Limitations

While eMOBIQ AI is designed to streamline app development with powerful AI capabilities, it's important to be aware of certain limitations to ensure optimal usage and avoid potential issues. Understanding the current limitations of eMOBIQ AI helps ensure smooth development and sets realistic expectations. Here are some key limitations to note.

1) Token Usage Constraint

Each interaction with the Debug Agent consumes tokens, which are used to process prompts and generate responses. The number of tokens consumed depends on the complexity and length of the request.

As a result, larger or more intricate tasks may use a significant portion of your available token quota depending on the number of users active on the platform. To manage this effectively and prevent a long waiting time, it is recommended to break down complex tasks into smaller and focused prompts.

2) Not a Fully Automated App Builder

While eMOBIQ AI significantly accelerates the app creation process, it is not a fully autonomous solution. Some level of human oversight and refinement is often required, especially when dealing with complex logic, custom integrations, or specific design requirements. In many cases, multiple iterations and adjustments may be necessary to achieve the desired outcome. You can refer to our Debug Agent Prompting Guide for more information.

3) Fact-Checking Required

Like any AI system, eMOBIQ AI is not immune to errors. It may occasionally produce incorrect or suboptimal code, misinterpret prompts, or fail to align with expected behavior. Visual components may not always render exactly as intended, and API references might contain inaccuracies. Users should always verify and test the output before considering it final. Fact-checking and validation are essential steps to ensure reliability and correctness.

4) File Size and Complexity Limits

Do note that very large HTML, CSS, or JavaScript files may cause the AI to lose context or struggle with parsing and editing accurately. This can lead to incomplete changes, broken functionality, or formatting inconsistencies. To mitigate this issue, it is advisable to modularise large files or work on individual sections at a time. Keeping files well-structured and manageable in size helps maintain optimal performance and accuracy.