"Frontends are no longer written only for humans. AI tools now actively work inside our codebases. They generate components, suggest refactors, and extend functionality through agents embedded in IDEs like Cursor and Antigravity. These tools aren't just assistants. They participate in development, and they amplify whatever your architecture already gets right or wrong. When boundaries are unclear, AI introduces inconsistencies that compound over time, turning small flaws into brittle systems with real maintenance costs."
"This makes the cost of bad architecture very tangible. Sloppy boundaries, implicit conventions, and "we all know how this works" assumptions don't stay contained. When AI generates code, they become debt that spreads automatically. Here's the core idea: frontends must prioritize interpretability and predictability. AI doesn't share our intuition or historical context. It is now a first-class consumer of the codebase. Poor structure doesn't just slow humans down, it becomes a liability when AI assumes patterns that don't exist or violates rules that were never made explicit."
AI tools now operate inside codebases, generating components, suggesting refactors, and acting as agents within IDEs. These tools participate in development and amplify existing architectural strengths and weaknesses. Unclear boundaries, implicit conventions, and informal assumptions cause AI to introduce inconsistencies that compound over time. Generated code can transform small design flaws into brittle systems with tangible maintenance costs. Frontend architecture needs explicit structure, predictable patterns, and clear rules so AI can reliably consume and extend the code without creating widespread debt or semantic drift. Prioritizing interpretability and predictability reduces risks introduced by AI participation.
Read at LogRocket Blog
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