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From YouTube: A Sneak Peek at the Future of GitHub Copilot - GitHub Copilot X

Description

GitHub Copilot improves developer velocity, reducing or eliminating these tasks, by providing code suggestions based on current context in the developer's IDE. GitHub Copilot X continues to build upon the technology, allowing developers to expand the surface in which they're able to take advantage of generative AI.

00:00 - Introduction
03:16 - Overview
04:35 - GitHub Copilot X
14:09 - GitHub Copilot CLI demo
31:42 - GitHub Copilot Chat
43:11 - Q&A
1:08:35 - GitHub Copilot for Pull Requests
1:10:37 - GitHub Copilot for Docs
1:16:55 - Closing

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I think this is it I think this is good. Looks like we've got some people here.

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um If somebody wants to say um something in the chat to, let me know that everybody's connected, but in the meantime we can go ahead and get rock and roll in here so uh good morning, good afternoon, good evening, depending on where in the world you happen to be, my name is Christopher Harrison I'm, a senior Enterprise Advocate at GitHub, and today, I'm really excited to chat about the future of generative, Ai and GitHub co-pilot and in particular, talk about GitHub, co-pilot, X, What, It, Is, What, It Isn't, what all it encompasses and sort of lay out where we think the future of generative AI is going when it comes to supporting developers.

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Now this is live, so please feel free to ask all the questions that you want. You may notice that I'm looking down periodically. That's because that's where my instance of the chat is is I'm down here on my second screen.

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um So if you want to ask questions, feel free to go ahead and throw them on into the chat. Let me just open up the public screen um here we go.

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And ensure that people are out there, Yes No Maybe there we go perfect all right here we go.

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Excellent Okay cool, so, let's get on into it now. I want to talk real quickly about kind of what the flow is going to be today. So I'm going to go through a couple of intro, slides and I'm, going to talk a little bit kind of very quickly about copilot X, but before I really dig into copilot.

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X I actually want to take a step back talk a bit about GitHub co-pilot and then we'll go ahead and transition more into chatting about uh GitHub copilot, X I'm, also going to do off a lot of demo today, I'm going to do an awful lot of coding, because I think that that's really the best way to kind of understand what it is that we're looking to accomplish here and how it is that we think that this technology can help best support developers. So you're going to notice a lot of live demos. Now.

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What that also means is that I'll be doing live. Demos and I'll be doing live demos with products that are still in development, so it is very likely that something is going to break. It is very likely that things might not work exactly as expected and that's simply the nature of the beast.

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That's simply the nature of live demos working with a beta product and also working with AI, because it's not going to be deterministic, so things might behave a little bit differently so for that I apologize, but that's just sort of the the way that things flow so yeah, exactly somebody says uh nothing. Works is planned on a on a demo absolutely, and that will almost certainly be the case today.

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So with all that being said, let's kick right on into it, and I always like to start basically every presentation that I do with this slide right here, so I've been at GitHub for just shy of a year now, and this slide has changed about four times in the amount of time that I've been here in particular that top left number of a hundred million developers.

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The reason that I like to start with this slide is because you don't hit 100 million developers by solely focusing in on business customers by solely having developers that have been told, go use this tool that instead, what happens is these are developers that are choosing to use GitHub they're looking at the tool set that we we've built the tool set that we've provided and they're going hey? This gives me what I need to be most successful at my job and that's because that is our primary focus.

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Our primary focus is around the developer that we want to make sure that the developer has the best experience, that's going to enable them to do their best work and the biggest place that we've seen this change, certainly over the last couple of a few months, has been when it comes to GitHub co-pilot. Now, a couple months ago we announced this thing called GitHub, copilot X, and so let's talk a little bit about what GitHub copilot X is.

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First of all, this is not a product and it's also not necessarily a suite of products, but really what this is is our vision that when we released GitHub co-pilot, what we saw is the power of generative AI when it comes to code creation of how it is that it can help support developers, how it can make developers more productive, and so we looked around and we went okay. Where else could this help?

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What other interfaces are developers looking for and, of course, one of the biggest places and one of the places that we'll be spending the most amount of time on as we go through into our demos, is looking for some form of interactive chat that chat GPT, of course, kind of set the world on fire.

