6 ms·

The more I work with LLMs and try things like "vibe coding" the less worried I am about AI taking my job any time soon. In the right contexts, I find LLMs can

The more I work with LLMs and try things like "vibe coding" the less worried I am about AI taking my job any time soon. In the right contexts, I find LLMs can speed up my work a lot. But it's nowhere close to being able to replace what I do.

varenc 2y ago
Speeding up your work does lead to job loss. If some developers can suddenly be 3x as productive than a company doesn't need as many engineers.
- cmdli 2y ago
  The job loss depends on the average speed up, however. If the AI is only effective in 10% of tasks (the basic stuff), then that 3x improvement goes down to 1.3x.
  - toogan 2y ago
    > The job loss depends on the average speed up, That's such a economical fallacy that I'd expect the HN crowd to have understood this ages ago. Compare the average productivity of somebody working in a car factory 80 years ago with somebody today. How many person-hours did it take then and how many does it take today to manufacture a car? Did the number of jobs between then and now shrink by that factor? To the contrary. The car industry had an incredible boom. Efficiency increase does not imply job loss since the market size is not static. If cost is reduced then things are suddenly viable which weren't before and market size can explode. In the end you can end up with more jobs. Not always, obviously, but there are more examples than you can count which show that.
    - ekidd 2y ago
      This is all broadly true, historically. Automating jobs mostly results in creating more jobs elsewhere. But let's assume you have true, fully general AI. Further assume that it can do human-level cognition for $2/hour, and it's roughly as smart as a Stanford grad. So once the AI takes your job, it goes on to take your new job, and the job after that, and the job after that. It is smarter and cheaper than the average human, after all. This scenario goes one of three ways, depending on who controls the AI: 1. We all become fabulously wealthy and no longer need to work at all. (I have trouble visualizing exactly how we get this outcome.) 2. A handful of billionaires and politicians control the AI. They don't need the rest of us. 3. The AI controls itself, in which case most economic benefits and power go to the AI. The last historical analog of this was the Neanderthals, who were unable (for whatever reason) to compete with humans. So the most important question is, how close actually are we to this scenario? Is impossible? A century away? Or something that will happen in the next decade?
      - toogan 2y ago
        > But let's assume you have true, fully general AI. Very strong assumption and very narrow setting that is one of the counter examples. AI researchers in the 80s already told you that AI is around the corner in the next 5 years. Didn't happen. I wouldn't hold my breath this time either. "AI" is a misnomer. LLMs are not "intelligence". They are a lossy compression algorithm of everything that was put into their training set. Pretty good at that, but that's essentially it.
- c0redump 2y ago
  Or it just leads to 3x more stuff being made. This conclusion isn’t nearly as trivial as you’re making it out to be.
- AnimalMuppet 2y ago
  Only if that company has a finite wish list for their software. That is rarely the case.
- dghlsakjg 2y ago
  That assumes a static demand for development services, which has, more or less, never happened since computing became a thing. Python, and other high level languages made a lot of development much faster, but it never lead to reduced engineering needs. Cloud made deploying services massively easier, and as a result we actually have a lot more people working in infrastructure. Faster development mostly leads to expanded economic viability for new types of software. The real question is what becomes economically feasible if development costs are halved.
  - jetrink 2y ago
    Jevon's Paradox: https://en.wikipedia.org/wiki/Jevons_paradox https://en.wikipedia.org/wiki/Jevons_paradox "In 1865, the English economist William Stanley Jevons observed that technological improvements that increased the efficiency of coal use led to the increased consumption of coal in a wide range of industries. He argued that, contrary to common intuition, technological progress could not be relied upon to reduce fuel consumption."
    - ModernMech 2y ago
      It's the same reason widening the road doesn't lead to less traffic.
- simonw 2y ago
  Alternatively: if LLMs make devs 3x productive that means companies can get 3x the value out of an engineering hire, so they should hire more. (Unless that company somehow has no substantial engineering backlog, which I've yet to encounter anywhere I've ever worked.)
  - varenc 2y ago
    This definitely feels true for tech companies where the prospect of more more productive engineers improves their bottom line. The same sort of companies that have a near infinite appetite for talented engineers. But there's a lot of coders in industries whose core business isn't technology. Knapheide for example, a truck outfitting company where my brother codes. I'd imagine in those companies, being able to do the same work with fewer engineers and less cost would lead to fewer hires. Technology isn't their core product and they aren't being held back by software.
    - simonw 2y ago
