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information on how the current API of some-thing works into my brain fast enough, because the docs are non existent, outdated, or scattered and hard to collate.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 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 do think people are going way overboard with markdown though, and that'll be the new documentation debt. Needs to be relatively high level and pointers, not duplicate details; agents can parse code at scale much faster than humans.
Docs as code is still writing and not coding. Those are simply different skills. As programmers, we find coding to be fun and glamorous and writing to be difficult. Emotionally, it's much easier to finish a piece of code and feel genuinely happy with it (you are proud of your achievement) than it is to write a paragraph of docs and feel genuinely happy with it (you can feel in your bones that it's not good but you don't know how to improve it and you just want it over with). We have not built anywhere near the level of skill for writing than we did for coding when we wrote our own little programs for ourselves and never built a habit of thinking about how other people would interact with our code.
(For me, this is exacerbated by having been more isolated from other people than the average population, partly due to neurodivergence and partly because the hobby was niche at the time, and I assume this is also true of a lot of people currently employed as professional programmers.)
I do welcome the improvements to doc and APIs this brings though!
Last week, a colleague finally added for Claude all the documentation I'd have needed on day one. Meanwhile, I'm addressing issues from the other direction, writing custom linters to make sure that Claude progressively fixes its messes.
Which of course reduces traffic to sites and thus the incentives to create the content you're looking for in the first place :(
The traditional search results suffer a lot because AI and AI content generation have enable a lot of aggressive SEO/spam plays.
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...!
Pragmatic sure, but we're building a tower of chairs here rather than building ladders like a real engineering field.
I don't bring huge codebases to it.
I was able to one-shot a parameterized SVG template creator for a laser cutter. Unlikely I could have achieved the same with 40 hours of pure focus.
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++.
You can have the Kotlin experience with a mix of static asserts, constexpr and concepts.
C++ IDEs also offer many goodies which those that insist in using vi and emacs keep missing out.
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.
Someone at work recently termed this “Claude Creep”. It’s so easy to generate things push you towards going further but the reality is that’s you’re setting yourself up for more and more work to get them over the line.
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.
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.
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.
> I’ve had the idea that from a social perspective it’d be regarded like plastic surgery, in that it only looks weird when its over-done, or done badly.
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.
My family, close friends, and my partner will definitely tell me when I neglect or abuse my mental and physical health. This includes bad decisions about the way I look.
And every time they do this I am thankful to them, because they usually notice these things way sooner than I would have.
Just post a picture on the internet and let strangers comment. You will absolutely get honest feedback, but you probably don’t really want that. TBH same with code and ideas, given the reception my articles have had over the years on HN and Reddit. Can be brutal.
One big issue I've found is that HN seems to automatically comments from all new users, no matter the content. I used to try to change handles every so often because HN doesn't allow people to delete their comments after the first hour, which becomes a bigger and bigger privacy issue over time (and frankly, extremely hostile to users). Especially for those of use who don't use AI, our individual writing styles are likely identifiable over a long enough period of time.
But the last few times I tried it, all of my comments were immediately shadowbanned. No notification or any indication on the new account, but if I checked with an older account, the comments were all "dead." I try to put effort into my comments, reading through the entirety of the comment I'm replying to (often multiple times), proofreading them myself (I never use AI), and linking to any claims I'm making. All of this takes considerable time. It's extremely frustrating to put that kind of effort into a comment and have it autobanned. It's even more frustrating when the system deceives you and makes you believe it's been posted, and you have to check with another account to learn that it was actually set to dead.
Supposedly there's a desire for comments that people put effort into and aren't written by AI. But why would new users bother putting in that work when their comments get automatically and secretly killed, without them having any way of knowing?
I'm starting to think that the best solution is to move away from these types of online communities in general.
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.
We always find that small teams of locals can do much much more than a team with an unlimited number of low cost "developers". Not just because the competence of low cost devs is poor, but also the structure of how you work changes for the worse with a bigger team, for the worse with a distributed team, and for the worse with a skill-diverse team.
Thats before you get into the cultural flaws of favored destinations like India.
So we have been able to argue things like add one local + ai is better than about 20-100 Indians, depending on role and business structure needed to manage low-competence low-trust "developers". So we are planning to completely on-shore in the near future.
The bean counters are happy, and the quality of the work is improving.
And you just say this like it’s nothing. Lack of respect to tons of Indian people who work in IT, of which I have had the pleasure to work with.
I do not believe I have even seen "good value" output.
What is there to respect?
The historical value of a low cost region is get crap work for few dollars. "Just barely good enough". AI can do this by itself.
If you add AI to poor work, you get more extremely shit work for less dollars. If you add AI to a skilled worker you get a large volume of OK to poor work.
Basically my suspicion is as the tools improve they make low skill regions obsolete first.
There are many reasons why; but simply there is no surplus of super developers anywhere; you might find one anywhere, but they will not stay low cost for very long... And if you try to structure your business to find any number of employees overseas you quickly become overwhelmed by the averages and cultural practices of an area.
I fully believe its possible to find a single competent Brazilian or Indian for cheaper than in the west, but I dont think its possible to structure a company in a way that you can hire 20.
And they write hundreds of MD files (for skills) that never break. No sense of accountability.
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.
AI is not a feature of the product. GTM will be interesting, have some good ideas.
It's really up to you to be clever. I've never used Js/Ts/node/these apis etc. I started programming as a non-cs engineer to automate stuff and then got into SWE. This is truly an amazing time.
I've seen a few live streams vibecoding video games on Twitch, and it was so hilariously bad and cringe-inducing I am back working on (hobby) game dev, my hopes restored, at least for the immediate future.
