Poor Commits
This is the polluted history pain point. An AI doesn't inherently understand the human context or intent behind a change, so its commit messages are often useless in one of two ways. You either get uselessly vague messages like fix or update code, or you get the opposite: summary overload, where the AI generates a multi-paragraph novel for a simple one-line fix. Both extremes pollute the git history, making it impossible to scan and destroying its value for debugging.
An AI's default commit message describes what it did (e.g., Updated index.js), but it completely misses the critical why (e.g., Fixes-ticket:123, to handle null user auth). Furthermore, AI-generated commits often violate the atomic principle, bundling multiple unrelated changes (like a bug fix, a refactor, and a typo correction) into a single, confusing commit. Finally, without explicit guardrails, these commits will almost never follow your team's specific Conventional Commit or Jira-linking standards.
This renders your git history, one of your most valuable long-term assets, unreadable and useless. It makes incident response and debugging significantly harder, as developers can't use git blame or git bisect to quickly find the root cause of a regression. Team standards degrade, onboarding new developers becomes more difficult (as they can't read the story of the code), and the entire history of the project becomes a write-only log of noise.
The Full Page Novel
The AI generates a three-paragraph, full-page commit message—complete with its own thought process—for a change that only fixed a typo (a 1-line diff).
The Useless Fix
The classic, context-free commit message that just says fix, update, or commit, providing zero value to anyone reading the log.
The Kitchen Sink Commit
An AI-generated commit that includes three unrelated changes: 1) a bug fix for the login page, 2) a refactor of a utility function, and 3) updates to the README.md.
The Conventional Commit Failure
The AI generates a message like changed the user service, when your team's standard requires a format like feat(auth): add MFA support (refs: JIRA-456).
The problem isn't the AI; it's the lack of a human-in-the-loop verification and governance system. These workflows are the perfect antidote.
Professional Commit Standards
View workflow →The Pain Point It Solves
This workflow directly attacks the polluted history problem by requiring conventional commit format with context in commit body explaining why changes were made, and documenting any tool or script creation with clear ownership. Instead of allowing AI to create vague or verbose commit messages, this workflow enforces clear, structured, and useful commit messages.
Why It Works
It enforces commit quality. By requiring conventional commit format (type(scope): description), including context in commit body explaining why changes were made (not just what changed), referencing issue numbers when applicable (Fixes: #123), and keeping commit history professional, this workflow ensures that AI-generated commits are readable, useful, and follow team standards. This prevents git history from becoming a write-only log of noise and makes debugging significantly easier.
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Explore our workflows and guardrails to learn how teams address this issue.
Engineering Leader & AI Guardrails Leader. Creator of Engify.ai, helping teams operationalize AI through structured workflows and guardrails based on real production incidents.