I’ve been experimenting with a logic-first approach to prompting, moving away from the typical ‘persona-based’ instructions. As a structural contractor, I’ve tried to apply structural integrity principles to how we weigh tokens. The Concept: Instead of asking the AI to ‘be professional,’ I’m testing a Structural Tension Matrix . This involves using a specific ‘Sovereign Vocabulary’ designed to act as high-weight anchors in the transformer’s attention mechanism. Why I’m posting here: My previous attempts at explaining this were met with skepticism (and rightly so, as it sounded like jargon). I want a technical critique on the LNFZ Protocol (Logic-Normal-Form-Zero). It’s an execution schema focused on killing AI fillers by enforcing ‘forensic’ constraints on the output structure. The Metrics: In my recent builds, this approach reduced ‘conversational slop’ by roughly 40% while maintaining high density in technical tasks. However, it fails in creative/poetic contexts where ‘fluff’ is actually a feature. The Document: I’ve drafted a 2-page technical blueprint of this schema. For the sake of Rule 3, I am the author. No pricing talk here—I just want to know if this community thinks ‘Structural Logic’ is a valid path or if LLMs are fundamentally too probabilistic for this kind of rigidity. You can access the full technical blueprint and the schema here: https://gum.co/u/15stqino submitted by /u/HDvideoNature
Originally posted by u/HDvideoNature on r/ArtificialInteligence