> As an introductory project, I rewrote Numpy in Rust. It was great fun.

That's not a rewrite at all it's just a wrapping of an existing linear algebra Rust library (faer, blas, etc..) with a more Numpy like API. It seems to me that every AI project I look at is just a mashup/wrapper over existing things. Where are the real bootstrapped new things with AI ? Is there any big OSS project (Linux kernel, postgresql, Django, whatever) with serious bugfixes or new features implemented by AI that we could look at ?

Are so much people in programming implementing middleware / wrapping existing API all day that it gives them a feeling of liberation to be able to delegate those tasks ?

    • LLMs generate junk
    • LLMs generate a lot of junk

  "Stop": [
  {
    "hooks": [
      {
        "type": "command",
        "command": "afplay -v 0.40 /System/Library/Sounds/Morse.aiff"
      }]}],
  "Notification": [
  {
    "hooks": [
      {
        "type": "command",
        "command": "afplay -v 0.35 /System/Library/Sounds/Ping.aiff"
      }]}]

Easy to implement -> can talk to ElevenLabs or OpenAI and it's a pretty delightful experience

  ... there are some serious costs and reasonable 
  reservations to AI development. Let's start by listing 
  those concerns

  These are super-valid concerns. They're also concerns that 
  I suspect came around when we developed compilers and 
  people stopped writing assembly by hand, instead trusting 
  programs like gcc ...

One might as well equate the predictability of a Fibonacci sequence[0] to that of a PRNG[1] since both involve numbers.

0 - https://en.wikipedia.org/wiki/Fibonacci_sequence

1 - https://en.wikipedia.org/wiki/Pseudorandom_number_generator

But saying that AI development is more fun because you don’t have to “wrestle the computer” is, to me, the same as saying you’re really into painting but you’re not really into the brush aspect so you pay someone to paint what you describe. That’s not doing, it’s commissioning.

"The skillset you've spend decades developing and expected to continue having a career selling? The parts of it that aren't high level product management and systems architecture are quickly becoming irrelevant, and it's your job to speed that process along" isn't an easy pill to swallow.

Do we want everyone to operate at PM level? The space for that is limited. Its easy to say you enjoy vibe coding when you are high up the chain but for most devs we are not as experienced or lucky to be able to feel stable when workflows change every day.

But I dont feel I have enough data to believe whether vibe coding or hand coding is better, I am personally doing tedious task with AI, and still writing code by hand all the time.

Also the author presents rewriting Numpy in rust as some achievement but the AIs most probably trained on Numpy and RustyNum, AI are best at copying the code so its not really a big thing.

The code interleaves rules and control flow, drops side effects like “exit” in functions and hinges on a stack of regex for parsing bash.

This isn’t something I’ve attempted before but it looks like a library like bashlex would give you a much cleaner and safer starting point.

For a “throwaway” script like this maybe it’s fine, but this is typical of the sort of thing I’m seeing spurted out and I’m fascinated to see what people’s codebases look like these days.

Don’t get me wrong, I use CC every day, but man, you do need to fight it to get something clean and terse.

https://gist.github.com/mrocklin/30099bcc5d02a6e7df373b4c259...

Can someone tell me what the current thinking is on how we'll get over that gap?

AI can take you down a rabbit hole that makes you feel like you are being productive but the generated code can be a dead end because of how you framed the problem to the AI.

Engineers need enough discipline to understand the problems they are trying to solve before delegating a solution to a stochastic text generator.

I don’t always like using AI but have found it helpful in specific use cases such as speeding up CI test pipelines and writing spec; however, someone smarter than me/more familiar with the problem space may have better strategies that I cannot of think of, and I have been fooled by randomness.

[0]: https://claudio.click

Does the potential gain as an early adopter make it morally ok.

Because thats what these tiered uses of these AI and how it's been getting better works imo. It got lots of training data from juniors and seniors using it the last 2 years, it got better. It gets more appealing and leverages human psychology and marketing to get higher level engineers to train it as it and the companies extract more data. It needs and gets more data from the people willfully complying and using it. Wondering if theres a game theory design for this conundrum - what typically happens in nature in these scenarios?

