Although AI vibe software development coding may appear to be fast, the results often do not work correctly or make it into successful production products.
According to the Google chief executive Sundar Pichai in https://www.bbc.com/news/articles/c8drzv37z4jo:
People should not “blindly trust” everything AI tools tell them, the boss of Google’s parent company Alphabet has told the BBC.
In an exclusive interview, chief executive Sundar Pichai said that AI models are “prone to errors” and urged people to use them alongside other tools.
AI vibe coding often suffers from problems such as:
- Security issues
- Reliability issues
- Performance issues
- Incompatibility with your internal APIs and functions
- Incompatibility with external APIs and functions
- Inconsistent data formats and database parameters
- Inconsistent architectural structure
- Inconsistent User Interface (UI)
- Inconsistent code comments that are not integrated with the entire system
When any of these problems are present, additional time may be required to repair or replace the intended functions.
The recommended methodologies to repair AI vibe coding problems are:
- Write clear and concise descriptions of the intended functions, including internal and external API interactions and data structures
- Identify how the intended functions may impact security and whether security updates have been applied
- Identify how the intended functions interact within your system with respect to time (e.g. synchronous, asynchronous, background subprocess)
- Identify which internal and external API requests and responses are valid
- Identify how to achieve improved performance
- Identify how to utilize functions that exist in other parts of your system
- Organize code into logical blocks that are understandable, have meaningful function and variable names, and are maintainable (i.e. not “spaghetti code”)
- Generate graphical representations of the intended functions UIs and related UIs within your system
- Enhance code comments to be consistent and unified with the rest of your system
Consider also that AI tools output information from their models using mathematics and statistics, which means that AI output is taken someone else’s prior work and is neither innovative nor unique.
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