Coding Is Not Solved: Why AI Can't Replace Accountable Engineers
Coding Is Not Solved – Alex Ewerlöf Notes
Alex Ewerlöf, a veteran developer with two engineering degrees, argues that the claim 'coding is solved' misunderstands software. While LLMs excel at personal projects and proofs of concept, most production software—healthcare, finance, aviation—demands accountability that AI cannot provide. He warns of 'AI overdose' and urges leaders not to force AI into every workflow, as it degrades services and puts an expiration date on developers' skills.
AI cannot be held accountable. It cannot suffer any consequences. The worst thing you can do to AI is to unplug it. And although it mimics human emotions (due to training data), it couldn’t care less.
- efficax
Reading the code does not mean you understand the code. One lesson that experience in software gave me: I never understood the code. You think it works a certain way, until you find out that it doesn't.
What LLMs make possible is for me to say: find out all the ways this thing works. Analyze the different ways we can run this software, build a fuzzer, build property tests, and run this software in every scenario possible. Log full traces. Log all the outputs. Now, analyze each scenario for bugs. You can't do that by hand.
If we are committed to it, if we put the resources towards it and dedicate the time to it (and we could do this just by saying: it will take half as long as it used to take!), software built by llms in healthcare, finance, automotive, defense, power plans, aviation, manufacturing can all be made MORE reliable and better with LLMs... without ever reading a single line of code. The LLMS are very good at logic, by the way.
Anyway all of this reads like someone who is not actually using LLMs to build software or hasn't tried them in a while. I felt the same way in 2025. I've written 100s of thousands of lines of difficult code. You, the person reading this, has probably interacted with software I've written. For a time you would've interacted with it every time you made a debit card transaction in the united states, for example. I understand code, and care about quality, and that's why I'm all in on LLMs for code.
- askonomm
What I've found is that AI allows lazy and incompetent developers to be more lazy and more incompetent. This then has the effect that product quality suffers more, faster. As a result of the sheer amount of code now being pushed out, code reviews, a thing that previously somewhat prevented lazy and incompetent developers from pushing out horrible code, is effectively dead in the water since no human can actually review such amounts of code realistically anymore. Some companies have adopted AI to review code, which, well ... you have AI make code, AI review code ... I hope you can see the stupidity here if you expect to see any deterministic results at all.
I guess time will tell if the consumer will adapt to the lower quality of products, allowing companies to justify the existence of lazy and incompetent developers, or if the consumer will push back, forcing companies to increase the quality of their developers.
Note: I use AI every day and it is entirely possible to create high quality software with it, so long as you are not lazy and incompetent.
- temp00345
I read such articles more or less every day.
This article would be 100% correct if it came out 1 year ago, 75% correct 9 months ago, 50% correct 3 months ago and it's probably 25% correct now if not less.
I totally understand where this is coming from. I too am struggling with accepting that my 30+ years of programming experience is quickly becoming obsolete. I'm losing sleep about this, it's tough.
But just go ahead and give the latest models (Opus 5.5 / Astra 6 as of today) another try.
See what they are capable of and read the code which they produce.
Any problem area, low level C++ or high level Typescript or Clojure or a weird combination of these..
Don't be shy, give them a big task, let them build an entire app, UI and all..
Now compare the output to Opus 4 or gpt-5 from 1 year ago - when they couldn't put together a single function without it being weird and buggy.
This is exactly my problem, not that the models are very good already, but how fast they got so good.
So if coding is not solved yet, it'll get there very soon.
- thesumofall
I think the author underestimates how boring and simple 90% of enterprise software is. The part that isn’t powering aircraft and power plants. So much of it originates from one-nighters, badly managed subcontractors, and requirements that are of low quality to begin with (because they are written by people who have very different day jobs). And you know what? Most of that runs 24/7 without a glitch. LLMs just gives us more of that. And maybe it’s even better
- brainless
I have been programming for about 30 years (including school years). Professionally for 18 years.
