Two years ago, I started experimenting with AI-assisted development tools. Today, they’re embedded into daily workflows across our engineering organization. Getting there wasn’t about adopting the latest model. It was about separating what meaningfully improves engineering outcomes from what adds noise.
After integrating AI into production development at a large cloud infrastructure company, I’ve learned that success depends far more on where you apply these tools than on the tools themselves.
The Friction That Actually Matters
The…

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