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- Hacker News
- Not to be that one guy asking why this is on the front page of HN, but why is this on the front page of HN?by Retr0id
- Tricky to make predictions based on costs or quality when the costlier parts, training and inference, are totally disconnected from reality thanks to VC money and when total cost of ownership over time is radically different.by utopiah
- We might not even need libraries after all, since APIs, libraries and abstractions in general exist for humans to grasp complexities. Abstractions have their merits, but they have downsides too, and AI might be a way to solve them. The interesting part for me is where that ends, because it's systems all the way down, and even on a higher level abstractions exist to allow humans to make sense of the world. Services, products, companies, political parties, what if in the future we don't need any of it anymore because the abstraction is obsolete?by groestl
- > Business will accept 99.99 at fraction of cost of 99.999.
In my experience, there are far too many 9s in that sentence. But the sentiment absolutely holds.
by beej71 - > you might find the quality subpar, but in terms of cost ratio, it is commercially good enough. Business will accept 99.99 at fraction of cost of 99.999.
What is this based on?
- > Software Engineering as science will be largely dedicated to AI development
Which will require fewer people.
Simple software engineers who work on CRUDs and are not PhD-s and stuff will go away. Most of software is like this. The few percent who work on kernels, AI models, etc. will still have work. The rest won't, or rather much less people will be needed to simply use AI to do that work.
by dmortin - > No one is going to write new UI libraries if SOTA models know React best, no one is going to bother with new languages if SOTA models know Python, Go, JavaScript, and so on the best.
And here I sit with my own native cross-platform GUI library, made with my own Lisp-To-Rust programming language... Tell me more about what we all are not doing :)
- In my 30's I really hit my stride as a developer and system architect. Enough experience, seniority, and autonomy to own and build out large complex systems.
Many, many mid career devs, I fear, will miss this window. They will become reliant on the LLMs more and more. 2 months back, I was asked to backtest an interview question and 2 out of our 3 most senior engineers (both in their 30's) could no longer write a generic method.
I liken this experience to learning cursive as a kid. It wasn't about writing cursive; it was about developing dexterity and hand-eye coordination. Getting the reps in, so to speak. Even if the future is all AI, that window of expanding one's knowledge and understanding of system design and architecture through hands-on experience (and failure!) facilitates the formation of "taste" through reps: why A over B or C. When B over A or C?
Many, many devs will end up "going nowhere". They will be able to prompt and push code with the façade of productivity, but I think building stable, scalable, complex systems requires knowing which angles to probe and which questions to ask; things learned via reps of trying, failing, learning, failing some more, thinking hard, drawing it out, and finally hitting the breakthrough.
I recently published a series of blog posts that focuses on the underlying architecture decisions that I think can help teams set a solid foundation for building with AI [0]. I think the guidance and patterns in it are unlikely to be emergent from an LLM without very explicit prompting. The goal is to share the thought process and intent for each technical decision. I think this type of thinking may become more rare as folks surrender their reps to LLM defaults.
[0] https://chrlschn.dev/blog/2026/08/the-unexpected-ai-stack-cs...