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If you will that there was a lot of excitement around this chat, bot that I could go in I could ask questions and I could get human style answers, but back from that, and that's something that we as developers want to be able to have, we think interactively and so being able to embed that right there inside of an IDE right there, where I'm writing code, that's going to be really big, that's going to be really important, and so that's one of the places where we're thinking about when it comes to generative Ai and how it can support Developers, so GitHub, copilot X is our vision.

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That's really what we were announcing there is that these are all the different places that we see right now, where generative AI can help out. So this is not a an individual product. This is not a roadmap necessarily, but really it's an announcement of our vision and we'll get into some of the specifics.

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Some of the specific areas and some of the potential products that you might see shipped out at some point, but the big thing that I want to make sure that I highlight here is that all of this is still very much in development.

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All of this is still being explored, so things very well may change that some of the products that we talk about today might not actually get released, that some of the products that we talk about today might find themselves as part of separate products or might get rolled into other ones and so forth. So please do keep in mind that all of this is very, very, very early on.

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So before we get into GitHub copilot X, though I think we want to take a step back and talk about GitHub copilot, because this is really kind of where it starts.

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So what is GitHub co-pilot GitHub copilot is an AI pair programmer that what GitHub called pilot will do is it will look at your context as you are writing code, as you are adding in comments and start to make suggestions that probably the the most famous feature, the most powerful feature that we see when we're talking about GitHub copilot is the ability to write a comment that a developer can write out. A comment: explain a natural language.

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What it is that they're looking to do what it is they're looking to accomplish and then GitHub co-pilot can then make a suggestion of the next line of code of the next class of the next function of the next block of code that it thinks matches.

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What that comment is looking for and then basing it around the context that it sees so, for example, if it sees that you're using a particular naming strategy for your variables or that you're using a particular tabbing strategy or that you're always using a particular feature that copilot will then use that context to help shape these suggestions that it is then going to make.

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And what's really nice about that, is that now that can allow me to offload boilerplate code that can allow me to offload repetitive code that when we think about writing code these days, we've got all of these Frameworks. That can really help us out, but there's only so much that you can abstract away and that at some point, you've got to write some level of code and sometimes that winds up being relatively boilerplate and so by being able to offload that out to GitHub co-pilot.

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That allows me, as the developer, to be able to focus in on the bigger picture to be able to solve the bigger problems to allow me to better stay in the zone. One of the other, very big places and we'll actually come back and talk more about this later, is when it comes to test creation.

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That I don't think that there's an organization that's out there that feels really comfortable in the amount of tests that they have and, if we're being honest as developers, we don't necessarily always like writing tests, but at the end of the day, unit tests, end-to-end tests, they're just code and since GitHub co-pilot can write code for me, then it can in turn, write my unit tests for me as well. That I can say: hey, create a unit test for this function or create a set of tests.

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That's going to test for this this, and this and GitHub copilot can help me out in that Arena now the way that it does its magic behind the scenes here is, as I'm doing things inside my IDE. It's going to send that context up to copilot. It's going to use this custom model that we've built that's been trained out on billions of lines of publicly available code and then eventually send those suggestions down for me right there inside of my IDE.

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So this is GitHub copilot and chances are you've probably already played around with this you've. Probably already seen some demos on this, and and hopefully especially since you're connected you're kind of excited about this now GitHub called pilot is wonderful and I want to make sure that I'm very clear here in highlighting that what I'm about to say is a no way shape or form trying to downplay or poke holes at GitHub co-pilot, because in my mind, I have not seen a developer tool.

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That's been released in in my programming lifespan that has had a greater impact on my productivity than GitHub co-pilot.

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But that being said, GitHub copilot is a tool, and it's specifically built for me writing code inside of my IDE, and so what we've seen is that's great and it's wonderful and it's wonderful to be able to support developers there. But that's not the only place that developers I'm going to kind of kick ahead a little bit with my slides here. That's not the only place where developers are looking to interact with the system or are maybe looking for the support of generative AI, so GitHub co-pilot.

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As it's currently built is a wonderful tool for my developer, going in writing code and getting a little bit of support as they go. But let's talk a bit then about some of the other places that my developers are going to be interacting with the system and might be looking for some level of support, and so one of the biggest places is going to be co-pilot for the CLI.

