5 ms·

The elephant in the room: the job market and LLMs will make some programmers redundant. Maybe a lot of them. The programmers who will get hit hardest have spent

The elephant in the room: the job market and LLMs will make some programmers redundant. Maybe a lot of them. The programmers who will get hit hardest have spent their careers mastering the parts of programming easiest to automate or outsource. They have not spent the time to learn communication skills, organization skills, or develop business domain expertise. They just know how to code, and not even proficiently enough to compete with a really good auto-complete bot.

gaudat 4y ago
Aka web front-end developers?
- gregjor 4y ago
  Anyone who conflates knowing how to write code with adding business value. Front-end, back-end, doesn’t matter. If you don’t bring more to the table beyond knowing Java or Javascript or HTML at the advanced bootcamp level, skill up.
- wildrhythms 4y ago
  I feel like backend is more predictable. Known inputs and outputs (think an API). I can get ChatGPT to act like an API with a single query; but actually building a front-end application not so much.
  - jmuguy 4y ago
    What do you imagine the backend is doing? Just providing a connection to a database somewhere?
  - serpix 4y ago
    I wonder how you are currently predicting a random api change, login flow change, business reorganisation change, inheriting and integrating a new microservice to the ecosystem of n existing other applications.
  - quonn 4y ago
    But also only for sort of trivial applications. I run into real problems all the time. It's true that a lot of applications are trivial and often there is no budget for the interesting parts - and that's about to change. So perhaps this development is a good thing.
- whatch 4y ago
  Some of them, yes. But I believe there are still enough problems in the front-end difficult for LLMs in larger applications. I like the summary regarding front-end here [0]. [0] https://www.joshwcomeau.com/blog/the-end-of-frontend-development/ https://www.joshwcomeau.com/blog/the-end-of-frontend-develop...
- evilduck 4y ago
  Depends on how you want to show your bias. I've worked with some interesting front end applications that made their moderately complex backends look like trivialities, and I've seen whole teams of mostly useless CRUD API developers who struggle with minimal business logic complexity who are going to be made redundant by one good AI assisted backend dev. Maybe you should introspect a bit.
- gregjor 4y ago
  Thinking in terms of technical specializations and sub-fields illustrates the problem. If you think front-end and back-end describe different species of programmers, or radically different skills in terms of business value, that comes down to the same (I think wrong) idea that Javascript will prove easier to automate than Java because some languages or tools require more skill. The LLMs don't need skill, just training data. Languages and tools and specializations won't matter except that the more widely-used languages will represent a larger training set for the LLMs. The programming industry went through a similar existential crisis back in the 1990s, when pundits predicted outsourcing/offshoring would eliminate our jobs (in the US, anyway). And some jobs did go to Bangalore and Karachi. Programmers didn't get hit as hard as the manufacturing sector, and the work seemed to expand to create more demand. Eventually companies figured out that outsourcing introduces different inefficiencies and problems, often more than it solves. In one of his long articles about LLMs Stephen Wolfram made an interesting point: LLMs apparently show us that we have over-estimated the complexity of human language. Human beings tend to have a high opinion of their own intelligence so that seems very likely. Now that we have software that can produce human-like language we can either tell ourselves the AI overlords have arrived and give up, or we can revise what we think we know about learning human language. Likewise, now we have programs that can write passable code, and here on HN you have to wade through all of the "What do I do now?" posts. Another interpretation: a whole lot of code available to the training models doesn't need much actual intelligence to decipher or write, and we as programmers have solved the same handful of similar problems millions of times. Writing passable code, while not easy to learn, represents the easiest and most replaceable part of developing useful software that has value for the business that paid for it and the customers that use it. And it represents one of the least efficient and least predictable parts of the development process. Imagine framing carpenters just throwing up their hands and fretting about their future when nail guns took over from hammers. The new tool made the carpenters more efficient in some tasks. I expect LLM coding assistants can do the same, but since they can only regurgitate code already written by human programmers they will show apparent skill at solving common problems in common ways, and no skill at anything beyond that. When I switched to full-time freelancing about 15 years ago I stopped using a resume, I stopped highlighting my "technical skills" (e.g. languages, frameworks, tools, etc.). When talking to a prospective client I immediately focus on their