"The glue adds a flavor and texture profile that traditionalists may not be used to on their cheese pizza. But I've had Michelin-star quality pizzas without glue in them that weren't half as delicious as this one was with. AI-mediated glue-za is the future of pizza, no doubt about it."
But, there are a few nuggets we figured are worth sharing, like Anchor Comments [1], which have really made a difference:
——
# CLAUDE.md
### Anchor comments
Add specially formatted comments throughout the codebase, where appropriate, for yourself as inline knowledge that can be easily `grep`ped for.
- Use `AIDEV-NOTE:`, `AIDEV-TODO:`, or `AIDEV-QUESTION:` as prefix as appropriate.
- *Important:* Before scanning files, always first try to grep for existing `AIDEV-…`.
- Update relevant anchors, after finishing any task.
- Make sure to add relevant anchor comments, whenever a file or piece of code is:
* too complex, or
* very important, or
* could have a bug
[1]: https://diwank.space/field-notes-from-shipping-real-code-wit...
I typically try to also include the original Claude chat’s link in the post but it seems like Claude doesn’t allow sharing chats with deep research used in them.
Update: here’s an older chatgpt conversation while preparing this: https://chatgpt.com/share/6844eaae-07d0-8001-a7f7-e532d63bf8...
I posted on HN largely to get feedback.
1. Add instructions in CLAUDE.md to not touch tests.
2. Disallow the Edit tool for test directories in the project’s .claude/settings.json file
I meant though in the wider context of the team - everyone uses it but not everyone will work the same, use the same underlying prompts as they work. So how do you ensure everyone keeps to that agreement?
As a very experienced engineer who uses LLMs sporadically* and not in any systematic way, I really appreciated seeing how you use them in production in a real project. I don’t know why people are being negative, you just mentioned your project in details where it was appropriate to talk about the structure of it. Doesn’t strike me as gratuitous self promotion at all.
Your post is giving me a motivation to empower the LLMs a little bit more in my workflows.
*: They absolutely don’t get the keys to my projects but I have had great success with having them complete specific tasks.
I typically try to also include the original Claude chat’s link in the post but it seems like Claude doesn’t allow sharing chats with deep research used in them.
See this series of posts for example, I have included the link right at the beginning: https://diwank.space/juleps-vision-levels-of-intelligence-pt...
I completely get the critique and I already talked about it earlier: https://news.ycombinator.com/item?id=44213823
Update: here’s an older chatgpt conversation while preparing this: https://chatgpt.com/share/6844eaae-07d0-8001-a7f7-e532d63bf8...
That's not something to be proud of.
"Please don't use HN primarily for promotion. It's ok to post your own stuff part of the time, but the primary use of the site should be for curiosity."
- Is there a more elegant way to organize the prompts/specifications for LLMs in a codebase? I feel like CLAUDE.md, SPEC.mds, and AIDEV comments would get messy quickly.
- What is the definition of "vibe-coding" these days? I thought it refers to the original Karpathy quote, like cowboy mode, where you accept all diffs and hardly look at code. But now it seems that "vibe-coding" is catch-all clickbait for any LLM workflow. (Tbf, this title "shipping real code with Claude" is fine)
- Do you obfuscate any code before sending it to someone's LLM?
Yeah, the comments do start to pile up. I’m working on a vscode extension that automatically turns them into tiny visual indicators in the gutter instead.
> - What is the definition of "vibe-coding" these days? I thought it refers to the original Karpathy quote, like cowboy mode, where you accept all diffs and hardly look at code. But now it seems that "vibe-coding" is catch-all clickbait for any LLM workflow. (Tbf, this title "shipping real code with Claude" is fine)
Depends on who you ask ig. For me, hasn’t been a panacea, and I’ve often run into issues (3.7 sonnet and codex have had ~60% success for me but Opus 4 is actually v good)
> - Do you obfuscate any code before sending it to someone's LLM?
In this case, all of it was open source to begin with but good point to think about.
1. We ran into really bad minefields when we tried to come back to manually edit the generated tests later on. Claude tended to mock everything because it didn’t have context about how we run services, build environments, etc.
2. And this was the worst, all of the devs on the team including me got realllyy lazy with testing. Bugs in production significantly increased.
kasey_junk•4h ago
You can use how uncomfortable you are with the ai doing something as a signal that you need to invest in systematic verification of that something. As a for instance in the link, the team could build a system for verifying and validating their data migrations. That would move a whole class of changes into the ai relm.
This is usually much easier to quantify and explain externally than nebulous talk about tech debt in that system.
diwank•31m ago