to be quiet in here. I didn't even have to clink glasses or anything. All right. Hi, welcome to day two and final day of the KeyBanc Technology Leadership Forum at Vail. Really nice to be here with everybody here in the, in the Rockies. I'm Michael Turits, enterprise software analyst here at KeyBanc. And I'm very happy to have CJ Desai from ServiceNow here today, President and COO. Thank you very much, CJ, for coming. Thank you for inviting, and it's a pleasure to be here. Great. a quick background on CJ. CJ has been at ServiceNow for six years? 6.5. 6.5. Yes. Okay. 6.5 years, President and COO now, up until, I guess, about 1 year ago, he was also Chief Product Officer. Yeah. Was at other large software companies and tech companies, including EMC, Symantec, and Oracle. I think that what I'd like to do is start talking about ServiceNow and the history of ServiceNow, and where it's come to at this point, but then move on to the subject of Generative AI and talk about it in a general sense. Then at the end, come back to where ServiceNow is involved there. Okay. So funny thing, of course, about ServiceNow is, is, you know, ServiceNow is gonna be an $8.5 billion company this year, in our model, and yet you can still, search and say: What is ServiceNow? What does ServiceNow do? ServiceNow even has its own videos describing what, what it does. It, it's a, it's a really amazing... that to me, and I hope you don't mind if I'll just tell a little bit of an anecdote first. Please do. You can. In, in trying to understand what ServiceNow does, sometimes people say that it's enterprise workflows. I have to tell the story of the first time that I met ServiceNow right around the time they were going public. Their founder, Fred Luddy, was in the room. He had been a chief technology officer, among other places, at BMC Remedy and at Peregrine, some predecessors to, in ITSM. He said, "Well, if you really want to understand..." Where I began to really understand, where Fred said he began to understand the breadth of what could be done, he said, "was while looking at what, what some of these ITSM companies were doing and where they were being applied." He said, "You know, if you're in the US Navy and you are feeling depressed, unfit for service, unable to do whatever you need to do on the deck, then you actually fill out a form that says, 'I'm unable to do this, and I need help,' and that's a ITSM trouble ticketing form. When you're able to return to work, that trouble ticket is closed." When he saw applications like that, he said, "This is, this is something much bigger." I tell that as an anecdote, but then I'll go back and ask CJ to talk about the beyond that. Yeah ... instance, about the history of ServiceNow and how it came from being something about trouble ticketing to such an important company today. Yeah, absolutely, Michael, you know, it's great to be here. Fred is a great innovator. Even today, he still codes, which is awesome, and once in a while, he will actually log into our build system and say: "Why is this this way?" Just amazing inspiration to ServiceNow engineering community. When Fred created this company, 2003, when he had the idea, we are still 19 years old because 2004, it was officially incorporated. He basically said: "I'm gonna create..." It was very simple design principles. "I'm gonna create a cloud-based platform," and platform was important because PaaS as a term or Platform as a Service was not even that well known. "I'm gonna create a cloud-based platform where anybody can route work seamlessly. I'm not creating an ITSM company, but I'm creating a platform with core tenets of tasks, orchestration, notification, approvals, so when you want to get anything done, you can get that done via ServiceNow platform. That's it. ITSM was the first killer use case that was built as a demo on ServiceNow platform and, of course, then over time, productized fully. Then, like Michael was saying, whether it's for IT ticketing, whether it's for HR ticketing, whether it's for customer service and many other areas, when you want a task to be done in a certain sequence, and there are notification and approvals that are required so that the task or a ticket gets resolved, that's how Fred created this company. He always told me, even when he hired me, he said, "CJ, this platform has unlimited TAM." I'm like, "Of course, a founder is gonna say that the platform has unlimited TAM." He really said, "You can build any type of application on this platform, any type of workflow on this platform. All you need is which process you want to automate, and you can build it because the platform provides all core services. I, think that's, it's, it's an amazing thing, and one of the things that it's important to understand when I gave that $8.5 billion number, that they've achieved that with essentially, essentially organically. They've been tucking acquisitions. Yeah ... but there have been no major acquisitions, and everything has taken-- You buy it, it takes... What would you say from the time you buy something to the time it actually gets out onto the platform? 