Summary

This chapter has introduced you to how to code with LLMs. You’ve explored the potential benefits, learned practical steps to get started (planning and iterating), and gained valuable insights into using LLMs effectively. Remember, these are just the most simple examples of what can be done along with some advice.

There’s plenty more to learn to do this well, but this can help you get started. We need to understand how to deal with code that has bugs and doesn’t work how we intend.

We might want to improve upon the speed or the memory usage of the code.

GPT-4, Gemini, and so on don’t innately know what you want to achieve or which resources you want to save or fully exploit.

In Chapter 3, we’ll delve into debugging, code refactoring, and optimization.