A versioned engineering handbook for secure software development, Git workflows, code review, software releases, and AI-assisted engineering.
Acadify Solution Engineering Standards is a practical, reusable software engineering handbook for teams that want consistent development practices across the software delivery lifecycle.
It covers:
- Git branching, commits, pull requests, and collaboration
- Secure and maintainable coding practices
- Peer code review standards
- Release management, rollback, and production verification
- Engineering governance and contribution workflows
- Automated Markdown and formatting quality checks
The handbook is designed for software engineers, backend developers, frontend developers, full-stack developers, DevOps engineers, QA engineers, technical leads, engineering managers, and teams adopting AI-assisted development workflows.
| Topic | Guidance |
|---|---|
| Git workflow | Branching & Git |
| Secure coding | Coding Practices |
| Code review | Peer Reviews |
| Software releases | Release Management |
| Governance | Engineering Standards Governance |
| Contributions | Contributing Guide |
| Security reporting | Security Policy |
A shared engineering standard reduces ambiguity across teams. Instead of relying on individual habits, projects can use explicit rules for:
- branch and pull-request workflows
- coding quality and security
- review expectations
- release readiness
- operational ownership
- documentation and governance
The goal is not bureaucracy. The goal is repeatable engineering quality.
AI coding assistants and generative AI can accelerate implementation, but engineering teams still need human review, security controls, tests, and production verification.
For AI-assisted development, this handbook provides a foundation for applying familiar engineering controls to AI-generated or AI-assisted changes:
- Define the intended behavior.
- Review generated code like human-written code.
- Validate security, correctness, dependencies, and data handling.
- Run automated checks.
- Review the change before merge.
- Verify behavior after release.
This repository can serve as a starting point for extending standards around LLM applications, RAG systems, prompt engineering, AI evaluation, model integrations, AI security, and responsible AI development.
Software engineering standards are documented practices and rules that help teams build, review, release, and maintain software consistently.
This repository provides practical standards for Git workflows, coding practices, peer review, release management, security, and engineering governance.
A useful engineering handbook commonly covers development workflows, coding standards, code review, security, testing, release management, incident or operational practices, and governance.
This repository organizes those practices into focused, versioned Markdown documents.
A good branching strategy should make collaboration predictable, keep changes reviewable, and support safe releases. The appropriate model depends on the team's deployment and release workflow.
See Branching & Git for the documented approach used by this handbook.
A good code review process checks correctness, maintainability, security, test coverage, compatibility, and release impact while keeping reviews focused and actionable.
See Peer Reviews.
AI-generated code should be treated as code that requires normal engineering verification. Reviewers should check behavior, security, dependencies, tests, data handling, and maintainability rather than assuming generated code is correct.
A release process should define readiness checks, deployment verification, rollback options, ownership, and post-release validation.
See Release Management.
This repository is relevant to searches and discussions about:
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The repository uses automated formatting and Markdown linting through GitHub Actions. Changes are reviewed through the repository contribution workflow, with ownership and security guidance documented separately.
Current handbook version: 1.1.1
Last reviewed: 2026-09-30
Before adopting these standards in another organization, review the repository's license and governance terms. Teams may adapt the practices to their architecture, regulatory environment, deployment model, and risk profile.
Acadify Solution Engineering Standards is maintained as a living handbook. Standards evolve as engineering practices, software architectures, security expectations, and AI-assisted development workflows change.