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 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...!

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 :(

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.

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.

If you’re an employee who can finish their work 25% faster but you’re not getting a 4-day work week, what are the incentives for not introducing creep?

It's a matter of whether you are just writing more regular quality things, or whether you are improving the quality of what you write. There's many things that increase quality, but are time consuming, which Claude Code can do for you.

One thing I recently did was run a pass over some unit test and functional test suites, asking for standardization on initialization, and creating reasonable helper methods to minimize boilerplate. Any dev can do that, if they have a week, and it'll future code changes more pleasant later. For Claude, an hour was a -8000 line PR that kept all the tests, with all the assertions.

It's what people need to figure out out of a a codebase. Our normal quality practices have an embedded max safe speed for changes without losing stability. If you use LLMs to try to change things faster, the quality practices have to improve if one wants to keep the number of issues per week constant. Whether it's improving testing, or sending the LLM to look at logs and find the bugs faster, one needs to increase the quality budget.

Some of the expanded scope that I’ve done almost for free is usually around UX polish and accessibility. I even completely redid the —help for a few CLI tools I have when I would never have invested over an hour on each before agents.

I agree that the efficiency and quality are very hard to measure. I’m extremely confident that when used well, agents are a huge gain for both though. When used poorly, it is just slop you can make really fast.

Dude. I’ve been thinking about this a lot! I think it’s because the traditional way we internalize the costs of what we are building just got take for a ride. We don’t really (or I don’t anyway) fully know what “too much scope” feels like with one of these Claude thingies. So it’s easy to completely both overestimate complexity and underestimate it too. Some times the LLM makes a seemingly daunting refactor be super simple and sometimes something seemingly not complex can take it forever… and there really is, for me, a good “gut sense” of how something will go.

So lately I’ve just decided that I’ll time box things instead of set defined endpoints. And by “endpoint” I really mean “I’m done for the day” and honestly maybe thinking about it… “I’m done with this project”.

I don’t know. But the term “Claude Creep” is absolutely something I can identify with. That thing will take you down a rathole that started with just pulling in some document and ends with you completely repartitioning your file system. lol.

[flagged]

And just like that, a new term has been coined.

Yes this + also APIs! Due to LLMs needing APIs suddenly things that were strictly behind GUI can easily opened up for programmatic use. Double edged sword, due to infosec etc concerns, but sure is nice for personal productivity automation.

An important aspect of comparison is that nobody is going to tell you that your surgery is noticeable or looks bad.

Your friends, family, partners, coworkers, aren't going to say anything, neither are people you meet casually, certainly not service workers, strangers aren't going to pull you aside to tell you the truth about your nose job, etc.

I hope the same social taboo doesn't transfer over to AI content. We should honestly critique AI generated content, used either in-whole or in-part with human creations. If the inclusion of AI content botched your article, saying so should be socially acceptable.

We saw some of this here on HN. It used to be that when AI content would be submitted here, it was a social faux pas to even mention it was LLM generated, same thing with LLM generated comments, no matter how obvious it was. Mentioning a comment was AI was socially verboten and you'd be finger-wagged at.

Eventually, AI fatigue caused the community to discount Show HN entries, submissions and comments, and the signal to noise ratio could no longer be ignored.

Now, turn on showdead. Those same comments, that users were expected to interact with as if they were made in good faith by real people, litter every submission's comment section. These comments objectively hurt discussion and it's a good thing they're shadowbanned.

Culturally, I hope we can reach a point where critique of AI content, including code, doesn't brand critics as haters, Luddites, or worse, and stifle conversation about what our communities really value and want.

It's the same way with writing as with video. There are some videos now where it's actually hard to tell. You can only tell it's AI when it's bad. When it's done well, you don't even know it's AI.

So it creates this selection effect where people only associate AI with fake and bad. The good stuff, they don't associate with AI at all.

It's funny you mention that. The only difference is sometimes you need a functionality without doing the plumbing. At the end of the day if you're getting the output you need, the process doesn't matter. It's an interesting analogy but only works if the inspector is another expert dev.

Several of my friends who don't know any programming are creating video games and music software with AI agents.

Much of what they are doing is incomprehensible to me. I often find that being a programmer is actually holding me back in this regard, because I feel the need to understand everything the code is doing, as well as the specialized knowledge (e.g. the math involved in audio processing and sound effects). Whereas my friends can just say... yeah add a phaser effect to the synth and it just does it.

