AI & Computingarticle2026-09-03

HOW TO PRODUCE ORIGINAL SCIENTIFIC ARTICLES AT THE CUTTING EDGE OF KNOWLEDGE USING THE ALGUILAS METHOD? THE ALGUILAS PROMPT PACK READY TO RUN.

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Abstract

How to use this pack (Beta Version) Option 1: Upload this file to an AI agent – preferably as part of a new project within the agent – and request that the Alguilas Method be run. The rest will proceed as normal. In other IAs: After generating a Word file containing the paper, use other AI systems (ideally more than three) to critique the paper using the following prompt: ‘Analyze the paper’s originality, coherence, impact and ranking. Identify significant areas for improvement. Independently simulate a peer review. Provide a brief summary.’ Paste everything into a Word document. Ask the first AI that generated the text to review this Word document and update the original paper. Repeat these steps several times until the improvements become insignificant. Always review the paper yourself and suggest new questions based on your own experience and instinct (this is the most important part). Option 2: Seven prompts. Copy each one into your assistant when you reach that stage, replacing the bracketed placeholders. You do not need to have read the Statement first; each prompt carries what it needs. Prompts 1, 2, 4, 5, 6 and 7 go to the system you are producing with. Prompt 3 goes to a different system — a different model family, not a new conversation with the same one. That is the one step that cannot be delegated to the producing system, and it is item C8, the most load-bearing gate in the standard. Two things stay with you and are not delegable: · Verifying every citation against the primary source. Assistants generate references that look correct and are not. No prompt fixes this. · Declaring status honestly. Only you know whether the external criteria were actually met. Frontier sections are marked. If your paper does not assert novelty, priority, or the discovery of a gap, delete them and run the Core alone. Most work does not need them.

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View paper (DOI)Open access versionOpenAlexZenodo (CERN European Organization for Nuclear Research)Published 2026-09-03

Authors: José Caetano de Mattos