210 The Aiassisted Development Process Knowledge Chunk Methodology
title: “2.1: The AI-Assisted Development Process & Knowledge Chunk Methodology” tags: [“kb”]
2.1: The AI-Assisted Development Process & Knowledge Chunk Methodology
Summary: This project is a prototype for an AI-human collaborative development process that uses a persistent, structured “Knowledge Base,” composed of “Knowledge Chunks,” to serve as a single source of truth for project context.
Details:
This methodology is built on three core pillars:
- Discrete Agent Entities: The problem-solving process is modeled as a collaboration between a primary “Project Implementation Agent”, which manages the project lifecycle, and a suite of “Mini Project Agents” (e.g., Research Agent, Code Generation Agent) invoked on-demand for specific tasks.
- The Knowledge Base: A persistent, machine-readable repository located in
ai/knowledge_base/chunks/that serves as the single source of truth for all project-specific context. - Knowledge Chunks: These are the currency of the development process. A Knowledge Chunk is a concise, durable, and machine-retrievable unit of synthesized project context, stored as a Markdown file. They serve as the foundational elements for Retrieval-Augmented Generation (RAG), allowing an agent to perform a semantic search over the Knowledge Base to retrieve relevant context, which solves for context loss and enables a scalable workflow.
Key Artifacts:
- The Knowledge Base: The
ai/knowledge_base/chunks/directory. - The Project Implementation Agent: The primary AI agent responsible for managing the project lifecycle.
- The Mini Project Agents: Specialized AI agents that can be invoked on-demand to perform specific tasks.
- The Knowledge Chunk: A concise, durable, and machine-retrievable unit of synthesized project context.