'Cause you don't roll it out, you make it part of the platform. Yeah. Our acquisition strategy has been pretty simple. We typically either buy an amazing team that we want to be part of ServiceNow, or we buy a piece of technology or a technology, and then once we buy that technology-... specifically, we do not want to put that complexity of integration on our customers. That is the core principle. Michael, as you said, we will take that technology and integrate in ServiceNow's code base, and that typically takes us 9 to 15 months. Sometimes we are done in 6 to 7 months, but typically 9 to 15 months. Our worst-case scenario may be 18 to 21 months, but the median is in the 1-year-ish range that we typically do, so that customers know that now this is just part of ServiceNow platform. We have done that with RPA, we have done that with our AIOps technologies, and many other... It's just part of the platform. You've again, the first use case, as you said, was ITSM. Correct. I, I don't know if this is a, an apocryphal story or not, but supposedly I heard that Fred actually came to some of his early investors and said, "Oh, I have this thing, it can do workflows. Yeah. They said, "Nobody's going to invest in that. Yeah. You got to tell them what they're going to use it for. Correct, the use case. Yeah, that is correct. He said, "Okay, fine. Yeah. I'll start with IT service management and travel ticketing. That's right. You did start with that and took on and really disrupted the industry. Talk about how you've moved from there into these other areas of the enterprise, into HR, et cetera. Yeah. and then why that was possible. If you look at an organization, you know, our customers, all enterprise customers, the CIOs typically are in service of their peers. If they buy CRM, then the CIO will run the CRM software. If they buy ERP, the CIO will run the ERP software for supply chain or a CFO, right? Typically, the CIOs are running software for their peers and make sure the software is up and running, so you automate CRM, or supply chain planning, or procurement, or whatever the case might be. Where a ServiceNow CIO is our people. We said: This is ERP of IT, and we are going to create products, starting with ITSM, but we are going to create products for the CIO's organizational structure. CIO has somebody who is running service management, somebody who is running operations management. Two-thirds of CISOs typically report to the CIO, then you sometimes have risk reporting, project management. The beautiful thing the ServiceNow team did is literally map the product portfolio serving the CIO, that we are building this product for you so that you can keep service management, operations management, asset management, and all that in control. Then, Michael, once we just made sure that that focus, CIO being the core, core stakeholder for ServiceNow, we said this helpdesk concept could be extended to HR, because when somebody has an HR-related issue, they actually call somebody in HR. It typically happens over email or a phone call. Like 20 years ago, there was some 1-800 HR number for every company. We can create similar thing for HR, HR helpdesk. Then we also said, "Why not we do that for customer service?" Because customer service, you typically, "Hey, hey, I'm calling you for a request," then you will orchestrate a workflow. Then we continue to expand that now in procurement and few other areas. The core primitives are always very, very simple. We always take help of our CIOs to introduce us to the CHROs, to the chief customer officer, that's why that point is super important, that we were serving the CIOs, we always will serve the CIOs, then we ask them, "Hey, can you introduce us to the CHRO or chief people officer, because we have a product for HR organizations. That's from a business perspective. How about from an engineering or technology perspective? There's this thing in ITSM called a configuration management database. Yeah or CMDB. Yeah. You've got all the data on every IT asset every connection and to an extent, every user or IP address in the company. across the clouds. Yeah. Whether you are using private cloud, you are using one public cloud, you are using multi cloud, you still have assets in all those clouds. You still have physical machines, virtual machines, containers, and others, and our goal is to provide the CEO with that full visibility on: Where are my assets? How are they doing? Are they secure? How important has that been in terms of, let's say you get a... I won't call it getting a monopoly on workflows within the enterprise, but really getting a fix on that so it's easier for someone to add another workflow to ServiceNow than add a third-party workflow. That's. Michael, you bring up a good point. For IT, we are the system of record. We are the system of record, and that allows us to be system of record because we have the asset repository, as in configuration management database. Then the same principles, because one of the other things we have done, every single product that we have created in ServiceNow's history has been built on the same platform. When a customer, say, a large corporation in financial services, is using us for ITSM and they want to use us for HR, they literally go to the platform and turn on the HR functionality, and all the similar mechanics of request management, case management, and others work in the exact same way. We are very unique that even with end of the year, $8 billion+ subscription revenue, we have done all of our products on the same platform. Can you keep going? In other words, can you keep going with just this platform, or sooner or later, would you need something to attach to it? Yeah, I get asked that