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**PRE RELEASE** - if you're reading this, this post has not been published fully yet - feedback welcome but please don't pass this around just yet!
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# Putting AI to Work in Complex Codebases
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# Getting AI to Work in Complex Codebases
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It seems pretty well-accepted that AI coding tools struggle with real production codebases. The [Stanford study on AI's impact on developer productivity](https://www.youtube.com/watch?v=tbDDYKRFjhk) found:
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1. A lot of the "extra code" shipped by AI tools ends up just reworking the slop that was shipped last week.
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2. Coding agents are great for new projects or small changes, but in large established codebases, AI can often make developers *less* productive.
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2. Coding agents are great for new projects or small changes, but in large established codebases, they can often make developers *less* productive.
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The common response is somewhere between the pessimist "this will never work" and the more measured "maybe someday when there are smarter models."
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