I also like how that entire field, gamers and devs, compared to regular software engineering, is so set against AI it can provide some pushback to the starry-eyed comments you read on here all the time. The only people using LLMs in gamedev are grifters and the dreaded idea people with not a single bone of talent or love for the craft in their body.
What happened to your hope previously?
Did you get discouraged by the idea that it was now easier for other people to make games?
I'm curious about this anti-AI sentiment you're talking about in the games world. I'm not really part of any gamedev communities, but I did make some simple browser games myself, including a multiplayer game. (In early 2024 I was doing a game jam every week!)
I didn't use much AI at the time, maybe copy-pasted a few snippets from ChatGPT, and that really felt like cheating!
I'm getting back into game dev now, after becoming a lot more comfortable with AI programming tools. I haven't really used AI for game dev, but I imagine they'd be helpful with some aspects like debugging, and the usual code snippets (tab complete etc).
The games my friends are making are text-based, "choose your own adventure" type games (interactive fiction?), so it's pretty straightforward for LLMs. I don't imagine they'd do very well with realtime stuff though, at least not without very heavy hand holding.
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.
The style isn’t a limit of the technology, it’s a limit of the lobotomized models from OpenAI and Anthropic. The open source community has lots of models that are great at creative writing.
would you mind sharing some examples please?
The section about being "glazed" into action resonates. Hidden within this concept I think is something profound about human motivation, innuendo and all.
> AI generated prose is at best boring, and at worst genuinely unappealing. I’m continually tempted, because in theory it should work well. The AI has perfect spelling and grammar, has more than enough context to produce article-length content, and can do in seconds what takes me hours.
I have a thesis in mind...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.I think we'll find that for most AI stuff.
Since LLMs, if I see a video I think is interesting, I take the transcript, feed it into an LLM, I summarize it and ask it a couple of questions. I've turned 12 minute videos back into the 5 phrases news it was based on. I suppose that when you're the one generating the request, it feels more personal. It is also very interesting that most LLMs respond like a normal person when you talk to them directly, but suddenly adopt the more annoying blogger speech patterns when you tell them 'create content'.
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?
Also, with videos like "what X said about situation Y in discourse Z". Sometimes you're just curious, and you can't realistically extract that efficiently from a full one-hour speech on a geolocked, untranscribed mass-media website, so it's easier to summarize the transcript of the 12 min video directly.
As for why everything is 12 minutes long, it's most likely because content creation isn't optimized to teach you anything or be useful, it's optimized to maximize watch time so platforms can serve more ads to you. The pattern is: I got you intrigued in something; you want the answer? pay me your time.
Marketers present a list of potential problems
The smallest success stories are marketed as indicators of future success, but to verify this, one must wait patiently for the future to arrive
> For now at least I’m keeping my Claude Pro subscription, but given the persistant rumors of undisclosed rate limiting, and ever improving performance of local LLMs, I can easily imagine that I’ll cancel my subscription before the end of the year.
I would be interested what date this was? I am surprised if it's been recent that Claude didn't 1 shot this.
a system that can allocate all the atoms / energy better than all of mankind won't eternally exist to coddle hairless apes
[1] https://en.wikipedia.org/wiki/Wikipedia%3AAI_or_not_quiz [2] https://en.wikipedia.org/wiki/Wikipedia%3ASigns_of_AI_writin...
AI generated. Some of the clues include:
- Most obviously, a failed ISBN checksum
- Other source-to-text integrity issues; for example, the WWF source says very little about Malaysia specifically, only mentions Sunda tigers (Panthera tigris sondaica), and does not mention tapirs at all
- Very short yet consistent paragraph length
- Generic "see also" links, one of which is redlinked
This is not the sort of thing that I pay attention to unless I'm doing detailed research. And even then I'd probably have a bot check these for me, ironically, since it's such a mechanical job. At the very least detecting AI like this requires conscious effort.
I can easily tell AI writing. I'm sure plenty goes under the radar, but I can still catch a lot.
The gap between LLM-generated writing and the composite style of the average Wikipedia page is more narrow than most people may believe.
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.
However the default tone and output style of Claude and ChatGPT are very obvious.
> My recollection is whenever I've seen data on this--the educators who think they can spot students cheating--the conclusion is people are really bad at identifying LLM-generated content.
If you can share that data we can discuss it, but there's nothing really to discuss here without a source
Among people who review a lot of user-submitted content, it becomes easy to spot the consistent voice of LLM writing. Wikipedia has a full page on it: https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing
Ask it to write in the style of patio11 or someone else with a distinctive tone, and it will do a remarkable job.
It will pass pretty consistently. Not sure I love it.
This article doesn't have the tells, it looks human written.
It's possible I should envy you, I'm not sure.
I can't prove it but I'm comfortable enough in my judgment to say it.
HN and YouTube are the worst offenders for me.
My friend is trying to do the same, the Docker stack he made for his SaaS is really amazing, it is following the standards from the ancient age.
Local models are about 25 months behind the current SOTA. If that holds, businesses won't need the paid models for many things.
Some people push Claude and Claude Code at work, weights are closed, even Claude Code is completely closed and proprietary.
If terms, which Anthropic controls, ever change, all work and time spent on these products will be for naught.
No, I don’t think any skills or knowledge is acquired by the use of these tools can be reliably translated to another tool / model.
Hence I firmly think it’s utter nonsense rubbish to engage with that, and even Qwen3.5-Coder-Next plus OpenCode spits out working apps.
Really, do better product users.
Not counting from 1971s DARPA? Sorry I'm allegric when LLMs being called AI like nothing existed before it.
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.