question, Michael, every single time by our customers as well as our investors. Coming back to your Fred story, I fundamentally believe on behalf of ServiceNow, that we can continue to build additional products where we see that workflow provides value to the customer, and this platform can still keep going. We started our, what we call originally ERP workflow, but it's mainly for the office of CFO in finance and procurement. We started that product last year. The pipeline built so fast because it was workflow that works with the system of record like an SAP, and you can just say SAP. SAP has ECC, which is still alive in many corporations. They have, of course, S/4HANA, but SAP has a lot of other products like Ariba, Concur, and so on, and we work with all of them, right? So we are the system of action on top of the system of record, and there is so much work we can do for that particular stakeholder, as in the CFO or Head of Procurement or Head of Supply Chain, that we believe that we are just getting started on that specific workflow, and we can continue to build. Yeah, I mean, first of all, I was gonna ask you, it begs the question at this point, if you're moving into ERP, you say ERP, and we think SAP, and we think Oracle. Oracle. -at this point. we were just talking HR a minute ago. You think HR, and you're gonna think Workday and arguably Oracle- Yeah ... SAP as well. You talked about customer service management, we're gonna think about Salesforce, et cetera. I think you're in a great position to talk about this because you've been at other large enterprise software companies. You've been at Symantec, you've been at Oracle, you've been at EMC. Let's make sure we understand how you fit in. How do you fit in doing HR relative to a Workday, customer service relative to a Salesforce, or as you were pointing out, ERP relative to an SAP? Yeah. This question comes up all the time because when we go and do our work- You make me feel like I don't come up with anything original. I'm sorry. Yeah. No, no, no. When we go and talk to our customers, let's just say a large healthcare company, and we say, "We do HR," their first question is: "Hey, I already have an HCM, one of the flavors that you described." They are like: "CJ, so are you saying we have to replace that?" I said, "Absolutely not," right? This just happened last week with a very large pharmaceutical company. What we do is a system of action on top of HCM. Let me make it very specific. The system of action on top of HCM is when an employee joins this healthcare company, they are a life sciences company. When an employee joins this life sciences company, you have a checklist that is specific to HR, which HCM will do, right? Hey, we need to fill out the I-9 form. We need to do this, do that, get the passport," et cetera, et cetera, identification. Then you have to provision IT credentials for that employee. You have to provision security credentials for that employee. You may have to do badging for that employee. You have to say, "Here is the facility location that this employee will sit in," whether it's hybrid or the person working in the office. All those are workflows, and HCM does not provide those workflow. Once we explain that simply, in a second, they're like, "Ah, I got it. I still need my HCM, which is my people directory. I do performance management, talent management." When it's workflow across the enterprise, that's what you do. Maybe we should have not called it HR product, and maybe we should have called it employee product, so we avoid this confusion. That's a few hundred million dollar business now for us, we just started 5 years ago, because it's an and. You need an HCM, and you need ServiceNow. Actually, some of our largest customers are some of those HCM providers, like Oracle, that work alongside of ServiceNow. One last thing on customer service. Customer service, we say that when a customer requests something. I'll just take an example of a bank. I'm changing my location, and I said, "Here is my new address, from my current address to the new address." I told that to the bank, and the bank's customer service representative said, "Hey, CJ, that's gonna take you 10 to 12 days before our records reflect that." I said, "10 to 12 days, why?" They say, "Well, you have an account with us on the asset management side, you have an account with us on credit card," this, that. "Those are all different systems, and we will need to upgrade your address in 57 different systems before we say, 'Now, CJ, this is new address.'" What ServiceNow did for customer service is the workflows that are mid-office and back-office workflows, not just the engagement layer, and that's how we created a business. You know, Michael, you have known all of our CEOs in the past, and Frank Slootman was still very reluctant to say, "Should we go after this particular space?" Because there are incumbents, as you mentioned, "And should we go after that space?" We all said, "Yes, absolutely," because there are a lot of workflows that happen after a customer makes a request to change the address. Now, that business is doing very, very well for ServiceNow. There are 1 million other things I could ask you about ServiceNow in general, because it's a fascinating company that I've been, you know, associated with in one way or another for a long time. I'm gonna use you to speak about the generative AI topic. Okay. You