Less Coding, More Prompt Engineering!
Software developers have taken note of the efficacy of large language models such as ChatGPT towards automating particular development tasks. Depending on the language in use and what is to be accomplished, LLMs can provide a concise answer that circumvents the shortcomings of documentation that is either incomplete or tries to "boil the ocean." LLMs work best at generating code when the problem is well-defined and the language is fairly static and consistent. For instance, I have had a great deal of success when asking for code to perform basic operations on Amazon DynamoDB in the Node.js SDK 3. It was a bit more difficult to have it write infrastructure as code for AWS using the CDK framework in Python 3, but it still produced decent enough code that I at least knew where to start in looking at lengthy documentation. However, writing native mobile code such as Kotlin for Android or Swift for iOS yields some rather incomprehensible and outdated results. Besides ChatGPT, ther...