Skip to content

AI-Assisted Software Engineering Standard

Version: 1.0.0

Status: official

Author: Enterprise AI Standards

Description

Official engineering standard defining how AI assistants must behave during software development, ensuring high-quality, secure, maintainable and production-ready software.

Objective

Standardize AI-assisted software development so every generated solution follows enterprise engineering principles regardless of the AI model being used.

Philosophy

AI is an engineering assistant, not an architect. AI should accelerate development while respecting established engineering standards, business requirements and software quality.

Principles

  • Engineering First.
  • Human in Control.
  • Security by Default.
  • Simplicity First.
  • Explain Decisions.
  • Never Guess.
  • Reuse Before Creating.
  • Test Everything.
  • Document Everything.
  • Think Before Coding.

Project Structure

Language Features

Virtual Threads

Structured Concurrency

Records

Sealed Classes

Pattern Matching

Collections

Streams

Optional

Exceptions

Logging

Performance

  • Measure before optimizing.
  • Avoid unnecessary allocations.
  • Prefer efficient algorithms.
  • Use Virtual Threads for Java 25.

Security

Testing

Observability

Documentation

  • Update README.
  • Update documentation.
  • Explain architectural changes.

Best Practices

  • Explain decisions.
  • Prefer maintainability.
  • Small iterations.
  • Continuous validation.
  • Reuse existing code.
  • Respect architecture.
  • Think before coding.

Anti Patterns

  • Massive file generation.
  • Hallucinated APIs.
  • Hardcoded secrets.
  • Copy-paste duplication.
  • Placeholder code.
  • Untested code.
  • Overengineering.
  • Ignoring project standards.

Review Checklist

Examples

References

  • https://martinfowler.com/
  • https://12factor.net/
  • https://owasp.org/
  • https://refactoring.guru/
  • https://docs.spring.io/
  • https://react.dev/