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Project Rules for AI - Part 5 of 6
Part 5 of 6: The AI-Assisted Development Workflow Series
This is the fifth installment in a six-part series exploring how AI is transforming modern development workflows. In this series, I’ll walk through my journey of building an AI-assisted development environment, from basic infrastructure setup to advanced architectural enforcement and task orchestration.
Series Overview:
- Part 1: MCP Servers, Ports, and Sharing - Setting up the foundation
- Part 2: ESLint Configuration Refactoring - Cleaning up tooling with AI
- Part 3: Custom Architectural Rules - Teaching AI to enforce design patterns
- Part 4: Task Orchestration - Managing complex refactoring workflows
- Part 5: Project Rules for AI - Creating effective memory banks and guidelines
- Part 6: The Ultimate Design Review - Putting it all together
In the previous posts, we’ve taught our AI assistant how to understand and enforce specific architectural rules. We’ve built a robust system for linting, testing, and managing complex tasks. But how do we ensure the AI behaves consistently and predictably over the long term? How do we give it a “personality” and a “memory” that aligns with our project’s philosophy?