I agree in principle, but I think the 2-5% estimate is extremely low. I could be sold on most developers spending ~25%, up to 40% of their time on code. But very few people are spending 2% of their time on it. Unless you're some sort of super senior staff / advisor to the CTO at a gigantic company, which has already placed you on rare terrain.
This is a really, really, really bad comparison. I used to say the same thing. But the semantic distance between compiling a for loop to equivalent assembly instructions is much smaller than the distance between "I'd like a web application that can store and retrieve todo items." The space of the latter is practically infinite in what can be "compiled."
That’s literally what the post is about. I don’t see your point. The post is saying that formal tools currently do not handle performance and reliability problems. No one said otherwise.
I’m starting to think this take is legitimately insane.
As said in the article, a conservative estimate is that Gen AI can currently do 2.5% of all jobs in the entire economy. A technology that is really only a couple of years old. This is supposed to be _disappointing_? That’s millions of jobs _today_, in a totally nascent form.
I mean I understand skepticism, I’m not exactly in love with AI myself, but the world has literally been transformed.
Super interesting, but I think this will be very difficult in practice due to the gigantic effect of nondeterminism at the hardware level (caches, branch prediction, out of order execution, etc.)
I think this is less about guarantees and more about understanding behavioral characteristics in response to different loads.
I personally could care less about proving that an endpoint always responds in less than 100ms say, but I care very much about understanding where various saturation points are in my systems, or what values I should set for limits like database connections, or how what the effect of sporadic timeouts are, etc. I think that's more the point of this post (which you see him talk about in other posts on his blog).
This is the single most impactful blog post I've read in the last 2-3 years. It's so obvious in retrospect, but it really drove the point home for me that functional correctness is only the beginning. I personally had been over-indexing on functional correctness, which is understandable since a reliable but incorrect system isn't valuable.
But, in practice, I've spent just as much time on issues introduced by perf / scalability limitations. And the post thesis is correct: we don't have great tools for reasoning about this. This has been pretty much all I've been thinking about recently.
You just have to finish development in 8 hours.