 Here's my very strong view of the world is that we have created very deep, exceptional technical talent in pockets across industry, whether it's on a software company who's developed a platform in its engineering, or at a data analytics firm who've developed deep techniques. The fact of the matter is this though, in the services industry where many of us are working, it's all about how our clients articulate value, and the way they define value is in their business strategies. And so to me, and I've said to my team many times, we have to take all that capability and now contextualize it to industry. So what does that mean? It means large language models and we're all talking about them are great, but they have certain areas where they can deliver superior outcomes. Applying them to every problem like a blunt force object isn't going to work very well. And so understanding that large language models are really great at coordinating lots of data sets that are coming in for the kinds of iterative things we have to do when we're interacting, let's say, in a payable function. The payables helped us. I mean, it may be a very mundane use case, but it's because we understand the work that happens in payables and we understand the technology now that can be applied there. And that to me, that coming together of the convergence is why we believe as a company we're starting with domain and business knowledge. And then we're shifting left to bring in more and more capability from technology and AI and data, as opposed to starting with technology and using it, ad hoc across companies, across industries, etc. It's all about really understanding the strategy of our clients and how we can use technology to accelerate that. And so to me, convergence is the name of the game for the next five years.