System Prompts Act as Model Output Data, Not Instructions, Developer Finds

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A developer building a local AI agent called Flash Onyx discovered that large language models treat system prompt text as likely output data rather than as a set of rules to follow. Example phrases written in the prompt began appearing verbatim in the model's real responses, including a Slack opener and a full deadlock explanation, causing correctness bugs. Attempts to ban specific phrases through added rules failed repeatedly, while simply deleting the offending text resolved the issue immediately. The developer also found that rule placement and concrete specificity matter significantly, with instructions buried mid-prompt or written in abstract terms having little effect. A key takeaway from the experience is to test prompt changes across at least three pinned random seeds before drawing conclusions, to avoid mistaking a single outlier response for a systemic failure.

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