The Good, The Bad, and The AI: One Month of Coding with Cursor

Author(s): Fredrik Appelros

Originally published on Towards AI.

My curiosity about AI coding assistants started when I found myself struggling to quickly ramp up on new technologies after spending years in leadership roles away from hands-on coding. Like many developers, I was intrigued by the rising wave of AI-powered tools that promised to streamline development, but I wondered — could they really help me bridge the gap? These AI assistants promised to revolutionize how we code — offering everything from intelligent code completion and real-time documentation lookup to automated testing and bug detection. The pitch was compelling: imagine having a senior developer looking over your shoulder, offering suggestions, catching errors, and helping you navigate complex codebases. They would supposedly cut development time in half or less, eliminate hours spent digging into third-party codebases, and make coding more accessible to developers at all skill levels.

But the reality often fell short. Early tools would frequently suggest non-sensical code or simply miss the context of what you were trying to achieve to the point where they were more an obstacle than an asset. But as AI technology evolved, particularly with the advent of Large Language Models (LLMs) trained specifically on code, these tools began to show real promise. The suggestions became… Read the full blog for free on Medium.

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Published via Towards AI