Yaqui Ramos AI

  In the AI marketplace ecosystem, the difference between a generic prompt and a successful "Agent Skill" lies in the structure. After analyzing my trajectory on PromptBase and optimizing my own assets, I have consolidated a methodology that guarantees precise, professional results for the end-user. ​Core Design Principles ​ Exclude variables in the body: A professional Agent Skill must be self-contained. The user should not waste time editing the prompt; the AI must be configured to extract the necessary information on its own. ​ Prioritize readability: Visual structure is key. Information must always be presented using clear lists, avoiding tables that can fragment the response on mobile interfaces or fast-paced chat sessions. ​ Focus on utility: Every line of the prompt must have a direct purpose that solves a specific problem (SOPs, document analysis, code generation, etc.). ​The 3-Layer Architecture for Agents ​To build agents that truly work, I always apply t...

  Have you ever set up an automation, only to realize that the AI controlling it ignores half of your instructions or invents procedures that don't exist? It is frustrating. We have moved from the era of "clicking" to the era of "delegating," but the reality is that delegating to a language model without a solid structure is a recipe for operational chaos. <!-- Google tag (gtag.js) --> <script async src="https://www.googletagmanager.com/gtag/js?id=G-DBZBQJCPJ0"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-DBZBQJCPJ0'); </script> ​In my automation projects, from n8n pipelines to custom Google Apps Script solutions, I have learned a fundamental lesson: AI is only as good as the prompt architecture that drives it. ​The 3 Pillars of an Industrial Agent ​If you want your automation to do m...