      I actually think we may see the opposite happen with those kinds of companies too. At the moment, a truck outfitting company building a customer CRM optimized for their workflow is an absurd idea: they would need a team of a dozen developers working for a year before they could even get a feel for if it was a feasible project or not. Add LLM assistance and maybe a team of three developers could get to an initial working version in three months. At that point, companies that had previously ruled out custom software development entirely may find that it makes sense for them - growing the demand for software engineers as a whole.
      - varenc 2y ago
        I guess I'm skeptical how much of an impact better software could have on the business success a truck outfitting company? But maybe I'm being overly skeptical. I bet if I really got in the weeds there I'd see tons of opportunities were better/more software could really accelerate things. Thanks for checking my pessimism!
bobxmax 2y ago
I work at a company relatively well-known in Startup-land and I've replaced a product team which had 9 devs 2 years ago with 2 devs with AI. Devs are just coping so hard around LLMs its hard to watch. OTOH the few engineers who have embraced it are excelling.
- pton_xd 2y ago
  You likely should have replaced those devs years ago. Kudos to LLMs helping you figure that out though.
  - bobxmax 2y ago
    Nope. They were talented devs who all (well, most) landed in great companies after. We just didn't need them anymore because LLMs and tools like cursor are insanely good.
- stavros 2y ago
  I'd like to come back to this in a year to see how maintainable the codebase is.
  - bobxmax 2y ago
    Guess what happens when you can suddenly build features ahead of schedule? You can make them bulletproof instead of cutting corners. Our code is better and more robust than it's ever been. Our rate of user-reported bugs have dropped more than 50% since we started "vibe" coding 6-ish months ago.
- jgilias 2y ago
  After all these years 10x devs have become a reality.
- barbazoo 2y ago
  > I've replaced a product team which had 9 devs 2 years ago with 2 devs with AI. Totally believable bro
jgilias 2y ago
I feel exactly the same. On the other hand, the “speed up my work a lot” part is important, and shouldn’t be overlooked. Like, if someone reads this article and figures they don’t need to learn to use AI for their coding job, that’s the wrong conclusion to make.
- Trasmatta 2y ago
  Agreed, I feel that a developer who refuses to learn to work with AI tools will inevitably fall behind those that do. But I don't see AI being able to replace a developer who can work WITH AI anytime soon (at least on anything non trivial).
dataflow 2y ago
> But it's nowhere close to being able to replace what I do. I'm increasingly worried that that's not the same bar employers will have.
hollerith 2y ago
Wait 10 years, though.
- cmdli 2y ago
  I heard the same thing about self driving cars. AI advancements aren’t predictable, and it’s easy to understand or overestimate.
- nextts 2y ago
  This is what is really interesting. What will they do in 10 years. Will you need to learn mathematics to Phd level to produce code that an LLM cannot produce. Will we all become business analysts (Will AI do that too?). I don't think BA is a step down or up. It is probably interesting I did think of going down that path. People laugh at coders like we are the only manual loom operators when everyone's job, even PotUS can replaced by the AI we can dream will exist. My thoughts: buy SPX so you own a sliver of the new overlords.
TrackerFF 2y ago
Now think where we were 5 years ago, and where we will be in the next 5-10 years. A lot of kids are going to enroll college to study CS, computer engineering, software engineering, etc. - and will not finish their degrees until 3-5 years. They might just find themselves redundant (junior positions, that is)
minimaxir 2y ago
The only defense of vibe coding I'll make is that LLMs are very good at identifying decent implementations of business logic, such as workflows I may not have otherwise considered or found on StackOverflow. That then becomes a decent starting point for future iteration, but would never trust the "vibe" of the code itself even if that's what all the AI hypesters are doing. Despite developing LLMs for years I haven't actually used them much in day-to-day work, but asking Claude 3.7 Sonnet my coding questions has been a superior experience to just Googling them (particularly if there are specific functional requirements/constraints)
jevndev 2y ago
I feel like a lot of people are forgetting how good llms are at small isolated tasks because of how much better they've gotten at larger tasks. The best experiences I've had with llms all involve sketching out the interfaces for components I need and letting it fill in the implementation. That mentality also rewards choices that lead to good/maintainable code. you give functions good names so the AI knows what to implement. You make the code you ask it to generate as small as possible to minimize the chance of it hallucinating/going off the rails. You stub simple apis for the same reason. And (unsurprisingly) small, well defined functions are extremely testable! Which is a great trait to have for code that you know can very well be wrong. In time the AI will be good enough design whole applications in this vibe-code-y way... But all of the examples I've seen so far indicate that even the best publicly available models aren't there. It seems like every example I've seen has the developer bickering with the ai about something it just won't get right - often wasting more time than they were slightly more hands on. Until the tech gets over that I'll stick to it being the "junior developer I give a uml diagram to so they can figure out the messy parts".

