How to Upgrade Your Organization's Operating System for the Age of AI

Help me think through how this episode applies to my situation. Start by asking what I am trying to change. Separate the episode's claims from your suggestions, and say when the notes do not support a claim. Use the transcript to find passages, then check the audio before quoting. Transcript: https://yuvalyeret.com/podcast/episodes/how-to-upgrade-your-organizations-operating-system-for-the-age-of-ai/transcript.md ## Published episode notes Episode Overview In this crossover episode with the Scrum.org Community Podcast, Yuval Yeret joins Scrum.org CEO Dave West to unpack why 95% of AI initiatives fail, not because of the tech, but because of outdated organizational operating systems. Together they explore how they’ve seen product thinking and empirical agility help leaders align strategy, product, and delivery to make AI deliver business impact. Together, they explore how mid-market and scale-up leaders can evolve their “Company Operating System” to become truly AI-ready: adaptive, outcome-driven, and designed for learning. Highlight Quotes / Concepts * “AI isn’t failing, our operating systems are.” * “Treat your company like a product, develop it with evidence, feedback, and intent.” * “Empiricism isn’t just for software teams. It’s how organizations survive uncertainty.” * “The best results come when leaders focus AI on their biggest business constraints, not shiny experiments.” Chapters * 00:00 Welcome * 02:35 Challenges in AI Adoption * 03:51 Transforming Organizational Operating Systems * 07:28 Product Thinking in AI * 19:06 Context Development for AI * 45:46 Final Thoughts and Takeaways Notable Quotes “Where people find gold with AI is when they use product techniques to think through strategy and execution, not when they chase shiny tools.” , Yuval Yeret “AI exposes every weakness in how your business learns.” , Dave West “Your operating system determines whether AI is a toy or a transformation.” , Yuval Yeret “Don’t replace humans with AI, replace bureaucracy with learning.” , Yuval Yeret Learn More: * Improving AI Impact using Agility-based Operating Systems * EOS (Entrepreneurial Operating System) * OKRs (Objectives and Key Results) * Leveraging Evidence-Based Management to develop your company * Improvement Kata / Toyota Design System Is your organization’s operating system ready for AI? Take Yuval’s free AI-Ready Operating System Scorecard and find out where your business is leaking traction, and how to fix it before your next AI initiative stalls. 👉 https://scorecard.yeretagility.com/quiz/ai-traction-scorecard This podcast episode was recorded and published originally on the Scrum.org Community podcast: https://www.scrum.org/resources/ai-and-implications-your-organizations-operating-system. To hear more, visit yuvalyeret.substack.com ## Transcript This transcript was edited from automatic speech recognition for readability. Speaker turns may be wrong or absent, and it may contain recognition errors. Check the audio before quoting or attributing a passage. Episode: https://yuvalyeret.com/scaling-ai-podcast/how-to-upgrade-your-organizations-operating-system-for-the-age-of-ai/ ## The friction around operating system Where people are finding gold using AI is when they use product techniques to think through AI strategy and execute on AI projects 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 hire AI? Where do we want to focus REI? We want to be focusing AI on our strategic challenges. On the things we believe, we'll move the needle, or we'll affect the bottom line. Welcome back to Scaling with Agility. I'm Yvall Yerith. Today's episode is a crossover. Conversation I had with Dave West that's from the talk about AI and the implications for your organization's operating system. The short version AI isn't failing, but our operating systems are. Companies pour millions into AI pilots, but strategy, product, and delivery still move on different clocks. And in a lot of cases, art even applied to AI pilots because we don't see AI as a development challenge. What David and I discussed in this podcast is how should we rethink our operating systems, align them around outcomes, flow, evidence, the same principles that make great product organizations work. How can we apply that to how we approach AI and beyond? What we're seeing in organizations that are doing this is they're able to make more bets, They're able to fail faster, which results in more successful beds and a business that can actually turn AI technology into traction. I think you'll find this discussion I have with Dave West, both challenging and practical. Hope you enjoy this episode. Hello and welcome to the Scrum.org community podcast. I'm your host, Dave West, CEO here at 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 the AI projects are failing at about 95%. Meaning, because it's very important to define a meaning here, meaning that the 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, Yaval, who's also gonna 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 the technology? Is it et cetera, et cetera? 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 a really interesting topic. So I'm very lucky that Yivel wasn't busy on this Friday afternoon. And I persuaded him to come and join us on today's podcast. I've got your value there. You know, you may know him, PST, safe, fellow, camban leader. What's interesting about you, Val, 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, Yivelle. Thank you, Dave. Glad to be here. Yeah, it's interesting because you've done a lot of research on operating systems and the whole thing really around how organizations operate, you know, both a 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 dino therapeutics conversation, which you were heavily involved in, in their transformation and the like. So I guess at the heart of this question, the kick to all of this, you've got, we've got AI and particularly dramatic AI and LLMs. And now we're getting these agent kind of mechanisms coming into the market, we're in chat, GPT, we've got LMS. So the question is, what is the implication for organizations operating systems of this new technology? So I look at it as the convergence of a couple of things mentioned that no. So maybe a bit of a background. How I back into this world of company level operating systems, whatever you call it, that's the way I think about it. In some of the organizations that I work with, DINOS 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 constraints 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 knowledge, organization, in people operations, in finance, in marketing, in partner sex, in the interaction between these different groups, because a lot of other comes from that. That's how I got into this space. I encountered Dinah was using some flavor of the entrepreneurial operating system. EOS, which afterwards I learned was really popular in, you know, the world of scale-ups and mean market