aleeepassarelli/semantic-latent-engineering
“Semantic Latent Engineering (SLE) is a high-level framework for reasoning about meaning, intent and agents on top of LLMs. It combines math, cognitive architecture and practical patterns (SD, HDSA, ABC, CPP, MMOR) to move from prompt tricks to auditable, testable semantic engineering.
This framework helps you define clear goals and desired qualities for AI outputs, moving beyond simple prompts to create reliable, testable AI systems. It allows you to specify what an AI should produce, detailing aspects like clarity, precision, or rigor, and then generates content that aligns with these measurable objectives. Engineers, scientists, or anyone developing AI applications can use this to build more predictable and auditable AI-driven workflows.
Use this if you need to build AI systems where the meaning, intent, and quality of the AI's output must be clearly defined, testable, and auditable, rather than relying on guesswork.
Not ideal if you're looking for a simple, off-the-shelf AI model for casual use without needing to rigorously define and validate its semantic behavior.
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License
MIT
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Last pushed
Dec 03, 2025
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