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The AI coding trap

chrisloy.dev

121–130 of 424 posts

Re: The AI coding trap

#121
post #7

I would love to see an anti-AI take that doesn't hinge on the idea that technology forces people to be lazy/careless/thoughtless. The plan-build-test-reflect loop is equally important when using an LLM to generate code, as anyone who's seriously used the tech knows: if you yolo your way through a build without thought, it will collapse in on itself quickly. But if you DO apply that loop, you get to spend much more ti…

I never made a case against LLMs and similar ML applications in the sense that they negatively impact mental agility. The cases I made so far include, but are not limited to:

— OSS exploded on the promise that software you voluntarily contributed to remains to benefit the public, and that a large corporation cannot tomorrow simply take your work and make it part of their product, never contributing anything back. Commercially operated LLMs threaten OSS both by laundering code and by overwhelming maintainers with massive, automatically produced and sometimes never read by a human patches and merge requests.

— Being able to claim that any creative work is merely a product of an LLM (which is a reality now for any new artist, copywriter, etc.) removes a large motivator for humans to do fully original creative work and is detrimental to creativity and innovation.

— The ends don’t justify the means, as a general philosophical argument. Large-scale IP theft had been instrumental at the beginning of this new wave of applied ML—and it is essentially piracy, except done by the powerful and wealthy against the rest of us, and for profit rather than entertainment. (They certainly had the money to license swaths of original works for training, yet they chose to scrape and abuse the legal ambiguity due to requisite laws not yet existing.)

— The plain old practical “it will drive more and more people out of jobs”.

— Getting everybody used to the idea that LLMs now mediate access to information increases inequality (making those in control of this tech and their investors richer and more influential, while pushing the rest—most of whom are victims of the aforementioned reverse piracy—down the wealth scale and often out of jobs) more than it levels the playing field.

— Diluting what humanity is. Behaving like a human is how we manifest our humanness to others, and how we deserve humane treatment from them; after entities that walk and talk exactly like a human would, yet which we can be completely inhumane to, become commonplace, I expect over time this treatment will carry over to how humans treat each other—the differentiator has been eliminated.

— It is becoming infeasible to operate open online communities due to bot traffic that now dwarves human traffic. (Like much of the above, this is not a point against LLMs as technology, but rather the way they have been trained and operated by large corporate/national entities—if an ordinary person wanted to self-host their own, they would simply not have the technical capability to cause disruption at this scale.)

This is just what I could recall off the top of my head.

Re: The AI coding trap

#122
post #85

Earlier quoted context omitted.

> If the thinking bit is your favorite part, AI allows you to spend nearly all of your time there if you wish, from concept through troubleshooting. This argument is wearing a little thin at this point. I see it multiples times a day, rephrased a little bit. The response, "How well do you think your thinking will go if you had not spent years doing the 'practice' part?" , is always followed by either silence or a non…

Separate from AI, as your role becomes more tech lead / team lead / architect you're also not really "doing" as much and still get involved in a lot of thinking by helping people get unstuck. The thinking part still builds experience. You don't need to type the code to have a good understanding of how to approach problems and how to architect systems. You just need to be making those decisions and gaining experience…

> You just need to be making those decisions and gaining experience from them.

The important part that everyone glosses over is the "gaining experience" part.

The experience you gained writing code lead to you being tech lead / team lead /architect.

The experience you get from those roles, including "helping people get unstuck", makes you valuable because there are people involved, not just technology. IOW, that is different to the experience you get from prompting.

We have yet to see how valuable the experience from prompting will be. At this point the prompters are just guessing that their skills won't atrophy, and that their new experience won't be at the same level as vibe-coders who can't spell "Python".

As a fairly senior person myself, and an occasional user of LLMs, and someone who has tried CC in recent months, the experience I got from LLMs, while not nothing, was not recognised by me as valuable in any way - it basically put me at the same skill level as a vibe-coder.

OTOH, the experience I got mentoring very junior engineers the month before that I recognised as instantly valuable; at the end of it I had learned new strategies for dealing with people, growing them, etc.

The only "experience" you get with LLM is "put another coin into the slot and pull the lever again".

Re: The AI coding trap

#123

Earlier quoted context omitted.

> The article sort of goes sideways with this idea but pointing out that AI coding robs you a deep understanding of the code it produces is a valid and important criticism of AI coding. Why? Code has always been the artifact. Thinking about and understanding the domain clearly and solving problems is where the intrinsic value is at (but I'd suspect that in the future this, too, will go away).

Code isn't an "artifact", it's the actual product that you are building and delivering. You can use flowery language and pontificate about the importance of the problem domain if you like, but at the end of the day we are producing a low level sequences of instructions that will be executed by a real world device. There has always been, and likely will always be, value in understanding exactly what you are asking the…

In most domains, code is not the actual product. Data is. Code is how you record, modify and delete data. But it is ultimately data that has meaning and value.

This is why we have the idiom: “Don’t tell me what the code says—show me the data, and I’ll tell you what the code does.”

