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Building better AI tools

hazelweakly.me

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Re: Building better AI tools

#101

Post by Veen »

ahamilton454 wrote: post #29

This is one of the reasons I really like deep research. It always asks questions first and forces me to refine and better define what I want to learn about. A simple UX change makes the difference between education and dumbing users of your service.

As a technical writer, I don't use Deep Research because it makes me worse at my job. Research, note-taking, and summarization are how I develop an understanding of a topic so I can write knowledgeably about it. The resulting notes are almost incidental. If I let an AI do that work for me, I get the notes but no understanding. Reading the document produced by the AI is not a substitute for doing the work.

Re: Building better AI tools

#102

Post by biophysboy »

margalabargala wrote: post #91
biophysboy wrote: post #48

Earlier quoted context omitted.

A retort you often hear is that prior technologies, like writing or the printing press, may have stunted our calligraphy or rhetorical skills, but they did not stunt our capacity to think. If anything, they magnified it! Basically, the whole Steve Jobs' bicycle-for-the-mind idea. My issue with applying this reasoning to AI is that prior technologies addressed bottlenecks in distribution, whereas this more directly at…

I still don't think that's true. It's just the medium that changes here. A better analogy than the printing press, would be synthesizers. Did their existence kill classical music? Does modern electronic music have less creativity put into it than pre-synth music? Or did it simply open up a new world for more people to express their creativity in new and different ways? "Code" isn't the form our thinking must take. To…

That's why I made a caveat that AI is only bad if it limits your creative development. Eno took synthesizers to places music never went. I'd love for people to do the same with LLMs. I do think they have more danger than synthesizers had for music, specifically because of their flexibility and competence.

Re: Building better AI tools

#103

Post by miltonlost »

margalabargala wrote: post #91
biophysboy wrote: post #48

Earlier quoted context omitted.

A retort you often hear is that prior technologies, like writing or the printing press, may have stunted our calligraphy or rhetorical skills, but they did not stunt our capacity to think. If anything, they magnified it! Basically, the whole Steve Jobs' bicycle-for-the-mind idea. My issue with applying this reasoning to AI is that prior technologies addressed bottlenecks in distribution, whereas this more directly at…

I still don't think that's true. It's just the medium that changes here. A better analogy than the printing press, would be synthesizers. Did their existence kill classical music? Does modern electronic music have less creativity put into it than pre-synth music? Or did it simply open up a new world for more people to express their creativity in new and different ways? "Code" isn't the form our thinking must take. To…

AI for writing is not like a synthesizer. It's a player piano, and people act as if they're musicians now.

Re: Building better AI tools

#104

Post by bGl2YW5j »

cmiles74 wrote: post #70
okr wrote: post #45

Earlier quoted context omitted.

Soldering transistors by hand was a thing too, once. But these days, i am not sure, if people wanna keep up anymore. Many trillions of transistors later. :) I like this zooming in and zooming out, mentally. At some point i can zoom out another level. I miss coding. While i still code a lot.

I think this is a fundamentally different pursuit. The intellectual part was figuring out where the transistors would go, that's the part that took the thinking. Letting a machine do it just let's you test quicker and move onto the next step. Although, of course, if you only solder your transistors by hand once a year you aren't likely to be very good at it. ;-) People say the same thing about code but there's been a…

Great point about the conflation. This makes me realise: for me, writing code is often a big part of thinking through the problem. So it’s no wonder that I’ve found LLMs to be least effective when I cede control before having written a little code myself, ie having worked through the problem a bit.

Re: Building better AI tools

#105

Post by leptons »

margalabargala wrote: post #91
biophysboy wrote: post #48

Earlier quoted context omitted.

A retort you often hear is that prior technologies, like writing or the printing press, may have stunted our calligraphy or rhetorical skills, but they did not stunt our capacity to think. If anything, they magnified it! Basically, the whole Steve Jobs' bicycle-for-the-mind idea. My issue with applying this reasoning to AI is that prior technologies addressed bottlenecks in distribution, whereas this more directly at…

I still don't think that's true. It's just the medium that changes here. A better analogy than the printing press, would be synthesizers. Did their existence kill classical music? Does modern electronic music have less creativity put into it than pre-synth music? Or did it simply open up a new world for more people to express their creativity in new and different ways? "Code" isn't the form our thinking must take. To…

A synthesizer is just as useless as a violin without someone to play it.

