Even before coding harnesses become mainstream, a lot of tools offered to automatically generate commit messages based on the diff (I think JetBrains IDEs started to offer it very early) and I always cringed when I've seen it.

The reason why I don't like diff-base commit messages is because they are redundant. If I want an LLM-generated summary of the diff, I can easily generate it myself, there is absolutely no reason to put it in the commit message.

What I would like to see in the commit message is some additional context that is not a part of the diff. I don't need to read what has changed, because I can already can see it in the diff (or get an LLM to summarize it for me). But I often do need to understand why this change was made. What were they trying to achieve? That's the important part that is not contained in the diff itself. And this is the part that diff-base commits rarely contain.

I think that even something simple like a link to a Jira (or other bugtracker ticket) is much more helpful than diff summary. Maybe instead of "fix" or "update" you could write just a couple of words about what are you trying to fix and why does it need updated. Still better, than a diff-summary.

I have the opposite issue - some of my team members now submit mini-essays generated by the LLM. Like 300-500 word commit messages with everything from the essence of the change up to philosophical design trade off discussions.

Like most writing, what is left out is as important as what is included.

But AI commit messages are still bad. Way too verbose and focused on the wrong level: that of code mechanics. That's just wrong. Messages should focus on the level of intent and design, with the primary purpose being to aid human review. They should include a high level overview of the change, decisions, caveats, information not obvious from reading the diff.

So I wrote a skill that captures these principles and allows the agent to even research past related commits and to ask focused questions in order to uncover the intent rather than guessing and writing a bad one.

Now the AI writes better commit messages than it used to, and even writes better than most humans (who can't be bothered to write a good one). Not better than a good manual message, but you can't have everything.

But sometimes even the good writers are tired or didn't think things through. Being able to compare with the AI's version is still useful.

Here is the skill for anyone interested: https://github.com/FooBarWidget/ai-skills-and-principles/blo...

Depends on my "documentation principles" skill: https://github.com/FooBarWidget/ai-skills-and-principles/blo...

If they already knew what function or detail is involved, they would be already be doing a "all commits that touched this line" filter, and my comment about affecting $thing would probably be superfluous.

I also don't need to tell them such details in the commit, because that is better expressed by the actual diff.

So in a sense, I'm trying to provide good keywords, about transactions, errors, logging, button color, whatever.

E.g. in one country, 21% of high school students do not even achieve “sufficient reading literacy”…

So the question should be - what are we going to do with this? LLM can produce texts but we as people will not be able to understand anyway…

About PISA research for example here: https://www.edweek.org/leadership/reading-ability-craters-on...

Not that I disagree much, but for myself I have an actual cause connecting the two parts, and it's not something inherent to AI.

Basically, synthetic content is like those fancy desserts - they look nice and the top layer possibly has an exquisite flavor (probably on purpose), but once you cut deeper, it's some weird fruit or nut or other foodstuff that belongs next to potatoes and meat, not in a cake. So I learned to avoid such desserts and stick to basic stuff I know are good entirely, like IDK a cream pie or cream-filled chocolate stuff or such.

Same is with content. My problem isn't that it's AI, but that it's wrong, full of mistakes human authors don't make. Hallucinations mid-text that make half of it convincingly argue bullshit. Or the uncanny or repetitive factor in art that kicks in after few seconds of looking.

Like with desert, I'm avoiding disappointment and wasted hopes. When synthetic context gets better, I'll be consuming it just like "vanilla" one, for the same reasons.

I know lots of AI-enabled writers believe this, but I've never actually seen it be true.

It often makes them less informative and a lot less sincere.

what do you think this process is? why don't we just write lists of ideas to each other, in the raw format you presumably started with? is there any value in it?

my opinion is that the process is literally nothing more than thinking deeply about the ideas and trying to phrase them in the clearest possible way such that you lead someone else into understanding them.

LLMs have awful, terrible judgement of what other people know, or are likely to infer from a piece of text.

Where does this feeling come from? Is it just because the work is complex? We’re all (excepting maybe the amish) comfortable with using at least some automation, be it mechanical or digital, elsewhere in our lives

What’s preventing the editor from using one of your prompts/tooling and replacing you entirely?

There’s zero value in sharing ai-generated output unless your ai has access to something nobody else’s does on which to base things. If all it’s doing is web research you should share your prompt instead. That way people don’t have to deal with ai-written walls of text.

The problem here is that the volume of low-mid content is making it harder to find the best content.

For instance, if I said the grass is green vs if I said the grass looks nice vs if I said the grass is doing well and looks how it should vs if I said in my opinion the grass is healthier than its ever been.

Is there anybody on this site who isn't?