The battle in AI is shaping up to be a battle for context. Everything in AI is about making sure that agents are effective as possible. That effectiveness comes down to whether the agent has the right domain expertise, access to the right context and tools to work with, and are involved in workflow in a way that users can easily interact with, review its work, and incorporate it into the rest of the process. As a consequence, the platforms that are able to capture and leverage the best and most context within their agents —and be able to pick the right models for the task- will be the place where agents do their best work. You can just look at coding agents, legal agents, or support agents as examples of what this looks like at scale. This is why the applied AI layer has a lot more value than just being an LLM wrapper. The ability to organize the critical knowledge for the work being done, and maintain this knowledge in a governed way where only the right people and agents have access, and the ability to improve the context for agents more and more over time, is critical. Over time, this layer will be able to route work between a variety of models, leveraging frontier intelligence for planning and orchestration and review, and a mix of lower cost models (open or closed) for the large volume of work between these tasks. The applied layer is also in a good position to train and develop its own models as well that are purpose built for their domains. Never good to bet against the bitter lesson, but equally taking a near frontier base model and post training it for just one type of domain work can -in many cases- lower costs or deliver better performance for certain tasks. Finally, this applied layer is also where most of the change management of the workflow will need to occur. This is why FDEs are so important at the applied layer, because this is the point where the customer needs to have specific business problem solved by a particular vendor. Whichever companies can solve that completely in an end-to-end fashion will have the greatest moats. As each day goes on, we’re learning more about what the likely long term market dynamics will look like in AI.