If it was any good at sales I'm pretty sure a company I did a contract for would be thriving by now. Instead they have a product that is ~500 times faster than the competition, with better UX for the most common activity in that field and much better built-in analysis tools for end results, run in real-time (which competitor software cannot do). Sure, it's not a massive market in terms of demographics, but I'd expect real sales people to succeed with what they have. Something very real has gone wrong with sales and it's not something they've been able to solve using LLMs.

I know this company uses LLMs, because I'm working on another project for them where one of the co-founders is relentlessly spamming the repo with overwrought Claude Code output like there is no tomorrow. This shit sucks at code generation and it most likely sucks at everything else too, except people often assume it's better at things they don't know about.

> I've turned 12 minute videos back into the 5 phrases news it was based on.

Why not read the original news?

Okay, there are many reasons why you might not want to do that, such as ads, tracking, having to pay for a subscription if you only want one article, and just plain boredom. I wasn't trying to call you out, it was more of a question for society at large.

Why has it become more appealing to have a "content creator" turn 5 phrases of news into a 12 minute video and then have an LLM convert it back, rather than reading the 5 phrases?

> that there is something fundamental to the human spirit that relishes a sort of friction that LLMs cannot observe or reproduce on their own.

    Whatever happens, we have got
    The Maxim gun, and they have not.

Yeah, I think this is always the case. We get more powerful tools that do the same thing in 5th amount of time, now we are asked to do 5x more. Capitlalism.

Have a look here [1] and here [2] - I think they are good resources, but fallible in the long run. I think yes, I do, often confirmed by communication with people I know (i.e. i suspect they have used AI to make something -> I ask). This falls victim to confirmation bias, though. I suspect a nontrivial amount of writing I read is AI generated without me realising, and I'm wary also of falsely flagging AI-generated content that is actually from humans.

[1] https://en.wikipedia.org/wiki/Wikipedia%3AAI_or_not_quiz [2] https://en.wikipedia.org/wiki/Wikipedia%3ASigns_of_AI_writin...

Yes, here, reddit, X, at work in people's emails and status reports.

You will start to recognize it over time. The major AI models each have their own voice and patterns that they overuse.

The more you see those patterns the more you start recognizing them. By now I can recognize quickly if a blog post or README.md was generated by Claude or ChatGPT because the signs are so obvious.

Even Hacker News comments that are AI written are easy to spot if they weren't edited. I know I'm not alone because when I recognize an AI comment I check their comment history and find other people calling out their AI-generated submissions, too.

Learning how to recognize the output of the popular AI models is becoming a critical business skill, too. You need to be able to separate out the content from someone who was doing real work that you should take seriously as opposed to the output of someone who is having ChatGPT produce volumes of text that they don't review. The people who do that will waste your time.

Yes, often, and often here on HN or Substack if I point it out, it doesn't lead to anything good. Many don't recognize it, many do, the author gets defensive etc.

This article doesn't have the tells, it looks human written.

Literally every day from green accounts on Hacker News, and in many, many TFAs.

My comment history is months of me pointing it out about articles here. You're just not noticing it, it's everywhere and is extremely obvious to me.

It's possible I should envy you, I'm not sure.

I see it all the time in basically every form of text communication. What makes you think you are not seeing it?

There's at least two comments in this submission from green accounts if you enable showdead.

All the time, especially on LinkedIn.

Yes, all the time.

HN and YouTube are the worst offenders for me.

I'm pretty sure this was written or heavily edited by an llm.

https://www.seriouseats.com/eggplant-grilling-tips-11759622

> you now are having a business is planned by a paid chatbot, they can shutdown anytime or make it more expensive

Local models are about 25 months behind the current SOTA. If that holds, businesses won't need the paid models for many things.

Could the "LLM" of 1971 DARPA produce working code that it translated from a legacy codebase to Java and this within a short timeframe? ;-)

Doesn’t it all look like child’s play though?

You would need to go back to McCullough, Pitts and von Neumann in the 1940s if you wanted to talk about where it really got started.

The 1970s were a long, dark AI winter, thanks to FUD spread by Minsky and Papert. A lot of recent work could have been done back then despite the lack of good hardware, as seen in the other HN story where the guy trained a transformer on a PDP-11. But the whole field was radioactive after their book came out.