71–80 of 372 posts
> Copilot excels at low-to-medium complexity tasks Oh cool! > in well-tested codebases Oh ok never mind
Have it write tests for everything and then you've got a well tested codebase.
Earlier quoted context omitted.
So I need to ask: what is the overall goal of your project? What will you do in, say, 5 years from now?
What I'm most excited about is allowing developers to spend more of their time working on the work they enjoy, and less of their time working on mundane, boring or annoying tasks. Most developers don't love writing tests, or updating documentation, or working on tricky dependency updates - and I really think we're heading to a world where AI can take the load of that and free me up to work on the most interesting and…
Earlier quoted context omitted.
I feel like I saw a quote recently that said 20-30% of MS code is generated in some way. [0] In any case, I think this is the best use case for AI in programming—as a force multiplier for the developer. It’s for the best benefit of both AI and humanity for AI to avoid diminishing the creativity, agency and critical thinking skills of its human operators. AI should be task oriented, but high level decision-making and…
You might want to study the history of technology and how rapidly compute efficiency has increased as well as how quickly the models are improving. In this context, assuming that humans will still be able to do high level planning anywhere near as well as an AI, say 3-5 years out, is almost ludicrous.
I wish they optimized things before adding more crap that will slow things down even more. The only thing that's fast with copilot is the autocomplete, it sometimes takes several minutes to make edits on a 100 line file regardless of the model I pick (some are faster than others). If these models had a close to 100% hit rate this would be somewhat fine, but going back and forth with something that takes this long is…
> Copilot excels at low-to-medium complexity tasks in well-tested codebases, from adding features and fixing bugs to extending tests, refactoring, and improving documentation. Bounds bounds bounds bounds. The important part for humans seems to be maintaining boundaries for AI. If your well-tested codebase has the tests built thru AI, its probably not going to work. I think its somewhat telling that they can't share n…
I feel like I saw a quote recently that said 20-30% of MS code is generated in some way. [0] In any case, I think this is the best use case for AI in programming—as a force multiplier for the developer. It’s for the best benefit of both AI and humanity for AI to avoid diminishing the creativity, agency and critical thinking skills of its human operators. AI should be task oriented, but high level decision-making and…
Similar to google. MS now requires devs to use ai
> Copilot excels at low-to-medium complexity tasks in well-tested codebases, from adding features and fixing bugs to extending tests, refactoring, and improving documentation. Bounds bounds bounds bounds. The important part for humans seems to be maintaining boundaries for AI. If your well-tested codebase has the tests built thru AI, its probably not going to work. I think its somewhat telling that they can't share n…
We've been using Copilot coding agent internally at GitHub, and more widely across Microsoft, for nearly three months. That dogfooding has been hugely valuable, with tonnes of valuable feedback (and bug bashing!) that has helped us get the agent ready to launch today. So far, the agent has been used by about 400 GitHub employees in more than 300 our our repositories, and we've merged almost 1,000 pull requests contri…
I'm curious to know how many Copilot PRs were not merged and/or required human take-overs.
Now Microsoft sits on a goldmine of source code and has the ability to offer AI integration even to private repositories. I can upload my code into a private repo and discuss it with an AI.
The only thing Google can counter with would be to build tools which developers install locally, but even then I guess that the integration would be limited.
And considering that Microsoft owns the "coding OS" VS Code, it makes Google look even worse. Let's see what they come up with tomorrow at Google I/O, but I doubt that it will be a serious competition for Microsoft. Maybe for OpenAI, if they're smart, but not for Microsoft.
I wish they optimized things before adding more crap that will slow things down even more. The only thing that's fast with copilot is the autocomplete, it sometimes takes several minutes to make edits on a 100 line file regardless of the model I pick (some are faster than others). If these models had a close to 100% hit rate this would be somewhat fine, but going back and forth with something that takes this long is…
My experience has mostly been the opposite -- changes to several-hundred-line files usually only take a few seconds. That said, months ago I did experience the kind of slow agent edit times you mentioned. I don't know where the bottleneck was, but it hasn't come back. I'm on library WiFi right now, "vibe coding" (as much as I dislike that term) a new tool for my customers using Copilot, and it's snappy.
The claude and gemini models tend to be the slowest (yes, including flash). 4o is currently the fastest but still not great.
Which model does it use? Will this let me select which model to use? I have seen a big difference in the type of code that different models produce, although their prompts may be to blame/credit in part.
Edit: From the TFA: Using the agent consumes GitHub Actions minutes and Copilot premium requests, starting from entitlements included with your plan.
[0] https://docs.github.com/en/copilot/managing-copilot/monitori...
I'm all for new tech getting introduced and made useful, but let's make it all opt in, shall we?