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Endigest AI Core Summary
UC Berkeley student research reveals how the next generation of developers is building genuine AI literacy rather than dependency.
•Students universally framed AI as a 'tutor' or 'teacher,' using it metacognitively to identify knowledge gaps and clarify concepts rather than to complete assignments.
•Eye-tracking study showed developers gave less than 1% visual attention to AI during interpretive tasks, but 19% during mechanical tasks like boilerplate code.
•Students actively built guardrails against overdependence: limiting access to paid models, returning to hand-coding for basics, and asking AI to guide rather than answer.
•DORA 2025 report found 90% of tech professionals use AI daily, yet ~30% report little to no trust in AI-generated code, highlighting the need for critical evaluation.
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Key industry recommendations: experiment with AI customization settings, build verification practices into workflows, and preserve space for unassisted work on complex problems.
This summary was automatically generated by AI based on the original article and may not be fully accurate.
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