4 ms·

While I think there's truth to what you say, I'd also point our that workers in many pre-automated industries with an "artisan" approach also considered themsel

While I think there's truth to what you say, I'd also point our that workers in many pre-automated industries with an "artisan" approach also considered themselves irreplaceable because they figured, correctly, that nobody could build a machine with the capability of reproducing their workflow, with all its inherent uncertainty, flexibility and diverse physical and mental skills. What they failed to predict was that some people wouldn't try to automate them like-for-like. Instead they would reconfigure their entire approach to fit with the specific advantages and limitations of the machinery. And this new approach might even be qualitatively worse in various ways, but not so much as to overwhelm the economic advantages that provided by the things machines were good at. AI likely isn't going to slot into a developer-shaped hole in a software team. But it's possible we'll see new organisation approaches, companies, and development paradigms that say: How far can you get if you put prompt-generated code at the heart of the workflow and make everything else subservient to it. I'm not sure, right now, that that approach is feasible, but I'm not sure it won't be in a year or two.

Quarrelsome 4y ago
That's an extremely interesting thought. Perhaps we will see organisations in the future structure themselves more like a suite of unit tests. Instead of getting a developer or software house to plug a specific need in their org and being entirely outside of the development process: they will reflect the development process organisationally to ensure they catch any problems with the current output and just feed the box new prompts to increase their efficiency or efficacy. Their competitive advantage in their field then becomes the range of their tests (borne through experience), efficiency in running their pipeline of testing and ability to generate effective prompts.
- yc-kraln 4y ago
  This is already how automotive companies work. They are huge organizations which do four things: marketing, financing, design, and requirements. The supplier management and project management all fall under requirements management and enforcement.
- jackcviers3 4y ago
  I firmly believe that we should be studying model analysis and using that to create a field of peompt engineering. Both from a security standpoint and a productivity standpoint.
- Jeff_Brown 4y ago
  Tests and type signatures. Hopefully soon, dependently typed signatures.
nuancebydefault 4y ago
Indeed, a programmer's job feels artisan oftentimes. I think a reason for it is that projects are often ill defined from day one. They are defined by people who do not know enough about the system to set good requirements. The engineer works both bottom-up from the existing primitives of an existing system and top-down from requirements and tries to solve the puzzle where both approaches meet. Such work is very hard to automate. I believe there is a very big opportunity for AI to be used in a workflow such that inconsistencies between requirements, on all levels, and actual systems become clear a lot faster. The feedback loop to the requirements will be shorter, prototypes will exist sooner. The current workflow has little space for an AI worker. I believe this will change and have a major impact on the art of developing products. The AI programmer is still at its infancy, let's talk again 5 years from now.
oblio 4y ago
For that we need to make the AI deterministic or at least shape processes on specific error rates which are probably higher than that of the average smart human. We had to do that for the industrial approach and it wasn't a simple, fast or intuitive process.
globalise83 4y ago
"How far can you get if you put prompt-generated code at the heart of the workflow and make everything else subservient to it" OK, challenge accepted - will go down your suggested route - thanks :)
marstall 4y ago
Iteration and integration, the tasks which take most of at least my time as a developer, could fade significantly - or become automated themselves. We won't have understanding of our code, similar to how we don't understand the machine language being generated by our compilers now. We will be using our intuition about GPT to bring into being fully designed and integrated systems with 10 paragraphs at the prompt. Which could in the end greatly increase the influence of a programmer in a given organization. Our role will be a softer, almost cyborgian one. But this will indeed require the destruction of all that came before it. Questions like "but does it work with this 3rd party API, or this platform?" must become irrelevant for this future to happen. A bit similar to how the web destroyed mainframe, perhaps, by first creating its own compelling world, then making the mountain come to it.
- AverageDude 4y ago
  I don’t understand the high level language to machine language comparison with AI. HLL to machine language is translation. We hardcode things. This literal translates to this thing. Machine language has it own mind (figuratively) and it’s not doing translation. It can put some silly bug by misunderstanding the requirements which may cause a billion dollar software meltdown. And who is going to be responsible for that? The more black box programming becomes the more dumb human programmer gets. There will be stagnation. There won’t be any new “design patterns”.
Jeff_Brown 4y ago
A deep insight. Thanks.
trabant00 4y ago
Two problems with the analogy: The artisans fields where machines took over where hundreds and thousands of years old. We understood them very good. And maybe more importantly factory automation is deterministic and needs to be, as opposed to generative ML.
deleted 4y ago
[deleted]
shagie 4y ago
The artisan of old created one bowl at a time and made artisan pots. A machine that makes bowl can automate the artisan's job away. However, the next challenge is that the machine itself is now an "artisan" device. I'm sure the first bowl printing machine ( https://youtu.be/bD2DNSt8Wb4 https://youtu.be/bD2DNSt8Wb4 ) was purely artisan... but now you can buy them on Alibaba for a few thousand dollars ( https://www.alibaba.com/product-detail/Printing-Machine-Ceramic-Pad-Printing-Machine_62221224148.html?s=p https://www.alibaba.com/product-detail/Printing-Machine-Cera... ) I am sure there is a (bowl printing machine) machine out there. But if you say "I want a bowl printing machine that can do gradient colors" that first one (and probably the first few until it gets refined) are all going to be artisanal manufacturing processes again. This all boils down to that at some point in the process, there will be new and novel challenges to overcome. They're moving further up the production chain, but there is an artisan process at the end of it. The design of a new car has changed over time so that it is a lot more automated now than it was back then ( https://youtu.be/xatHPihJCpM https://youtu.be/xatHPihJCpM ) but you're not going to get an AI to go from "create a new car design" to actually verifying that it works and is right. There will always be an artisan making the first version of anything.
- esfandia 4y ago
  > There will always be an artisan making the first version of anything. Until we reach the bootstrap point (the singularity?), i.e. when the GPT-making machine is GPT itself. Or maybe we're still one level behind, and the GPT-making machine will generate the GPT-making machine, as well as all the other machines that will generate everything else.

