Using LLMs#
This section covers how to use Large Language Models (LLMs) as AI coding assistants, which can significantly enhance your programming experience.
The part is structured as follows:
Overview#
Programming often requires writing repetitive code and debugging nasty errors. These tasks can be time-consuming and may distract you from your original goal of solving a problem or building a feature.
Large Language Models can be especially useful in this context, as they can be trained on large amounts of code to provide intelligent code completions, suggestions, and even bug fixes. It is common practice in today’s software development landscape to use AI-powered tools to help with writing code. This concept in programming came to be known as pair programming with AI, which stems from the notion of pair programming, which is when two developers write code together, allowing them to spot each other’s mistakes and collaborate on ideas while programming. Pair programming with AI has become so powerful that even in a top-tier company like Google which only hires the best programmers, CEO Sundar Pichai made a statement that over 25% of Google’s code is now written by AI, and this number is expected to grow in the future. This shows how AI is revolutionizing the way we write code.
In this series of notebooks, we explore how to effectively use AI coding assistants to streamline your Python development process. Some key concepts to take away from this workshop include:
Effective prompting: Be specific and detailed in your prompts to receive accurate and relevant responses.
Generating code: Use AI to generate repetitive or boilerplate code, but maintain control over the process.
Debugging errors: Use AI assistants to quickly identify and fix bugs in your code.
Human-in-the-loop: Always review and validate AI-generated code to ensure quality and accuracy.