A

So the power of copilot but they're inside of the terminal I am a big big fan of the CLI I love using the CLI um and there's a few different reasons for this.

A

That part of it is because I like to be able to create scripts that are going to make my life easier part of it's because I type relatively quickly and so being able to just and get right to exactly what it is that I'm looking for is extremely powerful and, of course, another very big part of that is the fact that when we look at a lot of the Frameworks that are out there, and especially for me, I'm I'm, primarily a web developer when it comes to development there's.

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So many CLI tools that are out there that basically every single web framework, it seems- has their own custom, CLI and so trying to remember all of those little bits of syntax can become a little bit of a pain and so it'd be nice to be able to get some level of support right there, as I'm doing my thing so Adam says um uh uh no more uh man than Google uh man being, of course, the uh the little help that you could get from the command line. That's that's from the goal here.

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That's that's where we're pointing to is to be able to interact with uh generative AI right there on the CLI. So how does this work? Well, let's go ahead and take a real, quick look at a at a demo here. So let me see, can I get my layout here to just go full screen and get rid of me.

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No speaker, videos, there we go okay, I knew I could do it all right just took me a minute to find it okay, so let's go ahead and and take a look here and let me just um clear that out cool, so what I want to do is I want to create a front. End uh uh react app and I know that there's something about like create react app, but I can't remember exactly what it is that I'm supposed to be doing. So this is where uh copilot for CLI can come into play.

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So this is going to start with two question marks and now I can right here, naturally describe what it is that I'm looking for so I'm going to say, create uh react app uh with name front end like that and oh.

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Oh um give me one second here.

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Hold on one second, apparently, the update that I made did.

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Not save like it should have not a problem. Give me two seconds here.

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There we go okay, beautiful all right, sorry about that see, I told you there was gonna, be there was going to be a bug uh somewhere uh somewhere along the way, all righty uh Brew, install I, love that yeah. Okay, uh let's try this one more time here we go so I'm gonna, go question, my question mark and then I'm gonna say uh create react app with name uh front end.

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There we go and then hit enter so now. Here's what we're going to notice is the response that I get back. Is here's the command, npx create react, app front end and then here's the explanation so npx is used to run the command uh from a package without installing it create react. App is a package that creates new react. App front to end is the name of the new app and then you're going to notice down below that. It asks me whether or not I want to run this command.

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So let's pause right here for a moment and let's talk a little bit about this, so you'll notice that I started up at the very top with a bit of natural language. This is what I'm looking to do.

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Copilot for CLI then comes back and says: okay, here's the command that I came up with so MPX create react, app front end, and then it's going to give me the full explanation. One of the most important things that we always need to remember about generative AI is the fact that we're not always going to get back perfect answers.

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We can in fact, sometimes get back incorrect information now. Obviously this is something that nobody wants. Obviously uh we among many many many every other company, that's doing anything in the generative AI space.

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We are all working to help avoid that as best as we can, but the simple fact of the matter is: is that that can happen and when we're talking about writing code, one of the very big things that we always want to remember is we need to keep in mind that any code that's been generated by generative AI should still go through all the normal processes. So there should be a human review. There should be automated code quality. There should be Security reviews, like all of the things that you would normally do to your code.

A

You want to do the exact same thing if it's GitHub co-pilot, that's writing that code and in turn the same thing holds true here. Is that whatever it is that this is going to come up with I want to make sure that?

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Yes, this is something that I want to run and especially when we start talking about the command line, we definitely want to make sure that this is in fact going to do what I'm looking for it to do that if all of a sudden I'm seeing an rmfr, an rmrf that I want to, you know, maybe be a little bit more cautious about that. So that's why it's really nice to see here's the command, here's the explanation, and so now I can go. Oh okay! Yes, this is what I was looking for. I can see.

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That's the explanation. All of this looks really good. Let me go ahead and run that command am I sure. Yes, let's go ahead and run that and then away. It goes from there.

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Ux appears to be uh quite similar to figios um uh Al salei uh Hayden says I'm, going to take your word for it. I honestly have not worked with any of the tools outside of GitHub at some point, I really should go back and and do that, but um but I honestly uh uh haven't yet gone back and uh and and done that. So um that being said, can't wait to to get get your hands on it. Yeah I, uh I I can't wait for everybody to have access to it as well.

