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Two kinds of AI users are emerging

martinalderson.com

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Re: Two kinds of AI users are emerging

#211

Post by everdrive »

PunchyHamster wrote: post #142

I'd argue 2 types of users are * People using it as a tool, aware of its limitations and treating it basically as intern/boring task executor (whether its some code boilerplate, or pooping out/shortening some corporate email), or as tool to give themselves summary of topic they can then bite into deeper. * People outsourcing thinking and entire skillset to it - they usually have very little clue in the topic, are int…

And what people don't understand is that these two modes, much like those which can successfully restrict their calories and stay in shape, are dispositional more than anything. Most people will fail to "upgrade" to the better path, and people in the better path will fail to understand why most people are complaining about LLMs.

Re: Two kinds of AI users are emerging

#212

Post by djeastm »

decimalenough wrote: post #18

> I helped one recently almost one-shot[3] converting a 30 sheet mind numbingly complicated Excel financial model to Python with Claude Code. I'm sure Claude Code will happily one-shot that conversion. It's also virtually guaranteed to have messed up vital parts of the original logic in the process.

I doubt that 30-sheet Excel model itself was validated by the most rigorous of standards. Unless it had its own test suite before the one-shot (which could be leveraged by the AI), people have probably been taking its outputs for granted for years.

Re: Two kinds of AI users are emerging

#213

Post by netdevphoenix »

PunchyHamster wrote: post #142

I'd argue 2 types of users are * People using it as a tool, aware of its limitations and treating it basically as intern/boring task executor (whether its some code boilerplate, or pooping out/shortening some corporate email), or as tool to give themselves summary of topic they can then bite into deeper. * People outsourcing thinking and entire skillset to it - they usually have very little clue in the topic, are int…

> The second group is one that thinks talking to a chatbot will replace senior developer

No one is going to replace senior developers. But senior developer pay WILL decrease relative to its historical values.

Re: Two kinds of AI users are emerging

#214

Post by rob »

The number of people I've run into with a non-technical background that think ChatGPT is the definitive end-all for AI is very high. Most just don't know anything else even exists.

I do wonder how long they'll be able to use this to their advantage before something "else" comes along. Like how IE had the largest market share before Chrome and other alternatives started catching up.

Then again, some markets like YouTube still haven't had any real serious alternatives. Maybe ChatGPT will always be number one in the consumer eyes.

Re: Two kinds of AI users are emerging

#215

Post by sharperguy »

netdevphoenix wrote: post #213
PunchyHamster wrote: post #142

I'd argue 2 types of users are * People using it as a tool, aware of its limitations and treating it basically as intern/boring task executor (whether its some code boilerplate, or pooping out/shortening some corporate email), or as tool to give themselves summary of topic they can then bite into deeper. * People outsourcing thinking and entire skillset to it - they usually have very little clue in the topic, are int…

> The second group is one that thinks talking to a chatbot will replace senior developer No one is going to replace senior developers. But senior developer pay WILL decrease relative to its historical values.

Surely making use of a new tool that makes you more productive would increase your value rather than decreasing it? Especially when, knowing the kinds of mistakes AI could make that would affect your codebase negatively in terms of maintainability, security etc would require significant experience.

Re: Two kinds of AI users are emerging

#216

Post by Draiken »

unlikelymordant wrote: post #157
jjav wrote: post #153

Earlier quoted context omitted.

> Isn't this true of any greenfield project? That is a good point and true to some extent. But IME with AI, both the initial speedup and the eventual slowdown are accelerated vs. a human. I've been thinking that one reason is that while AI coding generates code far faster (on a greenfield project I estimate about 50x), it also generates tech-debt at a hyperastonishing rate. It used to be that tech debt started to cat…

In your experience, can you take the tech debt riddled code, and ask claude to come up with an entirely new version that fixes the tech debt/design issues you've identified? Presumably there's a set of tests that you'd keep the same, but you could leverage the power of ai in greenfield scenarios to just do a rewrite (while letting it see the old code). I dont know how well this would work, i havn't got to the heavy t…

Take Claude Code itself. It's got access to an endless amount of tokens and many (hopefully smart) engineers working on it and they can't build a fucking TUI with it.

So, my answer would be no. Tech debt shows up even if every single change made the right decisions and this type of holistic view of projects is something AIs absolutely suck at. They can't keep all that context in their heads so they are forever stuck in the local maxima. That has been my experience at least. Maybe it'll get better... any day now!

