Upgrade

This document outlines the highest-value upgrades for making this SmallLanguageModel stack much more intelligent, reliable, and useful in real work.

Upgrade Plan

This document outlines the highest-value upgrades for making this SmallLanguageModel stack much more intelligent, reliable, and useful in real work.

1. Core Principle

The smartest version of this system will likely be a hybrid system, not just a standalone tiny generator.

A. Retrieval Intelligence

Current retrieval is lexical and rule-boosted. That is good, but it can become much stronger.

B. Structured Data Reasoning

A lot of intelligence will come from understanding JSON, metadata, records, and schemas well.

C. Reasoning Pipeline

The system should move beyond one-shot retrieve-and-answer.

D. Long-Term Memory and Knowledge Graphs

Right now the system is document-grounded, but not relationship-aware enough.

E. Better Training Data Design

The model needs better data structure, not only more data volume.

F. Evaluation and Benchmarks

Without evaluation, upgrades will drift and regress.

G. Better Model Architecture

The current tiny transformer is a good base, but smarter local behavior may need architectural upgrades.

H. Domain Adapters

The smartest system will answer differently depending on domain.

I. Tool Use and Execution

Long-term, the system should not only answer from docs. It should also know when to inspect local artifacts directly.

J. Conversation Quality

The assistant should become more stable across multi-turn conversations.