Prompt Engineering

Budget LLM Context Windows Without Losing Critical Instructions

Large-language-model applications rarely fail because a prompt is one token too long. They fail because context growth is handled without priorities. Chat history expands, retrieval returns more passages, tool results become verbose, and eventually the application truncates whichever text happens to be easiest to cut. A safer design treats the context window as a budget with explicit allocations. The goal is not to fill every available token. The goal is to preserve the information that controls behavior while leaving enough room for a complete answer.