Using ctx for LLMs
When working with LLMs, the prompt is only part of the problem. The harder part is deciding which context should travel with the request: source files, command output, constraints, previous decisions, and the exact shape of the failure. Most writing about LLMs asks how they make our work more efficient. The more interesting question here is narrower: how do we work more efficiently with the models themselves? In my work, that often means leveraging multiple tools, each with a focused role, rather than treating the LLM as a single chat window that has to hold everything at once. ...