All of these can create a diff across lots of files, but can be easily explained to a reviewer.

The problem is that I can’t trust an LLM to act deterministically the way I trust some people to. So I can’t just take that higher level view of “yep cool that sounds like a good idea” and skim the changes.

    --dangerously-skip-permissions

1. (conventional usage) https://code.visualstudio.com/docs/devcontainers/containers

2. (actual spec) https://containers.dev/

"Our ability to zoom in and implement code is now obsolete Even with SOTA LLMs like Opus 4.5 this is downright untrue. Many, many logical, strategic, architectural, and low level code mistakes are still happening. And given context window limitations of LLMs (even with hacks like subagents to work around this) big picture long-term thinking about code design, structure, extensibility, etc. is very tricky to do right."

If you can't see this, I have to seriously question your competence as an engineer in the first place tbh.

"We already do this today with human-written code. I review some code very closely, and other code less-so. Sometimes I rely on a combination of tests, familiarity of a well-known author, and a quick glance at the code to before saying "sure, seems fine" and pressing the green button. I might also ask 'Have you thought of X' and see what they say.

Trusting code without reading all of it isn't new, we're just now in a state where we need to review 10x more code, and so we need to get much better at establishing confidence that something works without paying human attention all the time.

We can augment our ability to write code with AI. We can augment our ability to review code with AI too."

Later he goes onto suggest that confidence is built via TDD. Problem is... if the AI is generating both code and tests, I've seen time and time again both in internal projects and OSS projects how major assumptions are incorrect, mistakes compound, etc.

I feel both that I can move faster and operate in areas that were previously inaccessible to me (like frontend). Experienced developers should all be doing this. We're good enough to avoid AI Slop, and there's so much we can accomplish today."

If frontend was "inacessible" and AI makes it "accessible", I would argue that you don't really know frontend and should probably not be doing it professionally with AI. Use AI, yes but learn frontend without AI first. And his "Experienced developers should all be doing this" is ridiculous. He should be honest and confess that he doesn't like programming. He probably enjoys systems design or some sort of role involving product design that does not involve programming. But none of these people are "developers".

>> [...]

>>No, you’re not too good to vibe code. In fact, you’re the only person who should be vibe coding.

All we have to do is produce more devs with 20 years of experience and we'll be set. :)

Experienced engineers can successfully vibe code? By definition it means not reading the output.

If you’re not reading your output, then why does skill level even matter?

What I always find amusing are the false equivalences, where one or several (creative) processes involving the hard work that is a fundamental part of the craft get substituted by push-to-"I did this!1!!" slop.

How's the saying go? "I hate doing thing x. The only thing I hate more is not doing thing x". One either owns that, or one doesn't. So that is indeed not mysterious. Especially not in a system where "Fake it till you make it" has been and is advertised as a virtue.

Why not output everything in C and ASM for 500x performance? Why use high level languages meant to be easier for humans? Why not go right to the metal?

If anyone's ever tried this, it's clear why: AI is terrible at C and ASM. But that cuts into what AI is at its core: It's not actual programming, it's mechanical reproduction.

Which means its incapabilities in C and ASM don't disappear when using it for higher-level languages. They're still there, just temporarily smoothed over due to larger datasets.

At work the projects are huge (200+ large projects in various languages, C#, TypeScript front-end libs, Python, Redis, AWS, Azure, SQL, all sorts of things).

AI can go into huge codebases perfectly fine and get a root cause + fix in minutes - you just need to know how to use it properly.

Personally I do "recon" before I send it off into the field by creating a markdown document explaining the issue, the files involved, and any "gotchas" it may encounter.

It's exactly the same as I would do with another senior software engineer. They need that information to figure out what is going on.

And with that? They will hand you back a markdown document with a Root Cause Analysis, identify potential fixes, and explain why.

It works amazingly well if you work with it as a peer.

