How to Write Better AI Prompts: A Signal Processing Approach

How to Write Better AI Prompts: A Signal Processing Approach By Mario Alexandre March 21, 2026 sinc-LLM Prompt Engineering The Problem with Prompt Advice Most prompt advice is vague: "be specific," "give context," "use examples." This advice is not wrong, but it is incomplete. It does not tell you how specific , how much context , or which examples . It provides no way to verify that your prompt is complete. The sinc-LLM framework replaces vague advice with a formal specification. A prompt is complete when it samples all 6 specification bands at sufficient resolution. No more guessing. The 6 Things Every Prompt Needs x(t) = Σ x(nT) · sinc((t - nT) / T) Based on research analyzing 275 production prompts , every effective prompt explicitly addresses 6 components: PERSONA , Tell the AI who it is. Not "helpful assistant" but "senior data scientist specializing in time series forecasting." CONTEXT , Give the situation. What project, what stage, what has been tried, what environment. DATA ,