A lot of AI agent workflows are becoming expensive for a very boring reason: We keep giving the agent too much context and not enough direction. The usual pattern looks like this: Here is my whole repo. Here are 12 tools. Here are 9 docs. Here is the bug. Please figure it out. Enter fullscreen mode Exit fullscreen mode Sometimes it works. But it is also how you end up with huge token usage, messy tool calls, slow runs, and an agent that spends half the session rediscovering what a human already knows. More context feels safer. In practice, it often makes the workflow worse. The problem is not context. The problem is unfiltered context. AI agents do need context. They need the right files, the right constraints, the right examples, and the right definition of done. What they do not need is every possible thing that might be relevant. That is where many workflows go wrong. A small task becomes a giant investigation because the agent has no boundary.…