Re: The AI coding trap

#124
post #7

I would love to see an anti-AI take that doesn't hinge on the idea that technology forces people to be lazy/careless/thoughtless. The plan-build-test-reflect loop is equally important when using an LLM to generate code, as anyone who's seriously used the tech knows: if you yolo your way through a build without thought, it will collapse in on itself quickly. But if you DO apply that loop, you get to spend much more ti…

I never made a case against LLMs and similar ML applications in the sense that they negatively impact mental agility. The cases I made so far include, but are not limited to: — OSS exploded on the promise that software you voluntarily contributed to remains to benefit the public, and that a large corporation cannot tomorrow simply take your work and make it part of their product, never contributing anything back. Com…

> — The ends don’t justify the means. IP theft that lies in the beginning of this new wave of applied ML is essentially piracy

Isn't "AI coding" trained almost entirely on open source code and published documentation?

Re: The AI coding trap

#125
post #118
post #99

This diagram (which resonated): Traditional Coding: [ Thinking & Coding ....................... | Fixing ] AI-Assisted Coding: [ Coding | Thinking & Fixing ................ ] suggests a workflow where AI is used almost exclusively to speed up the writing of known, targeted code whose structure has already been thought out. And possibly as a (non-coding) sounding board during the thinking out.

The thinking part is the same, yes, but I doubt the fixing is. Fixing something you have written is much easier than fixing something someone else (or an AI) has written, just because you don't have the mental model for the code, which is the most important part of debugging and refactoring.

Agree completely -- that's what my suggestion was getting at.

Re: The AI coding trap

#126

Earlier quoted context omitted.

> The article sort of goes sideways with this idea but pointing out that AI coding robs you a deep understanding of the code it produces is a valid and important criticism of AI coding. Why? Code has always been the artifact. Thinking about and understanding the domain clearly and solving problems is where the intrinsic value is at (but I'd suspect that in the future this, too, will go away).

Reminds me of critisms of python decades ago. that you wouldn't understand what the "real code" was doing since you were using a scripting language. But then over the years it showed tremendous value and many unicorns were built by focusing on higher level details and not lower level code

Comparing LLMs to programming languages is a fake equivalence. I don’t have to write assembly because LLVM will do that for me correctly in 100% of the cases, while AI might or might not (especially the more I move away from template crud apps)

Re: The AI coding trap

#127
post #124

Earlier quoted context omitted.

I never made a case against LLMs and similar ML applications in the sense that they negatively impact mental agility. The cases I made so far include, but are not limited to: — OSS exploded on the promise that software you voluntarily contributed to remains to benefit the public, and that a large corporation cannot tomorrow simply take your work and make it part of their product, never contributing anything back. Com…

> — The ends don’t justify the means. IP theft that lies in the beginning of this new wave of applied ML is essentially piracy Isn't "AI coding" trained almost entirely on open source code and published documentation?

Yes. But here we are, people ignoring all the theft that has happened. People generating images on stolen art and call themselves artists. People using it to program and call themselves programmers. Also, it seems to me that so many people just absolutely ignore all the security related issues coming with coding agents. Its truly a dystopia. But we are on hackernews so obviously people will glaze about "AI" on here.

Re: The AI coding trap

#128

Earlier quoted context omitted.

> I would love to see an anti-AI take that doesn't hinge on the idea that technology forces people to be lazy/careless/thoughtless. The article sort of goes sideways with this idea but pointing out that AI coding robs you a deep understanding of the code it produces is a valid and important criticism of AI coding. A software engineer's primary job isn't producing code, but producing a functional software system. Most…

> The article sort of goes sideways with this idea but pointing out that AI coding robs you a deep understanding of the code it produces is a valid and important criticism of AI coding. Why? Code has always been the artifact. Thinking about and understanding the domain clearly and solving problems is where the intrinsic value is at (but I'd suspect that in the future this, too, will go away).

Code is the final artifact after everything is shipped. But while the development is active, it is more than that (at least for now), as you need to know implementation details even if you are really proficient at the domain knowledge.

Although I do agree that there is a possibility that we'll build a relatively reliable abstraction using LLMs at some point, so this issue will go away. There probably be some restrictions, but I think it is possible.

Re: The AI coding trap

#129
post #7

I would love to see an anti-AI take that doesn't hinge on the idea that technology forces people to be lazy/careless/thoughtless. The plan-build-test-reflect loop is equally important when using an LLM to generate code, as anyone who's seriously used the tech knows: if you yolo your way through a build without thought, it will collapse in on itself quickly. But if you DO apply that loop, you get to spend much more ti…

Idk I feel like even without using LLMs the job is 90% thinking and planning. And it’s nice to go the last 10% on your own to have a chance to reflect and challenge your earlier assumptions.

I actually end up using LLMs in the planning phase more often than the writing phase. Cursor is super good at finding relevant bits of code in unfamiliar projects, showing me what kind of conventions and libraries are being used, etc.

Re: The AI coding trap

#130

Earlier quoted context omitted.

"AI" does not encourage real thinking. "AI" encourages hand waving grand plans that don't work, CEO style. All pro-"AI" posts focus on procedures and methodologies, which is just LARPing thinking. Using "AI" is just like speed reading a math book without ever doing single exercise. The proponents rarely have any serious public code bases.

I see a lot of comments like this and it reflects strongly negatively on the engineers who write it imho. As in I've been a staff level engineer at both Meta and Google and a lead at various startups in my time. I post open source projects here on HN from time to time that are appreciated. I know my shit. If someone tells me that LLMs aren't useful i think to myself "wow this person is so unable to learn new tools th…

Alternatively - there's 5 million other things I could be learning and practicing to improve as a programmer before trying out the new AI codegen-du-jour. Until I'm Fabrice Bellard, focusing on my fundamental skills will make me a better programmer, faster, than focusing on the hype of the day.
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