You could hook both of those things up to servos and make a machine do it, but it's the notes being played that are where creativity comes in.

I've liked some AI generated music, and it even fooled me for a little while but only up to a point, because after a few minutes it just feels very "canned". I doubt that will change, because most good music is based on human emotion and experience, something an "AI" is not likely to understand in our lifetimes.

Re: Building better AI tools

#106

Post by marcosdumay »

taylorallred wrote: post #14

One thing that has always worried me about AI coding is the loss of practice. To me, writing the code by hand (including the boilerplate and things I've done hundreds of times) is the equivalent of Mr. Miyagi's paint-the-fence. Each iteration gets it deeper into your brain and having these patterns as a part of you makes you much more effective at making higher-level design decisions.

My practice in writing assembly is so lost by now that it's not much different than if I never learned it. Yet, it's not really a problem.

What is different about LLM-created code is that compilers work. Reliably and universally. I can just outsource the job of writing the assembly to them and don't need to think about it again. (That is, unless you are in one of those niches that require hyper-optimized software. Compilers can't reliably give you that last 2x speed-up.)

LLMs by their turn will never be reliable. Their entire goal is opposite to reliability. IMO, the losses are still way higher than the gains, and it's questionable if this is an architectural premise that will never change.

Re: Building better AI tools

#107

Post by stronglikedan »

donsupreme wrote: post #17
taylorallred wrote: post #14

One thing that has always worried me about AI coding is the loss of practice. To me, writing the code by hand (including the boilerplate and things I've done hundreds of times) is the equivalent of Mr. Miyagi's paint-the-fence. Each iteration gets it deeper into your brain and having these patterns as a part of you makes you much more effective at making higher-level design decisions.

Many analog to this IRL: 1) I can't remember the last time I write something meaningfully long with an actual pen/pencil. My handwriting is beyond horrible. 2) I can't no longer find my way driving without a GPS. Reading a map? lol

I couldn't imagine operating without a paper and pen. I've used just about every note taking app available, but nothing commits anything to memory like writing it down. Of course, important writings go into the note app, but I save time inputting now and searching later if I've written things down first.

Re: Building better AI tools

#108

Post by hazelweakly »

mikaylamaki wrote: post #99

The code gen example given later sounds an awful lot like what AWS built with Kiro[1] and it's spec feature. This article is kinda like the theory behind the practice in that IDE. I wish the tools described existed instead of all these magic wands [1] https://kiro.dev/blog/introducing-kiro/

Indeed it is! In fact I actually had something like Kiro almost perfectly in mind when I wrote the article (but didn’t know AWS was working on it at the time).

I was very happy to see AWS release Kiro. It was quite validating to me seeing them release it and follow up with discussions on how this methodology of integrating AI with software development was effective for them

Re: Building better AI tools

#109

Post by nextworddev »

This post is confusing one big point which is that the purpose of AI deployments isn’t to teach so that humans get smarter but to achieve productivity at the process level by eliminating work that isn’t rewarded for human creativity

Re: Building better AI tools

#110

Post by cmiles74 »

tptacek wrote: post #74
cmiles74 wrote: post #71

Earlier quoted context omitted.

There's no AI tool today that will resolve incidents to anyone's satisfaction. People need to be in the loop not only to take responsibility but to make sure the right actions are performed.

Nobody disputes this. Weakly posits a bright line between agents suggesting active steps and agents actually performing active steps. The problem is that during incident investigations, some active steps make a lot of sense for agents to perform, and others don't; the line isn't where she seems to claim it is.

Understood. To your example about the logs, my concern would be be that the AI chooses the wrong thing to focus on and people decide there’s nothing of interest in the logs, thus overlooking a vital clue.
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