LLMs can't be strategic because they do not understand the big picture -- that the real work of good software is balancing a hundred different constraints in a way that produces the optimal result for the humans who use it.
It's not all that different from the state of big corp software today! Large organizations with layers of management tend to lose all abiliy to keep a consistent strategy. They tend to go all in on a single dimension such as ROI for the next quarter, but it misses the bigger picture. Good software is about creating longer term value and takes consistent skill & vision to execute.
Those software engineers who focus on this big picture thinking are going to be more valuable than ever.
>Good software is about creating longer term value and takes consistent skill & vision to execute.
>Those software engineers who focus on this big picture thinking are going to be more valuable than ever.
Not to rain on our hopes, but AI can give us some options and we can pick the best. I think this eliminates all middle level positions. Newbies are low cost and make decisions that are low stakes. The most senior or seniors can make 30 major decisions per day when AI lays them out.
I own a software shop and my hires have been: Interns and people with the specific skill of my industry(Mechanical engineers).
2 years ago, I hired experienced programmers. Now I turn my mechanical engineers into programmers.
> Not to rain on our hopes, but AI can give us some options and we can pick the best.
But that's kind of my point. A bunch of decisions like that tend to end up with a "random walk" effect. It's a bunch of tactical choices which don't add up to something strategic. It could be, but it takes the human in the loop to hold onto that overall strategy.
Why can’t LLMs understand the big picture? I mean, a lot of companies have most of their information available in a digital form at this point, so it could be consumed by the LLM.
I think if anything, we have a better chance in the little picture: you can go to lunch with your engineering coworkers or talk to somebody on the factory floor and get insights that will never touch the computers.
Giant systems of constraints, optimizing many-dimensional user metrics: eventually we will hit the wall where it is easier to add RAM to machines than humans.
> LLMs can't be strategic because they do not understand the big picture -- that the real work of good software is balancing a hundred different constraints in a way that produces the optimal result for the humans who use it.
There’s good reason to think that they could understand the big picture just fine, even today, except that they’re currently severely constrained by what we choose, or have time, to tell them. They can already easily give a much more comprehensive survey of suitable options for solving a given problem than most humans can.
If they had more direct access to the information we have access to, that we currently grudgingly dole out to them in dribs and drabs, they would be much more capable.
I don't feel like the abstraction away from assembly language resulted in fewer software engineering jobs. Nor do I feel like Java's virtual machine resulted in fewer systems engineering jobs. Somehow I don't feel that writing in English rather than pure logic will result in fewer engineering problems either. A lot more actually. But at least we'll get the requirements out of users into something concrete faster.
What is definitely going to be abundantly clear is just how much better machines can get at creating correct code and how bad each of us truly is at this. That's an ego hit.
The loving effort an artisan puts into a perfect pot still has wabi sabi from the human error; whereas a factory produced pot is way more perfect and possesses both a Quality from closeness to Idealism and an eerieness from its unnaturalness.
However, the demand for artisan pottery has niched out compared to Ikea bowls, so that's just how it is.
It's not all that different from the state of big corp software today! Large organizations with layers of management tend to lose all abiliy to keep a consistent strategy. They tend to go all in on a single dimension such as ROI for the next quarter, but it misses the bigger picture. Good software is about creating longer term value and takes consistent skill & vision to execute.
Those software engineers who focus on this big picture thinking are going to be more valuable than ever.
>Those software engineers who focus on this big picture thinking are going to be more valuable than ever.
Not to rain on our hopes, but AI can give us some options and we can pick the best. I think this eliminates all middle level positions. Newbies are low cost and make decisions that are low stakes. The most senior or seniors can make 30 major decisions per day when AI lays them out.
I own a software shop and my hires have been: Interns and people with the specific skill of my industry(Mechanical engineers).
2 years ago, I hired experienced programmers. Now I turn my mechanical engineers into programmers.
But that's kind of my point. A bunch of decisions like that tend to end up with a "random walk" effect. It's a bunch of tactical choices which don't add up to something strategic. It could be, but it takes the human in the loop to hold onto that overall strategy.
I think if anything, we have a better chance in the little picture: you can go to lunch with your engineering coworkers or talk to somebody on the factory floor and get insights that will never touch the computers.
Giant systems of constraints, optimizing many-dimensional user metrics: eventually we will hit the wall where it is easier to add RAM to machines than humans.
Only thing to add, maybe we have the most senior of seniors verifying the decisions of AI.
Because LLMs don't understand things to begin with.
Because LLMs only have access to aource code and whatever .md files you've given them.
Because they have biases in their training data that overfit them on certain solutions.
Because LLMs have a tiny context window.
Because LLMs largely suck at UI/UX/design especially when they don't have referense images.
Because...
While I do tend to believe you, what evidence based data do you have to prove this is true?
IMO the onus is to prove that they can be strategic. Otherwise you're asking me to prove a negative.
There’s good reason to think that they could understand the big picture just fine, even today, except that they’re currently severely constrained by what we choose, or have time, to tell them. They can already easily give a much more comprehensive survey of suitable options for solving a given problem than most humans can.
If they had more direct access to the information we have access to, that we currently grudgingly dole out to them in dribs and drabs, they would be much more capable.
What is definitely going to be abundantly clear is just how much better machines can get at creating correct code and how bad each of us truly is at this. That's an ego hit.
The loving effort an artisan puts into a perfect pot still has wabi sabi from the human error; whereas a factory produced pot is way more perfect and possesses both a Quality from closeness to Idealism and an eerieness from its unnaturalness.
However, the demand for artisan pottery has niched out compared to Ikea bowls, so that's just how it is.
Given the models are unlikely to stop getting better, I think it is fair to say the human contribution is going to keep getting "leaner".
That is going to change the job, but also head count.
But I agree harnessing models opens up opportunities for better product design, ... but only ... everywhere.
The people who design the most usable software have always been in a minority. They will be valuable for some time.