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The AI coding trap

chrisloy.dev

241–250 of 424 posts

Re: The AI coding trap

#241
post #94

For now, my mind is still made up. I leave the door open to be shown any serious piece of software that is built primarily through agentic workflows. Having tried to use these tools over the past month to build a critical piece of infrastructure for my company, I agree with OP. I spent so much time wrangling back unnecessary garbage that the LLM found was important, that I wondered if just writing it in one shot woul…

> Son, your system is not durable, your tests are misleading, and you can't reason about what's happening

You just described the majority of pre-LLM enterprise software.

Re: The AI coding trap

#242
post #56

Earlier quoted context omitted.

On a mac you can just use a hotkey to talk to an agentic CLI. It needs to be a bit more polished still IMO, like removing the hotkey requirement, with a voice command to break the agents current task.

Does it use an LLM powered voice to text model ? I find the generic ones like the ones I can use anywhere on Mac to be crap. If you've used the ChatGPT voice to text model you know what I mean.

Have you tried Soniox? It's really not expensive ($0.12/h, $200 free credits when you sign up) and really accurate.

https://soniox.com/

You can use it with Spokenly (free app, bring your own Soniox API key) on macOS and iOS (virtual voice keyboard)

https://spokenly.app/

Disclaimer: I've worked for Soniox

Re: The AI coding trap

#243

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…

Agree. I've never had the attention span to learn code, but I utilize LLM's heavily and have recently started managing my first large coding project with CC to what seems like good results.

As LLM get better, more and more people will be able to create projects with only rudimentary language understanding. I don't think LLMS can ever be as good as some of the outrageous claims; it's a lot like that 3rd grade project kids do on writing instruction on making a PB&J. LLM's cannot read minds and will only follow the prompt given to them. What I'm trying to say is that eventually there will be a time where being able to effectively manage coding agents efficiently will be more externally valuable than knowing how to write code.

This isn't to say that engineering experience is not valuable. Having a deep understanding of how to design and build secure and efficient software is a huge moat between experienced engineers and vibecoders like me, and not learning how to best use the tools that are quickly changing how the world operates will leave them behind.

Re: The AI coding trap

#244
post #242

Earlier quoted context omitted.

Does it use an LLM powered voice to text model ? I find the generic ones like the ones I can use anywhere on Mac to be crap. If you've used the ChatGPT voice to text model you know what I mean.

Have you tried Soniox? It's really not expensive ($0.12/h, $200 free credits when you sign up) and really accurate. https://soniox.com/ You can use it with Spokenly (free app, bring your own Soniox API key) on macOS and iOS (virtual voice keyboard) https://spokenly.app/ Disclaimer: I've worked for Soniox

Why would I buy this if my Mac has it for free? Is it “just better”?

Re: The AI coding trap

#245
post #144
post #124

Earlier quoted context omitted.

> — 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?

Intellectual property theft? If gp’s referring to the Books3 shadow library not having been legally bought, it’s not realistically more than 197k books worth less than $10MM. And let’s not forget Intellectual property rights only exist “ To promote the Progress of Science and useful Arts.”

There's certainly some debate to be had about ingesting a book about vampires and then writing a book about vampires.

But I think programming is much more "how to use the building blocks" and mathematics than ingesting narratives and themes. More like ingesting a dictionary and thesaurus and then writing a book about vampires.

Re: The AI coding trap

#246
post #133

Earlier quoted context omitted.

> What's the difference between a messy codebase created by a genAI, and a messy codebase where all the original authors of the code have moved on and aren't available to ask questions? The difference is the hope of getting out of that situation. If you've inherited a messy and incoherent code base, you recognize that as a problem and work on fixing it. You can build an understanding of the code through first reading…

So there’s another force at work here that to me answers the question in a different way. Agents also massively decrease the difficulty of coming into someone else’s messy code base and being productive. Want to make a quick change or fix? The agent will likely figure out a way to do it in minutes rather the than hours it would take me to do so. Want to get a good understanding of the architecture and code layout? Wo…

In my experience this approach is kicking the can down the road. Tech debt isn't paid down, it's being added to, and at some point in the future it will need to be collected.

When the agent can't kick the can any more who is going to be held responsible? If it is going to be me then I'd prefer to have spent the hours understanding the code.

Re: The AI coding trap

#247
post #110

I think what the article gets at, but doesn't quite deliver on, is similar to this great take from Casey Muratori [1] about how programming with a learning-based mindset means that AI is inherently not useful to you. I personally find AI code gen most useful for one-off throwaway code where I have zero intent to learn. I imagine this means that the opposite end of the spectrum where learning is maximized is one where…

"learning is maximized is one where the AI doesn't generate any code for me"

Obviously you have to work to learn, but to me this is a bit like saying learning is maximized when you never talk to anyone or ask for help — too strong.

Re: The AI coding trap

#248
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 would love to see an anti-AI take that doesn't hinge on the idea that technology forces people to be lazy/careless/thoughtless.

It’s not force but simply human nature. We invent tools to do less. That’s the whole point of tools.

Re: The AI coding trap

#249
post #242

Earlier quoted context omitted.

Have you tried Soniox? It's really not expensive ($0.12/h, $200 free credits when you sign up) and really accurate. https://soniox.com/ You can use it with Spokenly (free app, bring your own Soniox API key) on macOS and iOS (virtual voice keyboard) https://spokenly.app/ Disclaimer: I've worked for Soniox

Why would I buy this if my Mac has it for free? Is it “just better”?

It's really accurate and supports 60+ languages

Re: The AI coding trap

#250
Looks like another BS article that tries to compare a junior dev. to an AI. And its not even close. Anyone that actually tried to use AI tooling should know better. Feels like the CEOs that got sold this ideas are force-feeding this idea to senior devs and sadly senior devs are trying to gulp it down instead of rejecting the entire idea.

LLMs are more like a lightning fast pseudo-random text generator at this point. To see that though you'd need to run it a few times, test it and understand the output. Something that's a bit beyond the casual amateur ability. Maybe what we need is the AI bubble to burst first.

Its sad that we've gotten here though. Every tried having a coffee with your preferred AI as opposed to doing it with a highly motivate junior? Maybe you're not even going to get a chance to experience this.

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