companies, sometimes companies that have nothing to do with technology or very little to do. As a way to bring some, you know, some discipline in organizations as they scale to let founders, to help founders scale their organization. to come back to 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 it at two levels. Go ahead. No, I was just going to quickly say, because a lot of AI adoption, I'm looking a little bit more details about that number, is being done outside traditional IT organization. It's being done in sales, marketing, legal, et cetera. And they're taking this technology and saying, oh, can I build something that quickly reviews contracts? And they build something and it worked, and then they realized 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 I wanted. So, I just wanted to do it. That's what I'm seeing anyway. So that probably has an implication, right? I mean, if you look at it, you were talking about those numbers, and I have Deja Vu, because we both know what in all the calls and reports about success itself by three projects, success from the perspective of do they complete on a budget, on time, do they deliver the scope? And then, you know, later on after we improved 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 minorities 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 the nirvana of being customers and outcome focused empirical evidence product organization 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 a similar challenge of there's this new technology, there's this new opportunity, very tempting to spend your time on L.L.N.D.D. and 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 the project. And we've learned what are the problems with trading complex initiatives, called strategic initiatives as the project. We've learned that focusing on scope, even if you deliver that scope, that would necessarily deliver the value. So ultimately, the premise is, because EOS and the like or most operating systems that are being used by organization would treat AI, like they would treat, oh, we need to build a new building, we need to run an event, we need to, it literally is a defined scope, 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 that isn't necessarily the most successful orientation for AI, right? AI, right? But I'd argue that it's not just a I'd argue that if you look at it, from what I was, okay, my experiences. Whenever I look at the challenges that companies are really faced, their strategic challenges, what keeps their CEO, C level management team up at night, tackling those challenges, developing their organization, working on growth, whether it's, you know, a mom and pop shop, whether it's a scale-up company, whether it's a lead market or whether it's 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. ## What is really happening in the system There are bets on if we build this new standard operating procedure. If we build this new process, if we give people CHETPT, 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? A lot of the time our focus is too much on the use it's 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 aspect We're not thinking about our organization as an organ is a living thing We're not really You know making the assumption that we don't know That we need to balance championing you know focusing on something with being skeptics It's not being the interest of leadership, these statistics about their slippings you can issue this No, I definitely have unfortunately fallen for that myself Yes, unfortunately, but I just want to take it back. So what we found with Scrum in particular was the 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, that's not used the word support because it's so pomengled, it's almost like they are, that product mindset, that, coupled with the investments and the structures and the empowerment that provides a mechanism to ultimately deal with that complexity because it gives continuous context, as it were. Now, I probably waffled on and used all sorts of bizarre words there, but at the heart of that Roda is the right paradigm, right? We've found, and is that true for these organizations or anything with AI? 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 full-fill and serving them whatever it is that you do. It can be a professional service, it can be a dental clinic, an architectural firm, it can be a product company that software is a service that on boards 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 work for 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 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 concussions, can do a better job serving our customers and operating these customer factors. So I do think product, the product model, the product metaphor works because once you start to see these key business processes that product and you have people that own their, effectiveness of 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? And the thing that's also interesting about the paradigm. So yeah, an organization could think about the capabilities that it uses to serve the customers and the products itself provides as all products, meaning a health desk, be a product. The sales and marketing would be a product. And you can think of the capabilities of an organization around that. The benefit of that is that you treat, you have a roadmap for 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 a task top, just making decisions about where we invested, 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 at that moment of crisis we made a decision and hired somebody or spent some money. It was not very strategic. The benefit of approaching this from a product paradigm is you get that strategicness 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. 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 a well-bound problem. Meaning I provide a consistent context, I pick the right model, the AI engine knows the boundaries. And the solution that comes out from the AI engine is very different when it hasn't got those boundaries. We're actually, interestingly, using AI on leadership around some of the ideas that we're building around products. Now it's getting very complicated. So, and by binding that, by actually saying, this is what we mean, this is the boundary. It's made it a lot more successful. That's another compelling reason to start thinking about your business in that sort of product paradigm as well, in AI. Does that make sense? sense is that what you've seen as well? Yes, I think about it as context development. So you're 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 spend a lot of time, I spend more time developing the context for my AI usage than the actual ROM. It's improved my personal AI effectiveness dramatically. If you look at how I do it, if you look at the fact that I'm creating a space, a such a tricky project, probably not the right name. We're talking about products or Gemini, Jim, whatever. And the instruction prompt that