1 link tagged with all of: llm-optimization + agent-behavior + prompt-engineering + code-structure
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Most prompts degrade into contradictory messes because teams keep adding to them without removing anything, causing real performance hits. Treating prompts like code—structured, modular, and maintained—can unlock 30-50% improvements in speed, retention, and costs.
- Prompts grow through accretion without review, creating contradictions and hidden ambiguities that agents can't resolve; one startup cut LLM spend by $20M/year just by removing duplication
- Prompt decisions are product decisions—agent behavior shapes user experience directly, so vague specifications like "never mention competitors" fail because they lack concrete rules
- MECE structure (mutually exclusive, collectively exhaustive sections) eliminates overlap and makes prompts maintainable like modular code; separate concerns into context, behavior, and output sections