It feels like just yesterday AI coding assistants were a novelty, a neat trick for generating small code snippets. Now, they're evolving at a breakneck pace, with many IDEs introducing 'Plan' modes. The idea is compelling: let the AI break down complex tasks, map out development steps, and even lay down the initial code framework. It's all about easing the developer's burden, right? Companies like Tencent (CodeBuddy), ByteDance (Trae), and Baidu (Comate) are all offering this functionality, often for free. Cursor, a popular AI IDE, also jumped into the fray with its Plan mode back in version 2.0, and it's generally considered quite mature.
So, how do these Plan modes stack up against each other, especially Cursor's? I was curious to see how they'd handle a substantial request: building a full HR management backend system. This wasn't just a simple script; it involved employee management, attendance, payroll, performance reviews, recruitment, user permissions, data visualization, Excel import/export, and responsive design, all with API docs and unit tests. A true test of planning and execution.
The reality check? None of them could magically churn out a complete, bug-free system. That's a big takeaway – these tools are powerful assistants, not replacements for human oversight and debugging. However, there were definite differences in their approaches and outcomes.
Trae, for instance, with its SOLO interface, seemed to offer the highest degree of completion. It allowed for a more iterative development process, where you could build and debug as you went. Still, even Trae required significant bug fixing on a page-by-page basis. Comate showed noticeable improvement, managing to generate front-end interfaces, though the functionality was a no-go, needing extensive fixes. CodeBuddy, unfortunately, was a bit of a nightmare. The TypeScript errors were so rampant it felt like playing 'whack-a-mole' – fix one, and two more popped up. Eventually, it had to be abandoned.
Cursor's experience was a bit different. While it was quick to generate a plan (around 15 minutes), it hit a roadblock by requiring database configuration, which wasn't provided as an example. For developers less familiar with backend specifics, this presented a significant hurdle, forcing an early stop.
When it comes to the actual plan documents generated, CodeBuddy really shone. Its latest version produced incredibly detailed plans, covering everything from UI color schemes and overall architecture to front-end and back-end specifics. Cursor and Trae were next, including data design, but they lacked the visual design and flowchart details that CodeBuddy offered. Comate's plans were the most basic, essentially just listing project files and linear steps.
It's fascinating to see how these tools interpret a complex request. Cursor's Plan mode, as described in its documentation, is designed for planning and clarifying medium-to-large feature implementations. It's built to generate detailed plans, ask clarifying questions, and present them in an editable markdown format. This interactive approach, where you can review and edit the plan before execution, is a key differentiator. It emphasizes control and clarity, which is crucial for complex projects. The reference material highlights that Cursor's Agent mode often starts by creating a plan, which significantly boosts the quality of the generated code. This suggests a thoughtful, staged approach to tackling complexity.
Comparing the 'execution consistency,' Cursor stands out. It sticks strictly to the generated plan, creating corresponding files and functions without straying. Other tools, while perhaps more flexible, sometimes deviate from the initial plan, making the final output less predictable. Cursor also incorporates interactive elements like 'requirement clarification' and 'technical solution selection,' giving developers more agency in the process.
Ultimately, the 'Plan' mode in AI coding assistants is a powerful concept, but it's still very much a work in progress. While they can't automate the entire development lifecycle yet, they are becoming indispensable partners in breaking down complexity, generating initial structures, and guiding the development process. Cursor's emphasis on a clear, editable plan before execution, coupled with its execution consistency, offers a compelling approach for tackling larger, more intricate software development tasks.
