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What we've done is created a blueprint, a framework for digital modernization, digital transformation. And depending upon the journey that a customer or a partner is on, we use that as a frankly, a way in which we we engage, meet people where they are and think through kind of the strategy, the roadmap, and activate within within more of a factory style approach and delivery model with the right people, with the right set of key performance indicators, holding the team accountable with more SLOs, service level objectives and outcomes that we want to make sure that we're being able to deliver far more purposeful and valuable solution. They may be looking to modernize the system, but it's never a system only approach. They look at things holistically. They understand what are the needs of the users, they understand what are the needs of the mission, and they create holistic solutions that look across all of these dimensions. What are the needs of the people? What are the needs of the system? What are the constraints? What are the cultural changes that need to happen in order to enable the types of modernizations needed to meet the mission of the future? You know the way in which we think about the success is: How do you bring folks together? How do you engage in a more purposeful kind of alignment of those priorities? And how do you make sure that you're bringing the team along to that effect? I mean, for me, Pathfinding is about creating consensus. Right? There's sort of the old proverb, if you have if you have a giant elephant in front of you and everybody is looking or touching or feeling a different part of that elephant, they all the different perception of what it is that they're looking at, right? So with we build journey maps, we build ecosystems, maps. When we build do pathfinding, it's about how do you bring all these different people, different valid perspectives into the same environment and let's lay out that whole map. Let's lay out the whole experience and create consensus around not only what is the state of the state, Where do we see the most opportunity for growth and where do we see the most opportunity for change? And then can we align on sort of a common operating picture of what needs to be addressed and then I think when you half of the challenge and in my experience and modernization and design is really building momentum and getting consensus, getting both the end user as well as sort of that key policy decision maker aligned on what needs to happen. And when you have that that magic right. And that's where you can really push your strategy forward. There is a there's a designer that I like, her name is Jacinda Walker, and she kind of has this thing she says where she says, what can't be measured, can't be managed. So I think managing, measuring the experience and measuring the impact and knowing then how to manage that is critical. And so we do that both in a quantitative as well as a qualitative way. Quantitatively we're using traditional usability measurement, right? So it's, you know, fundamentally it's did the thing work, yes or no? Did it work the way we thought it would? And did the end user, were they satisfied with how it worked? Right? And so there's ways both that a qualitative and quantitative way we can create really kind of empirically standardized tools to measure those variables. I think the other thing that we've seen happen over supporting multiple, you know, grand scale modernization efforts is we're not only supporting a single team, we're supporting multiple teams oftentimes distributed that really has that need for a software factory infrastructure platform tooling approach to really help accelerate the development of those capabilities at the speed of need as artificial intelligence becomes more available and as as problems can be solved with artificial intelligence, organizations are going to need different types of data and they're going to need to label that data much, much more rapidly. The notion is if we're shifting this product mindset, you know, it's not just the software itself, but treating the data as a product, right, as you kind of alluded to it. And that comes with not just the understanding, the leading edge, the risks, how people intend or might use it, and being making data available in a secure or reliable way. But when there are issues with the data, how do we react? And and have kind of plan teams to be able to correct that such that we're focused on data quality as a priority to deliver those KPIs and key service level objectives that are required, especially of a mission critical mission, essential set of capabilities that are needed to.