know, for me, I mean, We're all talking about this lots. We started with a keynote yesterday morning by our Mosaic group, who had a number of consultants and technical practitioners of generative AI and AI in general. Then I hosted a panel yesterday here on investing in AI, mostly VCs, but also some crossover investors. So now I'm going to get your enterprise company view of it, both how you view the overall landscape, and then what you guys are doing in particular. I'm gonna start out with the most general of questions, which is really, at this point, we all know we've been doing AI/ML for years. What is the difference? What's different in what happened since November of 2022 with the general availability of ChatGPT? In what sense is Generative AI different than AI as we've known it? Yeah. I would say, even ServiceNow has been on the AI roadmap since 2017. That's when we first did a technology tuck-in of a company that did supervised machine learning, and we said: How can we make that part of ITSM on our platform stack, initially for ITSM customers? We have been going through the supervised machine learning, deep learning evolution over time. For us, when we looked at, you know, 2022 and announcement around ChatGPT 3.5 Plus, what was clear is machine's ability to understand natural language and provide a response back in natural language. We saw massive improvement compared to previous NLP technologies. That's it, literally. Machines can understand that when I type in something, it actually understands that question, and then it carries forward that context, right? Since you are from New York, if New York Knicks are playing, and you say, "Okay, who won the game?" It'll say, "Okay, Knicks won the game," and say, "Who was the lead scorer?" It knows that that's in the context of New York Knicks, and you can keep on going in that context, in that game. That never happened before, right? That's right. You had to do one at a time what you ask of machine. This, basically, the aha moment or the inflection moment, that AI technology's working, where you can communicate with machine in a natural language, and machine will respond back and carries forward the context like a human does. We said, "Okay, this is really good. Now let's figure out how it can be applicable to ServiceNow use cases." ServiceNow has employee-facing use cases, some of them I touched on, customer-facing use cases, partner-facing or supplier-facing use cases, and we can leverage this capability. You can compute, compute fast. The response comes pretty good, accurate 70%, 80%, 85%, 90% of the time, and that's why it was a true inflection moment, in terms of just AI technology compared to the past. I'm gonna stick with some very big picture questions. What do you think will be the biggest this is a completely open-ended question, but what do you think this, the biggest impact will be on the way that we all do business because of this? I would say, at the highest level, You know, there are terms that have been in the industry now, whether it's a copilot, this, that, so on, but I think that the level of assistance that machines provide to human has gone to the next level, and I think that's the biggest productivity gain for any type of user, even if you are a marketing human being. I'll tell you, at ServiceNow, our CIO, he's amazing, he tried for our inside sales team, they were writing emails when they reach out to our customers. He said, "Now, can I use generative AI so that they can write these emails faster?" He saw that they were able to write emails faster, and when we sent to our customers, customers could not tell if that email came from a human or that email came from gen AI. When I think about the impact it is having, it is just making humans do their job better in a variety of industries, broad brush speaking. We'll have to just look for, based on the use case, what are the error rates, meaning hallucination rates or accuracy rate is number 1. Second thing, in certain industry, like, you would not want an HR department use generative AI, and if there is an HR case when an investigation is going on, generative AI makes a decision that this particular employee's employment should be terminated. There will be. You will need explainability on how that decision was made, and you will still need human in the loop. I think this is an augmentation of human getting work done at a much faster pace, depending on certain tasks. I'd like to drill down a little bit on some of the more technical or infrastructural, infrastructure-related things that you're doing, in order to enable gen AI. It's been striking in terms of some of the press releases that you've put out, the partnerships that you've had. You're not, you're not only announcing SKUs, capabilities, but you're talking about and working with the industry to develop, I would say, all the way down the stack. I'm gonna, I'm gonna ask you about that infrastructure layer. For example, w- what are you doing from a large language model perspective, whether it's, you know, the simple thing to say, "Okay, we're using OpenAI. We're using Azure OpenAI services"? Are you just using those models? Are you developing your own LLMs? How are you going about it? Right. We were very fortunate, and I want to say fortunate rather than saying we had the foresight, is in 2020- You, you can take credit for that. That's okay. In 2020, we were able to