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ICE","type":"story","url":"https://electrek.co/2025/09/11/hyundai-now-delaying-ev-battery-plant-raided-by-ice/"}],[42701745,{"by":"namanyayg","descendants":57,"id":42701745,"kids":[42702423,42702065,42702150,42702738,42702599,42702532,42702363,42702559,42702231,42702292,42702600,42702063,42702138,42702127,42702208,42702889,42702541,42702366,42702125,42702078,42702409,42701876,42702718,42702167,42702959,42702558,42702087,42702140,42702021,42702192,42702017,42702058,42702660],"score":40,"text":"For teams actively using AI coding assistants (Copilot, Cursor, Windsurf, etc.), I'm noticing a frustrating pattern: the more complex your codebase, the more time developers spend preventing AI from breaking things.

Some common scenarios I keep running into:

* AI suggests code that completely ignores existing patterns

* It recreates components we already have

* It modifies core architecture without understanding implications

* It forgets critical context from previous conversations

* It needs constant reminders about our tech stack decisions

For engineering teams using AI tools:

1. How often do you catch AI trying to make breaking changes?

2. How much time do you spend reviewing/correcting AI suggestions?

3. What workflows have you developed to prevent AI from going off track?

Particularly interested in experiences from teams with mature codebases.","time":1736879878,"title":"Ask HN: Teams using AI – how do you prevent it from breaking your codebase?","type":"story"}],[41147393,{"by":"throwaway2562","descendants":73,"id":41147393,"kids":[41183426,41179505,41180030,41180235,41183963,41180479,41183876,41186756,41180392,41179806,41184839,41185871,41183494,41186006,41179986,41183972,41179985,41179522],"score":183,"time":1722701184,"title":"Nxylon: New super-black material made from 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user:	secult
created:	July 27, 2016
karma:	30