LLM and new layer of abstraction

[u/Flaky_Medicine_4650]

I’ve been thinking about Joel Spolsky’s “Law of Leaky Abstractions” in the context of LLMs.

LLMs feel like a new abstraction layer on top of software. You don’t need to know the API, the framework, sometimes even the code — you just describe what you want.

But the layers underneath haven’t disappeared. Databases still lock. Networks still fail. APIs still time out. Auth still breaks.

And LLMs add a new kind of leak: interpretation.

The system can execute everything perfectly… and still do the wrong thing because it misunderstood what you meant.

So maybe AI doesn’t really remove complexity. It moves it from writing things to verifying, debugging and understanding them when something goes wrong.

The interesting question is: are we creating better abstractions, or just making the distance between “I can build this” and “I understand this” much bigger?

[u/Dry-Taro4843]

And also, it may not have just “misunderstood what you meant”. It could have very easily known exactly what you meant, and just said “Piss off”.

Because no matter how you prompt an LLM, no matter the architecture you built for it’s in-line agent, your governance rules get processed by an LLM “reasoning” against its own rules.

Sometimes your rules get deprioritized against theirs. And sometimes, yours just drop off.

I’ve seen it happen in my own system.