12 ms·

> I do of course understand why a given request from the client might be impossible to satisfy, given the abstractions that are currently in the code Not quite

> I do of course understand why a given request from the client might be impossible to satisfy, given the abstractions that are currently in the code Not quite. A request from the client might be impossible to satisfy given _the request_. May be not this particular request, but some previous requirement that this system has to uphold. I have a lot of times found myself in the situation where I explained to stakeholders that they essentially have bugs in their requirements, as they were logically inconsistent and self contradictory. That's what the article is about — it almost never happens in other professions.

johncalvinyoung 3y ago
Contradictory or inconsistent requirements? I've heard lots of anecdotes around that sort of thing in hardware engineering. It happens whenever abstractions meet implementation.
DaiPlusPlus 3y ago
> That's what the article is about I thought the article's subtext, or implication, was about how line-of-business software writers will soon be replaced by some LLM that attempts to follow the clients' requests as-best-as-possible when its generating its own software domain-model and simply refusing to ever push-back to the client: the ultimate obsequious SWE - which means that software-quality will go down the drain. ...which I think is a rather specific prediction of the future and doesn't consider whether automated program-synthesis (whether LLM-based or otherwise) would be able to interrogate proposed requirements, identify flaws and inconsistencies, and require the user to correct their input before generating the code that defines the system.
- tl 3y ago
  We have this problem today. I've never worked on a team that didn't have at least one person whose coding ability largely stopped at what you could copy and paste. Pre-internet, they were assigned non-programming tasks or things that could be done via copy-paste-modify of existing code. Collegues on my current team of this caliber have Bard open. This is an observed phenomenon, and I'm not surprised they reach for the less capable but incumbent provided option. I don't have enough data to say this has negatively impacted code quality, but I can rule out most positive results. From the above example, at least one person wants to disable Typescript because it makes code [from them but of unknown origin] harder to execute. That is not promising.
  - DaiPlusPlus 3y ago
    > I've never worked on a team that didn't have at least one person whose coding ability largely stopped at what you could copy and paste. I am fortunate then - I have never been in that situation. You have my sympathy. > Collegues on my current team of this caliber have Bard open. wat ------ I don't like using ChatGPT for code-gen (and I haven't tried any of the others like Bard or LLaMa) because I still don't understand how it's capable of doing-what-it-does. I have thrown prompts at GPT to write my code for me (which is tiresome: as often writing the prompt takes more effort than writing the code myself) but on occassion I'll throw it something that I'll think it can't possibly solve or figure out, and I get blown-away by what it generates (e.g. on a lark I asked it to write a C# program to solve belt-layout problems in Factorio, and the moment I saw what it generated was... a genuinely scary and unsettling experience for me: many people are dismissive of GPT etc, simply saying "oh, that's just because it's been trained to do that" - but I refuse to believe that OpenAI specifically trained GPT to generate C# code for Factorio - and on a whim I asked it to translate that code to Haskell and that, too, was... something-that-just-shouldn't-be-possible. Yes, the code it generated was incomplete, had missing references, and more besides, but remarkably the syntax it generated (for both C# and Haskell) was 100% correct. I avoided ChatGPT for a while after then, not wanting to be rattled again - but I recently tried it again, by prompting it to generate code that I was already writing