact that I'm creating a space, a chatgpt project, probably not the right name, if we're talking about products or Gemini, Gem whatever. And the instruction prompt that I use there, I develop it using something like Scrum. I don't run a full scrum process, but I stop myself, let's say after a day that I've been using that prompt, and I asked myself, as well as the AI engine, how are we doing? Are we getting good results? How could we improve this prompt based on the conversations we've had? Let's look at how often did I have, you know, constructive feedback for you, or even non constructive feedback for you, because I'm not as nice with AI as I should be with the future overlords. And we improve the prompt. We create another version of the prompt. And you know, it's not under source control right now. I should, you know, probably do that better, but I have a version 4.5 of my personal Advisory Board, Jamie, that I use so content development is crucial. And like you're saying, the more the more you think about your your products, your customer factory. How are you creating value in your organization? Where are the constraints? Where are the bottlenecks? What's the strategic focus? The better results AI will give you, and the better results people that are developing AI capabilities for the organization will be able to deliver the key for me, what I see where people are finding gold using AI, whether it's a small organization, whether it's an individual or whether it's an enterprise, is when they use product techniques, whether they call it product or not. So to think through AI strategy and execute on AI development attempts, or AI projects, if you want to call it that, with the mindset of, let's focus on what's the problem that we want to solve here? What is our strategy? Where do we want to play with AI inside the organization? The challenge in the past was, where do we hire another person? The challenge right now is, no, we're not going to hire hire additional people. But where do we want to hire AI? Where do we want to focus our AI attempts? Is it marketing? Is it the fact that we're leaking people? Is the customer overall customer experience that involves both the product as well as customer success? Is it onboarding and activating people? We get people. We get MQLs, but those people aren't really using our product. Maybe it's something on the product side. Maybe it's something else that relates to onboarding customers, whatever it is the we want to be focusing AI on our strategic challenges, on the things we believe will move the needle or will affect the bottom line, if we improve them,

Dave West  21:31  
and things like OKRs can provide a really good mechanism for grounding, that, that that, that focus, as it were, and if you're using a product model, those OKRs work within the context of the of the products, in the context of a broader business strategy. I really, I I haven't really thought about this before, and I know we started talking about it, and I said, Stop. Let's put this on a podcast. So it's probably a little sort of left Fieldy. But as you decompose your business into a series of products, each of those products have a value. Have you know, certain service levels, certain capabilities, certain stakeholders, obviously, who have a set of needs. You start building these, these contract context warehouses for each product, and then exploring prompts that you know based on this, the problems that are manifest, the OKR, the objectives that you're trying to solve, as it were, and then ultimately, that creates an overall operating system. It's like decomposing the computer, you know, to use the operating system analogy or metaphor, into a series of elements that have clearly the bound interfaces, which is obviously the capabilities that they provide. And you get to then explore that using AI, and the AI becomes secondary to the value that the product provides in the context of the OKRs that you're providing. Is that right? Is that? Is that real left field, or is that what you're proposing,

Yuval Yeret  23:20  
in a sense, but also, as you're talking through the decomposition, there's a there's a siren going on in my head. Yeah, about the anti pattern that I see often when people go into this decomposition. You mentioned Help Desk earlier is Help Desk product. I don't know. We need to be careful. Again. I talk about our value streams like it's it's tempting for people to take their organization and say, You're the VP sales. Sales is a product, you're the VP marketing. Marketing is a product, you're the VP product. Product is a product, or the VP people, it's a product. But what we've seen, for example, at dyno, to bring it back, is that the product is not those functions. The product is the onboarding experience or and separately, the overall employee experience, what I call The Aviator experience and the the partner

