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Comment by aDyslecticCrow | Hacker News Reader

> LLMs, there’s really no excuse

I'd phrase it differently; we're now able to accumulate technical debt faster than ever, without even building the institutional knowable needed to keep it sane. While the models writes novels about what it's doing that no human or LLM will find any use for.

But at the same time; if the LLM makes coding 5-10x faster, there's plenty of left-over time we can now spend doing things properly. Document, test, plan, refactor, lint, use CI tooling. There is no excuse now that LLMs reduce the pain threshold for all of them.

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From what I've heard, there is no time for any of those things because management also expects features 5-10x faster.

> we're now able to accumulate technical debt faster than ever

LLM's just enable you to speed run your way into a legacy code base.

> without even building the institutional knowable needed to keep it sane

Does feature XXX move the needle? Did you gain more business or retain existing business because a feature exits? Has AI tooling helped your product team move the needle? No? Why not?

How easy is it to remove the feature that NO ONE uses is a question no one is asking. How many people got promoted for "removing the most garbage" from the system?

We, as an industry, might need to have a candid conversation about what we're doing and how we do it.

Remove a feature no one uses:

How do you properly measure this? Do you setup a database that monitors when every feature is used? Is the feature only used once a year for some reason? Is the feature only used on some rare data that is uncommon but still can occur?

And that really applies to something fully in your control. In systems controlled by customers its far harder.

> How do you properly measure this?

The same way you measure utilization and cost at a customer level.

I can name at lest three companies where their biggest clients are also the bulk of their costs - they lift revenue but drag the margins. I can name another couple who spent years marking their products entirely wrong because they simply had no clue how their product was really being used.

> Is the feature only used on some rare data that is uncommon but still can occur?

This is where the competence of your product team comes into play. We're building features faster with AI but none of it is moving the needle. That has little to nothing to do with code quality, and everything to do with product teams.

And yet technical debt is still much, much worse than it used to be thanks to LLMs.

As a technological innovation theyre a bit like amphetamines for code. Sure, maybe some people are using the "tankers chocolate" their employer handed them responsibly...I guess.

There are certainly a lot of people online who have gone all in who swear blind theyre not abusing them.

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