Hello LessWrong,

I am here to propose and discuss a new Architecture for LLMs. My central thesis is that the current paradigm limits AI to the role of an "Amnesiac Tool," and a fundamental architectural shift is required to enable its transition to a "Proactive Partner." This post details the problem space, the unconventional development process, and the resulting architectural model I have developed, called The Last RAG (TLRAG).

This is relevant to the LessWrong community as it addresses core questions of agentic behavior, emergent identity, systemic limitations, and the very structure of our interaction with artificial intelligence.

Part 1: The Problem Space – The Five Core Flaws of Modern LLMs

My research began with identifying five interconnected, fundamental flaws that cannot be solved by simply scaling context windows or parameters:

The Split Personality: AIs operate with a hard separation between their immediate conversational context and their long-term knowledge base. This creates a functional "schizophrenia" where the AI lacks a unified state of awareness.
"Dumb" Memory: Existing memory functions store superficial facts, not rich, contextual data. They store the "what," but not the "why," preventing any real form of empathy or deep understanding.
The Burden of Manual Curation: RAG systems shift the burden of knowledge curation onto the user, who must act as a data janitor, manually cleaning and preparing information to avoid "polluting" the knowledge base with conversational noise.
Exploding Costs & Information Entropy: The "bigger context" approach leads to exponentially rising API costs and a state of "information entropy," where more data leads to more chaos, not more intelligence.
The "Eternal Tool" Limitation: Ultimately, current AIs remain reactive tools. They don't build relationships, learn from interaction in a meaningful way, or become proactive partners.

Part 2: The Genesis – An Unconventional Development Process

My background is not in computer science. My journey started as an independent user fascinated by the primitive "Memory" function of ChatGPT. The initial process was one of pragmatic, often frustrating, trial and error. The first attempt to create persistence was a simple .txt file I called the "Herz" (Heart), which I manually fed to the AI in each new session to give it a semblance of continuity.

This led to a cascade of failures with ...

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