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AI should only run as fast as we can catch up

(higashi.blog)
196 points yuedongze | 1 comments | 08 Dec 25 17:38 UTC | HN request time: 0.214s | source
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blauditore ◴[08 Dec 25 18:26 UTC] No.46195811[source]▶
All these engineers who claim to write most code through AI - I wonder what kind of codebase that is. I keep on trying, but it always ends up producing superficially okay-looking code, but getting nuances wrong. Also fails to fix them (just changes random stuff) if pointed to said nuances.

I work on a large product with two decades of accumulated legacy, maybe that's the problem. I can see though how generating and editing a simple greenfield web frontend project could work much better, as long as actual complexity is low.

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hathawsh ◴[08 Dec 25 18:39 UTC] No.46195979[source]▶
I think your intuition matches mine. When I try to apply Claude Code to a large code base, it spends a long time looking through the code and then it suggests something incorrect or unhelpful. It's rarely worth the trouble.

When I give AI a smaller or more focused project, it's magical. I've been using Claude Code to write code for ESP32 projects and it's really impressive. OTOH, it failed to tell me about a standard device driver I could be using instead of a community device driver I found. I think any human who works on ESP-IDF projects would have pointed that out.

AI's failings are always a little weird.

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1. divan ◴[09 Dec 25 10:55 UTC] No.46203506[source]▶
I start new projects "AI-first" – start with docs, and refining them on the go, with multiple CLAUDE.md in different folders (to give a right context where it's needed). This alone increases the chances of it getting tasks right tenfold. Plus I almost always verify myself all the code produced.

Ironically, this would be the best workflow with humans too.