> While I’m certain that this technology is producing some productivity improvements, I’m still genuinely (and frustratingly) unsure just how much of an improvement it is actually creating.

I often wonder how much more productive I'd be if just a fraction the effort and money poured into LLMs was spent on better API documentation and conventional coding tools. A lot of the time, I'm resorting to using an AI because I can't get information on how the current API of some-thing works into my brain fast enough, because the docs are non existent, outdated, or scattered and hard to collate.

This is facts. All of this talk about putting agent skills directly into repos (as Markdown!) is maddening. "Where were LITERALLY ALL OF YOU whenever the topic of docs as code came up?"

This is doubly maddening with NotebookLMs. They are becoming single sources of knowledge for large domains, which is great (except you can't just read the sources, which is very "We will read the Bible to you" energy), but, in the past, this knowledge would've been all over SharePoint, Slack, Google Drive, Confluence, etc.

I feel like Google search results have gotten tremendously worse over the past 2 years too. It's almost like you have to use AI search to find anything useful now.

Which of course reduces traffic to sites and thus the incentives to create the content you're looking for in the first place :(

> I often wonder how much more productive I'd be if just a fraction the effort and money poured into LLMs was spent on better API documentation and conventional coding tools.

Probably negligible. It's not a problem you can solve by pouring more money in. Evidence: configuration file format. I've never seen programmers who enjoy writing YAML. And pure JSON (without comments) is simply not a format should be written by humans. But as far as I know even in the richest companies these formats are still common. And the bad thing they were supposed to replace, XML config, was popularized by rich companies too...!

My favorite thing is when some projects now have better documentation in their Claude skills or MCPs than they ever did for users.

As someone who does broad activities, it supercharges a lot of things. Having a critical eye is required though. I estimate 40%-60% improvements on basic coding tasks.

I don't bring huge codebases to it.

I agree. I think of AI as a search engine on steroids.

But I think it IS the best way to search for information, to be able to put a question in natural language. I'm always amazed just how exactly on-point the answer is.

I mean even the best of docs out there that have a great search bar like the Vue docs still only matches your search term and surfaces relevant topics.

> better API documentation and conventional coding tools

Agreed, and it depends on the language I suppose. I'm a C++ developer and when you start working with templates even at a non-casual level, the compiler errors due to either genuine syntactic errors or 'seems correct but the standard doesn't support' can be infuriatingly obtuse. The LLM 'just knows' the standard (kind of, all 2k pages), and can figure out and fix most of those errors far faster than I can. In fact one of my preferred usages is to point Codex at my compiler output and get it to do nothing more than fix template errors.

Kotlin, for example, is much more in your face, in the IDE which does a correctness pass, before you even invoke the compiler (in the traditional sense) and the language spec is considerably leaner with less (no?) UB, unlike C++.

Yeah I get this impression too. AI feels like it's papering over overwrought and badly designed frameworks, tech stacks with far too many things in them, and also the decline of people creating or advocating for really expressive languages.

Pragmatic sure, but we're building a tower of chairs here rather than building ladders like a real engineering field.

then you should be delighted we have LLMs one of the use cases they are best suited to is writing documentation, much better than humans can.

[dead]