business problems rather than whatever things I have used before. They pay me to solve problems with technology. If that means I need to learn something new, I will do that (and fast). I have 40 years experience in the software business, very little actually new or novel happens in the world of programming. If all I could offer to a client came down to "I know Python" I would limit myself, and I would make myself replaceable by a cheaper programmer or an LLM because knowing Python makes very little difference in the big picture -- a necessary but not sufficient skill because I solve business problems, I don't only write Python code. Now that an LLM can write passable Python the people who only offer that skill should worry, and they should expand their skills to include things LLMs can't do and likely won't do anytime soon. That will apply to other fields, not just programmers, but since I know programming I'll stick to what I know.
ResearchCode 4y ago
I thought it would be the opposite. People heavy on the soft skills and light on tech are more easily replaceable by a large language model. They seem the most promising for slide decks or fill in Excel sheets, or generate a meeting protocol for a pointless meeting.
- quonn 4y ago
  I think the market will get squeezed from both ends: Both the leetcoders and the those only producing superficial stuff can be replaced. There is a lot in between that will remain useful for some time.
- jeremyjh 4y ago
  Business domain knowledge is not used for creating slide decks and having pointless meetings. It is used to decide what to build, and to some degree how to build it.
  - mlboss 4y ago
    LLMs are also good at reasoning. It would be good exercise to see if they can decide what to build.
    - jeremyjh 4y ago
      They are good at generating plausible sounding tokens one after another. Often those will be good ideas. But this isn't the same as reasoning.
- travisjungroth 4y ago
  Depends on the "soft skills". ChatGPT doesn't look good at prioritization. It can't tell you which of two numbers is bigger, so that's not a great sign. Of course you can offload that to a calculator, but then you lose the actual LLM. So prioritization seems good for a while. If your soft skill is turning requests into tickets and looking at PRs to figure out which tickets are already closed, yeah things ain't looking good.
Silhouette 4y ago
We've had boilerplate generators for a long time. Sometimes they avoid some mundane work when you're first setting up. That's a good thing. Sometimes you end up changing a lot of what they produce because it's not exactly what you need. That's less good. But they can never do anything truly innovative because ultimately they are based on work that was already done before. And those creative steps they can't take are where most value is added. Programmers who can understand a real problem and come up with a good way to solve it using software will still be needed. "Programmers" who are glorified human clipboards just copying and pasting all day will be less needed. But those jobs were already at risk from the next library or scaffolding tool anyway long before the current generation of AI-based tools came along.
- TheNewsIsHere 4y ago
  > We've had boilerplate generators for a long time. Sometimes they avoid some mundane work when you're first setting up. That's a good thing. Sometimes you end up changing a lot of what they produce because it's not exactly what you need. That's less good. But they can never do anything truly innovative because ultimately they are based on work that was already done before. And those creative steps they can't take are where most value is added. > Programmers who can understand a real problem and come up with a good way to solve it using software will still be needed. This keeps coming up in my own circles, including with non-technical folks. The best way I've heard it put is "you know, these AIs only know what we've already figured out." The newest contingent of AI technologies is impressive for what they are, but what they are is both somewhat inevitable and not truly intelligent in the way most businesses require of their technical people in order to succeed. Of course we can automate away the basics, we've been doing that with successive technologies and challenges for a very long time. Someone up-thread mentioned AI replacing automation folks as an easy example, but I don't see that happening so quickly. I do a lot of automating, and for a start there's so much automation "left to be done in the world" that there are no shortages of hard challenges left that AI couldn't (yet?) crack. There's a huge amount of business<->technology synthesis that has to happen to automate beyond the basics. But more expansively speaking, writing off humans being in the loop is ridiculous on its face. Humans will _always_ be in the loop somewhere, unless of course we take EM Forster's _The Machine Stops_ as an instruction manual rather than the warning it is. I don't mean that in a doom-and-gloom way but rather that I just don't think humans will ever give up enough control to enable something like that. I don't think that's such a bad thing, either. It's as ridiculous to say that human programmers are obsolete as it is to say we're that we're anywhere near computers developing complete, new computers for other humans to use.