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uh There is back here yeah uh you'll notice that there's the waitlist URL right there, so you can go ahead and uh and grab that so cool um Anna mentions that the description part is really important. Yeah could not uh could not agree more um and then Patrick says the default. Pre-Selected option should probably be revised. Query not run command, so I I absolutely hear that.

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um But one thing you might have noticed is that even though I I hit enter on that, in fact here, let's just do this- um our um RM RF um that front end that I just created. Let's just remove that real quick and then let's rerun that GitHub command.

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Okay. So the default is run this command and let me hit enter on this and now what you're going to notice it gives me this follow-up. It says this will execute this suggested command in your shell am I sure, and the default is actually set to no here. So, even though that default is to run the command, it's still giving me that follow-up of hey are you sure that you want to run this and the default is going to be?

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No so I'm going to say yes, because I do want to run this, but the default is no, so we are putting in that little bit of of a safety net there, so yep yeah, so Michael um uh linked directly out to the GitHub next uh location, and in fact, let's do this.

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Doesn't sound effects help by the way yeah, so you can notice right here uh all of the different tools and so forth that we are building out and one of those is copilot for CLI uh usable prototype, which is what I am currently playing around with, and then you can sign up for the wait list there. So if you just do a search for GitHub, copilot, uh sorry GitHub next do a search for GitHub next. That will eventually get you to the page or you can hit the link that Michael shared out or you can.

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Come on hit that link that's right there, let's see Patrick has the question: does uh GitHub co-pilot or GitHub plan on allowing administrators to monitor, requests, logs and so forth so code Whisperer offers a more in-depth access to control management, making it attractive to businesses so um I'm not able to speak to code Whisperer because again, I haven't played around with the the product at all um when it comes to monitoring. What's going on behind the scenes with requests and so forth?

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First thing that I want to mention is that these round trips right here, where we're setting up the questions setting up the context sending back the suggestion. All of this is ephemeral, meaning that it's a one-off that it's going to send up the information, send it back and then none of that is going to be stored or logged anywhere. So none of your code requests none of the code suggestions, none of that's going to be stored.

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There is usage data, however, that is stored and that's going to include thing things like the number of requests that somebody makes what the acceptance percentage is, what the acceptance is, but they go back and they modify the code, those types of things right now we don't have a dashboard where you can see that.

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But if you reach out to your GitHub rep they're going to be able to go pull that information for you, we are working on getting out a um getting at a report screen where you could see that, but as of right now, that's not there so being able to see the exact uh queries and so forth. That's not there and that's very much a design decision, because we we want to keep all of that private.

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So all of that winds up going away, but as far as usage data goes, that is something that we can provide to you and we are looking at building out a dashboard for that. So cool cool.

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All right, let's see so, let's go back to my uh GitHub CLI, so you'll notice that it did in fact run create react app um as per uh I. Think almost any npm script, uh there are some vulnerable packages that are installed so we'd have to go in and uh and update all of those, and then it just ran that normal npx command.

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So if I do an LS here, you'll notice that I I now have that front end, and if I kick on over to Visual Studio code, which I already had open, there is everything with my um uh with my setup, just as I, just as I would expect so. There's my my front end my public, my source to get ignored that it created because it ran npx create app. So it's got all of that right there, all of that through the uh through the CLI.

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um You can also uh do something like this, so I could say like get and maybe initialize uh directory I'm going to leave that typo in there um oops. Is it just simply one there we go one question mark okay, so you'll notice that I did have a typo in there which I left in there on purpose. I didn't type it on purpose, but I left it in there and so now it'll come back and go hey. You want to get a net and then I could go ahead and uh and run this command hit.

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Yes, and then let it go from there and sure enough it. It ran, get a knit and you'll notice. I got the uh the little change right there, so pretty slick, so you are able to now start to get a little bit of interactive support through generative AI right there inside of your uh right inside of your CLI, and it does support being able to make uh General requests oops.

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Let me just get to the right slide here: yeah uh General requests forget and then for the GitHub uh CLI as well using uh GH question mark now again this is a usable prototype. This is still very much in early development, so there's kind of the real quick overview of that and I'll pause here, partly to take a sip of coffee and partly to see if there are any questions.

