And in the time it takes to do all of that, the guy could have already written a meaningful commit message and be done with that issue for the day.
You only have to describe how you want commits written once and then the AI will just handle it. Is not that anyone of us can't write good commits, but humans get tired, lose focus, get interrupted, etc.
Just in my short time using Claude Code, it generally writes pretty good commits; it often adds more detail than I normally would not because I'm not capable but because there's a certain amount of cognitive overhead when it comes to writing good commits and it gets harder as our mental energy decreases.
I found this custom command [1] for Claude Code and it reminded me that there's no way a human can consistently do this every single time, perhaps a dozen times per day, unless they're doing nothing else--no meetings, no phone calls, etc. And we know that's not possible:
# Git Status Command
Show detailed git repository status
*Command originally created by IndyDevDan (YouTube: https://www.youtube.com/@indydevdan) / DislerH (GitHub: https://github.com/disler)*
## Instructions
Analyze the current state of the git repository by performing the following steps:
1. *Run Git Status Commands*
- Execute `git status` to see current working tree state
- Run `git diff HEAD origin/main` to check differences with remote
- Execute `git branch --show-current` to display current branch
- Check for uncommitted changes and untracked files
2. *Analyze Repository State*
- Identify staged vs unstaged changes
- List any untracked files
- Check if branch is ahead/behind remote
- Review any merge conflicts if present
3. *Read Key Files*
- Review README.md for project context
- Check for any recent changes in important files
- Understand project structure if needed
4. *Provide Summary*
- Current branch and its relationship to main/master
- Number of commits ahead/behind
- List of modified files with change types
- Any action items (commits needed, pulls required, etc.)
This command helps developers quickly understand:
- What changes are pending
- The repository's sync status
- Whether any actions are needed before continuing work
Arguments: $ARGUMENTS
It's not possible for a human to do what an LLM does at scale, for sure. But that's the difference, humans are not robots, so they will turn the the problem around and will try to find ways on how to not have to do this in the first place. E.g. minimizing pending changes left around by making small frequent commits. A lot of invention comes from people being annoyed doing something all over again manually. LLM stirs up things a little bit as it provides a completely different way of doing such tasks. You don't have to invent a better process if the LLM can do it repeatedly for a reasonable price. The new pressure then comes from minimizing LLM costs, I guess.
Wishful thinking. They will often ignore your general instructions, due to the statistical nature of their output. Source: have many such detailed general instructions that routinely get ignored.
These tools aren't magic, if there are reasons for code changes outside of the diff LLMs aren't going to magically fabricate a commit message that gives that context.