But we are, even as of Opus 4.5, so wildly far away from what the author is suggesting. FWIW my experience is working in the AI/ML space at a major tech company and as a maintainer + contributor of several OSS projects.

People are blindly trusting LLMs and generating mountains of slop. And the slop compounds.

Even the earliest compilers didn't work by the programmer writing code, copying the assembly output into their source tree, and throwing away the code.

This is not a value judgement, they simply aren't the same thing at all.

This is true (to an extent), but the generated LLM code is also verifiable. We use automated tests to do it.

People keep saying this like it is an absolute fact, whereas in reality it is a scale.

Compilers are more deterministic than LLMs in general, but no they are not completely deterministic. That's why making reproducible builds is hard!

https://stackoverflow.com/questions/52974259/what-are-some-e... and https://github.com/mgrang/non-determinism give some good examples of this.

This leads to the point: in general do we care about this non-determinism?

Most of the time, no we don't.

Once you accept that the next stage is accepting that most of the time the non-deterministic output of an LLM is good enough!

This leads to how do I verify it is good enough which leads to testing and then suddenly you have a working agentic loop....

Some people find software architecture and systems thinking more fun than coding. Some people find conducting more fun than playing an instrument. It's not too mysterious.

I don't care if you use AI but leave me alone. I'm plenty fast without it and enjoy the process this author callously calls "wrestling with computers."

Of course this isn't going to help with the whole "making me fast at things I don't know" but that's another can of worms.

I think it’s a bit like a gambling addiction. I’m riding high the few times it pays off, but most of the time it feels like it’s just on the edge of paying off (working) and surely the next prompt will push it over the edge.

Indeed, of all the possible things to say!

AI "development" /is/ wrestling the computer. It is the opposite of the old-fashioned kind of development where the computer does exactly what you told it to. To get an AI to actually do what I want and nothing else is an incredibly painful, repetitive, confrontational process.

You've got a good analogy there though, because many great and/or famous painters have used teams of apprentices to produce the work that bears their (the famous artist's) name.

I'm reminded also of chefs and sous-chefs, and of Harlan Mill's famous "chief surgeon plus assistants" model of software development (https://en.wikipedia.org/wiki/Chief_programmer_team). The difference in our present moment, of course, is that the "assistants" are mechanical ones.

(as for how fun this is or isn't - personally I can't tell yet. I don't enjoy the writing part as much - I'd rather write code than write prompts - but then also, I don't enjoy writing grunt code / boilerplate etc., and there's less of that now, - and I don't enjoy having to learn tedious details of some tech I'm not actually interested in in order to get an auxiliary feature that I want, and there's orders of magnitude less of that now, - and then there are the projects and programs that simply would never exist at all if not for this new mechanical help in the earliest stages, and that's fun - it's a lot of variables to add up and it's all in flux. Like the French Revolution, it's too soon to tell! - https://quoteinvestigator.com/2025/04/02/early-tell/)

I like this. I'm going to see if my boss will go for me changing my title from Solutions Architect to Solutions Commissioner. I'll insist people refer to me as "Commissioner ajcp"

Well, I'll have to take their word for it that they're passionate about maximizing shareholder value by improving key performance indicators, I know I personally didn't sign up for being in meetings all day to leverage cross functional synergies with the goal of increasing user retention in sales funnels, or something along those lines.

I'm not passionate about either that or mandatory HR training videos.

AI is more fun for programmers that should've gone into management instead, and prefer having to explain things in painstaking detail in text, rather than use code. In other words, AI is for people that don't like programming that much.

Why would you even automate the most fun part of this job? As a freelance consultant, I'd rather have a machine to automate the whole boring business side so I could just sit in front of my computer and write stuff with my own hands.

Programming a system at a low-level from scratch is fun. Getting CSS to look right under a bunch of edge cases - I won't judge that programmer too harshly for consulting the text machine.

This is especially true considering it's these shallow but trivia-dominated tasks which are the least fun and also which LLMs are the most effective at accomplishing.

