  This study aims to explore the best practices for utilizing GenAI as a
programming tool, through a comparative analysis between GPT-4 and GLM-4. By
evaluating prompting strategies at different levels of complexity, we identify
that simplest and straightforward prompting strategy yields best code
generation results. Additionally, adding a CoT-like preliminary confirmation
step would further increase the success rate. Our results reveal that while
GPT-4 marginally outperforms GLM-4, the difference is minimal for average
users. In our simplified evaluation model, we see a remarkable 30 to 100-fold
increase in code generation efficiency over traditional coding norms. Our GenAI
Coding Workshop highlights the effectiveness and accessibility of the prompting
methodology developed in this study. We observe that GenAI-assisted coding
would trigger a paradigm shift in programming landscape, which necessitates
developers to take on new roles revolving around supervising and guiding GenAI,
and to focus more on setting high-level objectives and engaging more towards
innovation.
