A year ago, I was one of many engineers who felt skeptical about AI tools - not just because they were new, but because there was a growing fear that tools like Cursor might eventually replace us, software engineers.
Fast forward to today: LLMs now produce about 90% of my code, while I manually write only about 10%.
So what changed? How did this shift increase my efficiency without increasing my mistakes - and why should you start using AI (and Cursor specifically) in your work?
Let’s explore.
Think of Cursor as a partner, not a competitor. The goal is still the same - to produce high‑quality, production‑ready code. Yes, you can absolutely do it on your own, just as developers have done since the very first programs were written.
But using an LLM can make that experience faster, smoother, and more secure. It’s not about replacing your skills; it’s about amplifying them.
There are a few different ways to use AI for writing code - from simple CLI tools to full‑blown IDE integrations. This article focuses on Cursor, because out of everything I’ve tried, it’s the one that fits my workflow best.
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Cursor is an AI-powered code editor that understands your codebase and helps you code faster through natural language. Just describe what you want to build or change and Cursor will generate the code for you.
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Here you can find main concepts when working with Cursor: https://cursor.com/docs/get-started/concepts
I’m not going to describe every concept here - the docs are excellent and absolutely worth checking out. My goal in this article is to give a high‑level overview of the features I personally find most valuable in my daily work.
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Code completion that predicts multi-line edits. Press Tab to accept suggestions based on your current code and recent changes.
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This is the most basic feature - but also one of the most impactful.