I use there, I develop it using something like Scrum. I don't try to fool Scrum process, but I stop myself after a day that I'm using that prompt. And I stop myself as well as a engine. How are we doing? Are we getting good results? How could we improve this prompt based on the conversations? Let's look at how often did I have, you know, construct your feedback for you or non-construct? Or you, because not as nice with the eyes. What you're over, Lord? And we improve the print. We create another version of the prompt. And you know, it's not under source control right now. You know, probably do that better, but the version in 4.5 of my personal advisory board, you know, I do that. I use so context 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 balance? What's this strategic focus? The better results AI will give you. And the better results people that are developing AI Cup of for the original journey will be able to believe 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 and enterprise is when they use product techniques, whether they call it product or not, to think through AI strategy and execute on AI development techniques or AI projects, if you wanna call it that way. 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 gonna hire additional people, but where do we want to hire AI? Where do we want to focus our AI? Is it marketing? Is it the fact that we're leaking people? Is the customer experience? involves both the product as well as customer sex. 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 customer. Whatever it is, 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. And things like OKRs can provide a really good mechanism for grounding that focus, I think, were. And if you're using a product model, those OKRs work in the context of the products products in the context of a broad business strategy. 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 field day, but as you decompose your business into a series of products, each of the products have a value, have certain service levels, certain capabilities, certain stakeholders, obviously, who have a set of needs. You start building these contact's warehouse history, and then exploring prompts that, based on the problems that are manifest, the okay, the objectives that you're trying to solve, as it were. And then ultimately that create an overall operating system. It's like decomposing the computer to use the operating system, analogy or metaphor into a series of elements that have clearly debounded interfaces, which is obviously the capabilities that they provide. ## The practical shift 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'll provide. Is that right? Is that real left field? Or is that what you're proposing? In a sense. But also as you're talking through the decomposition, there's a siren going on in my hand. Yeah, yeah. About the anti-pattern that I see often when people go into this company. You mentioned Peltdesk earlier. It's help desk product. I don't know, we need to be careful. Again, talking about our Valley Stream. Like it's tempting for people to take their organization and your DEVP sales sales is the product. Your DEVP marketing marketing is the product. Your DEVP product, product is the product. Your DEVP people, it's a product. But what we've seen, for example, the dyno to bring that is that the product is not those functions, the product is the onboarding experience or, and separately, the overall employee experience will deviate her experience. And the partner experience is the- And the chat so development, et cetera, et cetera. Yes, and that cuts, 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 with whether the language is to speak about value streams and the difference between the operational value streams, how the organization creates value 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 meat markets, there is these trends 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 resume. Let's, you know, be intentional about the balance we spoke, services that we provide, and, you know, product services, even if we're not a product company, let's productize our services. 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 figure out what's the best way to support the organization. Or I can't create a product-type service. He's I come in, there's an SKU, agility role. I help you figure out how to find gold with the app. 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 a visit to a concierge approach or a miniverist sheet, even though there's no product around there. 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 the product could be a useful matter. It's interesting. So I'm working with my son, both my sons go to a school here that designed for dyslexia, the language based learning disabilities. 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 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, 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 taken a lot of these are very specialist teachers. They know OG, they know, you know, stuff that's dyslexia that I mean, I can only barely understand being dyslexia myself. But the point is, you 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, the amount of tape that connects things, you know, a gaffer, you know, sicky tape. And so that's really interesting. It was funny that I'm going for the same thing now. So I guess at the heart of this, you know, the original question is, you know, around the failure of organizations about to adopt it, that AI will require a different operating system. I think, and I think, or to take advantage of AI, obviously. I, you know, yes, AI is just a tool, right? But, and I think it is grounded in the ideas of empiricism. Okay, continuous improvement. There's 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 shared services, or whether they're internal system, I don't know, and that's to be debated, right? But I think that's the realization I've come to you about. Do you agree? Yeah, yeah. I don't think it's necessarily an overall of your operating system. I mean, we're not talking about Reformating the operating system for your organization. Necessary 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? And yes, maybe it makes sense to go look at the OKRs. You might want to look at the US 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. Ask yourself, is your operating system good enough? It's sensing and responding, it's inspecting and adapting, it's organizing around outcomes. It's really helping you flow, focus and flow the top priorities for your organization. A lot of these operating systems do manage flow. They do talk about let's focus just on the big rocks, Stephen Covey stuff. There's a lot of commonality. But once you focus on these big rocks, you are those rocks defining outcomes, which allows you to seek towards your strategic goal rather than execute a plan that might not be the right plan. Art, do you have leading indicators in your scorecard that allow you to steer? If those are lagging indicators or you don't have any indicators at all, you can't really steer. you can just execute to the plant. It's much easier to follow a plan and say everything is green and the watermelon approach for these projects if you don't have evidence to confront reality. So those are the questions that I help leaders of these organizations ask themselves. these are operating systems set up for the sort of learning in the face of uncertainty that we need in for finding AI goals, for leveraging something as uncertain like AI and how it will affect people, how will the technology work. It moves so fast you can't really define it in terms of of a detailed spec or project plan, you need to focus on what's the outcome that we're 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's where you need this. 