Live data from Hacker News

I Spent 24 Hours with GitHub Copilot Workspaces

every.to

1–10 of 76 posts

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#3
To answer the question of whether something like this is the future of programming posed at the end of the article: I think in a lot of ways yes. It reduces the iteration time for making a new feature and handles a lot of the project management too. As AI get's smarter it makes sense to design workflows around how their capabilities can complement ours as developers and not just force them into existing workflows.

We're working on something similar to workspaces: https://www.bismuthos.com

We provide a workspace to build Python backends. Chat on the left, code and visual editors on the right. However, we also handle deployments, data storage (we have a blob store), serving (we built a home grown function runtime) and logging.

The experience is tightly integrated with our copilot and the idea is to get ideas off the ground as quickly as possible with as little devops hassle. Right now the focus is on building something new, but we're in the process of making it easier for existing projects to integrate with us too.

Feel free to drop by our (very) new discord too: https://discord.gg/E5Yn3vaM

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#4
I've noticed the same issue with AI coding, where you start to write requirements and then realize that you yourself don't have a perfect idea of what exactly this feature should be, or how it should work. It's easy to say the answer should be to simply think harder, or enter a dialogue with the AI about missing details, but if you try that you'll find yourself supplying an enormous amount of context you didn't expect to have to communicate. Context not even directly related to the code at hand, but about the broader business or industry, past lessons learned, something the CEO said to you last week about the feature, etc.

It's this kind of thing that makes me think tackling big feature requests is still an AGI-complete problem. Perhaps if it gets good enough at pure coding you can iterate your way to success.

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#5

… am I wrong for thinking the actual play Workspaces is making is in corporate spyware, and the rest is mostly secondary as far as what may get businesses to pay for it?

I don't know, but I think you and I have vastly different base assumptions.

Its a huge legal liability to have statements about how data won't be used and then use it, when you're a company that might compete in similar spaces, and Microsoft competes almost everywhere.

While I trusted githib when they were independent, I trust this feature from MS owned github more than I would them because the liability misuse opens them up to is so much more. If I was building a product and I was able to prove some MS depot used my info in an unauthorized way to build a product, I could sue that product out of existence, and someone always talks, so MS can't assume it will never be known, and they know that.

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#6
There was an impressive demo at AWS Summit London of their Code Whisperer and Q products taking a similar route to CW. Provide a user story and it'd create a PR.

I could see "AI workspace driven development" being the future of at the very least cutting through the smaller tickets of work and generally improving developer workflows.

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#8
When reading posts such as these, it occurs to me that AI is increasing the rate / lowering the bar for developers to make the jump to leader / architect.

Look at the lessons that the author has learned here:

* More specificity == better

* The importance of clear bulleted delivery items / criteria-for-success

* Unspecified details around a general goal is a ripe area for disappointment

All of these are things that a product owner / team leader learns in their first few projects (and so often must re-learn as the years go by).

AI is lowering barriers and promoting more developers to this role earlier. But everything that we learned about good Agile development in the past will still apply to the future.

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#9
post #7

I'm still not sure how this is different than the vs code plugin. It seems to function in about the same way. Just uses a bit of different context reference. But that scope can easily lead to incorrect code targeting.

I haven't played with CW yet, but based on the screenshots and whatnot, it feels like CW adds another layer of requirements-gathering to its workflow (along with clear bullet points for what the terms of success look like) that regular Copilot doesn't have.

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#10
post #4

I've noticed the same issue with AI coding, where you start to write requirements and then realize that you yourself don't have a perfect idea of what exactly this feature should be, or how it should work. It's easy to say the answer should be to simply think harder, or enter a dialogue with the AI about missing details, but if you try that you'll find yourself supplying an enormous amount of context you didn't expec…

> then realize that you yourself don't have a perfect idea of what exactly this feature should be

I talked about it the last time that Copilot Workspaces reached the front page two days ago and that was, I don't think the value is in the code generation, but rather in the ability to capture our thought process. CW is currently a bottleneck in my opinion and I think the code generation will have to get pretty good before we can see the value in writing everything down vs just coding as we have always done.

Post reply on HN