6 ms·

As someone who's both an IC and leads other developers I disagree with the explanation. As a technical lead, with people I can much better predict the quality o

by pron 7mo ago

As someone who's both an IC and leads other developers I disagree with the explanation. As a technical lead, with people I can much better predict the quality of the outcome than with LLMs, and the "failure modes" are much more manageable. As a programmer, I am actually more impressed with AI agents but in an informed and qualified way. Their debugging ability wows me; their coding ability disappoints and frustrates me. I think that the simple explanation for why executives are so hyped about AI is simply that they're not familiar with its severe current limitations. For example, Garry Tan seems to really believe he's generating 10KLOC of working code per day; if he'd been a working developer he would have known he isn't.

Aperocky 7mo ago
pass a certain LOC number, the utility become negative (unless they were pure tests).
- apothegm 7mo ago
  Even the utility of too many tests is negative. More upkeep and harder to change the code. And with LLMs also more context and token usage and cost.
  - Aperocky 7mo ago
    The biggest differentiating factor today is engineers and/or decision maker willing to say no to a certain feature or implementation. It's too easy to add bloat and complexity that can never go away, and with the tooling we now have a significant portion of engineers are now active risk to the projects they are working on.
- simianwords 7mo ago
  I disagree because I use it in a pretty huge codebase and it definitely saves time.
  - Aperocky 7mo ago
    I'm not talking about LLM, of course they save time. I'm talking about adding code to a code base. After a certain size, it's mostly garbage. I subscribe to the old unix principle and I have yet to seen a reason how LLM has changed it, it in fact became much more important now as a coding agent would happily add any crap to any repository.
- eddd-ddde 7mo ago
  I work in a huge code base. Thousands of projects I have never even taken a single look at. At least once a day I run into an issue and all I have to do is point an LLM at it, and it will successfully follow the chains of includes and function calls and accurately find root problems. It massively boosts my efficiency as just reading the code myself would take days.
orochimaaru 7mo ago
And one executive talks to other executives not to their engineers. I think this is more peer pressure than anything else.
- pydry 7mo ago
  They're oddly credulous of the shovel salesmen in the gold rush, too. E.g. when Jensen Huang said that you need to pair your $250k engineer with $250k of tokens.
- garciasn 7mo ago
  I lead a team of Data Engineers, DevOps Engineers, and Data Scientists. I write code and have done so literally for my entire life. AI-assisted codegen is incredible; especially over the last 3-4m. I understand that developers feel their code is an art form and are pissed off that their life’s work is now a commodity; but, it’s time to either accept it and move on with what has happened, specialize as an actual artist, or potentially find yourself in a very rough spot.
  - staticassertion 7mo ago
    I wonder if your background just has you fooled. I worked on a data science team and code was always a commodity. Most data scientists know how to code in a fairly trivial way, just enough to get their models built and served. Even data engineers largely know how to just take that and deploy to Spark. They don't really do much software engineering beyond that. I'm not being precious here or protective of my "art" or whatever. But I do find it sort of hilarious and obvious that someone on a data science team might not understand the aesthetic value of code, and I suspect anyone else who has worked on such a team/ with such a team can probably laugh about the same thing - we've uh... we've seen your code. We know you don't value aesthetic code lol. Single variable names, `df1`, `df2`, `df3`. I'm not particularly uncomfortable at the moment because understanding computers, understanding how to solve problems, understanding how to map between problems and solutions, what will or won't meet a customer's expectations, etc, is still core to the job as it always has been. Code quality is still critical as well - anyone who's vibe-coded >15KLOC projects will know that models simply can not handle that scale unless you're diligent about how it shoul dbe structured. My job has barely changed semantically, despite rapid adoption of AI.
detourdog 7mo ago
I'm sure an IC is not an integrated circuit or independent contractor. So what is it?
- auggierose 7mo ago
  It is silicon valley speech for "programmer".
- rkomorn 7mo ago
  Individual Contributor, usually as opposed to any kind of management role.
- pragmatic 7mo ago
  It’s manager speak for “less than.” The manager class sees worker units as fungible.
  - detourdog 7mo ago
    Must be from the divide and conquer school of management.
bitwize 7mo ago
A friend of mine works at a place whose CEO has been completely one-shotted; he vibe-coded an app and decided this could multiply their productivity like a hundredfold. And now he's implementing an AI mandate for every employee, replete with tracking and metrics and the threat of being fired of you don't play ball. I was explaining this to my wife, who asked, why doesn't the CEO understand the limitations and the drawbacks the programmers are experiencing. And I said—he doesn't care, because he's looking at what other businesses are doing, what they're writing about in Bloomberg and WSJ, what "industry best practice is", and where the money is going. Trillions of dollars are going in to revolutionizing every industry with AI. If you're a CEO and you're not angling to capture a piece of that, then the board is going to have some serious questions about your capability to lead the company. Executives are often ignorant of the problems faced by line workers in a way perhaps best explained by a particular scene from Swordfish (2001): "He lives in a world beyond your world..." https://www.youtube.com/watch?v=jOV6YelKJ-A https://www.youtube.com/watch?v=jOV6YelKJ-A The complaints of a few programmers just don't matter when you have millions or billions of capital at your command, and business experts are saying you can tenfold your output with half the engineering workforce. Right now there are only two choices for programmers: embrace generative AI fully and become proficient at it. Instead of surfacing problems with it, offer solutions: how can we use AI to make this better? Or have a very, very hard time working in the field.