varenc 2y ago

Speeding up your work does lead to job loss. If some developers can suddenly be 3x as productive than a company doesn't need as many engineers.

cmdli 2y ago
The job loss depends on the average speed up, however. If the AI is only effective in 10% of tasks (the basic stuff), then that 3x improvement goes down to 1.3x.
- toogan 2y ago
  > The job loss depends on the average speed up, That's such a economical fallacy that I'd expect the HN crowd to have understood this ages ago. Compare the average productivity of somebody working in a car factory 80 years ago with somebody today. How many person-hours did it take then and how many does it take today to manufacture a car? Did the number of jobs between then and now shrink by that factor? To the contrary. The car industry had an incredible boom. Efficiency increase does not imply job loss since the market size is not static. If cost is reduced then things are suddenly viable which weren't before and market size can explode. In the end you can end up with more jobs. Not always, obviously, but there are more examples than you can count which show that.
  - ekidd 2y ago
    This is all broadly true, historically. Automating jobs mostly results in creating more jobs elsewhere. But let's assume you have true, fully general AI. Further assume that it can do human-level cognition for $2/hour, and it's roughly as smart as a Stanford grad. So once the AI takes your job, it goes on to take your new job, and the job after that, and the job after that. It is smarter and cheaper than the average human, after all. This scenario goes one of three ways, depending on who controls the AI: 1. We all become fabulously wealthy and no longer need to work at all. (I have trouble visualizing exactly how we get this outcome.) 2. A handful of billionaires and politicians control the AI. They don't need the rest of us. 3. The AI controls itself, in which case most economic benefits and power go to the AI. The last historical analog of this was the Neanderthals, who were unable (for whatever reason) to compete with humans. So the most important question is, how close actually are we to this scenario? Is impossible? A century away? Or something that will happen in the next decade?
    - toogan 2y ago
      > But let's assume you have true, fully general AI. Very strong assumption and very narrow setting that is one of the counter examples. AI researchers in the 80s already told you that AI is around the corner in the next 5 years. Didn't happen. I wouldn't hold my breath this time either. "AI" is a misnomer. LLMs are not "intelligence". They are a lossy compression algorithm of everything that was put into their training set. Pretty good at that, but that's essentially it.
c0redump 2y ago
Or it just leads to 3x more stuff being made. This conclusion isn’t nearly as trivial as you’re making it out to be.
AnimalMuppet 2y ago
Only if that company has a finite wish list for their software. That is rarely the case.
dghlsakjg 2y ago
That assumes a static demand for development services, which has, more or less, never happened since computing became a thing. Python, and other high level languages made a lot of development much faster, but it never lead to reduced engineering needs. Cloud made deploying services massively easier, and as a result we actually have a lot more people working in infrastructure. Faster development mostly leads to expanded economic viability for new types of software. The real question is what becomes economically feasible if development costs are halved.
- jetrink 2y ago
  Jevon's Paradox: https://en.wikipedia.org/wiki/Jevons_paradox https://en.wikipedia.org/wiki/Jevons_paradox "In 1865, the English economist William Stanley Jevons observed that technological improvements that increased the efficiency of coal use led to the increased consumption of coal in a wide range of industries. He argued that, contrary to common intuition, technological progress could not be relied upon to reduce fuel consumption."
  - ModernMech 2y ago
    It's the same reason widening the road doesn't lead to less traffic.
simonw 2y ago
Alternatively: if LLMs make devs 3x productive that means companies can get 3x the value out of an engineering hire, so they should hire more. (Unless that company somehow has no substantial engineering backlog, which I've yet to encounter anywhere I've ever worked.)
- varenc 2y ago
  This definitely feels true for tech companies where the prospect of more more productive engineers improves their bottom line. The same sort of companies that have a near infinite appetite for talented engineers. But there's a lot of coders in industries whose core business isn't technology. Knapheide for example, a truck outfitting company where my brother codes. I'd imagine in those companies, being able to do the same work with fewer engineers and less cost would lead to fewer hires. Technology isn't their core product and they aren't being held back by software.
  - simonw 2y ago
    I actually think we may see the opposite happen with those kinds of companies too. At the moment, a truck outfitting company building a customer CRM optimized for their workflow is an absurd idea: they would need a team of a dozen developers working for a year before they could even get a feel for if it was a feasible project or not. Add LLM assistance and maybe a team of three developers could get to an initial working version in three months. At that point, companies that had previously ruled out custom software development entirely may find that it makes sense for them - growing the demand for software engineers as a whole.
    - varenc 2y ago
      I guess I'm skeptical how much of an impact better software could have on the business success a truck outfitting company? But maybe I'm being overly skeptical. I bet if I really got in the weeds there I'd see tons of opportunities were better/more software could really accelerate things. Thanks for checking my pessimism!

