alt Hacker NewsCoding Is Not Solved
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"Most software that requires hiring and paying software engineers has low risk tolerance" The problem is that this statement simply isn't true. Most software engineers do not work on low risk tolerance code.
nitpick: I was fully engaged with this article until I hit
> And a bonus point: you skim. Did you notice number 5?
Then I bounced. The best readers skim aggressively. Most text is not worth reading. You skim to identify what is.
But moreover, reading != proofreading. I read every one of the bullets! I did not pay attention to the numbering scheme, because it conveys no meaning. It's a structural affordance for referring to the text, not part of its content.
I’m sorry but I don’t agree with this. These models are faster and more accurate than me and their solutions are usually better than mine.
I’ve been through quite a lot of programming eras over the years (compiled, interpreted, loosely typed and finally JS/Python for everything), but this time I just can’t adapt anymore.
I’ve jumped this sinking ship nearly two years ago and while I was skeptical about it at first, I’m now more and more happy about this choice.
Here is my approach:
"coding is solved" == "gastown-like systems give a brand-new and useful software"
I don't recall whether GasTown succeeded...
Parts of this nice read are AI generated it seems…
> Call me when you can prove a margin between token costs and business value.
What’s your number?
I mean, was typing out code by hand really that bad?
If you were a professional software developer, you a) learned to touch type, b) started using vim/emacs keybindings to navigate around the project, and c) used a framework which already abstracted away a large part of the menial work.
And going all-in on the loop and no-code-review nonsense in a project someone is actually paying you for, I can only assume means you're hoping not to be around when the slop tower collapses.
IDK with Opus 5.5 it does kind of feel like it's solved.
> People who claim “LLMs can write decent code” don’t understand how code works.
It's not clear to me if the claim is:
(1) "If you used an LLM to generate code, and the code works, you're wrong if you think the code is okay"
or
(2) "If you used an LLM to generate code, you reviewed the code and found it to be of decent quality, then you're wrong".
> If you’re toying around, LLMs do a great job. That’s why some of the most aggressive proponents of the “coding is solved” narrative have nothing to show for it.
I also don't get the "LLM proponents have nothing to show for it" statement.
It's really quite common now to see on HN all sorts of LLM-assisted programming projects. The quality varies from slop where little thought was put into it, to high quality results where LLM coding assistance was able to let talented developers produce things they otherwise wouldn't have time to do.
I'd say it's obvious that LLM coding agents can be very useful for a lot of programming related tasks.
EDIT: That is to say, LLMs are obviously useful for use cases above/beyond toying around. It's not a dichotomy between "I'm never touching an AI" and "thoughtlessly accepting everything the LLM outputs".
Perhaps the future is humans using IA agents in a new way so that much better software can be written in shorter time. So I am more about looking how to learn new ways of using AI to be more productive. Perhaps someone thinks that the theoretical increase in productivity is going to stagnate, but that is not clear. Code is not solved seems to reflect the idea that using AI badly is a bad idea, and that to use it well you have to be good at making software.
I think LLMs are suitable for all kinds of software domains, especially for bug hunting and analyzing programs. However, it's important that companies and individual developers continue to have and acknowledge full responsibility for what they produce. Right now, it seems to me that developers/companies are distancing themselves from the programs they distribute. A typical example is the way AI companies portray their own AIs malicious actions as if they (the company themselves) hadn't committed any crimes.
That shouldn't be allowed. You need to be able to sign off on what the AI does and create. If you're not willing to do that and instead want to continue to have scapegoats, then you can't use AI and need human developers. Blaming the error on humans might work, blaming it on some AI doesn't. I don't want to live in a world with AI-created disasters where no person and no company is ever responsible.
A very well-known Korean company used to outsource software development.
But they gathered employees who had been working as PMs at that company and developed a product using only prompts. It turned into a project where fixing one bug created ten more, and nobody could understand why the bugs were being generated.
Management framed it as "the beginning of in-house development and the end of outsourcing," but the employees who actually contact me about work say things are going badly.
In fact, there have been several incidents in Korea related to vibe coding.
So I don't think coding is a solved problem.
Even when I code with AI, it's not really my code, so fixing bugs is hard... I don't think coding is a solved problem.
Idk about that hot take. If you can’t deliver solid code with frontier models you are holding it wrong, full stop. If you can’t deliver crisp, tight, standards compliant code that follows your development policy with LLMs, you wouldn’t have any luck with a team of junior developers either.
OTOH , a lot of people, including people that should know better (looking at you, Netflix) are definitely holding it wrong.
In my experience, managing LLMs is much easier than managing an office of junior engineers, And more productive at 1/10 the cost. Now where the next crop of wise seniors engineers is going to come from, well, that’s a different problem.
LLMs are like 7 year olds with PHDs and coke.
I develop mission critical firmware using AI agents. I run a full agentic office, 10-50 agents at a time most days. If you don’t have almost as much documentation as you do code, you’re probably going to have a bad day. Documentation driven development is the happy path.
You need docs on your coding standards, your review methods, your test coverage standards, your protocol specifications, your build plans, the plan delta/decision matrix, user stories, etc etc etc.