to see if it knew of a better approach or even as a time-saver (as C# is still not as expressive as I'd like); specifically, I was writing a ModelBinder for ASP.NET Core and it generated code that definitely would have "worked", but had plenty of room for improvement (mostly things that static-analysis would have caught). I wasn't able to observe ChatGPT generating "substantial" bodies of code: it seems best for generating something like a ~200-line class to solve a specific narrow problem (things exactly like that ModelBinder implementation I was working on), especially when I'm stuck for ideas on how to solve a problem entirely by myself. ------ Another example I just remembered as I write this was me asking ChatGPT a straightforward question about MSBuild: what do I need to put in a `.csproj` file to prevent the project from being built when the host environment is non-Windows. This is a screenshot of the interaction I had with it: https://imgur.com/a/TuejAYn https://imgur.com/a/TuejAYn - it starts-off on the right track, but hallucinates small details, or even directly contradicts itself, or generates output that is the precise opposite of what I asked. If ajunior-developer[1] wrote me something like what ChatGPT generated there, then it's easy to attribute that mistake (i.e. that of swapping the `==` and `!=` operators) to simply being a typo (at best), but at worst just absent-minded. But when ChatGPT does it I just don't understand how it's even possible for it to make a mistake like that while it clearly is quite on-top of the rest of the problem-space. And because ChatGPT makes those mistakes unpredictably, all the time, it means I can't trust the code it generates. The other reason, of course, is that it eliminates the challenge (if not thrill?) of me getting to solve a problem by myself, using my own innate reasoning abilities - and being the one who gets to solve problems is, I think, part of every engineer's vocation and sense of identity regardless of field (chemical, civil, mechanical, software, etc). ----- My last thought is that I'm not worried about GPT taking my job or otherwise replacing me: the SW industry already tried that 30 years ago with outsourcing to India, and that didn't kill-off west-coast SWEs - I'm only going to start getting worried about GPT et al. when they do advance to the point where they're almost entirely autonomous and self-directed, while also able to gather-requirements while also challenging assumptions in those requirements, perform its own verification and when the code it generates is at least on-par with what we can write. And I do believe we'll get to that point within 3-5 years from now (e.g. I assume it's straightforward to train an LLM to interrogate incoming requirements and convert that into some kind of normalized domain-model; and already we can wire-up GPT to external APIs, so we can do a conversation-loop between it and compiler error message output, etc). ----- [1] I dislike that term, personally - I feel it's unnecessarily condescending or even infantilising (I'm also fortunate to have never had that as a job-title, and every company I've worked for either had a numeric level nomenclature, or used silly/informal job-titles.
danenania 3y ago
Doesn't that also happen in just about any profession that involves building or engineering? I don't see how it's unique to code.
- Michelangelo11 3y ago
  Yes, thank you. That's also what I thought after reading clarifications along these lines in the thread.
- golergka 3y ago
  I don't know, I've never worked in these professions.
hinkley 3y ago
The worst this ever got, we had a multi-step form for data input (or as the old farts used to call it, a 'wizard'). Someone added a new requirement that meant that we went from needing data from section 3 to populate section 4, to also needing data from section 4 to populate section 3. I eventually had to draw them a diagram because they couldn't see what the problem was. In the end we had to both soften the requirement and rearrange the 2 sections, possibly into 3.
- bqmjjx0kac 3y ago
  > or as the old farts used to call it, a 'wizard' ... Am I old?

