Why Your AI in Cursor is Acting Dumb? Fixing Context Issues

In recent weeks, I have heard more and more voices from frustrated developers. If you also feel that working with models like Claude or GPT-4 inside Cursor has become cumbersome, slow, or just "dumber" than it was a month ago – you are not imagining it. This feeling of "one step forward, two steps back" is not coincidental, and it is directly related to how these systems manage their memory.

The problem: Context Window overload

The most common mistake is to think that the AI "remembers" our project. The truth is that language models are completely stateless [1]. Every time you send a message in Cursor, the system rebuilds the entire prompt sent to the model [1]. This includes the chat history, system settings, files you have opened, and tools (MCP) you have activated [1].

As the conversation gets longer, the Context Window fills up with irrelevant information – what is called "Context Pollution" [2]. The results? The model starts ignoring new instructions, inventing solutions you have already rejected, or simply "forgetting" the project architecture [2].

Why does it feel like the Agent has become stupid?

The frustration many experience with AI agents often stems from incorrect management of the information they receive. Here are some main reasons for this phenomenon:

• •File overload: Excessive use of

  @Codebase

  or adding dozens of files to a conversation causes the model to get lost in a sea of tokens [2].
• •Index issues: Sometimes the Cursor Index is simply not synchronized. If the AI starts hallucinating functions that do not exist, it is time to perform

  Reindex Codebase

  in the settings [2].
• •Accumulation of conflicting instructions: In long conversations, instructions you gave at the beginning might conflict with new requirements, creating inconsistent behavior [2].

How do you get the AI back on track?

To stop the "nonsense" and get back to productive work, you should adopt a few habits for context management:

1. •Focused work: Instead of throwing the entire project into the chat, use specific

   @Files

   to give the model only what it needs for the current task [2].
2. •Cleaning up conversations: Do not be afraid to start a new chat. When the conversation becomes too long, the AI starts suffering from the "Lost in the middle" problem – it remembers the beginning and the end, but loses the middle [2].
3. •Using Rules: Instead of repeating instructions every time, use Rules (or

   .mdc

   files) to define a consistent coding style and architecture [2].
4. •Tracking updates: Cursor is constantly working on improvements like Dynamic Context Discovery, which are designed to reduce the number of unnecessary tokens and improve accuracy [3].

Summary and conclusions

The frustration with these tools is an inseparable part of working at the technology frontier. We are working with systems that are still learning how to manage their memory efficiently. If you feel that the AI has "lost it," do not just blame the model – look at what you are feeding it. Careful management of the Context is the most important skill for an AI developer in 2025.

Personal tip: If something is not working, start over with a clean chat. It solves 90% of the problems.

Additional resources for deeper study:

• •Cursor Context Management Guide
• •How Cursor Works - Context Window
• •Official Cursor Documentation