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Okay, when can we use it? uh That's a fantastic question and I: don't have the answer to that so yeah, one very big thing about GitHub. Next is anything that's there right now we don't have a roadmap and, if I'm being honest, not everything that Finds Its way into GitHub next will find its way out into the wild. So there's still always a non-zero chance. This might not be released out, but it is something we're building. It's something we're looking at. It's something we want to ship so we'll see what happens from uh from.

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There looks awesome. Thank you. Yeah I kind of like it I kind of dig out um how about Purge get commands like pull purse, um uh pull push Branch merging, Etc yeah, so Tom asked this great question. You know what about like um pure git commands, Lin and and to kind of take this one one step further here. Is you know what about those.

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um Let's see, let me do a split screen. Let me just get myself back on screen there. We go so like what about those kind of more intriguing scenarios that that'll be the word that I will use there where you know, maybe I've made a commit and I realized. Oh wait! A minute! I need to undo like just one file of that or maybe I pushed and I really didn't want to, and I need to roll back to a prior commit and then push that out like how do I.

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How do I start to do that? And that really is kind of where we see this going, is being able to support those types of commands. So there's a there's a great website out there, uh the the the PC version of it is I. Think it's oh shoot, get uh that if you just fire up your favorite search engine, just do a search for oh shoot, get there's a a non-pc version uh on the website as well, and it gives you a lot of like great help of like hey I made a mistake.

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How do I undo that and that's kind of what we see for for the CLI is like those types of scenarios, uh especially when we're talking about get because you know any developer, that's been using it for I, don't know more than about an hour and a half has probably made a mistake and went. Oh wait. A minute. I need to I need to do something different here uh and so being able to ask the CLI: hey I made a commit, but I need to roll one back roll back one file.

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How do I do this uh would be really helpful. So that's where we see this going um and and where are we seeing this this uh this being built out so yeah question uh and uh also including uh standard shell commands for like Zip, folders and SSH yeah? Absolutely that that really is kind of where we see all of this Luigi asks a question: what are the languages that are supported so.

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Get them co-pilot in general uh has been trained on publicly available code and text and at the end of the day it is a large language model and basically, what's going to happen, is that the more information that it has the better? The suggestions are that it's going to be able to make that there's going to be a very tight relationship between those two uh between those two charts.

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So when it comes to what languages is this going to support the more widely spoken, a language is the better the support that you're going to uh that you're going to have so, if you're using say English Spanish Japanese, you know where there's there's a very large um uh large amount of publicly available text in those languages.

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It's going to be able to support those languages really well, if you're using a language, that's not as widely spoken, then you are going to notice that the support there isn't going to be as strong and that's just simply the nature of our large language models. So there isn't necessarily A hey.

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This is the language list of languages that it supports, but rather you will notice that the level of support that you're going to get will vary depending on just how much of that language, it's uh it's seeing so yeah um and then the follow-up question to that is.

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Is it able to understand compiler errors and give you suggestions, I'm, very glad that you asked that question, because that leads me perfectly to do into GitHub copilot chat, which I think is really where we want to kind of slide into next, so you've already played around with chat, GPT, uh I'm, I'm, gonna kind of make that assumption. If you haven't already, you should definitely go. Do that and what's wonderful about chat GPT is that you get a chat, bot style of experience. That I can ask a question.

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I can ask follow-up questions to it and I'm going to get information back from it, so I can use it to get code. Snippets I can use it to find out a bit more information about. You know, fill in the blank here now. I love chat, GPT, I I can sit around and kind of play around with chat TPT for for days and days and days. But when it comes to writing code, I find that chat.

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Gpt is a little bit hit and miss and part of it's because that's not what the tool is built for that the tool is built to give back uh human style answers to questions, and so can it do code as part of that? Yes, absolutely, but that's not what it's tuned for that's, not its primary purpose. The other very big thing about Chachi BT is the fact that it isn't going to have as much context that, if I want to say, hey create a controller.

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That's going to be using Django, that's going to be a back end for a react, app that I'm gonna have to explain all of this to chat GPT before I can start to get any usable responses back from that, that's going to take a little while- and this is of course, where GitHub co-pilot traditional GitHub copilot will really shot, because it's going to have all of that context that it's right there inside of my IDE. So it sees the files that I have open.