Quarrelsome 4y ago

That's an extremely interesting thought. Perhaps we will see organisations in the future structure themselves more like a suite of unit tests. Instead of getting a developer or software house to plug a specific need in their org and being entirely outside of the development process: they will reflect the development process organisationally to ensure they catch any problems with the current output and just feed the box new prompts to increase their efficiency or efficacy. Their competitive advantage in their field then becomes the range of their tests (borne through experience), efficiency in running their pipeline of testing and ability to generate effective prompts.

yc-kraln 4y ago
This is already how automotive companies work. They are huge organizations which do four things: marketing, financing, design, and requirements. The supplier management and project management all fall under requirements management and enforcement.
jackcviers3 4y ago
I firmly believe that we should be studying model analysis and using that to create a field of peompt engineering. Both from a security standpoint and a productivity standpoint.
Jeff_Brown 4y ago
Tests and type signatures. Hopefully soon, dependently typed signatures.

nuancebydefault 4y ago

Indeed, a programmer's job feels artisan oftentimes. I think a reason for it is that projects are often ill defined from day one. They are defined by people who do not know enough about the system to set good requirements. The engineer works both bottom-up from the existing primitives of an existing system and top-down from requirements and tries to solve the puzzle where both approaches meet. Such work is very hard to automate. I believe there is a very big opportunity for AI to be used in a workflow such that inconsistencies between requirements, on all levels, and actual systems become clear a lot faster. The feedback loop to the requirements will be shorter, prototypes will exist sooner. The current workflow has little space for an AI worker. I believe this will change and have a major impact on the art of developing products. The AI programmer is still at its infancy, let's talk again 5 years from now.

oblio 4y ago

For that we need to make the AI deterministic or at least shape processes on specific error rates which are probably higher than that of the average smart human. We had to do that for the industrial approach and it wasn't a simple, fast or intuitive process.

globalise83 4y ago

"How far can you get if you put prompt-generated code at the heart of the workflow and make everything else subservient to it" OK, challenge accepted - will go down your suggested route - thanks :)

marstall 4y ago

Iteration and integration, the tasks which take most of at least my time as a developer, could fade significantly - or become automated themselves. We won't have understanding of our code, similar to how we don't understand the machine language being generated by our compilers now. We will be using our intuition about GPT to bring into being fully designed and integrated systems with 10 paragraphs at the prompt. Which could in the end greatly increase the influence of a programmer in a given organization. Our role will be a softer, almost cyborgian one. But this will indeed require the destruction of all that came before it. Questions like "but does it work with this 3rd party API, or this platform?" must become irrelevant for this future to happen. A bit similar to how the web destroyed mainframe, perhaps, by first creating its own compelling world, then making the mountain come to it.

AverageDude 4y ago
I don’t understand the high level language to machine language comparison with AI. HLL to machine language is translation. We hardcode things. This literal translates to this thing. Machine language has it own mind (figuratively) and it’s not doing translation. It can put some silly bug by misunderstanding the requirements which may cause a billion dollar software meltdown. And who is going to be responsible for that? The more black box programming becomes the more dumb human programmer gets. There will be stagnation. There won’t be any new “design patterns”.

Jeff_Brown 4y ago

A deep insight. Thanks.

trabant00 4y ago

Two problems with the analogy: The artisans fields where machines took over where hundreds and thousands of years old. We understood them very good. And maybe more importantly factory automation is deterministic and needs to be, as opposed to generative ML.

deleted 4y ago

[deleted]

shagie 4y ago

The artisan of old created one bowl at a time and made artisan pots. A machine that makes bowl can automate the artisan's job away. However, the next challenge is that the machine itself is now an "artisan" device. I'm sure the first bowl printing machine ( https://youtu.be/bD2DNSt8Wb4 https://youtu.be/bD2DNSt8Wb4 ) was purely artisan... but now you can buy them on Alibaba for a few thousand dollars ( https://www.alibaba.com/product-detail/Printing-Machine-Ceramic-Pad-Printing-Machine_62221224148.html?s=p https://www.alibaba.com/product-detail/Printing-Machine-Cera... ) I am sure there is a (bowl printing machine) machine out there. But if you say "I want a bowl printing machine that can do gradient colors" that first one (and probably the first few until it gets refined) are all going to be artisanal manufacturing processes again. This all boils down to that at some point in the process, there will be new and novel challenges to overcome. They're moving further up the production chain, but there is an artisan process at the end of it. The design of a new car has changed over time so that it is a lot more automated now than it was back then ( https://youtu.be/xatHPihJCpM https://youtu.be/xatHPihJCpM ) but you're not going to get an AI to go from "create a new car design" to actually verifying that it works and is right. There will always be an artisan making the first version of anything.

esfandia 4y ago
> There will always be an artisan making the first version of anything. Until we reach the bootstrap point (the singularity?), i.e. when the GPT-making machine is GPT itself. Or maybe we're still one level behind, and the GPT-making machine will generate the GPT-making machine, as well as all the other machines that will generate everything else.