by pron 7mo ago

Aperocky 7mo ago

pass a certain LOC number, the utility become negative (unless they were pure tests).

apothegm 7mo ago
Even the utility of too many tests is negative. More upkeep and harder to change the code. And with LLMs also more context and token usage and cost.
- Aperocky 7mo ago
  The biggest differentiating factor today is engineers and/or decision maker willing to say no to a certain feature or implementation. It's too easy to add bloat and complexity that can never go away, and with the tooling we now have a significant portion of engineers are now active risk to the projects they are working on.
simianwords 7mo ago
I disagree because I use it in a pretty huge codebase and it definitely saves time.
- Aperocky 7mo ago
  I'm not talking about LLM, of course they save time. I'm talking about adding code to a code base. After a certain size, it's mostly garbage. I subscribe to the old unix principle and I have yet to seen a reason how LLM has changed it, it in fact became much more important now as a coding agent would happily add any crap to any repository.
eddd-ddde 7mo ago
I work in a huge code base. Thousands of projects I have never even taken a single look at. At least once a day I run into an issue and all I have to do is point an LLM at it, and it will successfully follow the chains of includes and function calls and accurately find root problems. It massively boosts my efficiency as just reading the code myself would take days.

orochimaaru 7mo ago

And one executive talks to other executives not to their engineers. I think this is more peer pressure than anything else.

pydry 7mo ago
They're oddly credulous of the shovel salesmen in the gold rush, too. E.g. when Jensen Huang said that you need to pair your $250k engineer with $250k of tokens.
garciasn 7mo ago
I lead a team of Data Engineers, DevOps Engineers, and Data Scientists. I write code and have done so literally for my entire life. AI-assisted codegen is incredible; especially over the last 3-4m. I understand that developers feel their code is an art form and are pissed off that their life’s work is now a commodity; but, it’s time to either accept it and move on with what has happened, specialize as an actual artist, or potentially find yourself in a very rough spot.
- staticassertion 7mo ago
  I wonder if your background just has you fooled. I worked on a data science team and code was always a commodity. Most data scientists know how to code in a fairly trivial way, just enough to get their models built and served. Even data engineers largely know how to just take that and deploy to Spark. They don't really do much software engineering beyond that. I'm not being precious here or protective of my "art" or whatever. But I do find it sort of hilarious and obvious that someone on a data science team might not understand the aesthetic value of code, and I suspect anyone else who has worked on such a team/ with such a team can probably laugh about the same thing - we've uh... we've seen your code. We know you don't value aesthetic code lol. Single variable names, `df1`, `df2`, `df3`. I'm not particularly uncomfortable at the moment because understanding computers, understanding how to solve problems, understanding how to map between problems and solutions, what will or won't meet a customer's expectations, etc, is still core to the job as it always has been. Code quality is still critical as well - anyone who's vibe-coded >15KLOC projects will know that models simply can not handle that scale unless you're diligent about how it shoul dbe structured. My job has barely changed semantically, despite rapid adoption of AI.

detourdog 7mo ago

I'm sure an IC is not an integrated circuit or independent contractor. So what is it?

auggierose 7mo ago
It is silicon valley speech for "programmer".
rkomorn 7mo ago
Individual Contributor, usually as opposed to any kind of management role.
pragmatic 7mo ago
It’s manager speak for “less than.” The manager class sees worker units as fungible.
- detourdog 7mo ago
  Must be from the divide and conquer school of management.

bitwize 7mo ago

A friend of mine works at a place whose CEO has been completely one-shotted; he vibe-coded an app and decided this could multiply their productivity like a hundredfold. And now he's implementing an AI mandate for every employee, replete with tracking and metrics and the threat of being fired of you don't play ball. I was explaining this to my wife, who asked, why doesn't the CEO understand the limitations and the drawbacks the programmers are experiencing. And I said—he doesn't care, because he's looking at what other businesses are doing, what they're writing about in Bloomberg and WSJ, what "industry best practice is", and where the money is going. Trillions of dollars are going in to revolutionizing every industry with AI. If you're a CEO and you're not angling to capture a piece of that, then the board is going to have some serious questions about your capability to lead the company. Executives are often ignorant of the problems faced by line workers in a way perhaps best explained by a particular scene from Swordfish (2001): "He lives in a world beyond your world..." https://www.youtube.com/watch?v=jOV6YelKJ-A https://www.youtube.com/watch?v=jOV6YelKJ-A The complaints of a few programmers just don't matter when you have millions or billions of capital at your command, and business experts are saying you can tenfold your output with half the engineering workforce. Right now there are only two choices for programmers: embrace generative AI fully and become proficient at it. Instead of surfacing problems with it, offer solutions: how can we use AI to make this better? Or have a very, very hard time working in the field.