Re: Two kinds of AI users are emerging

#217

Post by netdevphoenix »

charcircuit wrote: post #195
aljaz823 wrote: post #189

Earlier quoted context omitted.

I'd say you're still in the group 1. Your main goal is not the app but learning German. Therefore creating the app using AI is only a means to an end, a tool, and spending time coding it yourself is not important in this context.

The AI usage was not about learning German, but for creating an app. This would be group 2. He may use the tool he made to learn German, but using that tool isn't using AI

>using that tool isn't using AI

It is though. App is using AI underneath to generate audio snippets. That's literally its purpose

Re: Two kinds of AI users are emerging

#218

Post by skywhopper »

tharkun__ wrote: post #38
majormajor wrote: post #24

Earlier quoted context omitted.

One of the dirty secrets of a lot of these "code adjacent" areas is that they have very little testing. If a data science team modeled something incorrectly in their simulation, who's gonna catch it? Usually nobody. At least not until it's too late. Will you say "this doesn't look plausible" about the output? Or maybe you'll be too worried about getting chided for "not being data driven" enough. If an exec tells an i…

This is a pet peeve of mine at work. Any and I mean any statistic someone throws at me I will try and dig in. And if I'm able to, I will usually find that something is very wrong somewhere. As in, the underlying data is usually just wrong, invalidating the whole thing or the data is reasonably sound but the person doing the analysis is making incorrect assumptions about parts of the data and then drawing incorrect co…

This is, unfortunately, a feature of a lot of these systems. The sponsors don’t want truth, they want validation. Generative AI means there don’t even have to be data engineers in the mix to create fake numbers.

Re: Two kinds of AI users are emerging

#219

Post by K0balt »

gingersnap wrote: post #138
K0balt wrote: post #91

Earlier quoted context omitted.

It seems to be fantastic up to about 5k loc and then it starts to need a lot more guidance, careful supervision, skepticism, and aggressive context management. If you’re careful, it only goes completely off the rails once in a while and the damage is only a lost hour or two. Overall, still a 4x production gain overall though, so I’m not complaining for $20 a month. It’s especially good at managing complicated aspects…

Yes, I see the same thing. My working thesis is that if I can keep the codebase modular and clear seperations, so I keep the entire context, while claude code only need to focus on one module at a time, I can keep up the speed and quality. But if I try and give it tasks that cover the entire codebase it will have issues, no matter how you manage context and give directions. And again, this is not suprising, humans do…

Yes. Spot on. The good thing is that it makes better code if modularity is strict as well.

I’m finding that I am breaking projects down into clear separations of concerns and designing inviolate API walls between modules, where before I might have reached into the code with less clearly defined internal vs external functions.

Exercising solid boundaries and being maniacal about the API surface is also really liberating personally, less cognitive load, less stress, easier tests, easier debugging.

Of course none of this is new, but now we can do it and get -more- done in a day than if we don’t. Building in technical debt no longer raises productivity, it lowers it.

If you are a competent engineer, ai can drastically improve both code quality and productivity, but you have to be capable of cognitively framing the project in advance (which can also be accelerated with ai). You need to work as an architect more than a coder.

Re: Two kinds of AI users are emerging

#220

Post by xmcqdpt2 »

PunchyHamster wrote: post #144
stego-tech wrote: post #80

Earlier quoted context omitted.

Enterprise IT dinosaur here, seconding this perspective and the author’s. When I needed to bash out a quick Hashicorp Packer buildfile without prior experience beyond a bit of Vault and Terraform, local AI was a godsend at getting me 80% of the way there in seconds. I could read it, edit it, test it, and move much faster than Packer’s own thin “getting started” guide offered. The net result was zero prior knowledge t…

Yeah, I use it to get some basic info about topic I know little of (as google search is getting worse by the day..). That then I check. Honestly the absolute revolution for me would be if someone managed to make LLM tell "sorry I don't know enough about the topic", one time I made a typo in a project name I wanted some info on and it outright invented commands and usages (that also were different than the project I w…

> Honestly the absolute revolution for me would be if someone managed to make LLM tell "sorry I don't know enough about the topic"

https://arxiv.org/abs/2509.04664

According to that OpenAI paper, models hallucinate in part because they are optimized on benchmarks that involve guessing. If you make a model that refuses to answer when unsure, you will not get SOTA performance on existing benchmarks and everyone will discount your work. If you create a new benchmark that penalizes guessing, everyone will think you are just creating benchmarks that advantage yourself.

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