I'm curious if anyone here has used Large Language Models (LLMs) to learn new programming languages, tools, or technologies. Specifically, I'm thinking about how LLMs can aid in understanding documentation, like putting it into NotebookLM or other similar tools. We often hear about AI's role in automating code generation, but I'm interested in whether these models can actually assist in the learning process itself. Does using LLMs make learning faster and more effective compared to traditional methods? What has been your experience?
5 Answers
I’ve been using LLMs to summarize information from YouTube tutorials, which really speeds up my learning. It's a great way to digest a lot of material in a shorter timeframe!
Sometimes, I flip it around and get the LLM to quiz me about what I know to find any gaps in my understanding, and it works surprisingly well.
LLMs are really just good at predicting text, so I think their usefulness as learning tools is limited compared to proper documentation and interactive coding environments. You still need the original sources to truly learn the material.
LLMs can definitely help navigate new APIs, but they do make mistakes, so it’s crucial to confirm their suggestions with actual documentation. They are great for quickly finding information since you can ask questions in natural language, but double-checking is a must since they might suggest non-existent APIs.
I've onboarded with my new job mostly using Gemini, and it’s been amazing for getting straightforward answers to basic questions, addressing setup, and troubleshooting. I've also used it for platforms like Auth0, and it gets most things right quickly—just keep in mind it’s essential to verify what it says!
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