At home, I never had the time/will to be as thorough. Too many other things to do in life. Pre-LLMs, most of my personal scripts are just - messy.

One of the nice things with LLM assisted coding is that it almost always:

1. Gives my program a nice interface/UI

2. Puts good print/log statements

3. Writes tests (although this is a hit or miss).

Most of the time it does it without being asked.

And it turns out, these are motivation multipliers. When developing something, if it gives me good logs, and has a good UI, I'm more likely to spend time developing it further. Hence, coding is now more joyful.

And it turns out, these tend to

I am happy to accept that some people still prefer to write out their code by hand… that’s ok? Keep doing it if you want! But I would gently suggest you ask yourself why you are so offended by people that would prefer to automate much of that, because you seem to be offended. Or am I misreading?

And hey, I still enjoy solving interesting problems with code. I did advent of code this year with no LLM assistance and it was great fun. But most professional software development doesn’t have that novelty value where you get to think about algorithms and combinatorical puzzles and graphs and so on.

Before anyone says it, sure, there is a discussion to be had about AI code quality and the negative effects of all this. A bad engineer can use it to ship slop to production. Nobody is denying that. But I think that’s a separate set of questions.

Finally, I’m not sure painting is the best analogy. Most of us are not creating works of high art here. It’s a job, to make things for people to use, more akin to building houses than painting the Sistine Chapel. Please don’t sneer at use if we enjoy finding ways to put up our drywall quicker.

You're never really wrestling the computer. You're typically wrestling with the design choices and technological debt of decisions that were in hindsight bad ones. And it's always in hindsight, at the time those decision always seem smart.

Like with the rise of frameworks, and abstractions who is actually doing anything with actual computation?

Most of the time it's wasting time learning some bs framework or implementing some other poorly designed system that some engineer that no longer works at the company created. In fact the entire industry is basically just one poorly designed system with technological debt that grows increasingly burdensome year by year.

It's very rarely about actual programming or actual computation or even "engineering". But usually just one giant kludge pile.

I've coded professionally for 30 years (ergh!). I'm ok at it.

But I love building things with AI. I haven't had this much fun since the early 2000s.

Development is solely to exchange labor for money.

I haven’t written a single line of code “for fun” since 1992. I did it for my degree between 1992-1996 while having fun in college and after that depending on my stage in life, dating, hanging out with friends, teaching fitness classes and doing monthly charity races with friends, spending time with my wife and (step)kids, and now enjoying traveling with my wife and friends, and still exercising

It's like the articles point: we don't do assembly anymore and no one considers gcc to be controversial and no one today says "if you think gcc is fun I will never understand you, real programming is assembly, that's the fun part"

You are doing different things and exercising different skillsets when you use agents. People enjoy different aspects of programming, of building. My job is easier, I'm not sad about that I am very grateful.

Do you resent folks like us that do find it fun? Do you consider us "lesser" because we use coding agents? ("the same as saying you’re really into painting but you’re not really into the brush aspect so you pay someone to paint what you describe. That’s not doing, it’s commissioning.") <- I don't really care if you consider this "true" painting or not, I wanted a painting and now I have a painting. Call me whatever you want!

Creating software has a similar number of steps. AI tools now make some of them much (much) easier/optional.

The “lone genius” image is largely a modern romantic invention.

I have found in my software writing experience that the majority of what I want to write is boiler plate with small modifications but most of the problems are insanely hard to diagnose edge cases and I have absolutely no desire nor is it a good use of time in my opinion to deal with structural issues in things that I do not control.

The vast majority of code you do not control because you aren’t the owner of the framework or library your language or whatever and so the Bass majority of software engineering is coming up with solutions to foundational problems of the tools you’re using

The idea that this is the only true type of software engineering is absurd

True software engineering is systems, control and integration engineering.

What I find absolutely annoying is that there’s this rejection of the highest level Hofstetter level of software architecture and engineering

This is basically sneered at over the idea of “I’m gonna go and try to figure out some memory management module because AMD didn’t invest in additional SOC for the problems that I have because they’re optimized for some Business goals.”

