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Do we even need to learn coding anymore? The question sounds very timely as tools such as Cursor and Claude Artifacts are making everyone build apps without writing a single line of code. Cursor, which is also basically a glorified fork of the VS Code IDE, is making developers wonder if this transition to building apps in natural language marks the end of traditional IDEs.
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IDE, or integrated development environment, is a code editor that allows developers to write, test, and debug code, combining multiple tools and features into a single environment. IDEs are essential for using programming languages and making useful software.
The most famous IDE, VS Code, also allows developers to edit code such as IntelliSense code completion. However, with AI editors like Cursor, Zed, Magic, Codeium, or the most recent one Melty, integrating traditional IDEs into a developer’s workflow seems to have become redundant.
Or Has It?
There was a recent surge of developers actively uninstalling VS Code because of Cursor IDEs. But it is easily possible for VS Code to simply add an update of AI-assisted coding onto its platform, which would eventually mark the end of Cursor. Some people also predict that Microsoft might simply end up acquiring Cursor in the future.
John Lindquist, creator of egghead.io, said that he had a chat with Harald Kirschner, project manager at VS Code, about Cursor and VS Code recently, and the team is keenly aware of Cursor’s capabilities and there might be several things in the pipeline. “I think we’ll all be pleasantly surprised,” he said.
Other IDEs such as Jetbrains, PyCharm, and IDLE, are also facing a similar crisis as AI-generated coding gains traction.
Regardless, modern generative AI coding tools are capable of integrating several open-source LLMs instead of a traditional IDE like VS Code, making it handy for several AI developers. “You can select code and ask questions based on that piece of code. So you don’t have to keep switching between the IDE and browser,” explained a developer on X.
But it simply means that most of the IDEs in the future would come with generative AI integration. It would become the default for IDEs as it was for integrating no-code and low-code platforms.
Moreover, though it is becoming easier for non-developers to build apps, the task of building high-end software is still far away from these autocoding platforms. These tools can enable non-developers or those with minimal coding experience to create apps without needing to interact with an IDE, but those cannot be replicated everywhere.
When it comes to experienced developers, AI tools can fasten the prototyping process by generating samples of code through prompts to quickly test ideas. But in the long run, when it comes to dealing with complex, customised, and large-scale projects, traditional IDEs still are better at debugging and handling crucial features.
The Future of IDEs is AI-Assisted
Before talking about the end of IDEs, it is essential to understand what they stand for. With IDEs, developers have a standardised environment with a defined codebase for meeting specific requirements. This consistency of code cannot be fully controlled by an automated code generation platform like Cursor, or others.
On the contrary, future IDEs could take this further by generating larger chunks of code, or even entire modules, based on brief descriptions or prompts. The future of software development is likely to see AI-integrated IDEs becoming the norm. This would be helpful in analysing code in real-time and automatically correcting them.
Furthermore, with generative AI integrated into IDEs, these code editors would be able to suggest context-aware code, which is not just based on the syntax, and even optimise it. This would also enable a personalised developer style of coding, enabling natural language prompting with coding, much like Cursor and Claude.
AI-integrated IDEs will likely combine traditional development tools with generative coding, making software development more efficient, intuitive, and accessible while still providing the depth needed for complex projects. This would enable developers who know coding to take generative tools to the next level.
But at the same time, it would be difficult to manage generative AI code if it is available within the IDEs as people still would be hesitant to trust generative AI for boilerplate code. It could also result in the loss of coding skills for skilled developers.