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It sees the the Frameworks, the libraries that I'm using, and so when I ask those questions. It's going to give me those answers in context based on all of that information, but the real challenge that we wind up having when we're using our current version of uh GitHub co-pilot and again, do not get me wrong. I adore GitHub co-pilot, but we wind up lacking an ability to kind of go back and forth so that if I write out a comment here, let me do this uh to do: let's create a brand new file.

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Let's call this uh server.js and, let's add in a comment here um where I say: uh import. Express there we go oops. Oh you know what just.

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There we go and then uh cool so you're, going to notice that now, as I'm doing my thing, it's already making those contacts right um pick your picture. Sorry about that. Thank you. Thank you. Thank you. uh uh There we go.

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There we go all right, so I create my Express app there we go and then now uh at the server.

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It's good and then let me also um use uh body parser there we go okay, so you'll notice that I'm able to like add in those comments and then get my code suggestions as I go and that's wonderful, like I I, love that feature I love that capability, but the, uh but the challenge that we wind up having there is, if I'm looking to do any form of back and forth here, like maybe I, want to find out a little bit more about this block of code or um I want to like get a suggestion.

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If I don't like what I get I want to go back and and and ask some follow-ups and those types of things doing that with comment, isn't the most intuitive way to get in in and and do things, and so this is where having some form of chat really comes into play so that now I can go.

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Hey describe this code for me, I can go hey, um you know, find the bug or help me improve this code, and those types of things and I can now get those responses right here right here inside of my IDE with it. Knowing the context so, let's say, for example, that what I want to do is I want to create a uh a server here. So let me, let's just say copilot so I want to create um a mongoose model named uh speaker with uh what do I want name, email and uh LinkedIn.

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Url I can just ask it right here and so now what it will do is it will give me the code that I want. So it will give me all of that right there. So there's my brand new schema and then there is the model right there. So let's go ahead. Let's just inject that right here into my code. Let's just hit that little button right here insert that cursor and now that's right there cool!

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That's fantastic! That's wonderful! That's! That's! All! Now! Right there! Now when I'm, personally, writing code, this is quite frequently the way that I do things is that I will kind of do everything inside of like one file and I'll play around and I'll I'll get it to look the way that I want it to look.

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But as we all know, this is not really how I want this to eventually finish out that eventually I'm gonna want all of this Mongoose um uh information somewhere else, so that I'm going to want this out on on on a separate file. So what I can now do is I can highlight this block of code and I can now ask copilot I can go back to copile and say: hey oops hit the right button here and go back, go back and say Hey. You know help me out here. um How can I extract this.

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And so it comes back and it tells me hey, it looks like you want to extract. The speaker schema object from the server here's, the steps to do that. Select the uh schema, object, copy it uh create a new file and then go ahead and paste that in and then now I can have that out as a as a separate file. So let's do that. So, let's come back over here.

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um Sorry right, uh keystroke, typical: let's create a brand new file models, Js and let's go ahead and uh and paste that in come on sorry, so I I, I use Windows locally, uh but of course, for for work, stuff, I use a Mac and my brain because of the long weekend and I was doing an awful lot of work on on my Windows system. My brain is still going control, X control, V and I'm now having to to rewire it back to command uh X command, V.

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All right, so I created my brand new models right here, uh but I am noticing a bug. uh I am noticing that my uh my speaker uh isn't working there. So, let's, uh let's see, let's see if there's um if this will pick it up. So uh is there a problem with I? Don't know if this is gonna work. This is literally the first time I'm doing this. We're gonna find out. uh Is there a problem with um my code?

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uh Can't find a problem? Okay experiencing any issues: okay, um I can't access uh speaker um outside models.

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uh There we go so now it's going to give me the appropriate code to now export that out, so I went back and I said: hey I can't access it if I want to access it from the outside. What I need to do is export it. Here's how I could go ahead and modify it, and it gives me the full thing- and we notice down here at the very bottom, that it's got that module exports.

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So now let's go ahead and copy that and then let's paste that select now what I also really like, is that it even starts to give me kind of The Next Step. So with this modification I can now import the speaker model uh in other files using require all right Let's. uh Let's do that!

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So, let's uh come over here and then let's go ahead and just paste that code in just like that. So now I've got my my speaker and now I'm, even noticing that it's kind of suggesting an expression here, which is how can I use the speaker model in my express route handlers all right. Let's hit that.