gaudat 4y ago

Aka web front-end developers?

gregjor 4y ago
Anyone who conflates knowing how to write code with adding business value. Front-end, back-end, doesn’t matter. If you don’t bring more to the table beyond knowing Java or Javascript or HTML at the advanced bootcamp level, skill up.
wildrhythms 4y ago
I feel like backend is more predictable. Known inputs and outputs (think an API). I can get ChatGPT to act like an API with a single query; but actually building a front-end application not so much.
- jmuguy 4y ago
  What do you imagine the backend is doing? Just providing a connection to a database somewhere?
- serpix 4y ago
  I wonder how you are currently predicting a random api change, login flow change, business reorganisation change, inheriting and integrating a new microservice to the ecosystem of n existing other applications.
- quonn 4y ago
  But also only for sort of trivial applications. I run into real problems all the time. It's true that a lot of applications are trivial and often there is no budget for the interesting parts - and that's about to change. So perhaps this development is a good thing.
whatch 4y ago
Some of them, yes. But I believe there are still enough problems in the front-end difficult for LLMs in larger applications. I like the summary regarding front-end here [0]. [0] https://www.joshwcomeau.com/blog/the-end-of-frontend-development/ https://www.joshwcomeau.com/blog/the-end-of-frontend-develop...
evilduck 4y ago
Depends on how you want to show your bias. I've worked with some interesting front end applications that made their moderately complex backends look like trivialities, and I've seen whole teams of mostly useless CRUD API developers who struggle with minimal business logic complexity who are going to be made redundant by one good AI assisted backend dev. Maybe you should introspect a bit.
gregjor 4y ago
Thinking in terms of technical specializations and sub-fields illustrates the problem. If you think front-end and back-end describe different species of programmers, or radically different skills in terms of business value, that comes down to the same (I think wrong) idea that Javascript will prove easier to automate than Java because some languages or tools require more skill. The LLMs don't need skill, just training data. Languages and tools and specializations won't matter except that the more widely-used languages will represent a larger training set for the LLMs. The programming industry went through a similar existential crisis back in the 1990s, when pundits predicted outsourcing/offshoring would eliminate our jobs (in the US, anyway). And some jobs did go to Bangalore and Karachi. Programmers didn't get hit as hard as the manufacturing sector, and the work seemed to expand to create more demand. Eventually companies figured out that outsourcing introduces different inefficiencies and problems, often more than it solves. In one of his long articles about LLMs Stephen Wolfram made an interesting point: LLMs apparently show us that we have over-estimated the complexity of human language. Human beings tend to have a high opinion of their own intelligence so that seems very likely. Now that we have software that can produce human-like language we can either tell ourselves the AI overlords have arrived and give up, or we can revise what we think we know about learning human language. Likewise, now we have programs that can write passable code, and here on HN you have to wade through all of the "What do I do now?" posts. Another interpretation: a whole lot of code available to the training models doesn't need much actual intelligence to decipher or write, and we as programmers have solved the same handful of similar problems millions of times. Writing passable code, while not easy to learn, represents the easiest and most replaceable part of developing useful software that has value for the business that paid for it and the customers that use it. And it represents one of the least efficient and least predictable parts of the development process. Imagine framing carpenters just throwing up their hands and fretting about their future when nail guns took over from hammers. The new tool made the carpenters more efficient in some tasks. I expect LLM coding assistants can do the same, but since they can only regurgitate code already written by human programmers they will show apparent skill at solving common problems in common ways, and no skill at anything beyond that. When I switched to full-time freelancing about 15 years ago I stopped using a resume, I stopped highlighting my "technical skills" (e.g. languages, frameworks, tools, etc.). When talking to a prospective client I immediately focus on their business problems rather than whatever things I have used before. They pay me to solve problems with technology. If that means I need to learn something new, I will do that (and fast). I have 40 years experience in the software business, very little actually new or novel happens in the world of programming. If all I could offer to a client came down to "I know Python" I would limit myself, and I would make myself replaceable by a cheaper programmer or an LLM because knowing Python makes very little difference in the big picture -- a necessary but not sufficient skill because I solve business problems, I don't only write Python code. Now that an LLM can write passable Python the people who only offer that skill should worry, and they should expand their skills to include things LLMs can't do and likely won't do anytime soon. That will apply to other fields, not just programmers, but since I know programming I'll stick to what I know.