Dave West  24:26  
experiences and Capsule Development, etc, etc, yes,

Yuval Yeret  24:30  
and that cuts that often cuts across functions. And I think the jury is still out on whether talking about products is the right language for these organizations. There are advantages and disadvantages, whether the language is to speak about value streams and the difference between the operational value streams, how you know, how the organization creates value. You directly and what enables it to create value. I see some advantages to using a product language, and it's not because we talk about product in Scrum. The main advantage that I see in talking about products is when I talk to leaders of mid market firms, there is this trend that in order to scale to better fulfill the needs of your customers, you need to productize, you need to create more consistent products for your customers. So that's a language that is starting to resonate. Let's, you know, be intentional about the balance between bespoke services that we provide and, you know, productized services. Even if we're not a product company, let's productize our services. If you look at me, for example, I'm a service provider, I'm an Agile coach, I'm a management consultant, whatever you want to call it. You can consume my services by having a conversation with me, and we'll we'll figure out what's the best way to support your organization. Or I could create a productized service, which is, you know, I come in, there's an SKU agility roadmap. I help you figure out your how to turn, how to find gold with, with AI, okay, going through this process of switching from bespoke into a productized service is a product development exercise, although it might not have any product. You see a lot of lawyer legal firms, accountants, financial advisors, doctors, switching, switching models, switching from, you know, a visit to a concierge approach or a membership, even though there's, there's no product around that, and that's a they need to develop their organization to a point where That works. That is complex. That's the sort of stuff we're talking about. That's why I think product could be a useful metaphor.

Dave West  27:28  
It's interesting. So I'm working with my sons. Both my sons go to a school here that's designed for dyslexia, for language based learning disabilities and and I've been helping them on some projects, and I actually just wrote an email saying, Hey, I'm thinking about this more strategically now, having been exposed to some of the work that's being done, you know, the way these teachers do, they do their day Job, and then they're trying to reinvent the processes, systems and underlying capabilities of your of the organization. And I, you know, and I said, Hey, look, I've been looking at this, and I've realized that what we should do is look at these capabilities in the organization and group them in in as products, and have product owners around them. And the reason why we should do that is because I'm saying you got to call versus context, you know, outsource some of this stuff because it's, it's taken a lot of these are very specialist teachers. They know, og they know, you know stuff that's for dyslexia. That is, I can only barely understand being dyslexic myself. But the the point is, you know, and so I just sent that email because they've got a scaling problem. That is, as they've grown, their systems have sort of last possible moment they've fixed things as the amount of tape that connects things, you know, a gaffer, you know, sticky tape and, and, and so that's really interesting. It's funny that I'm going through this the same thing now. So I guess at the heart of this, you know, that original question is, you know, around the the failure of organizations to be able to adopt it, the that AI will require a different operating system, I think, and I think or to take advantage of AI, obviously, you know, yes, AI is just a tool, right? But, and I think it is grounded in the ideas of empiricism, continuous improvement. There's, you know, this idea of transparency, all of these things that the product world thinks about. And I think it's also grounded by this concept of boundary. And really. Understanding those boundaries effectively now, whether they're value streams or whether they're service, you know, shared services, or whether their internal system, I don't know, and that's to be debated, right? But, but I think it, I think that's the realization I've come to you, Val, do you agree?

Yuval Yeret  30:22  
Yeah, yeah, I don't think it's necessarily an overhaul of your operating system. I mean, we're not talking about reformatting the operating system for your organization necessarily. It depends, like, if you're still running, I don't know, Windows 3.0 for your organization, or you can't even say what's the operating system for organization? Yes, maybe it makes sense to go look at OKRs. You might want to look at EOS or scaling up, or use Scrum as the operating system for your organization. There are multiple options, but the question we're talking about here is, whatever it is, let's say it's Eos, because that's very popular in this space, yeah, yeah. Ask yourself, is your operating system good enough. It's sensing and responding, at inspecting and adapting, at organizing around outcomes. Is it really helping you flow, focus and flow the top priorities for your organization. A lot of these operating systems do manage flow. Okay, they do talk about, let's focus just on the big rock, Stephen Covey stuff. There's a lot of commonality, but once you focus on these few big rocks, er, those rocks defined in outcomes, which allows you to seek towards your strategic goal rather than execute a plan that might not be the right plan. Are, do you have leading indicators in your scorecard that allow you to steer? If those are lagging indicators or you don't have any any indicators at all, you can't really steer. You can just execute to the plan. It's much easier to to follow a plan and say everything is green. And, you know, use the the watermelon approach for these projects, if you don't have evidence to, you know, in front of you, to confront reality. So those are the questions that that I, that I help leaders of these organizations ask themselves. Is our operating system set up for the sort of learning in the face of uncertainty that we need in for for finding AI gold, for leveraging something as uncertain, like like AI, in how it will affect people. How will the technology work? It moves so fast you can't really define it in terms of, you know, a detailed a detailed spec or project plan, you need to focus on, what's the outcome that we really that we're looking for here? How is this related to the business constraint? Those are the questions to ask yourself about your operating system, ways of working, whatever you want to define, and to be clear, that operating system focuses not on the day to day whirlwind, not on operating your business. We're not saying use this operating system to serve your customers on a day to day basis. We're not talking about it for running your marketing on a day to day basis. It's about developing future things. It's about the unrealized value, the potential, the opportunities that you have as an organization, or the biggest problems that you have. That's where you need this empiricism, that question of, what are the things that we can just execute, and what are the things where we have uncertainty and we need a testing discovery, dare I say agile mindset to to tackle them. That's an important question, because the the anti pattern that I've seen is organizations that really like what they see. They look at the product organization, and they really like the agile ways of working, and they're saying, let's use it all over the place. Let's run our help desk using Agile. Let's run our sales team using Agile. And very quickly, that becomes an agile theater, because it doesn't make sense to to use Scrum for running an. Operational process, or running something that's simple or complicated, where, yeah, you can use Lean, you can maybe use Kanban to manage flow, but you don't really need the the inspection adaptation that comes from real product oriented, agile ways of working, like Scrum.

