[OC] I built a semantic framework for LLMs — no code, no tools, just language.

Hi everyone — I’m Vincent from Hong Kong. I’m here to introduce a framework I’ve been building called SLS — the Semantic Logic System.

It’s not a prompt trick. It’s not a jailbreak. It’s a language-native operating system for LLMs — built entirely through structured prompting.

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What does that mean?

SLS lets you write prompts that act like logic circuits. You can define how a model behaves, remembers, and responds — not by coding, but by structuring your words.

It’s built on five core modules:

• Meta Prompt Layering (MPL) — prompts stacked into semantic layers • Semantic Directive Prompting (SDP) — use language to assign roles, behavior, and constraints • Intent Layer Structuring (ILS) — guide the model through intention instead of command • Semantic Snapshot Systems — store & restore internal states using natural language • Symbolic Semantic Rhythm — keep tone and logic stable across outputs 

You don’t need an API. You don’t need memory functions. You just need to write clearly.

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What makes this different?

Most prompt engineering is task-based. SLS is architecture-based. It’s not about “what” the model says. It’s about how it thinks while saying it.

This isn’t a set of templates — it’s a framework. Once you know how to structure it, you can build recursive logic, agent-like systems, and modular reasoning — entirely inside the model.

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And here’s the wild part:

I don’t define how it’s used. You do. If you can write the structure, the model can understand it and make it work. That’s what SLS unlocks: semantic programmability — behavior through meaning, not code.

This system doesn’t need tools. It doesn’t need me. It only needs language.

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They explain everything — modules, structures, design logic. Everything was built inside GPT-4o — no plugins, no coding, just recursion and design.

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Why I’m sharing this now

Because language is the most powerful interface we have. And SLS is built to scale. If you care about modular agents, recursive cognition, or future AI logic layers — come build with me.

From Hong Kong — This is just the beginning.

— Vincent Chong Architect of SLS Open for collaboration

——- Want to explore it?

I’ve published two full white papers — both hash-verified and open access:

————- Sls 1.0 :GitHub – Documentation + Modules: https://github.com/chonghin33/semantic-logic-system-1.0

OSF – Registered Release + Hash Verification: https://osf.io/9gtdf/ ————— LCM v1.13 GitHub: https://github.com/chonghin33/lcm-1.13-whitepaper

OSF DOI (hash-sealed): https://doi.org/10.17605/OSF.IO/4FEAZ ——————