AI-Assisted Engineering Workspace & Brain Memory Vault

01. The Challenge & Context Problem

When orchestrating complex data engineering projects with AI coding tools across multiple repositories, long session context windows decay. Architectural decisions get forgotten, code modifications repeat previous work, and progress stalls due to fragmented documentation.

I needed a structured, persistent "Brain Vault" that functions as a single source of truth for all project decisions, session logs, and architectural briefs.

02. System Design & Indexing Architecture

I designed a modular Obsidian workspace architecture backed by Markdown wiki indexing and Obsidian Canvas visual maps.

• Automated Session Logging (sessions/): Chronological logs recording exact code modifications, CLI outputs, and architectural decisions per working session.
• Persistent Memory Index (memory/): Wiki pages defining core project constraints, scope boundaries, and API schemas.
• Architectural Decision Records (decisions/): Formal records documenting technical choices, trade-offs, and rationale.
• Sync Protocol: Standardized verification checklists executed before ending AI pair programming sessions.

03. Workspace Vault Directory Structure

Projects Brain Session /
├── README.md              ← Workspace Navigation & Active Priorities
├── First Brief.md         ← Initial project kickoff brief
├── sessions/              ← YYYY-MM-DD.md live session trajectory logs
├── memory/                ← Persistent context index (whoop.md, physicalstack.md)
├── decisions/             ← Architectural Decision Records (ADR)
├── inbox/                 ← Quick thoughts & pending task dump
└── output/                ← Final production plans & code deliverables

04. Productivity & System Impact

This system enabled seamless multi-project orchestration alongside Claude Code and Antigravity IDE, reducing context initialization overhead from 20 minutes to under 30 seconds per session.