It’s frankly junior level thinking

What if I have a block of marble and a vision for the statue struggling from inside it and I use an industrial CNC lathe to do my marble carving for me. Have I sculpted something? Am I an artist?

What if I'm an architect? Brunelleschi didn't personally lay all the bricks for his famous dome in Florence --- is it not architecture? Is it not art?

In b4 someone mentions some famous artists had apprentices under them.

I might start watching golf, and everytime someone else get's the ball in the hole i'll take credit for it. "Did you see what did there? "

This simply is a mediocre take, sometimes I feel like people never actually coded at all to have such opinions

Embedded in this, is the assumption that many SWEs can actually do those roles better than existing specialists.

If they can't - end of the line

But the technology does exist. The proof is in the models you can use today, on two lines:

First, what you describe is exactly what the labs are doing. We went from "oh, look, it writes poems and if you ask for code it almost looks like python" 3 years ago. Since then, the models can handle most programming tasks, with increasing difficulty and increasing accuracy. What seemed SF 3 years ago is literally at your fingertips today. Project scaffolding, searching through codebases, bug finding, bug solving, refactorings, code review. All of these are possible today. And it all became possible because the labs used the "signals" from usage + data from subsidising models + RL + arch improvements to "teach" the models more and more. So if you zoom out, the models are "learning", even if you or I can't teach them in the sense you meant.

Secondly, when capabilities become sufficiently advanced, you can do it locally, for your own project, with your own "teachings". With things like skills, you can literally teach the models what to do on your code base. And they'll use that information in subsequent tasks. You can even use the models themselves for this! A flow that I use regularly is "session retro", where I ask the model to "condense the learnings of this session into a skill". And then those skills get invoked on the next task dealing with the same problem. So the model doesn't have to scour the entire code base to figure out where auth lives, or how we handle migrations, and so on. This is possible today!

You spent the proverbial 10k hours like before. I don't know by AI has to lead to the lack of learning. I don't find people stop learning digital painting so far, even digital painting, from my perspective, is even more "solved" than programming by machines.

I heard that Pixar had a very advanced facial expression simulation system a decade ago. But I am very willing to bet that when Pixar hires animators they still prefer someone who can animate by hand (either in Maya or frame-by-frame on paper).

To use LLMs effectively, you have to be an excellent problem-solver with complex technical problems. And developing those skills has always been the goal of CS education.

Or, more bluntly, are you going to hire the junior with excellent LLM skills, or are you going to hire the junior with excellent LLM skills and excellent technical problem-solving skills?

But they do have to be able to use these tools in the modern workplace so we do cover some of that kind of usage. Believe me, though, they are pretty damned good at it without our help. The catch is when students use it in a cheating way and don't develop those problem-solving skills and then are screwed when it comes time to get hired.

So our current thinking is there's no real shortcut other than busting your ass like always. The best thing LLMs offer here is the ability to act as a tutor, which does really increase the speed of learning.

And I asked codex to fix them for me, first attempt was to add comments to disable the rules for the whole file and just mark everything as any.

Second attempt was to disable the rules in the eslint config.

It does the same with tests it will happily create a work around to avoid the issue rather than fix the issue.

> If you can't see this, I have to seriously question your competence as an engineer in the first place tbh.

I can't agree more strongly. I work with a number of folks who say concerning things along the lines of what you describe above (or just slightly less strong). The trust in a system that is not fully trustworthy is really shocking, but it only seems to come from a particular kind of person. It's hard to describe, but I'd describe it as: people that are less concerned with the contents of the code versus the behaviour of the program. It's a strange dichotomy, and surprising every time.

I mean, if you don't get the economics of a reasonably factored codebase vs one that's full of hacks and architecturally terrible compromises - you're in for a VERY bad time. Perhaps even a company-ending bad time. I've seen that happen in the old days, and I expect we're in the midst of seeing a giant wave of failures due to unsustainably maintained codebases. But we probably won't be able to tell, startups have been mostly failing the entire time.