PM Coding Guardrails

PM Coding Guardrails provides essential coding standards and quality gates specifically designed for product managers collaborating with AI assistants in shared codebases. This project addresses the challenges faced by PMs who utilize AI for coding, aiming to accelerate product delivery while minimizing the technical debt that can result from rapid development.

The Challenge

Product managers using AI often encounter issues that hinder the efficiency of engineering teams, such as:

• Pull requests that fail continuous integration and delivery (CI/CD) processes.
• Code that diverges from established team patterns.
• Accumulation of technical debt that complicates future development.
• Discontent among engineers who need to rectify issues created by hastily written code.

The Solution

The project offers practical guidelines that empower PMs to code effectively and responsibly, whether on solo projects or in collaboration with senior engineers in shared codebases.

Key Components

• pm-who-codes.md: Outlines the core philosophy and principles for PMs coding with AI.
• quality-gates.md: Provides a pre-commit checklist to ensure readiness for integration.
• solo-project-standards.md: Establishes standards for maintaining simplicity and maintainability in solo projects.
• session-management.md: Focuses on effective management of coding sessions to maintain context and continuity.

Target Audience

This repository is aimed at:

• PMs learning to code with the assistance of AI.
• PMs collaborating within shared codebases alongside engineering teams.
• Product builders aiming to ensure that their code is maintainable and shipped responsibly.
• Anyone utilizing AI tools for coding endeavors who seeks to prevent the development of flawed code that does not adhere to common coding standards.

Practical Use

It offers flexible integration options, allowing users to:

1. Incorporate guidelines seamlessly into their AI coding sessions.
2. Use the documents as references while coding and reviewing guidelines before commits.
3. Adapt the core principles to fit specific team environments, tools, and workflows.

Recommended Practices

The recommended approach emphasizes the importance of consistency, adherence to coding standards, and the significance of quality over speed. This project compiles best practices from experienced engineers who successfully integrate AI into their coding efforts.

Conclusion

PM Coding Guardrails establishes a foundation for product managers to code responsibly, ensuring that they balance rapid development with quality and maintainability. This initiative fosters an environment where features are delivered efficiently and reduce the need for later cleanup work by engineering teams.