Can anyone tell me why we have 40 or more programming languages, with about 10 popular ones? Then about 20 frameworks in each of them. And add another 200 popular libraries for each language? This matrix make no sense till you realize - it is preferences all the way down.
Most of us engineers have built our own mental model of programming. We are all right. But the users do not care. LLMs are here to produce code closer and closer to the metal as needed. They can sit and create a graph out of every spec, use an AST that they develop and run on the CPU if they have to. They will do it. No amount of us discussing will stop that.
Programming is going to be re-invented. I do not think the current ways to write software will even matter.
- hibikir
> You cannot be responsible for what you can’t control either. That understanding is key to reasoning about system behavior and fixing it when the AI inevitably fails.
This is not a good premise. All over law, you will find people made responsible for what they don't control and they kind of own. Unleash a dog that harms a child, or just have it in an environment where it can escape, and see what happens.
There is such things as unpredictable situations where one might not be held responsible, as a problem might occur well past reasonable guidelines.
So of course you can be held accountable for what an AI that uou supposedly cannot quite control does, or for the AI-written code you deliver. Treat it like the releasing a wolf pack, or selling an unsafe toy that can maim children. There's precedent everywhere.
- thefilmore
From the authors of "coding is solved": Today, a colleague trying to run Claude Code ran into an issue where it shows the Bun help menu instead [1]. Previously, Claude Code uninstalled itself several times when I used it. [2]
- hakunin
Those who claim LLM-generated software is good enough:
Haven’t written code in ages
Cannot spot if their code figuratively had 6 fingers!
Have a low bar for what good looks like
Don’t care about quality or NFR
Have difficulty understanding an S-curve
There are exceptions like antirez, but I think this does hold for many loud optimists out there.
- lordnacho
My thoughts on this:
- Coding in the small is solved. I have a current state, I want to change it, and I know how I want to change it. Eg, I have a blocking TCP handler for some reason, and I want to make it async. I can either fiddle with it or just let LLM make the changes for me.
- Coding in the larger sense is never solved. You need judgement to decide what you want made. No matter what you're building, there will be decisions to make (Who/what is it for?) and those decisions change over time. LLMs can take some default decisions for you, and if you're fine with those, you get the default (great for POCs). However you might not even realize what it decided to do for you. At some scale, you will be spending a lot of time going over those decisions. But what we have now is that the friction of changing the decisions is quite a lot lower. You can now test a lot of things that previously were very time consuming.
- The point that LLMs are probabilistic is not as important as it's made out to be. If I ask a junior dev to code up something, I also don't know what he'll make. Heck, you can be sure that you are able to solve something, yet you yourself don't know what the solution will look like. Maybe it turns out the library you were going to use isn't appropriate after all. You don't know what you will use in the end, but you do know that something will fix the issue. There can be more than one solution to a problem, and it doesn't always matter which one you find.
- I STILL t […]
- josephmtummon
Reading the article, I definitely agreed with the author, but I also found myself agreeing with the counter arguments in the comments.
What I find conflicting personally about AI coding practices, is that I completely agree that AI is incredibly impressive at completing even complicated tasks, and I can at the very least say it is much much better than I am at writing code.
My issue with it, is that it gives you a "lazy" option every time that doesn't require the same level of thinking. I understand that this is completely on me as the developer, and the simple solution is that I need to make sure I'm taking my time to learn and understand what exactly the LLM is producing. I try this and have set up separate skills to make sure I'm building my understanding as I go.
Regardless, if I sit down today and implement something without the use of LLM, it takes me a lot longer, but once I get into it, I find a state of flow that I can never get from the back and forth reading of LLM output. Then when I finish, even if my solution is not perfect, I have learned so much more and my own context of problem is so much better, where usually then I can review with an LLM. This usually leaves me with a better implementation and more importantly one I can stand over.
I think for a newer dev like me (~2 years experience), since I haven't built up years and years of problem solving experience, if I don't carve out time in my day to put down the AI tools and improve on my problem solving, I'll […]