welcome this amazing Canadian company called Element AI. Element AI, I'm just gonna round it off, had close to 200 amazing people, lots of PhDs. Yoshua Bengio, who is a Turing Award winner and wrote the seminal paper on LLM, became part of ServiceNow. The researchers from the Mila Lab and many others, they became part of ServiceNow. At that point in time, I still remember my conversation with Bill. I said, "Bill, somebody reached out to us. These are great engineers, data scientists, and researchers in Canada." Love Canada. "We want them to become part of ServiceNow. They have no revenue," so this was a people acquisition at 0 revenue. It's a people acquisition, and they will help us accelerate our AI roadmap. Michael, to answer the question, we consider, you know, they have been working on ChatGPT 2.0, and you talked about 2022. In 2021, at our November offsite in San Francisco, they came, the researchers came and showed me a demo of text-to-code. They said, "CJ, for ServiceNow-specific code, you can type in something, top 20 IT incidents that happened with severity 1," and it spit out the ServiceNow code in seconds. I literally thought that was science fiction. I'm like, "Ah, this can't be true. This seems too science-y," and so on. We are very fortunate that we have critical mass of researchers, data scientists, and engineers. Because right now, if you wanna go and hire 1 at a time, good luck to do that. That's 1, because you need people. You need people for AI, then you need the platform in which you can build in. We are absolutely building our own LLMs. We have already built them, because hundreds of billions of parameters on OpenAI. Just out of curiosity, do you start with open-source models, or? Yeah, we, we did partnership with Hugging Face. Right, that's what I was gonna ask you about. Our design principle was pretty simple. We said, "Hey, there is no way ServiceNow will run a 175 billion parameters model in our own cloud." We just can't. We can't send our customers' data, because it's our customers' data that's in ServiceNow Cloud, to OpenAI. Because when customer signs with ServiceNow, there is a trust that will protect the privacy of that data, not commingle data. It's a multi-instance architecture, because you asked the infrastructure question. Our design principle was, we want smaller models that can run on a single GPU, and can we do that? That's what our research team worked with Hugging Face, and first created a model for text-to-code or text-to-workflow. This model on text-to-code, because we are ServiceNow, we know how the ServiceNow code should be written. All the code that our engineers have written, including Fred's code, we trained that model, which is 1/10 the size of OpenAI model and is 40% more accurate. Now imagine a software engineer on ServiceNow at a large telecommunications company trying to write ServiceNow code. This will act as a copilot and help you write an accurate ServiceNow code. If you write that code with OpenAI, it will be inaccurate, because OpenAI absorbed the entire internet. It doesn't know which one is the right code versus the wrong code. so do you use OpenAI as well, and then you use your, your own LLMs also? or is it primarily yours? Primarily ours, because we want to run it. We want our customers' data to be in our cloud. If customer comes and says, "CJ, we want to use OpenAI, or we want to use Google's LLM," whichever, we will give them that choice. That is their choice. We say for ITSM or for customer service management, here is our large language model. It runs in ServiceNow Cloud. Your data will not leave the cloud premises. You have the privacy, and that's it. Okay. Yes, our own LLM is our strategy, and going forward, and without this team, we could have never done it. I just. Again, because I've been impressed by how much you've been doing in terms of infrastructure and how you've also made that a way visible to us. You have this, this, this partnership, this project called the BigCode project, right? Yeah. Have this StarCoder LLM. Yeah. We've seen this, and this is with Hugging Face... That's it. ... very well known in the industry. Yeah. Just talk a little bit about that. Yeah, I mean, we like the open-source models, and when you have open-source models, then you can train them on specific use cases, and those are great teams to work with. We collaborate well, and then based on use cases, we are spitting out LLMs per use case. LLM for ITSM, specific use case one, LLM for text-to-code. We will also do... We are a workflow company, so LLM for text-to-workflow, and a lot of that functionality is coming out in our September release, and this will run in ServiceNow data center because they are smaller models on NVIDIA GPUs. Jensen, to his credit, because as all of you know, that, you know, he worked very closely on the original ImageNet and all of that. When we acquired this company in Canada, he was the first one to reach out and say, "You got great machine learning talent. Let's work together, and I will provide you with the right, you know, the DGX product line, so that you can research better on LLMs. We are very proud of that partnership. Our engineers work hand in hand between NVIDIA and ServiceNow. You know, even last week, I was in New York, Michael, and talked to some of the largest banks and a couple of healthcare companies, and they all said. NVIDIA and ServiceNow partnering