This is exactly the magic I felt when using Copilot Chat-while being able to get a contextual suggestion that actually worked and helped me quickly progress to the next thing. I would learn by copying and pasting things I saw on StackOverflow and seeing how they fit in with the rest of my code (or by chatting with my buddy that I shared a cubicle with at the time).Ī lot of the time, these code snippets didn’t even work, but having something to start with really helped with the learning process and that excitement propelled me forward to the next step. I would spend hours, days, weeks doing tutorials and learning about different ways of implementing things. I remember when I was first starting in my career and discovering all these new frameworks. This idea of looking for external help and examples to understand code has been part of the learning process since well before we had AI pair programming tools. It was empowering to discover that I can get something done so much faster than what I would have anticipated without any help. If it offered me a suggestion that didn’t work out well, I could give it feedback on why that suggestion didn’t work, which enabled it to offer suggestions that better suited my needs.ĭespite working in an unfamiliar framework, Copilot Chat enabled me to immediately start churning out my ideas, which was incredibly satisfying. I didn’t have to leave my IDE and search for advice or a component to use because Copilot would suggest something in real time. What I most enjoyed about using Copilot Chat to create something new was discovering multiple ways I could implement my component. Making prototypes and generating new code But with Copilot Chat, each iteration of my photo gallery only took me about 20-30 minutes to go through. It had been a long time since I had used React, so it probably would’ve taken me a few days of searching and trial and error before coming up with something decent. Using a probabilistic model, which is currently based on OpenAI’s GPT-3.5-turbo, it found the best suggestion for me based on how I prompted it, including the question I asked, the code I’d started writing, and other open tabs in my IDE. In the end, I went through a couple different versions of this photo gallery with Copilot Chat. Since photography is a hobby of mine, I decided to make a photo gallery of the tulip fields and flower shows around Amsterdam. Recently, I was preparing a conference talk and demo about ReactJS, and I had to think a bit about what kind of app I wanted to make with the help of Copilot Chat. Navigating a new framework (and saving time) Now, developers can not only get code suggestions in-line, but they can ask Copilot questions directly, get explanations, offer prompts for code, and more, all while staying in the IDE-and in the flow. This goes beyond GitHub Copilot’s original capabilities, which focused on autocompletion and translating natural language comments into code. With GitHub Copilot Chat, you can now interface with Copilot as a context-aware conversational assistant right in the IDE, allowing you to execute some of the most complex tasks with simple prompts. ICYMI, all GitHub Copilot for Individuals users now have access to GitHub Copilot Chat beta! The capabilities of GitHub Copilot Chat
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