Deep AI work - by Vikram Sreekanti - The AI Frontier

This is part four in what (we’ve realized) is a series on AI-powered work. Our previous posts in this series covered an introduction to the concept of AI work, the interface between AI and human workers, and the extreme importance of integrations for AI workers. As you’ll see, our thinking is evolving quickly. We don’t have a particular goal for this series, and we’ll keep adding new ideas as we learn.

A couple months ago, we wrote about our framework for thinking about AI-powered products. We won’t repeat the whole post here, but briefly, we believe that AI-powered products should think of themselves as fulfilling job functions (e.g., SDR, software engineer, support agent), and as AI-product builders we should be thoughtful about which job functions we can fulfill and how we check each box. This is what will transform AI from being a novelty technology with great demos to something that changes our economy.

In that post, we highlighted that there was a spectrum emerging between products that are going broad (building frameworks to develop multiple AI workers on a single knowledge base) and products that are going deep (narrowly focused on owning one job function). We discuss the tradeoffs between each approach in depth there, but we concluded by saying that we weren’t sure what the best approach was at the time.

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