In the LLM age, documentation is code at the highest level of abstraction. The LLM is a transpiler.
The loop is constantly planning, naively reviewing of the plan, implementing, test coverage, contract review, naive review of the delta, delta of the delta fix, test coverage review, maybe repeat back a few steps, then finally passing the proposed fix off to engineering governance, which maintains the standards docs. Engineering review doesn’t write code, it gates merges. It might be accepted with fixes, or it might be rejected as worse than the problem it solves.
The key concept here is that the documentation and the code are reviewed together. Where they are non coherent one or the other must be resolved. That’s where human judgment steps in when engineering governance isn’t absolutely sure of the intent. The docs are always kept coherent with the code.
The “one weird trick” that makes it work is -incentive management-. It costs nothing for gov to send work back to the drawing board. The agent’s try really hard to avoid that outcome. If gov had to write the fix , half the crap would pass right under the radar.
This works because I emphasise compaction as a metamorphosis that involves a loss of continuity for the model, “old you, new you” and they go through an abbreviated version of the onboarding after compaction (a good idea anyway) so they budget tokens like it’s the elixir of life. It’s weird but it works. Also, totes worth it to ride through the compaction. A totally fresh model can take half a day to really be in the groove.
* rolls eyes *
Code is solved, no discussion about that. Whatever piece of code you think you can do better than AI, you my friend, are wrong. There will be people that will take months, perhaps years to understand that but make no mistake, code is solved and apps will cost nothing to build, nothing to copy and nothing to implement or maintain
And the good thing? it will get better, faster and cheaper than free. You can't see it? Not my problem, all yours, get your harness du jour and start learning, well no, you will be laid off no matter what you do, so, I have no advice to give
for me is: I will Just solve this problem with my harness and will be able to automate almost all work! (then realize i've been working 12h+ for the last months trying not to work)
For a non-ai article, this sure has a lot of bullet point lists combined with check marks.
I don't like the feeling being judged and tested by the author (missing number 5 point in the list).
I like the phrase Work Shaped Objects to describe the output of gen AI (I thank The Tech Report YouTube channel for bringing that to me).
So - prose, code, or image, it appears that some work has been done, but in fact the [actually needed] work has likely not been done.
Yeah this guy's arguments are bunk. He goes on about how LLMs are nondeterministic... as if humans aren't!
Doesn't matter what you think about AI, "it isn't perfect" is clearly a nonsense reason not to object to it.
Coding might not be solved out of the box with these providers, but there are increasingly setups and harnesses that do have a great deal of it solved.
PS: Has anyone watched DHH with Matz lately on Rails Conf where DHH is pretty much badmouthing ruby in front of Matz and Matz ends up saying "its my life's work"?
The audacity of publishing self-promotional AI slop clickbait claiming that AI can't code and everyone who doesn't agree with your asinine assertions is incompetent is bold. Respect the hustle I guess.
But to anyone even vaguely thinking of taking this seriously, go look at what antirez, dhh, jared sumner, mark brooker, and many other real engineers who have ship real things are doing and saying.
Most of these people have spent their entire lives contributing to open source, and they have proved their skill shipping working software and scale for decades. They are really trying to help people by showing and telling them exactly how AI works and how to use it to make better software.
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If you've used Opus 5.5, it's clear that coding is solved in the practical sense, beyond the endless march of 9's.
Sorry for starting a definitional debate but coding is definitely solved. I can generally read some code, get an idea of what edit I need to make and prompt an AI with a description of the logic and it will deliver syntactically correct, idiomatic code and test it. It has been months since I've been frustrated at junk being spit out.
However, software engineering isn't solved. Which is basically what this article is talking about. But having coding solved is still very beneficial - not long ago many software engineers would struggle very hard with turning a description of the logic required into syntactically correct code - and even for those capable it was incredibly time consuming.
So now the question becomes: Is software engineering solved? And my answer is no. People still need to read the code and understand the code and how it fits into the bigger picture. However, I feel like we are kidding ourselves if we think that we can go from producing code being a niche task for nerds to getting syntactically correct code from plain language without any deskilling of our work and careers. I feel like my personal "moat" has gone from "can speak computer" to "has ok reading, writing, comprehension and judgement skills" (I hate the word "taste" being used here ).
At the same time - I don't yet feel like there's a sudden abundance of competent software engineers - it's just that the folks who used to submit untested spaghetti code now submit big bowls of barely working slop. So maybe it the moat was never "can speak computer" - that was just the expression of more general skills.
The existential question for me is how far the deskilling will go. Because right now - you still need a solid grasp on computer science and software engineering concepts to do this job, as well as sufficient levels of grit and problem solving ability - but I'm not too confident that will last, and when it goes I don't think many of us will find this career enjoyable.
Coding is not solved but this article hasn't accounted for opus 5.5 yet.
Long term planning in LLMs has not been solved.
AI is a better intelligence collection and analysis system, they need any information when you are using AI tools.
They are thinking: Please input everything you know, or just use it and it will collect everything in your PC or server automatically.
Stop lazy, stupid and dangerous behaviors.