My #1 issue with AI for programming is that while I do trust it to produce OK boilerplate code, I can also just download that boilerplate code, if I haven't already written it myself. Free software is the answer.
AI’s coding evolution hinges on collaboration and trust
121–130 of 164 posts
Re: AI’s coding evolution hinges on collaboration and trust
#122“If it takes longer to explain to the system all the things you want to do and all the details of what you want to do, then all you have is just programming by another name,” I think this is going to make the difference between junior and senior engineers even more drastic than it is today. It's really hard to know what/how to even describe real problems to these tools, and the people who invest the most in their too…
That quote really perfectly encapsulates the challenge with these tools. There is an assumption that inherently code is hard to write and so if you could code in natural language it would save time. But code isn’t actually that hard to write. Sure some people are genuinely bad at it just like I’m genuinely bad at drawing but a bit of practice and most people can be perfectly competent at it. The hard part is the engi…
[dead]
Re: AI’s coding evolution hinges on collaboration and trust
#123My #1 issue with AI for programming is that while I do trust it to produce OK boilerplate code, I can also just download that boilerplate code, if I haven't already written it myself. Free software is the answer.
This is profound, and I think you have dove to the core of why LLMs are taking off for code.
They fix a problem: the mutual incompatibility between software. "Free software" is not the answer, as it's used today: for example, the canonical Free Software OS, Linux, is fragmented into many mutually incompatible ABIs.
We need to tear down barriers between software. Barriers between languages, frameworks and OS ABIs. I don't have a good plan , but think it is the true solution. LLMs paper over these incompatibilities, and in doing so, provide value. Imperfect, but good enough until we destroy the barriers properly.
Example: Why am I using an LLM for my rust code? Because it is taking code that solves my problem, but in Python, C, or papers, and translating in a way compatible with the rust dialect I use. The problem is solved multiple times, but not in a way I can use without a translation layer. LLMs provide that.
Re: AI’s coding evolution hinges on collaboration and trust
#124Earlier quoted context omitted.
> what makes you think they couldn't produce a larger, smarter, more expensive model? Because they already did try making a much larger, more expensive model, it was called GPT-4.5. It failed, it wasn't actually that much smarter despite being insanely expensive, and they retired it after a few months.
that was not a reasoning model.
None of them are reasoning models. Some of them have a loop of word-outputting.
Re: AI’s coding evolution hinges on collaboration and trust
#125Earlier quoted context omitted.
It doesn’t develop any thinking, it’s just predicting tokens based on a statistical model. This has been demonstrated so many times. They don’t make mistakes. It doesn’t make any sense to claim they do because their goal is simply to produce a statistically likely output. Whether or not that output is correct outside of their universe is not relevant. What you’re doing is anthropomorphizing them and then trying to ex…
When you reach into a "statistical model" and find that it has generalized abstracts like "deceptive behavior", or "code error"? Abstracts that you can intentionally activate or deactivate - making an AI act as if 3+5 would return a code error, or as if dividing by zero wouldn't? That's abstract thinking. Those are real examples of the kind of thing that can be found in modern production grade AIs. Not "anthropomorph…
I don't think you have any idea what you're talking about at all.
You've clearly read a lot of social media content about AI, but have you ever read any philosophy?
Re: AI’s coding evolution hinges on collaboration and trust
#126Earlier quoted context omitted.
> Everyday, I see ads on YouTube with smooth-talking, real-looking AI-generated actors. Each one represents one less person that would have been paid. Were AI-generated actors chosen over real actors, or was the alternative using some other low-cost method for an advertisement like just colorful words moving around on a screen? Or the ad not being made at all? The existence of ads using generative AI "actors" doesn't…
It's really both effects happening at once. AI is just like the invention of the assembly line, or the explosion of mass produced consumer packaged goods starting from the first cotton gin. Automation allows a massive increase in quantity of goods, and even when quantity comes with tradeoffs to quality vs artisanally produced goods, they still come to dominate. Processed cheese or instant coffee is pretty objectively…
the crazy thing is, I can get locally-roasted beans that are single-origin microlots from all over the world, in part because of the coffee boom that was a result of instant coffee and the desire for better.
