Engineering Best Practices

Foundations

• What Are Engineering Best Practices? — The anchor article. What best practices are (vs. cargo-cult dogma), how to establish them, the tension between standardization and flexibility, and how best practices adapt in the AI era.

• Codebase Conventions and Standards — Naming, file structure, code style, import ordering, comment conventions. Why consistency reduces cognitive load, how to enforce it with tooling, and the balance between too few rules and too many.

Testing & Quality

• Testing Strategies for Large Systems — The testing pyramid (and its alternatives), what to test at each level, dealing with external dependencies, property-based testing, mutation testing, and practical strategies for maintaining test quality at scale.

• CI/CD Best Practices — What CI/CD actually means (not just "we use GitHub Actions"), pipeline design, stage ordering, caching, parallelism, common mistakes, and how CI/CD adapts for AI-generated code.

Review & Documentation

• Code Review in AI-Assisted Teams — How the review process changes when agents generate code: what to look for, practical checklists, how reasoning traces transform the experience, and the balance between thoroughness and velocity.

• Documentation as Infrastructure — Docs aren't an afterthought — they're infrastructure. Types of documentation, docs-as-code workflows, keeping docs current, and why documentation is context for AI agents (not just for humans).

Contracts & Compatibility

• Versioning and Backward Compatibility — Semantic versioning, API versioning strategies, deprecation, schema evolution, and practical patterns for evolving public APIs without breaking consumers.

• Data Contracts and System Boundaries — Explicit agreements about data shape and semantics between systems. Consumer-driven contracts, Pact testing, syntactic vs. semantic contracts, and practical implementation.

Resilience & Accessibility

• Error Handling and Resilience Patterns — Fail fast vs. fail gracefully, exception hierarchies, error boundaries, retry patterns, circuit breakers, bulkheads, timeout strategies, graceful degradation, and building systems that handle failure well.

• Accessibility Fundamentals — WCAG compliance, the POUR principles, semantic HTML, ARIA, keyboard navigation, screen reader testing, and integrating accessibility into the development workflow instead of treating it as an afterthought.

Where This Hub Connects

• AI Code Governance & Quality — Governance extends best practices into the AI domain. Pre-commit hooks, CI validation, and code review take on new importance when agents generate code.

• Software Design — Design principles like SOLID, TDD, and DDD produce the code that best practices protect. Good design and good process reinforce each other.

• Software Architecture — Architectural decisions set the boundaries that best practices operate within. CI/CD pipelines, testing strategies, and conventions all exist in the context of your architecture.

• AI-Native Software Development — The AI-native paradigm changes which best practices matter most. Code review becomes paramount, documentation becomes agent context, and testing strategies adapt for AI-generated code.