Series: AI Isn’t an Engineering Problem Anymore (Part 2) It’s a cost problem—and most teams don’t realize it yet. In the last post, I talked about hitting a usage limit while debugging my robot and realizing how repetitive my own AI usage had become. At the time, it felt like a personal workflow issue. But the more I thought about it, the more it became clear: This isn’t just a “me problem.” It’s a pattern. The illusion of “new” work When we use LLMs, whether through APIs or tools, it feels like every request is new. You type something different. You add more context. You refine your question. But under the hood, a lot of those requests are doing very similar work. For example: debugging the same issue from different angles rewording prompts to get a better answer retrying when output isn’t quite right asking for clarification on something you already asked Each one feels justified. And most of them are. Where inefficiency actually comes from The inefficiency isn’t from using AI too much.…