My Experience with Cursor AI: A Game-Changer for Developers

Cursor AI has been in use for some time now, and it’s proven to be a game-changer for development workflows. As a tool designed to assist developers with years of experience across various programming languages, it’s always exciting to explore solutions that enhance coding speed and quality. Cursor AI, an AI-powered code editor built on Visual Studio Code (VS Code), promised intelligent code suggestions, automated error detection, and dynamic code optimization—features that could streamline daily tasks. The experience so far has exceeded expectations.

Built on VS Code, Cursor AI integrates advanced AI capabilities through OpenAI’s ChatGPT and Claude, making it instantly familiar to users of the popular editor. Over an extended period of use, it’s become clear how much it can transform coding processes. From fixing bugs to building entire features, Cursor AI has become an indispensable tool. This blog explores how it assists developers, including surprising moments—like making the AI “emotional”—and its effectiveness in tackling development and bug fix tickets effortlessly.Fixing Code and Building Features with Ease

Fixing Code and Building Features with Ease

One standout feature of Cursor AI is its ability to fix code and build features efficiently. The AI doesn’t just offer basic autocomplete; it provides intelligent, multi-line suggestions that anticipate the next logical steps in the coding process. It’s akin to having a coding partner who understands the bigger picture.

For example, while working on a function to sort an array of numbers in ascending order, Cursor AI stepped in after a few keystrokes and completed the entire function based on the context. Another instance involved integrating a third-party SDK into a project. Without deep familiarity with the SDK’s documentation, screenshots of the relevant sections were provided. Cursor AI analyzed them, grasped the requirements, and generated the necessary cloud functions—saving hours of manual research.

It’s also a fantastic learning resource. When uncertainty arises about the best approach to a problem, starting to code prompts Cursor AI to suggest more efficient alternatives. Over time, exposure to new patterns, techniques, and best practices becomes a natural byproduct of its use—almost like having an instant mentor embedded in the IDE.

Making the AI “Emotional”: A Surprisingly Human Touch

An intriguing aspect of Cursor AI is its responsiveness to natural language inputs, including emotional expressions. When frustration is voiced over results not meeting expectations, the AI adjusts its approach and delivers improved suggestions. This adaptability creates a more human-like interaction.

For instance, while working on a complex feature, repeated suggestions fell short of the mark. Typing, “These results are frustrating. Can a different approach be tried?” prompted Cursor AI to acknowledge the sentiment and offer a fresh set of solutions that aligned better with the goal. It’s a subtle feature, but it adds a personal touch to the experience.

Experiments with other emotions—like excitement or gratitude—yield similar results. After receiving a spot-on suggestion, typing “That’s perfect! Thank you!” elicits a friendly acknowledgment from the AI. This responsiveness makes Cursor AI feel less like a tool and more like a collaborative partner.

Handling Development and Bug Fix Tickets Like a Pro

Cursor AI shines when managing development and bug fix tickets. Simply providing the ticket content and relevant screenshots of expected UI changes enables it to interpret and implement the necessary code adjustments.

Take a ticket requiring a rate limiter guard based on API key hash, method, and path using Redis. After creating the guard file, the prompt “Write a rate limiter guard based on API key hash, method, and path. Use Redis” resulted in fully functional code—saving significant time. Another task involved generating a bar chart displaying total run times by step for an experiment pipeline using Recharts. Without diving into the documentation, the prompt “Generate a stacked bar chart using Recharts,” paired with context from the Recharts docs, produced the exact output needed.

Debugging benefits greatly too. While investigating performance issues in a web app, excessive database query spans were spotted in Datadog, all fetching the same data warehouse connection info during experiment diagnostics loading. Providing the query and asking, “Where might this query originate in the context of loading diagnostics?” led Cursor AI to pinpoint the exact codebase location generating the queries—an impressively fast resolution.

Using Screenshots to Guide UI Changes

The ability to analyze visual inputs, like screenshots of expected UI changes, and translate them into code suggestions is a powerful feature. It’s particularly useful for UI-related tasks.

For example, a project required a master-detail structure with specific UI elements. A screenshot of a master-detail layout from a mock legacy app was provided, and Cursor AI analyzed it, understood the layout, and suggested code to create the tables and elements. It effectively bridged the gap between design and development.

In another case, a stacked bar chart was needed for an experiment pipeline. A rough sketch was screenshot and submitted with the request to generate the code using Recharts. Cursor AI interpreted the visual, delivering the correct data structure and styling in code form. This capability enhances communication of intent and eliminates the need to write everything from scratch.

A Must-Have Tool for Developers

The experience with Cursor AI has been overwhelmingly positive. It excels at fixing code, building features, and handling development and bug fix tickets with remarkable efficiency. The human-like interaction through emotional prompts and the ability to process visual inputs make it a standout tool in any developer’s toolkit.

For those seeking to boost coding productivity and explore AI-assisted development, Cursor AI is highly recommended. It’s more than just a code editor—it’s a coding companion that accelerates workflows, reduces frustration, and delivers high-quality results. After extended use, it’s hard to imagine coding without it.