For a while, AI felt like a collection of flashy demos—cool, impressive, but not always useful in practice. That’s starting to change. The latest wave of AI tools isn’t just about what they can do, but how they fit into real workflows.

Claude 3.7 is a prime example. Instead of just answering questions, it adjusts how it thinks based on your needs—quick and snappy when you need speed, methodical when you need depth. Google’s PaliGemma 2 Mix is streamlining visual AI, replacing a mess of specialized tools with one model that can caption, analyze, and even read text in images. And Perplexity’s Deep Research is turning AI into something closer to a true research assistant, capable of sorting through the noise and delivering real insights.

The shift here is subtle but massive: AI isn’t just helping us work faster; it’s starting to change the nature of work itself. Instead of spending time gathering and organizing information, we’ll spend more time deciding what to do with it. Instead of manually optimizing content for SEO, we might soon be optimizing for AI assistants that act as decision-makers for consumers.

That last part is worth thinking about. If AI models are becoming the new gatekeepers—deciding which products, services, and brands to surface—how do we ensure they actually see us?

Let’s get into it.