Dave West  35:20  
So basically, what you're describing is the layer above the operating system that monitors the operating system and then inspects and adapts it and changes it.

Yuval Yeret  35:35  
I mean, it's a matter of definition. I think the operating system includes both, like the operating system is both running the operation, but also developing the future of the operation. If you look at Eos, for example, EOS tackles developing the organization. It talks about, what is our strategy? Yeah, what are our big rocks? It tries to work on the business, not just in the business. It focuses working on the business to the challenges of the business. It's heading in the right direction, but it needs to be complemented. In my experience, with agility as the way to really work on your business. Working on your business is much more complex than running it.

Dave West  36:24  
Yes, and what's interesting is the relationship the frequency that your business, your system has to change, is increasing, coupled with the way in which you orient those systems. You align them, you connect them, you connect them to business strategy, etc, is probably changing as well. So the distance between, it reminds me a little bit of we talk about Toyota Production System, TPS. But actually, what's more interesting for me has never been TPS. It's cool, don't get me wrong, but it's, it's TDs, the design system that one book that was been translated from Japanese very badly that you just read a sentence like three times and go. I'm not totally still sure what that means, but this i How did they, you know, what is the Toyota principles? Now, both TPS and TDs share some common principles, so maybe your sales organization can be empirical, goal driven, you know, provide transparency, have frequent, you know, etc, etc, that that could be a principle that both organizations share, however, that the actual the system is different. However, they have to embed closely, because when your manufacturing process isn't isn't working as effectively as it should. In the case of TPS, you know you're doing a Kaizen, you know you're fixing it, but that's going to have some design implications. So it has to come up into a broader design system, then flow back down.