together also gave us a lot of credibility in terms of what we are solving for, for our customers. On almost every conference call these days, people talk about what they're doing with Generative AI. Yes. They say, "And so, how do you plan to monetize generative AI? Yeah. You, you have talked about, at, you did announce recently. At length. Excuse me. Yeah. At length. At length. Yes. To talk about, you did announce, your Pro Plus premium SKU. Yeah. Can you talk about what that is, and how it adds to the existing Pro and Enterprise SKUs? We'll go from there. Let's start with that. Okay. ServiceNow biggest product line is ITSM, followed by ITOM, customer service management, HR. Those are, like, top 4 product lines that we have by revenue, okay? By customer base, and so on. In 2018, September, we released our Pro SKUs. Pro SKUs had 50% uplift, and Pro SKUs had a lot of functionality, some AI functionality, some analytics functionality, some other functionality that were part of our Pro SKU based on the product line. We said on the list price, it was a 50% uplift, okay? List price, it was 50% uplift. It has now been close to 5 years. We were able to recognize 25% uplift, which is pretty good, with all the enterprise discounts and so on, we have large customers. Not only we have been able to get 25% uplift, the seat count went up by 10% over the last five years. There have been too many questions asked by our investors and customers: "Hey, will this cause seat compression?" and this and that. Why did the seat count go up? Pretty simple. As companies are digitizing more, they have more tickets or more incidents that happen with their digital assets, so that volume is so high that they need more ServiceNow licenses to just fulfil those requests. I said, "Okay, you think about the simple framework of P times Q times R," I know, Michael- By the way, we started with P times Q. You added R at the end. I added R because this 10% was a very important point, that the rate of growth in seats you can now monitor by calling it 10%, assuming Q or P, however you want to do it. That's our history with ITSM Pro. With generative AI, by us creating the large language models, that will add to productivity gains for our customers by use cases. For that, we believe in certain use cases, the productivity gains are meaningful, that we created Pro Plus SKU because that's very specific to gen AI, the LLMs running in ServiceNow data centers or our cloud. Then, after discount, they will give us whatever the discount is, but the price we are charging based on our equation of the value our customers will get for those use cases. Okay. That we have... I think we are targeting, I think we talked about it, a little bit more than on the original Pro SKU? 60% more. 60%, right? 60% is the price uplift on top of Pro. Okay. One of the things that you talked about in the earnings call I thought was really interesting, was the assessment of value that you were seeing in your beta customers. Yeah. This isn't just a SKU. You've had this out, it's been in beta, some of your customers are using it. That's correct. You've said, "Look, we'll charge more, but there's value there. Yeah. That's why the. Yeah, I always said, Michael, if you remember our Q1 earnings call, which you were on, that we will charge price based on the value our customers will get. We are not going to charge- You laid that out for us. Yeah. Can you talk about that process of, of how you looked at, at what your the value your customers were getting out of it? Yeah. When we ran GitHub Copilot, right? We bought somebody else's generative AI product. Our head of engineering, Pat Casey, our CTO, he ran full control experiment on how much productivity we gain through GitHub Copilot for our engineers, right? That way, we can justify how much we pay Microsoft. How much you pay. Flip that. For us, we said, "Okay, you use the Pro Plus SKU, Ms. Customer, and this 100 users will not use Pro Plus SKU." Whether you call that control experiment, A/B testing, and then the tasks that benefit with Pro Plus SKU, how much productivity gain you get, and then those tasks make up what percent of your work week, right? Because you can say that, "Hey, this task with generative AI is 30% more productive." Okay, that's great, but then you are only spending 10% of your work week on that task. Based on that, we did a proper analysis of our own, ServiceNow's own IT team, ServiceNow's own customer support team, literally side by side. You're using generative AI, you're not, you're getting false positive, how much time you waste on a false positive. We said, "Okay, the productivity improvement could be single digits." If it is in single digits, so let's just take 5% productivity improvement, average cost of that particular job function is, say, $100,000. That's a $5,000 value per year based on all this math of staircasing, at detail level, so that's $5,000 value. Would you be willing to give ServiceNow $500 a year, and you keep the $4,500? That's it. More value accruing to the customer. 90/10 is our rule that we would like to. Now we have to prove by customer, by industry, as we... These kind of conversations are complex conversation, but we have to do outcome-based selling on Pro Plus. I guess the point is, if you're, if you're gonna go out and seek a 60% uplift, maybe end up with half of that in terms of yield... Yeah ... your, your view is that you've-