ResearchCode 4y ago

I thought it would be the opposite. People heavy on the soft skills and light on tech are more easily replaceable by a large language model. They seem the most promising for slide decks or fill in Excel sheets, or generate a meeting protocol for a pointless meeting.

quonn 4y ago
I think the market will get squeezed from both ends: Both the leetcoders and the those only producing superficial stuff can be replaced. There is a lot in between that will remain useful for some time.
jeremyjh 4y ago
Business domain knowledge is not used for creating slide decks and having pointless meetings. It is used to decide what to build, and to some degree how to build it.
- mlboss 4y ago
  LLMs are also good at reasoning. It would be good exercise to see if they can decide what to build.
  - jeremyjh 4y ago
    They are good at generating plausible sounding tokens one after another. Often those will be good ideas. But this isn't the same as reasoning.
travisjungroth 4y ago
Depends on the "soft skills". ChatGPT doesn't look good at prioritization. It can't tell you which of two numbers is bigger, so that's not a great sign. Of course you can offload that to a calculator, but then you lose the actual LLM. So prioritization seems good for a while. If your soft skill is turning requests into tickets and looking at PRs to figure out which tickets are already closed, yeah things ain't looking good.

Silhouette 4y ago

We've had boilerplate generators for a long time. Sometimes they avoid some mundane work when you're first setting up. That's a good thing. Sometimes you end up changing a lot of what they produce because it's not exactly what you need. That's less good. But they can never do anything truly innovative because ultimately they are based on work that was already done before. And those creative steps they can't take are where most value is added. Programmers who can understand a real problem and come up with a good way to solve it using software will still be needed. "Programmers" who are glorified human clipboards just copying and pasting all day will be less needed. But those jobs were already at risk from the next library or scaffolding tool anyway long before the current generation of AI-based tools came along.

TheNewsIsHere 4y ago
> We've had boilerplate generators for a long time. Sometimes they avoid some mundane work when you're first setting up. That's a good thing. Sometimes you end up changing a lot of what they produce because it's not exactly what you need. That's less good. But they can never do anything truly innovative because ultimately they are based on work that was already done before. And those creative steps they can't take are where most value is added. > Programmers who can understand a real problem and come up with a good way to solve it using software will still be needed. This keeps coming up in my own circles, including with non-technical folks. The best way I've heard it put is "you know, these AIs only know what we've already figured out." The newest contingent of AI technologies is impressive for what they are, but what they are is both somewhat inevitable and not truly intelligent in the way most businesses require of their technical people in order to succeed. Of course we can automate away the basics, we've been doing that with successive technologies and challenges for a very long time. Someone up-thread mentioned AI replacing automation folks as an easy example, but I don't see that happening so quickly. I do a lot of automating, and for a start there's so much automation "left to be done in the world" that there are no shortages of hard challenges left that AI couldn't (yet?) crack. There's a huge amount of business<->technology synthesis that has to happen to automate beyond the basics. But more expansively speaking, writing off humans being in the loop is ridiculous on its face. Humans will _always_ be in the loop somewhere, unless of course we take EM Forster's _The Machine Stops_ as an instruction manual rather than the warning it is. I don't mean that in a doom-and-gloom way but rather that I just don't think humans will ever give up enough control to enable something like that. I don't think that's such a bad thing, either. It's as ridiculous to say that human programmers are obsolete as it is to say we're that we're anywhere near computers developing complete, new computers for other humans to use.