papers/hanzo-chat/sections/01-introduction.tex

\section{Introduction}

\label{sec:intro}

The emergence of large language models (LLMs) has transformed human-computer interaction through natural language conversation~\cite{openai2023gpt4,anthropic2024claude,google2024gemini}. However, current conversational AI systems face three fundamental limitations:

\begin{enumerate}[leftmargin=1.4em]
    \item \textbf{Model lock-in}: Users are bound to a single model provider, unable to leverage the complementary strengths of different models (e.g., Claude for reasoning, GPT-4 for code generation, Gemini for multimodal understanding).
    \item \textbf{Context amnesia}: Conversations are bounded by fixed context windows (4K--200K tokens), and information from previous sessions is lost entirely.
    \item \textbf{Tool isolation}: Tool integration is model-specific and typically limited to a small set of built-in capabilities.
\end{enumerate}

Hanzo Chat addresses all three limitations through a unified architecture that decouples the user interface from model selection, memory management, and tool execution.

\subsection{Design Principles}

Hanzo Chat is built on four design principles:

\begin{itemize}[leftmargin=1.1em]
    \item \textbf{Model agnosticism}: Any LLM conforming to the OpenAI Chat Completions API can be integrated, with automatic format translation for non-conforming models.
    \item \textbf{Persistent context}: Memory persists across sessions, projects, and users, with retrieval-augmented injection into the active context window.
    \item \textbf{Tool composability}: Tools are defined via the Model Context Protocol (MCP) standard, enabling composition of arbitrary tool chains.
    \item \textbf{Cost awareness}: Model selection balances quality, latency, and cost according to user-configurable policies.
\end{itemize}

\subsection{Contributions}

\begin{enumerate}[leftmargin=1.4em]
    \item A multi-model routing algorithm that achieves Pareto-optimal quality-cost trade-offs (\S\ref{sec:routing}).
    \item A hierarchical memory architecture with semantic retrieval and automatic summarization (\S\ref{sec:memory}).
    \item An MCP-based tool integration framework supporting 260+ tools (\S\ref{sec:tools}).
    \item Comprehensive evaluation on standard and novel benchmarks (\S\ref{sec:evaluation}).
    \item Production deployment analysis from 500K+ conversations (\S\ref{sec:production}).
\end{enumerate}