zlacker

>>gregor+(OP)
This is exactly the direction I expect AI-assisted coding to go in. Not software engineers being kicked out and some business person pressing a few buttons to have a fully functional app (as is playing out in a lot of fantasies on LinkedIn & X), but rather experienced engineers using AI to generate bits of code and then meticulously reviewing and testing them.

The million dollar (perhaps literally) question is – could @kentonv have written this library quicker by himself without any AI help?

>>paxys+A6
> Not software engineers being kicked out ... but rather experienced engineers using AI to generate bits of code and then meticulously reviewing and testing them.

But what if you only need 2 kentonv's instead of 20 at the end? Do you assume we'll find enough new tasks that will occupy the other 18? I think that's the question.

And the author is implementing a fairly technical project in this case. How about routine LoB app development?

>>gokhan+na
> But what if you only need 2 kentonv's instead of 20 at the end? Do you assume we'll find enough new tasks that will occupy the other 18? I think that's the question.

This is likely where all this will end up. I have doubts that AI will replace all engineers, but I have no doubt in my mind that we'll certainly need a lot less engineers.

A not so dissimilar thing happened in the sysadmin world (my career) when everything transitioned from ClickOps to the cloud & Infrastructure as Code. Infrastructure that needed 10 sysadmins to manage now only needed 1 or 2 infrastructure folks.

The role still exists, but the quantity needed is drastically reduced. The work that I do now by myself would have needed an entire team before AWS/Ansible/Terraform, etc.

>>theweb+8d
I think there's a huge huge space of software to build that isn't being touched today because it's not cost-effective to have an engineer build them.

But if the time it takes an engineer to build any one thing goes down, now there are a lot more things that are cost effective.

Consider niche use cases. Every company tends to have custom processes and workflows. Think about being an accountant at one company vs. another -- while a lot of the job is the same, there will always be parts that are significantly different. Those bespoke processes often involve manual labor because off-the-shelf accounting software cannot add custom features for every company.

But what if it could? What if an engineer working with AI could knock out customer-specific features 10x as fast as they could in the past. Now it actually makes sense to build those features, to improve the productivity of each company's accounting department.

It's hard to say if demand for engineers will go down or up. I'm not pretending to know for sure. But I can see a possibility that we actually have way more developers in coming years!

>>kenton+Wo
Which solves the now problem for the tomorrow problem.

We assume quite a bit about the challenge when we say it’s getting feature out.

It’s sort of like saying we can sprint faster with these tools, when the race is a marathon.

Or a better example is Coke vs Pepsi.

How do LLMs impact long term project, firm, process viability ?