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Ask HN: Teams using AI – how do you prevent it from breaking your codebase?

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.

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The realistic wildlife fine art paintings and prints of Jacquie Vaux begin with a deep appreciation of wildlife and the environment. Jacquie Vaux grew up in the Pacific Northwest, soon developed an appreciation for nature by observing the native wildlife of the area. Encouraged by her grandmother, she began painting the creatures she loves and has continued for the past four decades. Now a resident of Ft. Collins, CO she is an avid hiker, but always carries her camera, and is ready to capture a nature or wildlife image, to use as a reference for her fine art paintings.

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