4 ms·

These posts are never written by software engineers, it’s always some tech exec, retired engineer, or VC. This author is apparently a professor at the Wharton S

These posts are never written by software engineers, it’s always some tech exec, retired engineer, or VC. This author is apparently a professor at the Wharton School of Management? None of these people have to ship or maintain real products, they’re just making side projects. The only decent software engineering perspective I’ve seen has been from Mitchell Hashimoto.

jimbokun 4mo ago
Well that’s kind of the point. They can just summon bespoke software out of the ether that only handles the use cases of themselves and a few of their collaborators. Making “side projects” was mot possible for non-developers before powerful LLMs. Now it is.
- shimman 4mo ago
  Making side projects isn't a trillion dollar industry tho, adding to the fact that we are facing another global supply chain crisis due to the Iran War; the US is about to commit the biggest self-own ever in the history of empire.
  - zelphirkalt 4mo ago
    The US has been on a course of self-owns ever since Trump got into office. That they still are a dominant power on the globe shows how much they were one before Trump, but it seems to be changing. At every self-own they commit, China laughs and inches up a little closer. I think we will see the day, when they are evenly matched in our lifetimes. But which self-own exactly do you mean, of the many there are?
  - Schmerika 4mo ago
    There are actually quite a few trillion dollar industries that exist thanks to "side projects". Apple was Woz's side project, once upon a time. Adsense came from Google's 20% time. Social media started as a side project. Forests grow from trees. Trees grow from seeds. More potential seeds = more potential forests.
    - queenkjuul 4mo ago
      All the undiscovered Woz's of the world add up to a trillion dollars? There's $1T of money out there waiting to be spent on side projects? The question was "are side projects a trillion dollar industry" not "has a side project ever started an industry" How much of a new $1T software product will anthropic capture in token costs, anyway?
- an0malous 4mo ago
  I don’t think that’s true, I think these authors are making a much stronger claim that AI is proficient or even an expert at software engineering. This author describes how complex and sophisticated their software is, and the only value he’ll concede to “coders” is that there might be a few bugs they’d need to fix. Imagine not being an architect and using Claude to put together a building plan, then concluding it’s basically done but we might need a real architect to double check the measurements. It may even be true but I’d be skeptical if it’s always non-architects saying this.
  - bathtub365 4mo ago
    Why do they even need coders to fix these bugs? It would be an order of magnitude (at least) to ask Claude to find and fix them, and it will likely be successful. Building in the physical world has physical and time constraints that cannot be overcome, which is one of the reasons architecture (and engineering) are so important in this domain. In software development these constraints were only inherent when people were writing the majority of the software. I feel like I’m seeing what I thought were fundamental constraints being eroded by the increasing speed and correctness of these tools and it’s making me reconsider the importance of some of the values that are held by software engineering. It’s obviously dependent on the domain and solution, but if your software can be extremely rapidly rearranged, bugs found and fixed with little effort, and features added with only a minimum prompt, I think the entire definition of technical debt has changed. I’ve been sceptical of these tools and still approach their output with caution. I also worry that, as a software developer, if more can be accomplished in less time there will be less room on this planet for software developers.
    - phil21 4mo ago
