It's clear that we're on a trajectory right now of AI models continuing to improve in capability across math, reasoning, logic, tool calling, and various domain-specific tasks that will get better as more training data continues to get generated. While there will be debates about how much these advancements will show up as major changes in the daily use cases that a consumer has, they *will* have a major impact across many categories of knowledge work. They will incrementally unlock new use-cases in healthcare, legal, financial services, life sciences, etc., where models can reliably perform progressively more critical tasks. On a recent podcast with Alex Kantrowitz, Dario Amodei had a great way of framing this, which is that if you improved the capability of an AI model to go from having an undergrad in biochemistry to a having a graduate degree in biochemistry, a small percentage of the consumer population would notice the impact, but the enterprise use cases for a company like Pfizer would go up meaningfully as a result of this. We should start to anticipate that this is now the era that we are in with AI. So, how does this begin to show up in the real world? It will show up through AI agents going after applied use cases. AI agents for coding, legal work, medical scribes, data extraction, insurance claims processing, pen testing, and so on. The opportunity right now is to build AI agents for verticals and domains with a deep understanding of that space. This is where the impact of context engineering, a deep understanding of the workflows, connections into enterprise data, and specialized user interfaces (that allow users to deploy, manage, and orchestrate these agents) will start to matter a ton. It will also mean building up distribution that aligns to that particular vertical or domain. It will probably mean some form of forward deployed engineering to not only help customers implement the agents, but also quickly learn which workflows the agents are optimized for and bring that back into the core platform. Ultimately, these markets will be won by the players that can best bridge today's enterprise processes (which are often messy and were not designed for automation) to a world where agents are integrated into these workflows. This is the era of AI we are now in.