Agreed with everything @kevinriggle wrote here.
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@inthehands @RuthMalan every dev wants a greenfield project. LLMs shade even greenfield projects brown.
But then it's not the devs that are asking for this* so much as a managerial class looking for the sort of silver bullet that brings down both pay and the amount of time dealing with a type of worker they find difficult.
*not the ones who are any good, anyway
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@rgarner @RuthMalan
Yup. All that.And Brooks’s maxim that there is no silver bullet still stands undefeated.
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@inthehands I agree with all of this, and I'd add: When I'm writing code, I'm *learning* about the problem as well through the process. When I fix a bug in my code, I (hopefully) learn not to make the same mistake again. When I help someone on the team fix a bug in their code, we both learn something. If we write documentation or a unit test to make sure the bug doesn't happen again, the organization "learns" something too.
It's unclear to me whether AI is even capable of learning in this way.
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Jeff Miller (orange hatband)replied to Paul Cantrell last edited by
@inthehands I appreciate how your line of argument chimes with Fred Brooks' "No Silver Bullet", along the lines of essential complexity of the problem and the solution matching up, except the comparison here being the embedded understanding (hopefully) in code written specifically for the problem, versus the embedded unchecked assumptions in generated code.
Novel software libraries have a similar problem: easy to adopt, not necessarily easy to evaluate.
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Jeff Miller (orange hatband)replied to Paul Cantrell last edited by
@inthehands
NSB -
@inthehands @RuthMalan and that thing about adding people to projects. An LLM isn't a person quite so much as the average of some.
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Yes, this from @sethrichards is what I’m talking about:
https://mas.to/@sethrichards/113642032055823958I had a great moment with a student the other day dealing with some broken code. The proximate problem was a Java NullPointerException. The proximate solution was “that ivar isn’t initialized yet.”
BUT…
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…It wasn’t initialized because they weren’t thinking about the lifecycle of that object because they weren’t thinking about when things happen in the UI because they weren’t thinking about the sequence of the user’s interaction with the system because they weren’t thinking about how the software would actually get used or about what they actually •wanted• it to do when it worked.
The technical problem was really a design / lack of clarity problem. This happens •constantly• when writing code.
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A good point from @rgarner, looking at this through the lens of Brooks’s Law:
https://mastodon.social/@rgarner/113642040777621582 -
You are 100% correct...
...right now.
But consider this, upper limits of AI transcend human performance constraints.
One of the possible paths for AI development is you have all these multiple agents working in orchestra.
One is responsible for overall architecture.
One for environmental impact.
Etc etc.Thought provoking post.
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@n_dimension
Please note the hypothetical downthread where I ask what happens if AI transcends human coding performance by a factor of infinity.For your line of reasoning to work, this thing we call AI has to do something that LLMs simply do not do, do not approach doing, are not on a trajectory toward doing, and are fundamentally architecturally incapable of doing. It’s like saying “eventually if this car goes fast enough, it will be a time machine!”
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Dr Andrew A. Adams #FBPE 🔶replied to Paul Cantrell last edited by
@inthehands
Coding is teaching a really, really dumb student how to solve a problem.
Teaching something is the best way to understand it properly. -
@rgarner @inthehands @RuthMalan Oh, I like this one. Even if it were an actual person, it’s a person who read your code but none of the design docs and hasn’t participated in any of your team’s discussions. They’d have a good chance of coming up with something reasonable, but could also totally bodge it without realizing it.
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@inthehands Oh, why hello, Amdahl!
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@inthehands The bet that a lot of these CXOs are making implicitly is that this will be like the transition from assembly to higher-level languages like C (I think most of them are too young and/or too disconnected to make it explicitly). And I'm not 100% sold on it but my 60% hunch is that it's not.
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@inthehands kickers are only on the field for a few minutes per game, fire them and make AI punt.
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@kevinriggle
Yeah, I’ve heard that thought too. It’s tantalizing nonsense. I could write about this at length, and maybe one day I will, but the very short version is that automation is not even remotely the same thing as abstraction. -
@inthehands Yes! Yes. This is it exactly.
One can imagine a version of these systems where all the "source code" is English-language text describing a software system, and the Makefile first runs that through an LLM to generate C or Python or whatever before handing it off to a regular complier, which would in some sense be more abstraction, but this is like keeping the .o files around and making the programmers debug the assembly with a hex editor.
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@OmegaPolice
That’s it: Amdahl’s Law law except optimization actually creates large costs in the other parts of the system! -
@kevinriggle
That’s exactly the line of thought, yes. And the thing that makes abstractions useful, if they are useful, is that they make good decisions about what doesn’t matter, what can be standard, and what requires situation-specific thought. Those decisions simultaneously become productivity boost, safety, and a metaphor that is a tool for thought and communication.