bobxmax 2y ago

I work at a company relatively well-known in Startup-land and I've replaced a product team which had 9 devs 2 years ago with 2 devs with AI. Devs are just coping so hard around LLMs its hard to watch. OTOH the few engineers who have embraced it are excelling.

pton_xd 2y ago
You likely should have replaced those devs years ago. Kudos to LLMs helping you figure that out though.
- bobxmax 2y ago
  Nope. They were talented devs who all (well, most) landed in great companies after. We just didn't need them anymore because LLMs and tools like cursor are insanely good.
stavros 2y ago
I'd like to come back to this in a year to see how maintainable the codebase is.
- bobxmax 2y ago
  Guess what happens when you can suddenly build features ahead of schedule? You can make them bulletproof instead of cutting corners. Our code is better and more robust than it's ever been. Our rate of user-reported bugs have dropped more than 50% since we started "vibe" coding 6-ish months ago.
jgilias 2y ago
After all these years 10x devs have become a reality.
barbazoo 2y ago
> I've replaced a product team which had 9 devs 2 years ago with 2 devs with AI. Totally believable bro

jgilias 2y ago

I feel exactly the same. On the other hand, the “speed up my work a lot” part is important, and shouldn’t be overlooked. Like, if someone reads this article and figures they don’t need to learn to use AI for their coding job, that’s the wrong conclusion to make.

Trasmatta 2y ago
Agreed, I feel that a developer who refuses to learn to work with AI tools will inevitably fall behind those that do. But I don't see AI being able to replace a developer who can work WITH AI anytime soon (at least on anything non trivial).

dataflow 2y ago

> But it's nowhere close to being able to replace what I do. I'm increasingly worried that that's not the same bar employers will have.

hollerith 2y ago

Wait 10 years, though.

cmdli 2y ago
I heard the same thing about self driving cars. AI advancements aren’t predictable, and it’s easy to understand or overestimate.
nextts 2y ago
This is what is really interesting. What will they do in 10 years. Will you need to learn mathematics to Phd level to produce code that an LLM cannot produce. Will we all become business analysts (Will AI do that too?). I don't think BA is a step down or up. It is probably interesting I did think of going down that path. People laugh at coders like we are the only manual loom operators when everyone's job, even PotUS can replaced by the AI we can dream will exist. My thoughts: buy SPX so you own a sliver of the new overlords.

TrackerFF 2y ago

Now think where we were 5 years ago, and where we will be in the next 5-10 years. A lot of kids are going to enroll college to study CS, computer engineering, software engineering, etc. - and will not finish their degrees until 3-5 years. They might just find themselves redundant (junior positions, that is)

minimaxir 2y ago

The only defense of vibe coding I'll make is that LLMs are very good at identifying decent implementations of business logic, such as workflows I may not have otherwise considered or found on StackOverflow. That then becomes a decent starting point for future iteration, but would never trust the "vibe" of the code itself even if that's what all the AI hypesters are doing. Despite developing LLMs for years I haven't actually used them much in day-to-day work, but asking Claude 3.7 Sonnet my coding questions has been a superior experience to just Googling them (particularly if there are specific functional requirements/constraints)

jevndev 2y ago

I feel like a lot of people are forgetting how good llms are at small isolated tasks because of how much better they've gotten at larger tasks. The best experiences I've had with llms all involve sketching out the interfaces for components I need and letting it fill in the implementation. That mentality also rewards choices that lead to good/maintainable code. you give functions good names so the AI knows what to implement. You make the code you ask it to generate as small as possible to minimize the chance of it hallucinating/going off the rails. You stub simple apis for the same reason. And (unsurprisingly) small, well defined functions are extremely testable! Which is a great trait to have for code that you know can very well be wrong. In time the AI will be good enough design whole applications in this vibe-code-y way... But all of the examples I've seen so far indicate that even the best publicly available models aren't there. It seems like every example I've seen has the developer bickering with the ai about something it just won't get right - often wasting more time than they were slightly more hands on. Until the tech gets over that I'll stick to it being the "junior developer I give a uml diagram to so they can figure out the messy parts".