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Comment by mshish | Hacker News Reader

Maybe, but I think one of the points is that the marginal cost of both understanding that legacy code base and safely refactoring it are increasingly trending down thanks to agentic coding tools. It changed the value and risk tradeoff for legacy apps, if deployed properly. There's still a lot of work (too much) to get the harness in place to make high confidence changes to legacy, critical apps. If someone makes that more automated, we'll be in a very different place for legacy refactoring and it will look a lot more like the clay molding the article discusses.

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As with anything LLM-related, I feel compelled to ask, is that actually what's happening, or are they just successfully convincing their users that's what's happening? I truly cannot tell.

I'm not using any LLMs directly (my workplace still bans them in-house) and my experience on the receiving end of contractors using them is quite poor. That includes one major, "we'll replace your ancient software with shiny new stuff"... with significantly reduced capability that in turn makes everything far more difficult than it was or ought to be. The UI appears much more user friendly, but really is just broken in multiple ways where the much-patched 1980s software it replaced was user-unfriendly but largely worked.

This all could be the result of poor coding, regardless of LLM use, of course.

I've been able to do relatively big refactors with great success, like porting thousands of lines of data transforms to drastically different data stores practically in one fell swoop. In the background. As I worked on other stuff.

The cost of experimenting is just mind mindbogglingly cheap now, it's really insane. Don't like the abstractions it comes up with, or think it generated a bunch of slop? Go again, who cares? With a little more steering, they'll often produce exactly what you want.

As for contracting firms, many of them were slop shops before AI, I imagine those kinds of firms are even worse slop shops now.

> I've been able to do relatively big refactors with great success, like porting thousands of lines of data transforms to drastically different data stores practically in one fell swoop. In the background. As I worked on other stuff.

This is a great use case, as you have ground truth to compare to. LLMs are phenomenal at this stuff. Where you don't have this is where they are less successful (in my experience).

With this new-found capability, you can use an LLM to plan and execute some long-needed refactors, or use it to pile on new features even faster with no regard for tech debt management.

As others have said... it's a tool. A powerful tool in the hands of a wise and skilled wielder who makes planned, focused changes, or a slop-cannon in the hands of someone who is happy to churn out features with minimal understanding of context or system design.

> The UI appears much more user friendly, but really is just broken in multiple ways where the much-patched 1980s software it replaced was user-unfriendly but largely worked.

LLMs don't magic away the need for careful and extensive testing. Good code still takes a lot of time. But it's also a lot less time than before.

I suspect a lot of problems come from people trying to one-shot entire apps, or from those who do not have the relevant experience or knowledge to understand that close-with-a-nice-modern-GUI is not nearly good enough.

where are you working that bans llm usage in house? can I work there too?

I'll just say that I work in a heavily regulated industry.

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