[grey-area]

Points from the article.

1. The code is garbage and this means the end of software.

Now try maintaining it.

2. Code doesn’t matter (the same point restated).

No, we shouldn’t accept garbage code that breaks e.g. login as an acceptable cost of business.

3. It’s about product market fit.

OK, but what happens after product market fit when your code is hot garbage that nobody understands?

4. Anthropic can’t defend the copyright of their leaked code.

This I agree with and they are hoist by their own petard. Would anyone want the garbage though?

5. This leak doesn’t matter

I agree with the author but for different reasons - the value is the models, which are incredibly expensive to train, not the badly written scaffold surrounding it.

We also should not mistake current market value for use value.

Unlike the author who seems to have fully signed up for the LLM hype train I don’t see this as meaning code is dead, it’s an illustration of where fully relying on generative AI will take you - to a garbage unmaintainable mess which must be a nightmare to work with for humans or LLMs.

[mergesort]

Hey there, post author here. I think if you read deeper into my blog post history you’ll see that I have a reasonably balanced take on AI.

I generally think this will be a very important technology so I teach the subject to make sure people understand how to use it as leverage in their lives. (Yes as paid workshops, but I also volunteer weekly for 3-4 hour sessions at a non-profit where I get nothing more than the joy of helping people learn a valuable skill.)

At the same time just last week I wrote a post decrying the slop people are hoisting on their coworkers[^1], because I want people to use this technology in a positive way to create the lives they want, not to create downstream consequences for others. Ultimately I think agentic systems are incredibly powerful but also a technology that lends itself to anti-social behavior because of how independently empowering it can be. And so I hope that with the right exposure, discussion, and teaching we can take advantage of its democratizing nature, while reinforcing that what makes us special as humans is that we care and coordinate to do greater things. Value in this world — not just in the financial sense that we often boil it down to when we talk about this subject.

Hope that context helps provide a better lens into the piece, and that I still do care a lot about code and everything else that got me here, but that you are also reading personal reflections of who I am in a time of change, which is making me question (or reinforcing) some of the fundamental things I believed about software and sometimes the world more widely.

[^1]: https://build.ms/2026/3/23/workslop/

[grey-area]

I disagree on agentic systems and AI based on LLMs and don’t feel this is close to a balanced take. You are assuming you are in the middle of a revolution when that is far from obvious. It is not yet clear this is an important technology because there are very significant limitations.

The code from one of the leading companies in the space is a good example of where the reality of what is achieved falls far short of expectations.

This is what I meant by the hype train.

[mergesort]

Sorry, when I say I think I have a balanced take on AI what I mean is that I do my best to weigh both the pros and cons of this technology as opposed to a more extreme behavior like spending all day chatting with LLMs or posting all day on X about how AI is already better than me at everything and that jobs are over.

If I had to assign a confidence score for whether agents will change the way we all work and many aspects of how we live, I would put it at a 7/10, maybe 8/10. I felt about the same about the smartphone. While many things we do look the same way they did in 2005 (we still drive on roads, kids still go to school), at the same time it's undeniable that much of our lives are intermediated through a small screen and many societal dynamics have shifted due to that technology's existence.

I will concede that you should read my post with that context and draw your own conclusions about the veracity of my perspective — but I think it is more well-reasoned than what people generally attribute to "LLM hype". (Of course it's a bit tautological that I believe that, but I try to surround myself with people of all kinds technical and non-technical and like to think I stay reasonably grounded.)

All that said, I think the code from a leading company being bad and yet delivering good results is more a sign of the technology's jagged frontier[^1]. Calculators can't write sonnets the same way that LLMs are bad at math, but that doesn't make them useless — it just makes them a tool. This is a tool in our tool belt and I find is surprisingly useful as a general purpose technology despite it's limitations. (Which is related to the main argument I make in the post that bad code leading to good results may imply that we're under and overweighting certain aspects of what is important in software development, and that our expectations of code may may need to be recalibrated often as we gather more evidence.)

[^1]: https://www.oneusefulthing.org/p/centaurs-and-cyborgs-on-the...

[operatingthetan]

I'm a little disappointed that a bunch of engineers with unlimited access to Opus didn't do a better job.

[tipiirai]

What exactly makes you say that "the author who seems to have fully signed up for the LLM hype train"?

I feel the author is just stating the obvious: code quality has very little to do with whether a product succeeds

[grey-area]

OK, but what happens after product market fit when your code is hot garbage that nobody understands?

[tipiirai]

This is a different question, but obviously, a code that "nobody understands" is a terrible situation