This should've been done in VSCode. Most developers don't want to write code in a browser. Once VSCode extension is built they could generalize it to other editors. I'm sure they are thinking of VSCode integration and I am hopping for that to be available soon
GitHub Copilot Workspace: Technical Preview
81–90 of 333 posts
Re: GitHub Copilot Workspace: Technical Preview
#82Student here: I legitimately cannot understand how senior developers can dismiss these LLM tools when they've gone from barely stringing together a TODO app to structuring and executing large-scale changes in entire repositories in 3 years. I'm not a singulatarian, but this seems like a brutal S-curve we're heading into. I also have a hard time believing that there is enough software need to make such an extreme prod…
Re: GitHub Copilot Workspace: Technical Preview
#83Re: GitHub Copilot Workspace: Technical Preview
#84Re: GitHub Copilot Workspace: Technical Preview
#85Re: GitHub Copilot Workspace: Technical Preview
#86Earlier quoted context omitted.
I like the Primeagen's examples for the simple stuff. On stream he fires up an editor and copilot then writes the function signature for quick sort. Then copilot gets it wrong. It creates a sort function, but one worse than quick sort but not as bad as bubble sort. These LLMs will get better. But today they are just summarizing. They screw up fairly simple tasks in fairly obvious ways right now. We don't know if they…
can't wait until they're good enough to screw up complex tasks in subtle ways after undercutting the pay of junior developers such that no one is studying how to program computers anymore
The electrons must flow.
Re: GitHub Copilot Workspace: Technical Preview
#87Interesting. I don't think the AI code generation will live up to developer expectations, but I do see the value in "project management for developers". The value I see with workspace is not the code generation, but the ability to help developers organize their thoughts.
What AI can really do well is take an already competent engineer and suddenly get rid of a lot of the annoying tedium they had to deal with. Whether it's writing boilerplate, doing basic project management, organizing brain dumps/brainstorming, etc.
Re: GitHub Copilot Workspace: Technical Preview
#88Earlier quoted context omitted.
Accountants thought spreadsheets would kill their profession, instead demand for them exploded. Compilers made it much easier to code compared to writing everything in Assembly. Python made it much easier to code than writing C. Both increased the demand for coders. Code is a liability, not an asset. The fact that less technical people and people who are not trained engineers can now make useful apps by generating mi…
This is what I've been predicting for over a year: AI-assisted programming will increase demand for programmers. It may well change how they do their work though, just like spreadsheets did for accountants and compilers did for the earliest generation of hand-code-in-ASM developers. I can imagine a future where we do most of our coding at an even higher level than today and only dive down into the minutia when the AI…
When was the last time you wrote assembler?
Re: GitHub Copilot Workspace: Technical Preview
#89Interesting. I don't think the AI code generation will live up to developer expectations, but I do see the value in "project management for developers". The value I see with workspace is not the code generation, but the ability to help developers organize their thoughts.
The real problem is a large part of the enormous hype train is investors thinking they can replace talented engineers w/ AI. That's fundamentally doomed for failure. What AI can really do well is take an already competent engineer and suddenly get rid of a lot of the annoying tedium they had to deal with. Whether it's writing boilerplate, doing basic project management, organizing brain dumps/brainstorming, etc.
Re: GitHub Copilot Workspace: Technical Preview
#90Hello! GitHub Next here, happy to answer questions and unpack how we think about AI tools for developers (spoiler: it's less about codegen and more about helping with the rest of the dev cycle — building an understanding of how the system works, clearly specifying how it should change, etc)
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).