      > I think the entire definition of technical debt has changed. I’ve been sceptical of these tools and still approach their output with caution. This very well summarizes my current thinking on the subject as well. And most of my career has been playing the role of technical debt nazi. Much to the detriment of my earning potential. Does AI make incredibly inefficient code most of the time? Yup. But it does it at lightspeed with minimal effort. I think many software engineers forget they exist to get real things done (in many cases at least) and they are a cost center for most businesses. If your end product is not selling software, very few people actually Doing the Thing(tm) will give a single solitary care about code quality or maintainability when they can just spend 30 minutes and $15 worth of tokens to fix it. It won't take over everything, but I've already seen otherwise very intelligent go-getter type folks who are not technical or know how to code made extremely useful things for themselves and their small little enterprises. And this will seemingly only get better and more efficient. For someone who really does love the idea of well architected and future-proof code this is just icky to even say or consider. But I'm coming around to this is the future for the majority of software for most places. And it may have the ability to seriously even the playing field for small enterprises in some industries. I'm currently using it to implement a zillion side projects at home I've been "meaning to get to" for years. It makes incredibly silly unmaintainable code most of the time - but I learned to not care, and just tell the AI bot to fix it/add to it as I go along. Worst-case I spend a single night deleting it all and starting from zero to "refactor" an entire thing.
- SpicyLemonZest 4mo ago
  It is, and it's cool that it is, but the calibration is important. Statements like this: > With Fable the spell has gotten powerful enough that I am no longer sure I am the wizard. I am closer to a patron. I describe what I want, I pay for it, and I judge the result. The conjuring happens somewhere I cannot watch, in hundreds of small choices I never get a vote on. The work has shifted from process to outcome. I no longer steer; I commission. have a very different meaning coming from a non-technical researcher than they would from someone who builds software for a living.
- bandrami 4mo ago
  Well, right, but if the real use case for LLMs is "making software that wasn't economical to make before" that's bearish for the labs because it means they're only going to be chasing the low end of the market.
neilv 4mo ago
Relevant quote: > I am sure it is not perfect (I only spent an hour working with the results), but a software engineer would iron out the remaining potential bugs that I could not find quickly [...] People have said things like this many times in the past, and, in the past (perhaps not now), it's always been a misunderstanding of what is good and bad, what's difficult and easy. For example, someone would draw a UI in a GUI painter that generates code (or a resource file), and a manager would see it and think the majority of the work towards the product is done. (Incidentally, then there seemed to be a reaction, towards making your UI mockups look abstract or otherwise different from runnable code, helping the nontechical to understand that this isn't 90% of the finished product.) Or a student intern hacks out a homework-grade demo, and a manager who understands neither software engineering nor product domain says "we just need some engineers to polish it up for production", and thinks the student is a star and why can't their engineers be as brilliant and productive. (I might have once been that energetic intern, who was happy for the encouragement, but then learned more, and saw it was a thing.) This common misunderstanding was sometimes self-correcting -- when trying to ship became a disaster of misery and regretted-attrition, or the product was poorly received by the market because it wasn't thought through nor implemented well, or building subsequent functionality atop it was a nightmare. (But adverse effects of bad approaches is one of the reasons for management and ICs to job-hop, before the unwanted effects affect them personally.) What might be different now is that some of these AI tools are outputting better-engineered work than some software engineers, and much faster. At the back of my mind, I'm wondering how the really great software engineers will continue to stand out, as the discipline is being devalued in the minds of most leadership, and anyone can prompt an AI to generate something that superficially appears to them like what they assume a great software engineer would produce. (Even if the great engineer would do much better quality of implementation, have innovative ideas that ML from open source code would not, and maybe arrive at better product concepts as they worked through the problems.)

