Learning to Code, 1990s vs. 2026
이 글은 1990년대부터 2026년까지 프로그래밍 학습 방식의 변화를 다룹니다. 과거에는 책과 직접 코딩 경험을 통해 깊은 개념 이해가 필수였으나, 현재는 AI 코딩 에이전트가 코드를 자동 생성하며 추상화 수준이 크게 높아졌습니다. 이로 인해 신입 개발자의 개념적 깊이가 얕아지고, AI 도구 활용 능력과 함께 근본적인 문제 해결 능력, 추상화 이해력 평가가 중요해졌다는 점을 강조합니다. 저자는 신입 개발자들이 AI 도구를 활용하되, 기본적인 서버 설정, 배포, DNS 이해 등 근본 원리를 꾸준히 학습할 것을 권장합니다.
https://ayende.com/blog/203975-a/learning-to-code-1990s-vs-2026/
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🚀 Why Debugging AI’s Mistakes Is the Best Skill You Can Build 🚀
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When you’re just starting out, having the right guidance can make or break your progress. For many new developers, AI seems like the perfect helper—offering suggestions, code snippets, and even solutions at the click of a button.
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Listen to this episode from The State of Developer Education on Spotify. In this episode of The State of Developer Education, Jon is joined by Nicolas Grenié, a Developer Advocate for Typeform. Join them as they discuss Nicolas' coding origin story, the evolution of developer advocacy over the past decade, and the impact of low-code/no-code tools. Nicolas shares valuable insights into the value of content creation and partnerships, as well as the role of AI in the developer ecosystem.
When delivering online courses, finding ways to keep participants engaged needs to be top of mind.
One of the tools I use is Miro - I pulled together some ideas of how I use it here:
https://www.kevincunningham.co.uk/posts/using-miro-in-the-digital-classroom
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