Yuval Yeret  38:04  
So a couple of thoughts. One is when you pull the Andon Cord, when you have an issue in your operation that you want to stop and fix, if a customer has turned that really surprised you and you, or you lost a sale or something happened, you want to stop. And you know, ask five whys you want to do a Kaizen moment you you want to think about how to improve the improvement might come. And the moment you did that, you moved from the operational value stream into the development value stream, yeah, my terminology, that another layer of the operating system, yeah, that at that moment, you might go into the your product world, which is, I think, What TDS is talking about. Or you might stay in the process world. You might reorganize the manufacturing line. You might move the quality check upstream. You might do different things, organize, you know, bring the tools closer what you know, use AI to improve the language that the sales reps use, or the customer experience people use, whatever it is that might not change your product, but that change that still changes how you operate, that that's developing your, your product, developing your your business, as constraints. For me, that's, you know, if people want to dive deeper into Toyota's wall there, I'm thinking about the improvement cut up, which is the discipline of constantly looking at the crucial metrics for our organizations. What we. Believe are the leading indicators. Let's take churn as an example. If we are thinking churn, if we know, hopefully we know rather than think. But that's, you know, a higher bar at the maturity of the organization already. If we know that churn is our biggest constraint right now for growth, we're spending tons of money marketing. We're bringing those people a lot of effort. They leave after the initial period. They leave after three months. They sign up for our products, and they leave after three months. We need to form an hypothesis, and that's where product thinking comes in, or just strategic thinking. What are the leading indicators that affect whether people churn or not? One example might be, do they use the product? If people use the product on this on the first week, and then they don't come back? We kind of see a correlation between that and a churn. The focus of the team, the, let's say, the product team that will be developing or improving or fixing our, you know, cost our customers experience, so that we see lower churn. The focus of that team would not be on churn, their product goal. I mean, it might, it might overall be on churn, but they hopefully have a clear strategy, a how to win, strategy that says we formed an hypothesis that the way to reduce churn is to fix usage, to make sure that people use the product more. That will be their product goal. Now they have an hypothesis for how do we do that improve usage, and we might learn that that's not working. They might have an intermediate goal. We'll work a sprint. We'll work a month on tweaks for what would get people to use the product more? How do we get them back on the wagon? Maybe it's through human, you know, prompts, rather than the product itself. Maybe it's the customer experience folks, the account managers, that do something rather than the product itself. Um, and we try it and we see, does it move the needle on usage? If it's not, let's find something else. If it is, let's scale it. Of course, we need to check that that cohort of people that use the product more actually don't churn. We might learn they still churn. Maybe it's too expensive, so that invalidates our our hypothesis, and it's an it's a continuous process that you want to run very quickly and frequently, to converge from the way you're running your operation right now to an upgraded version that works through the constraint that you have right now.

Dave West  43:06  
It is, I mean, it's sort of, when you start talking about it, you start decompose the I know we avoid the word decompose, but you start looking at it from different perspectives, how it drives through. Starts getting awfully complicated. But another benefit of at least thinking about is a product strategy is you've at least made some choices which reduces that complexity. So you know, in that example of the churn you've making, it's on this product bound to mine the dirt, off you go, small group of teams, etc, etc. 111, system notwithstanding. All right, we could talk for hours about this, you know, and, and we have, which much to everybody else around us is annoyance, often. And I guess I'd like to leave our audience of a little bit of a like, okay, you know the AI and the implications for your organization's operating model, operating system. Sorry, you know, what are the, what's the one thing we'd like to leave our audience with, you know? What is that one thing?

Yuval Yeret  44:19  
I have an invitation for people. So like I mentioned earlier, there are some questions that you can ask about the way you're currently operating that might indicate whether you're set up to find AI goals, you're optimized to find AI gold. I integ synthesized a set of questions that are inspired by our thinking on on products and agility into some sort of scorecard, a quiz that people can use to to work through these questions. I will leave. A we'll leave a link in the show notes for for how to find it. And I think it's a good start for thinking about this. We're not saying, Go, upgrade your operating system. We're saying, let's start by thinking about easy organization, scruit operating system red. Ai, ready? Let's say,

Dave West  45:29  
are you ready for AI, yes, an interesting question. Hey, Yuval, thank you for spending this Friday afternoon with me talking about this kind of very broad, very far ranging topic. Um, I've certainly learned a few things today which made me think about things differently. Not sure if that's learning. I guess that is learning. Um, the, yeah, the the relationship between operational systems and designing those systems, and how that has to be in a continuous process, integrated process of change based on the needs of those those systems in the context of a business strategy the needs of the organization is super, super interesting. And if we can better align those things using maybe product thinking as a mechanism, we could be in a really strong position, and then AI just becomes a very powerful tool for accelerating that, as opposed to AI being this amazing solution that we haven't really got the right problems for yet. I think that that's what I've taken away from today's talk. And for our listeners, thank you for listening and bearing with us as Yuval and I wandered aimlessly around the concept concepts of operating systems, organization, operating systems, AI, adoption, Eos, the Entrepreneurial Operating system, how it fits in with OKRs and all these other amazing concepts. Hopefully you took some value from today's today's podcast, and if you liked what you heard, please subscribe, share with friends, and of course, come back and listen some more. I'm lucky enough to have a variety of guests talking about everything in the area, professional Scrum, product thinking, and, of course, agile, as we heard today, organizational operating systems as well. So thank you and Scrum. You

Unknown Speaker  47:33  
you.

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