Is that final number really that crazy? With a well defined goal, you can put out 5-8K per day by writing code the old fashioned way. Also would love to see the code, since in my experience (I use Cursor as a daily driver), AI bloats code by 50% or more with unnecessary comments and whitespace especially when making full classes/files.

> I spend a lot of time setting Claude code up for success.

Normally I wouldn't post this because it's not constructive, but this piece stuck out to me and had me wondering if it's worth the trade-off. Not to mention programmers have spent decades fighting against LoC as a metric, so let's not start using it now!

You'll never see the code. They will just say how amazingly awesome it is, how it will fundamentally alter how coding is done, etc... and then nothing. Then if you look into who posts it, they work in some AI related startup and aren't even a coder.

Not open source but depending on certain context i can show whoever. im not hard to find.

Ive done just about everything across the full & distributed stack. So I'm down to jam on my code/systems and how I instruct & rely on (confidently) AI to help build them.

5k likes of code a day is 10 lines of code a minute solidly for 8 hours straight. Whatever way you cut that with white space, bracket alignment, that’s a pretty serious amount of code to chunk out.

If I am writing Go, it is easy to generate enough if/else and error checks. When working in java, basic code can bloat to big LoC over several hours(first draft, which is obviously cleaned up later before going to PR). React and other FE frameworks also tend to require huge LoC count(mostly boilerplate and auto completed rather than thoughtfully planned and written). It is not that serious amount as you may think.

Nitpicking like this must be fair, if you look at typical AI code - styles, extra newlines, comments, tests/fixtures, etc. it is the same. And again LoC isn't a good measurement in the first place.

Not all my 5k lines are hand-written or even more than a character; a line can be a closing bracket etc. which autocomplete has handled for the last 20 years. It's definitely an achievement, which is why it's important to get clarity when folks claim to reach peak developer productivity with some new tools. To quote the curl devs, "AI slop" isn't worth nearly the same as thoughtful code right now.

are people really committing 5k lines a day without AI assistance even once a month?

I don't think I've ever done this or worked with anyone who had this type of output.

It depends upon how well mapped out the problem is in your head. If it's an unfamiliar domain, no way.

Maybe if you are copy-pasting some html templates, but then it is not “writing code”. Handwriting complex logic, at 5k sloc per day, no way.

Nobody is writing 5k consistently on a daily basis. Sure if it’s a bunch of boiler scaffolding maybe.

I daily drive cursor and I have rules to limit comments. I get comments on complex lines and that’s it.

Can you share more about what you mean by a meta context/tasking management system? I’m always curious when I see people who have happily spent large amounts on api tokens.

So i use roo and you have the architecture mode draft out in as much detail as you want, plans, tech stack choices, todos, etc. Switch to orchestration mode to execute the plan, including verifying things are done correctly. It sub tasks out the todos. Tell it to not bother you unless it has a question. Cone back in thirty and see how it’s doing. You can have it commit to a branch per task if you want. Etc etc.

Here is some insight... I had gemini obfuscate my business context so if something sounds weird it is probably because of that.

https://gist.github.com/backnotprop/4a07a7e8fdd76cbe054761b9...

The framework is basically the instructions and my general guidance for updating and ensuring the details of critical information get injected into context. some of those prompts I commented here: https://news.ycombinator.com/item?id=43932858

For most planning I use Gemini. I copy either the entire codebase (if less than ~200k tokens) or select only that parts that matter for the task in large codebases. I built a tool to help me build these prompts, keep the codebase organized well in xml structure. https://github.com/backnotprop/prompt-tower

I'd be really interested in seeing the source for this, if it's an open-source project, along with the prompts and some examples. Or other source/prompt examples you know of.

A lot of people seem to have these magic incantations that somehow make LLMs work really well, at the level marketing and investor hype says they do. However, I rarely see that in the real world. I'm not saying this is true for you, but absent vaguely replicable examples that aren't just basic webshit, I find it super hard to believe they're actually this capable.

Not open source but depending on certain context i can show you. im not hard to find.

Aider writes 70-80% of its own code: https://aider.chat/HISTORY.html

While not directly what you're asking for, I find this link extremely fascinating - https://aider.chat/HISTORY.html

For context, this is aider tracking aider's code written by an LLM. Of course there's still a human in the loop, but the stats look really cool. It's the first time I've seen such a product work on itself and tracking the results.