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I Spent 24 Hours with GitHub Copilot Workspaces

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Re: I Spent 24 Hours with GitHub Copilot Workspaces

#11

Post by jmole »

kbenson wrote: post #5
vundercind wrote: post #2

… 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…

Yeah, but look at this through the lens of enshittification.

Microsoft will sell "Copilot enterprise" to companies that can afford to negotiate. But every individual out there on a normal subscription gets data mined.

OpenAI is similar - you can't negotiate a "no-logs" deal with them unless you are a player the size of say, Epic (the health industry giant).

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#12

Post by HanClinto »

kulor wrote: post #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.

It feels like CW is taking a step further left -- it takes a description of the problem and the codebase and creates a detailed user story (with bulleted points for success criteria and everything).

That feels like the right way to go -- almost baking an "agile done right" workflow into its engine.

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#13

Post by HanClinto »

sdesol wrote: post #10
extr wrote: 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 bef…

Agreed.

The most compelling part of the demo showcased in this post is the way that the tool built the bulleted list of success criteria -- that's so often a tedious and overlooked part of writing user stories, but its importance shouldn't be understated -- the fact that it bakes that step into the workflow feels like the most valuable piece of the puzzle here.

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#14

Post by airstrike »

jmole wrote: post #11
kbenson wrote: post #5

Earlier quoted context omitted.

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…

Yeah, but look at this through the lens of enshittification. Microsoft will sell "Copilot enterprise" to companies that can afford to negotiate. But every individual out there on a normal subscription gets data mined. OpenAI is similar - you can't negotiate a "no-logs" deal with them unless you are a player the size of say, Epic (the health industry giant).

> OpenAI is similar - you can't negotiate a "no-logs" deal with them unless you are a player the size of say, Epic (the health industry giant).

OpenAI's API license states that they won't use your data to train models, if that's any consolation. Unlike ChatGPT

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#15

Post by vundercind »

kbenson wrote: post #5
vundercind wrote: post #2

… 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…

I mean “here’s some telemetry (spying) data on your employees, in a nice little dashboard”

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#17

Post by jprete »

extr wrote: 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…

To me this looks similar to rubber-ducking or technical writing. All three involve mentally modeling the perspective of someone who may not share your knowledge or assumptions.

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#18

Post by ozten »

No mention of Cost for a task completed.

A similar system, CrewAI, I ran their hello world and it cost $4 against GPT-4.

There is a trade-off between my time and the cost of the feature against me just coding it up with LLM assistance which has a fixed cost of $20 per month.

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#19

Post by sottol »

The main thing that makes me skeptical is still what happens to a code base when you do this longer-term. And not just the code base but also the company when nobody understands the code any longer, but maybe neither are problems.

A couple questions:

* Will the codebase turn into a mess over time by having the AI apply changes over changes over changes? Do we even care? Or do we want a human to still be able to follow what is going on?

* Will you just be able ask the AI to refactor it all and clean it up? Then it wouldn't be a problem I presume.

* Are product-based tech companies/startups still defensible if anyone can basically recreate the product with some English?

* I don't know Codepilot Workspaces - are the prompts that generate and change the code kept somewhere? Imo they're part of the codebase now.

Re: I Spent 24 Hours with GitHub Copilot Workspaces

#20

Post by simonw »

sottol wrote: post #19

The main thing that makes me skeptical is still what happens to a code base when you do this longer-term. And not just the code base but also the company when nobody understands the code any longer, but maybe neither are problems. A couple questions: * Will the codebase turn into a mess over time by having the AI apply changes over changes over changes? Do we even care? Or do we want a human to still be able to follo…

My experience so far with LLM generated code is that it tends to be pretty easy to maintain in the future, because it uses obvious code patterns and includes genuinely relevant comments.

The trick is to know how to program already, and avoid checking in LLM-generated code unless you completely understand every line.

If you don't do that you'll run into the same problems as you would if you hire a contractor to build your codebase without understanding what they did for you.

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