Enthusiast builds a personal Cursor alternative with Claude and Google
A developer has shared how he built a full alternative to Cursor, the popular AI code editor. The main goal of the experiment was to escape expensive subscriptions and dependence on closed cloud services. The project used Google AI Studio and Claude Chat. The whole process was no-code: the neural networks designed the architecture and wrote the code from the user's text prompts. The case shows what modern LLMs can do in automating complex development and in building custom working tools tailored to the user's needs, without deep programming skills.
AI-processed from Habr AI; edited by Hamidun News
Enthusiast builds a personal Cursor alternative with Claude and Google
Artificial intelligence has been moving rapidly into every area of our lives, and software development is no exception. One prominent example is the arrival of specialized AI tools for programmers, such as the Cursor code editor. But high subscription costs and reliance on cloud services pushed one enthusiast to build his own, fully customizable alternative. Using Google AI Studio and Claude Chat, he showed how modern large language models (LLMs) can automate complex development processes and make it possible to create unique tools even without deep programming skills.
The project began when the developer realized how dependent he had become on paid services. Paying for Cursor and Claude Pro subscriptions, he ran into the limits of closed cloud solutions: he could neither deploy the tools locally nor modify them to suit his needs. That pushed him toward an ambitious idea: what if he built his own analogue, fully under his control and adapted to his requirements? An important condition was that he wanted to avoid writing code by hand and rely solely on the capabilities of LLMs.
The key tools were Google AI Studio, which gives access to powerful Google models with a generous free tier, and Claude Chat, which acted as an intelligent assistant and code reviewer. The whole process was no-code: the user described his requests and wishes in text, while the neural networks took over designing the architecture, writing the code and even debugging. This approach not only saved money but also sped up development considerably, turning a labor-intensive process into a dialogue with an AI.
The results of the experiment proved impressive. The developer managed to build a full alternative to Cursor that fully met his expectations. The case clearly shows the enormous potential of modern LLMs, not only for writing individual snippets of code or handling routine tasks, but for automating the entire development cycle of complex software products. Moreover, it opens the door to a wide range of users who, without deep programming knowledge, can now create custom tools tailored as closely as possible to their specific workflows and needs.
The story of this one enthusiast thus illustrates how the growth of AI is changing the way software gets built. Giving up dependence on expensive, closed services in favor of building your own customized solutions is becoming a realistic option. The project is not only economically attractive but also allows a new level of personalization in work tools, which will undoubtedly become a trend of the future in technology.
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