Re: AI’s coding evolution hinges on collaboration and trust
#127True, but it's catching up fast. A year ago, I used AI for small OS scripts. It worked fine and saved me the time of looking up switches for commands. Now, I can ask it to create a simple game of about 200 lines, and it does a pretty good job of writing bug-free code within a few seconds. It's only going to get better. Even if the tech doesn't improve further, I can see a future where all apps are endlessly configura…
> Programming has mainly been a career that requires the individual to understand English. Disagree, programming is a career where in order to be good you can 1. Break down a big problem into smaller ones, creating abstractions 2. Implement those abstractions one by one to end up with a full program 3. Refactor those abstractions if requirements change or (better) reimplement an abstraction a different way You do all…
> I can't imagine the vendor lock in of that.... You have the source, but it is in such a state that no human can maintain it?
It’s much worse than that.
What happens when the erroneous output caused by model blind spots gets fed back into the model?
Those blind spots get reinforced.
Doesn’t matter how small that error rate is (and it’s not small). The errors will compound.
Vendor lock-in won’t matter because it will simply stop working/become totally unrecoverable.
Re: AI’s coding evolution hinges on collaboration and trust
#128True, but it's catching up fast. A year ago, I used AI for small OS scripts. It worked fine and saved me the time of looking up switches for commands. Now, I can ask it to create a simple game of about 200 lines, and it does a pretty good job of writing bug-free code within a few seconds. It's only going to get better. Even if the tech doesn't improve further, I can see a future where all apps are endlessly configura…
I think you're right that LLMs are democratizing access to coding, but unless and until AI models reach a point where they can say 'no' to their users, the scenario you're imagining ('endlessly configurable apps') will probably lead to software that collapses under its own complexity.
Years ago, I supported a team of finance professionals who were largely quite competent at coding but knew nothing about software engineering. They had thousands of scripts and spreadsheets: they used version control, but kept separate long-lived branches for client-specific variations of different models. There were no tests for anything; half the tools would break when the clocks changed.
They weren't dumb, but their incentives weren't about building anything we might recognize as an engineered application. I suspect something similar will happen turning end users loose with AI.
Re: AI’s coding evolution hinges on collaboration and trust
#129I don't like the phrase "real coder". It's not clear what it means.
I really like the word "assistant" for what we have today. The AI code assistant tools available today, like Claude Code and GitHub Copilot, can't replace humans in doing software development. Not even close. But they are often useful to human developers, and today, that's the more important measure.
I've been spending time with various AI tools, especially Claude Code and GitHub Copilot. They're amazing one minute, and they make bone-headedly bad recommendations the next. It takes effort to learn how to create good prompts, and if you want the results to be good, you have to review and critique the results. I'm particularly concerned about security. They're definitely happy to write insecure code. If you know what you're doing, prompt them well, and review their results, you can get good results.
I don't know if they'll ever reach "full autonomy". They don't need to get there to be useful.
Re: AI’s coding evolution hinges on collaboration and trust
#130Earlier quoted context omitted.
Generative AI is replacing writers, designers, actors, ... it is nothing like just a spell checker or Phtoshop. Everyday, I see ads on YouTube with smooth-talking, real-looking AI-generated actors. Each one represents one less person that would have been paid. There is no exact measure of correctness in design; one bad bit does not stop the show. The clients don't even want real art. Artists sometimes refer to commer…
I agree with your sentiment. But where I struggle is: to what degree do each of those ads “represent one less person who would have been paid” versus those that represent one additional person who would not be able to afford to advertise in that medium. Of course that line of reasoning reduces similar to other automation / minimum wage / etc discussions
Obviously there's some mix of the two, but given then I've seen AI used (poorly) for both TV commercials (in expensive time slots) and billboards (I think expensive as well, but I don't really know) where you know they can afford to pay "real people" to do it, there's definitely a noticeable amount of real replacement.