jimbokun 4mo ago

Well that’s kind of the point. They can just summon bespoke software out of the ether that only handles the use cases of themselves and a few of their collaborators. Making “side projects” was mot possible for non-developers before powerful LLMs. Now it is.

shimman 4mo ago
Making side projects isn't a trillion dollar industry tho, adding to the fact that we are facing another global supply chain crisis due to the Iran War; the US is about to commit the biggest self-own ever in the history of empire.
- zelphirkalt 4mo ago
  The US has been on a course of self-owns ever since Trump got into office. That they still are a dominant power on the globe shows how much they were one before Trump, but it seems to be changing. At every self-own they commit, China laughs and inches up a little closer. I think we will see the day, when they are evenly matched in our lifetimes. But which self-own exactly do you mean, of the many there are?
- Schmerika 4mo ago
  There are actually quite a few trillion dollar industries that exist thanks to "side projects". Apple was Woz's side project, once upon a time. Adsense came from Google's 20% time. Social media started as a side project. Forests grow from trees. Trees grow from seeds. More potential seeds = more potential forests.
  - queenkjuul 4mo ago
    All the undiscovered Woz's of the world add up to a trillion dollars? There's $1T of money out there waiting to be spent on side projects? The question was "are side projects a trillion dollar industry" not "has a side project ever started an industry" How much of a new $1T software product will anthropic capture in token costs, anyway?
an0malous 4mo ago
I don’t think that’s true, I think these authors are making a much stronger claim that AI is proficient or even an expert at software engineering. This author describes how complex and sophisticated their software is, and the only value he’ll concede to “coders” is that there might be a few bugs they’d need to fix. Imagine not being an architect and using Claude to put together a building plan, then concluding it’s basically done but we might need a real architect to double check the measurements. It may even be true but I’d be skeptical if it’s always non-architects saying this.
- bathtub365 4mo ago
  Why do they even need coders to fix these bugs? It would be an order of magnitude (at least) to ask Claude to find and fix them, and it will likely be successful. Building in the physical world has physical and time constraints that cannot be overcome, which is one of the reasons architecture (and engineering) are so important in this domain. In software development these constraints were only inherent when people were writing the majority of the software. I feel like I’m seeing what I thought were fundamental constraints being eroded by the increasing speed and correctness of these tools and it’s making me reconsider the importance of some of the values that are held by software engineering. It’s obviously dependent on the domain and solution, but if your software can be extremely rapidly rearranged, bugs found and fixed with little effort, and features added with only a minimum prompt, I think the entire definition of technical debt has changed. I’ve been sceptical of these tools and still approach their output with caution. I also worry that, as a software developer, if more can be accomplished in less time there will be less room on this planet for software developers.
  - phil21 4mo ago
    > I think the entire definition of technical debt has changed. I’ve been sceptical of these tools and still approach their output with caution. This very well summarizes my current thinking on the subject as well. And most of my career has been playing the role of technical debt nazi. Much to the detriment of my earning potential. Does AI make incredibly inefficient code most of the time? Yup. But it does it at lightspeed with minimal effort. I think many software engineers forget they exist to get real things done (in many cases at least) and they are a cost center for most businesses. If your end product is not selling software, very few people actually Doing the Thing(tm) will give a single solitary care about code quality or maintainability when they can just spend 30 minutes and $15 worth of tokens to fix it. It won't take over everything, but I've already seen otherwise very intelligent go-getter type folks who are not technical or know how to code made extremely useful things for themselves and their small little enterprises. And this will seemingly only get better and more efficient. For someone who really does love the idea of well architected and future-proof code this is just icky to even say or consider. But I'm coming around to this is the future for the majority of software for most places. And it may have the ability to seriously even the playing field for small enterprises in some industries. I'm currently using it to implement a zillion side projects at home I've been "meaning to get to" for years. It makes incredibly silly unmaintainable code most of the time - but I learned to not care, and just tell the AI bot to fix it/add to it as I go along. Worst-case I spend a single night deleting it all and starting from zero to "refactor" an entire thing.
SpicyLemonZest 4mo ago
It is, and it's cool that it is, but the calibration is important. Statements like this: > With Fable the spell has gotten powerful enough that I am no longer sure I am the wizard. I am closer to a patron. I describe what I want, I pay for it, and I judge the result. The conjuring happens somewhere I cannot watch, in hundreds of small choices I never get a vote on. The work has shifted from process to outcome. I no longer steer; I commission. have a very different meaning coming from a non-technical researcher than they would from someone who builds software for a living.
bandrami 4mo ago
Well, right, but if the real use case for LLMs is "making software that wasn't economical to make before" that's bearish for the labs because it means they're only going to be chasing the low end of the market.

neilv 4mo ago

Relevant quote: > I am sure it is not perfect (I only spent an hour working with the results), but a software engineer would iron out the remaining potential bugs that I could not find quickly [...] People have said things like this many times in the past, and, in the past (perhaps not now), it's always been a misunderstanding of what is good and bad, what's difficult and easy. For example, someone would draw a UI in a GUI painter that generates code (or a resource file), and a manager would see it and think the majority of the work towards the product is done. (Incidentally, then there seemed to be a reaction, towards making your UI mockups look abstract or otherwise different from runnable code, helping the nontechical to understand that this isn't 90% of the finished product.) Or a student intern hacks out a homework-grade demo, and a manager who understands neither software engineering nor product domain says "we just need some engineers to polish it up for production", and thinks the student is a star and why can't their engineers be as brilliant and productive. (I might have once been that energetic intern, who was happy for the encouragement, but then learned more, and saw it was a thing.) This common misunderstanding was sometimes self-correcting -- when trying to ship became a disaster of misery and regretted-attrition, or the product was poorly received by the market because it wasn't thought through nor implemented well, or building subsequent functionality atop it was a nightmare. (But adverse effects of bad approaches is one of the reasons for management and ICs to job-hop, before the unwanted effects affect them personally.) What might be different now is that some of these AI tools are outputting better-engineered work than some software engineers, and much faster. At the back of my mind, I'm wondering how the really great software engineers will continue to stand out, as the discipline is being devalued in the minds of most leadership, and anyone can prompt an AI to generate something that superficially appears to them like what they assume a great software engineer would produce. (Even if the great engineer would do much better quality of implementation, have innovative ideas that ML from open source code would not, and maybe arrive at better product concepts as they worked through the problems.)