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, their, I say, agile mindset to tackle them, that's an important question. Because the anti-pattern that I've seen is organizations that really like what they see. ## What leaders should pay attention to 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 best 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 use Scrum for running an operational process. We're running something that's simple or complicated where, yeah, you can use Lean, you can maybe use Todman to manage flow, but to dolds really need the inspection adaptation that comes from real product oriented edge all ways of working. 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. 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, that calls developing the organization. Talks about what is our strategy, what are 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 fitting 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. Yes, and what's interesting is the relationship, the frequency that your business, your system has to chain 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. 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, gold-driven, provide transparency, have frequent, et cetera, et cetera. That could be a principle that both organisations share. However, the system is different. However, they have to embed closely, because when your manufacturing process isn't working as effectively as it should in the case of TPS, you're doing a Kaizen, you're fixing it, but that's going to have some design implication that has to come up into a broader design system and then flow back down. So, a couple of thoughts. One is when you pull down the cord, when you have an issue in your operation that you want to stop and fix, if a customer is churned, that really surprised you or you lost the sale or something happened, you want to stop and ask, why is you want to do a case and moment 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. I terminology, another layer of the operating system. That at that moment, you might go into your product wall, which is like think what TDS is talking about. Or you might say in the process wall, you might reorganize the manufacturing line, you might move the quality check upstream, you might do different things, organize, bring the tools closer, use AI to improve the language that the sales reps use or the customer experience, use whatever it is that might not change your product, but that still changes how you operate. That's developing your product, developing your business as constraints. For me, if people want to dive deeper into Yoda's world there, I'm thinking about the true than caught 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 thing, but that's, you know, a higher bar at the maturity of the organization already. If we know the Chinese are biggest, constrained 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 the first week and then they don't come back, we kind of see a correlation between that and they churn. The focus of the team, let's say the product team, that will be developing or improving or fixing 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 overall be on churn, but they hopefully have a clearer strategy, a how-to-win strategy that we formed in our hypothesis, that the way to reduce churn is to fix usage, to make sure that people use the product more. And the hypothesis. That will be their product goal. Now the hypothesis for how do we improve usage? And we might plan that that's not working. They might have an intermediate goal, we'll work a sprint, we'll work a month on the tweaks for what would get people to use the product more. How do we get them back on the wagon, Maybe it's through you many, you know, prompts rather than the product itself. Maybe the customer experience folks, they count 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 hypothesis. 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. It is, I mean, it's sort of, when you start talking about it, you start decomposing. 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 as you've at least made some choices, which reduces that complexity. So, you know, in that example of the churn, you're making it's on this product, bound to mine, the off-you-go, small group of teams, etc, etc. One system not with Stanek. All right, we could talk for hours about this issue now. And we have, which much to everybody else around us is annoyance often. And I guess I'd like to leave our audience with a little bit of a like, okay, the AI, the implications for your organization's operating model, operating system, sorry. What's the one thing we'd like to leave our audience with? What is that one thing? 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. Like to indicate whether you're set up to find the eye goals. You're optimized to find the eye goal. I synthesized a set of questions that are inspired by our thinking on products and agility into some sort of scorecard, a quiz that people can use to work through these questions. I will leave a link in the show notes 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 Is your organization a secret operating system? Red AI ready, let's say. And are you ready for AI? Yes, interesting question. Hey, Yavlle, thank you for spending this Friday afternoon with me talking about this kind of very broad, very far ranging topic. I've certainly learned a few things today, Which made me think about things differently. I'm sure if that's learning, I guess that is learning. 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 systems in the context of a business strategy in 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's what I've taken away from today's. And prior listeners, thank you for listening and bearing with us as you've all and I wandered aimlessly around the 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. ## Source boundary These are the published show notes from the podcast feed. They are a starting point for discussion, not a verbatim record of the conversation. The transcript is machine-generated and may contain errors or unlabeled speakers. Check the audio before quoting anyone.