Author here: To be honest, I know there are like a bajillion Claude code posts out there these days.
But, there are a few nuggets we figured are worth sharing, like Anchor Comments [1], which have really made a difference:
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# 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
Just to provide a contrast to some of the negative comments…
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 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.
>Think of this post as your field guide to a new way of building software. By the time you finish reading, you’ll understand not just the how but the why behind AI-assisted development that actually works.
Hi, AI skeptic with an open-mind here. How much will this cost me to try? I don't see that mentioned in your writeup.
There are a bunch of different options so it depends on the models you end up liking but the simplest place to start is to get Claude Max $100 tier and use Opus 4 (the others don’t really get you the full experience)
I hear a lot of good stuff about Claude Code lately, but before, it was all about Copilot or Cursor. And some options are a lot cheaper than others. Is Claude Code so much better now?
I admit I have no idea what the real differences are. Everybody seems to claim to be the best and most comprehensive AI coding solution.
There are a lot of posts around but this was very practical and gives me a system i can try to implement and perhaps improve. Much appreciated. Thanks for taking the time to write it.
One thing I would have liked to know is the difference between a workflow like this and the use of aider. If you have any perspective on that, it would be great.
Thank you! aider is a different beast actually, I found its memory/context handling best in class. Somehow though, I ended up liking Claude Code the most because of its TUI but really a matter of personal preference and workflow
Thanks for the great article, this is much needed to understand how to properly use LLM at scale.
You mentioned that LLM should never touch tests. Then followed up with an example refactoring changing 500+ endpoints completed in 4 hours. This is impressive! I wonder if these 4 hours included test refactoring as well or it is just prompting time?
At one place you mentioned, if a test is updated by AI, you reject the PR. How do you know if it was generated or updated by AI.
From the article I only got that it's a git commit message convention to add that but that too is only at commit level.
Great post. I'm fairly new to the AI pair programming thing (I've been using Aider), but with 20 years of coding behind me I can see where things are going. You're dead right in the conclusion about now being the time to adopt this stuff as part of your flow -- if you haven't already.
And regarding the HN post getting buried for a while there...[1] Somewhat ironic that an article about using AI to help write code would get canned for using an AI to help write it :D
Did you use Claude Code to write the post? I'm finding that I'm using it for 100% of my own writing because agentic editing of markdown files is so good (and miles better than what you get with claude.ai artifacts or chatgpt.com canvas). This is how you can do things like merge deep research or other files into the doc that you are writing.
Right. But you can copy paste that into a separate doc and have Claude Code merge it in (and not a literal merge - a semantic merge "integrate relevant parts of this research into this doc"). This is super powerful - try it!
The models are the same, but the actual prompts sent to the model are likely somewhat different because of the agentic loop - so I would imagine (without having done the experiments) there will be slight differences. Unclear whether they will be more or less than the variance in responses sent multiple times to the same experience (e.g., Claude.ai variance vs. Claude Code variance vs. variance between Claude.ai and Claude Code). Would be an interesting controlled experiment to try!
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?
> So how do you ensure everyone keeps to that agreement?
There's nothing specific to using Claude or any other automation tool here. You still use code reviews, linters, etc. to catch anything that isn't following the team norms and expectations. Either that or, as the article points out, someone will cause an incident and may be looking for a new role (or nothing bad happens and no one is the wiser).
But, there are a few nuggets we figured are worth sharing, like Anchor Comments [1], which have really made a difference:
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——[1]: https://diwank.space/field-notes-from-shipping-real-code-wit...