Prompt Bloat

Problem

Past a few thousand tokens, the prompt starts to squeeze retrieved context and tool definitions out of the model's attention budget, prompt-cache reuse degrades because every small edit changes the cached prefix, and instructions that were added at different times begin to contradict each other. The model resolves the contradictions inconsistently, so newer rules silently override older ones for some inputs and not others. This is distinct from a hero agent, which is about scope; this is about the accretion process itself, where the prompt is treated as append-only documentation rather than as code.

Solution

Don't. Treat the prompt as code: PR review, eval gate on length, quarterly pruning sprints. Lift recurring procedures into agent-skills. Move stable rules into a constitutional charter.

When to use

• Never use this; treat unbounded prompt growth as a process failure.
• Use prompt-versioning and eval-gates on length to keep prompts in budget.
• Lift recurring procedures into agent-skills and stable rules into a constitutional charter.