Research Report 6.2: Hybrid Architectures
Your LLM can write poetry but can't reliably add two numbers - hybrid architectures solve this by routing each subtask to the system that actually handles it well
Research into the architectural patterns for integrating LLMs with traditional algorithms and deterministic systems - covering serial, parallel, hierarchical, and event-driven integration patterns alongside handoff mechanisms, routing logic, caching strategies, and the performance tradeoffs of hybrid intelligent systems.
Also connected to
The agent that gives every other GSD agent the context it needs to write correct code
Documentation for a job automation engine that bridges personal knowledge systems with external services through OAuth integrations and event-driven architecture.
The CLAUDE.md that powers a production hybrid routing system - complexity-based scoring from 1-10, automatic model selection across four tiers (local Qwen through cloud Opus), contextual RAG embeddings that improve retrieval by 5-10%, and the architecture that achieves 95-99% cost savings versus all-cloud
A production-grade routing system that cuts LLM costs by 95-99% - complexity scoring routes simple queries to free local Ollama models while sending complex reasoning to Claude, with RAG semantic search, real-time monitoring, and 10 MCP tools for Claude Desktop integration
The complete guide to running local LLMs on an RTX 5070 with 12GB VRAM - model recommendations by task type, inference engine comparisons, quantization strategies, Claude Code integration patterns, and the multi-model architecture that handles everything from free coding assistance to privacy-first document processing