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AI coding

geohot.github.io

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Re: AI coding

#231

Post by triyambakam »

matt3D wrote: post #70

This is a more extreme example of the general hacker news group think about AI. Geohot is easily a 99.999 percentile developer, and yet he can’t seem to reconcile that the other 99.999 percent are doing something much more basic than he can ever comprehend. It’s some kind of expert paradox, if everyone was as smart and capable as the experts, then they wouldn’t be experts. I have come across many developers that beha…

It also seems wildly inconsistent for someone who founded a self driving company. If models can't write code, which is a very constrained problem space, how are they supposed to drive?

Re: AI coding

#232

Post by thesurlydev »

bdcravens wrote: post #25

I'm almost 50, and have been writing code professionally since the late 90s. I can pretty much see projects in my head, and know exactly what to build. I also get paid pretty well for what I do. You'd think I'd be the prototype for anti-AI. I'm not. I can build anything, but often struggle with getting bogged down with all the basic work. I love AI for speed running through all the boring stuff and getting to the goo…

This resonates with me. I'm also around the same age and have the same amount of experience.

I love AI and use it for both personal and work tasks for two reasons:

1. It's a way to bounce around ideas without (as much) bias as a human. This is indispensable because it gives you a fast feedback mechanism and validates a path.

2. It saves me typing and time. I give it one-shot, "basic work" to do and it's able to do accomplish at least 80% of what I'd say is complete. Although it may not be 100% it's still a net positive given the amount of time it saves me.

It's not lost on me that I'm effectively being trained to always add guardrails, be very specific about the instructions, and always check the work of AI.

Re: AI coding

#233

Post by jasonjmcghee »

sltr wrote: post #198

What an aggressive tone. By the author's implied definition of compiler, a human is also a compiler. (Coffee in, code out, so the saying goes.) But code is distinct from design, and unlike compilers, humans are synthesizers of design. LLMs let you spend more time as system architect instead of code monkey.

I wouldn't over index on his tone here- that's the only tone I've seen him use.

Re: AI coding

#234

Post by tokioyoyo »

folkrav wrote: post #185
matt3D wrote: post #70

This is a more extreme example of the general hacker news group think about AI. Geohot is easily a 99.999 percentile developer, and yet he can’t seem to reconcile that the other 99.999 percent are doing something much more basic than he can ever comprehend. It’s some kind of expert paradox, if everyone was as smart and capable as the experts, then they wouldn’t be experts. I have come across many developers that beha…

> the general hacker news group think about AI I’m surprised to see this. From my perspective, reading comments and seeing which posts rise to the top, HN as a whole seems pretty bullish on the tech as whole…

It’s changing over time. When copilot came out a few years ago, people were very against it due to it being trained oh GitHub codebase. Now there’s more support around it.

Re: AI coding

#235

Post by y1n0 »

matt3D wrote: post #70

This is a more extreme example of the general hacker news group think about AI. Geohot is easily a 99.999 percentile developer, and yet he can’t seem to reconcile that the other 99.999 percent are doing something much more basic than he can ever comprehend. It’s some kind of expert paradox, if everyone was as smart and capable as the experts, then they wouldn’t be experts. I have come across many developers that beha…

I don’t know. He covers this pretty early in the post.

> The only reason it works for many common programming workflows is because they are common. The minute you try to do new things, you need to be as verbose as the underlying language.

Re: AI coding

#236

Post by pier25 »

> It’s why the world wasted $10B+ on self driving car companies that obviously made no sense

Anyone knows what the author is referring to here?

I'm guessing a lot more than $10B has been invested into self driving. So probably referring to failed companies. But which ones?

Re: AI coding

#237

Post by within_will »

Natural language becomes like an abstraction above the high-level languages then, even above things like Scratch and Basic. But you can't define how big of an abstraction it is exactly, like I can say "write an GPS app" or "write a function that does x"

The former is more abstracted and the latter is less. It's this ambiguity and non-determinism that's tricky.

Re: AI coding

#238

Post by dmh2000 »

I'm 72, a dev for 40 years. I've lost a step or two. It's harder to buckle down and focus, but using AI tools have enabled me to keep building stuff. I can spec a project, have an agent build it then make sure it works. I just code for fun anyway.

Re: AI coding

#239

Post by leptons »

ChrisMarshallNY wrote: post #2

> AI makes you feel 20% more productive but in reality makes you 19% slower. How many more billions are we going to waste on this? Adderall is similar. It makes people feel a lot more productive, but research on its effectiveness[0] seems to show that, at best, we get only a mild improvement in productivity, and marked deterioration of cognitive abilities. [0] https://pmc.ncbi.nlm.nih.gov/articles/PMC6165228/

I suppose you've never used Adderall during coding sessions before (and assuming you don't have a prescription for ADHD).

Re: AI coding

#240

Post by insane_dreamer »

athrowaway3z wrote: post #116
vmg12 wrote: post #31

I think this gets to a fundamental problem with the way the AI labs have been selling and hyping AI. People keep on saying that the AI is actually thinking and it's not just pattern matching. Well, as someone that uses AI tools and develops AI tools, my tools are much more useful when I treat the AI as a pattern matching next-token predictor than an actual intelligence. If I accidentally slip too many details into th…

Both CRUD and boilerplate are arguably a tooling issue. But there are also a bunch of things only AI will let you do. My tests with full trace level logging enabled can get very verbose. It takes serious time for a human to parse where in the 100 lines of text the relevant part is. Just telling an AI: "Run the tests and identify the root cause" works well enough, that nowadays it is always my first step.

Yesterday I used Opus to diagnose an error and it sent me down a bunch of wrong paths, suggested fixes with bad unintended consequences. If I hadn’t carefully guided it and corrected it, not only would the bug not have been fixed but it would have made things worse. My point being that if you don’t have the domain knowledge and put on your thinking cap then you will likely be screwed. But this is not how AI is sold.
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