Interesting stuff! I've been trying ollama/gpt + continue.dev and copilot in VSCode for a bit now and the chat-style assistant is a huge plus. Especially in DevOps (my main work) the codegen is rather unhelpful, but the ability to let LLMs explain some sections and help in rubber-ducking is huge.
I see that a good output requires a good input (prompt). How does copilot workspace determine a good input for the prompt? I see that in the github repo there is already a bunch of "Tips and Tricks" to get better results. What is your experience so far? Should we change our way of creating issues (user-stories / bug-reports, change-requests) to a format that is better understood by AI/Copilot? (half-joking, half-serious).
I see that a good output requires a good input (prompt). How does copilot workspace determine a good input for the prompt? I see that in the github repo there is already a bunch of "Tips and Tricks" to get better results. What is your experience so far? Should we change our way of creating issues (user-stories / bug-reports, change-requests) to a format that is better understood by AI/Copilot? (half-joking, half-serious).