Using ChatGPT and AI assistants over the past year, here are my best use cases: - Generating wrappers and simple CRUD APIs on top of database tables, provided

Using ChatGPT and AI assistants over the past year, here are my best use cases: - Generating wrappers and simple CRUD APIs on top of database tables, provided only with a DDL of the tables. - Optimizing SQL queries and schemas, especially for less familiar SQL dialects—extremely effective. - Generating Swagger comments for API methods. Joyness - Re-creating classes or components based on similar classes, especially with Next.js, where the component mechanics often make this necessary. - Creating utility methods for data conversion or mapping between different formats or structures. - Assisting with CSS and the intricacies of HTML for styling. - GPT4 o1 is significantly better at handling more complex scenarios in creation and refactoring. Current challenges based on my experience: - LLM lacks critical thinking; they tend to accommodate the user’s input even if the question is flawed or lacks a valid answer. - There’s a substantial lack of context in most cases. LLMs should integrate deeper with data sampling capabilities or, ideally, support real-time debugging context. - Challenging to use in large projects due to limited awareness of project structure and dependencies.