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gavinray • today at 7:03 PM • 2 replies • view on HN

I lost my ability to fully explain the systems I work on around the time I transitioned from next-edit-prediction AI running in my IDE (early Copilot) and working primarily via Codex/Claude CLI's.

The further away I got from the implementation details, the fuzzier the semantics became. To the point that now I could not in good faith say I understand the system I have built from the ground-up and worked on the last ~4-5 years.

The solution to this, in my mind, is not to revert back to reviewing implementation details. The economics of that from a business/productivity perspective don't play out well.

The only viable solution in my mind is adapting code/languages themselves to the shift by making programs formally verifiable. That way you can be sure that the code "does what it says on the tin", and provably so.

I feel so strongly about this I've written on it:

https://gavinray97.github.io/blog/design-by-contract-and-eff...


Replies

oblio • today at 7:16 PM

> To the point that now I could not in good faith say I understand the system I have built from the ground-up and worked on the last ~4-5 years.

You weren't programming with LLMs in 2021 or 2022, be real. More like 2024 (that's already pushing it) or 2025.

➕ show 2 replies
pizzafeelsright • today at 7:34 PM

You get it.

The bridge is built. How do we test the load? Drive bigger and bigger trucks until it fails, note the weight, print the sign and rebuild the bridge the same way.