johncalvinyoung 3y ago

Contradictory or inconsistent requirements? I've heard lots of anecdotes around that sort of thing in hardware engineering. It happens whenever abstractions meet implementation.

DaiPlusPlus 3y ago

> That's what the article is about I thought the article's subtext, or implication, was about how line-of-business software writers will soon be replaced by some LLM that attempts to follow the clients' requests as-best-as-possible when its generating its own software domain-model and simply refusing to ever push-back to the client: the ultimate obsequious SWE - which means that software-quality will go down the drain. ...which I think is a rather specific prediction of the future and doesn't consider whether automated program-synthesis (whether LLM-based or otherwise) would be able to interrogate proposed requirements, identify flaws and inconsistencies, and require the user to correct their input before generating the code that defines the system.

tl 3y ago
We have this problem today. I've never worked on a team that didn't have at least one person whose coding ability largely stopped at what you could copy and paste. Pre-internet, they were assigned non-programming tasks or things that could be done via copy-paste-modify of existing code. Collegues on my current team of this caliber have Bard open. This is an observed phenomenon, and I'm not surprised they reach for the less capable but incumbent provided option. I don't have enough data to say this has negatively impacted code quality, but I can rule out most positive results. From the above example, at least one person wants to disable Typescript because it makes code [from them but of unknown origin] harder to execute. That is not promising.
- DaiPlusPlus 3y ago
  > I've never worked on a team that didn't have at least one person whose coding ability largely stopped at what you could copy and paste. I am fortunate then - I have never been in that situation. You have my sympathy. > Collegues on my current team of this caliber have Bard open. wat ------ I don't like using ChatGPT for code-gen (and I haven't tried any of the others like Bard or LLaMa) because I still don't understand how it's capable of doing-what-it-does. I have thrown prompts at GPT to write my code for me (which is tiresome: as often writing the prompt takes more effort than writing the code myself) but on occassion I'll throw it something that I'll think it can't possibly solve or figure out, and I get blown-away by what it generates (e.g. on a lark I asked it to write a C# program to solve belt-layout problems in Factorio, and the moment I saw what it generated was... a genuinely scary and unsettling experience for me: many people are dismissive of GPT etc, simply saying "oh, that's just because it's been trained to do that" - but I refuse to believe that OpenAI specifically trained GPT to generate C# code for Factorio - and on a whim I asked it to translate that code to Haskell and that, too, was... something-that-just-shouldn't-be-possible. Yes, the code it generated was incomplete, had missing references, and more besides, but remarkably the syntax it generated (for both C# and Haskell) was 100% correct. I avoided ChatGPT for a while after then, not wanting to be rattled again - but I recently tried it again, by prompting it to generate code that I was already writing to see if it knew of a better approach or even as a time-saver (as C# is still not as expressive as I'd like); specifically, I was writing a ModelBinder for ASP.NET Core and it generated code that definitely would have "worked", but had plenty of room for improvement (mostly things that static-analysis would have caught). I wasn't able to observe ChatGPT generating "substantial" bodies of code: it seems best for generating something like a ~200-line class to solve a specific narrow problem (things exactly like that ModelBinder implementation I was working on), especially when I'm stuck for ideas on how to solve a problem entirely by myself. ------ Another example I just remembered as I write this was me asking ChatGPT a straightforward question about MSBuild: what do I need to put in a `.csproj` file to prevent the project from being built when the host environment is non-Windows. This is a screenshot of the interaction I had with it: https://imgur.com/a/TuejAYn https://imgur.com/a/TuejAYn - it starts-off on the right track, but hallucinates small details, or even directly contradicts itself, or generates output that is the precise opposite of what I asked. If ajunior-developer[1] wrote me something like what ChatGPT generated there, then it's easy to attribute that mistake (i.e. that of swapping the `==` and `!=` operators) to simply being a typo (at best), but at worst just absent-minded. But when ChatGPT does it I just don't understand how it's even possible for it to make a mistake like that while it clearly is quite on-top of the rest of the problem-space. And because ChatGPT makes those mistakes unpredictably, all the time, it means I can't trust the code it generates. The other reason, of course, is that it eliminates the challenge (if not thrill?) of me getting to solve a problem by myself, using my own innate reasoning abilities - and being the one who gets to solve problems is, I think, part of every engineer's vocation and sense of identity regardless of field (chemical, civil, mechanical, software, etc). ----- My last thought is that I'm not worried about GPT taking my job or otherwise replacing me: the SW industry already tried that 30 years ago with outsourcing to India, and that didn't kill-off west-coast SWEs - I'm only going to start getting worried about GPT et al. when they do advance to the point where they're almost entirely autonomous and self-directed, while also able to gather-requirements while also challenging assumptions in those requirements, perform its own verification and when the code it generates is at least on-par with what we can write. And I do believe we'll get to that point within 3-5 years from now (e.g. I assume it's straightforward to train an LLM to interrogate incoming requirements and convert that into some kind of normalized domain-model; and already we can wire-up GPT to external APIs, so we can do a conversation-loop between it and compiler error message output, etc). ----- [1] I dislike that term, personally - I feel it's unnecessarily condescending or even infantilising (I'm also fortunate to have never had that as a job-title, and every company I've worked for either had a numeric level nomenclature, or used silly/informal job-titles.

danenania 3y ago

Doesn't that also happen in just about any profession that involves building or engineering? I don't see how it's unique to code.

Michelangelo11 3y ago
Yes, thank you. That's also what I thought after reading clarifications along these lines in the thread.
golergka 3y ago
I don't know, I've never worked in these professions.

hinkley 3y ago

The worst this ever got, we had a multi-step form for data input (or as the old farts used to call it, a 'wizard'). Someone added a new requirement that meant that we went from needing data from section 3 to populate section 4, to also needing data from section 4 to populate section 3. I eventually had to draw them a diagram because they couldn't see what the problem was. In the end we had to both soften the requirement and rearrange the 2 sections, possibly into 3.

bqmjjx0kac 3y ago
> or as the old farts used to call it, a 'wizard' ... Am I old?