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AI-Powered Dev: My Codescribble Debugging Nightmare

2025-01-26

The author used LLMs to build Codescribble, a simple shared text editor. While the initial development was incredibly fast, almost entirely LLM-driven, deployment became a major headache. The generated code suffered from hardcoded values, inconsistent methods, and a broken automated deployment script. Ultimately, the author spent far more time debugging and fixing LLM-introduced errors than anticipated. This experience highlights the need for developers to maintain a solid grasp of underlying technologies and thoroughly review AI-generated code. Blindly trusting AI can lead to significant inefficiencies and even counter-productive outcomes.

Development

Beyond RAG: A Knowledge Management System That Enhances, Not Replaces, Thought

2025-01-02

This article explores the design philosophy behind Zettelgarden, a knowledge management system aiming to enhance, not replace, human thought. The author recounts the evolution from paper cards to digital notes, highlighting how digital systems, while offering convenient search and linking, lose the serendipitous connections fostered by physical proximity. The author critiques the current over-reliance on automation and RAG (Retrieval Augmented Generation) models in AI-assisted knowledge management, arguing their limitations in handling massive datasets and their neglect of personal understanding and knowledge processing. Zettelgarden emphasizes the importance of personal notes, encouraging users to add commentary and insights, facilitating connections between ideas through a unique card structure. The author believes the future of knowledge management lies in human-computer collaboration, with computers handling organization and humans focusing on thinking and understanding.

Development