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So now it's got a full little thing here, so it's got the hey! Here's, your Express, here's your speaker! Here's the router, here's a router.get and then here's how to export this out. So it's actually creating a full routes.js file. For me, that's pretty slick all right! So let's do it just gonna kind of keep following along with what this is telling me to do so, let's say routes, dot, JS and then I could go ahead and just paste that code in so you'll notice.

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What I'm doing here is that I'm kind of writing along and I'm kind of using this as a little bit of support, I'm, asking it uh different questions and and so forth, and really kind of getting some really nice guidance here on everything that uh that that I need to uh to do, which is uh which is pretty slick, it's pretty slick.

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Okay, um let me go back and kind of get caught up on on some questions here. um So tell me: ask this question co-pilot uh training that is based on open uh public GitHub repos. So it's it's publicly available code and text so exactly where uh the what it's been trained on um hasn't been uh hasn't been released, uh but it's publicly available code and uh and text um a bit of a follow-up. Is this suitable for private repos?

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Is there some implied level of access to private code that should be necessary to, for this to work should be worried about code security. Matthew asks okay. So let's talk about a couple of things here, so number one is I'm going to go back to I want this slide here.

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We go and then I'm also going to bring myself back on there. We go perfect, okay, so the way that gitup copilot works- and this is going to be true for copilot CLI for copilot chat, Etc um yeah, which is that these round trips right here are ephemeral. So when it's setting up that context and the suggestion is going back when you're using GitHub copilot for business, this is ephemeral. None of this is going to be stored.

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So if you are using a private repository, what's going to happen, is that the question that you ask or the code that you have here that's being sent up as part of the context that will be sent up to co-pilot? That's going to be used by copilot to generate the suggestion, but then all of that will go away after that. So none of this is going to be stored. None of this is going to be used to retrain or to update the model or anything like that.

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So as far as code security or anything like that goes we're not hanging on to any of your code that we, we are working to keep your code safe by simply not storing it now.

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The next part of the question is, is you know things like what about say IP or what about you know, code, security and and so forth, and there's a couple of things that I always like to highlight there number one is the fact that if you go look at the uh the terms and the license for GitHub co-pilot for business, it does talk about IP. It does talk about an indemnity clause and you can go find out more information there.

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But the other part that I always like to highlight is the fact that, when we think about how developers write code today that there's only some percentage of that code, that's going to be written out of Hall cloth that my developer is just kind of doing their thing and they are generating all of that code, all on all on their own, that almost every developer, I'm, not even going to say almost every single developer, is looking at docs and They're copying and pasting from there they're going out to coding forums like stack, Overflow and They're copying and pasting from there they're going to chat, gbt they're going out to to Google, and so my developers are always using other sources and other resources to generate their code, and so, even before any other tools are are introduced.

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We always still wanted to make sure that we had process in place to check for things like IP to check for code security, and none of this changes that so whatever it is that you are currently doing. You should still keep doing that and in turn, if you're not already doing something like that, you probably should be already again, regardless of any tool like GitHub called pilot or or otherwise so yeah and then kind of the follow-up to to there when it comes to like attribution and all of that, the exact same uh rules apply.

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The last thing that I'm going to mention on all of that is there is a a post by uh Ryan Salva to do.

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um There we are I want this, and this there we go. uh So there is a post by Ryan Sava, uh who runs, uh helps manage everything with GitHub co-pilot, who has uh talked about creating tools that will give you an ability to start to see where your code uh comes from. If there are any publicly uh public matches- and things like that, so you can uh go check out his blog post for a bit more information on all of that and kind of get a bit more of a sense.

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So yeah, okay, uh Luigi, asked a question: can I push company policies, for example, uh naming things in Pascal case or camel case to avoid uh uh or avoid specific libraries includes Etc Great question, so the the short answer to that is there isn't a way to.

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Point to directly Point GitHub copilot at what you want it to try that sentence all over again.

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At present, there is not a specific way to put your thumb on the scale of GitHub copilot and specifically say always do this always do this, however, GitHub copilot is context aware, so in other words, it's going to generate suggestions that are not only based on its publicly available uh code, the the model that it's got, but also based on your context.

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So if it sees that you're always using a particular style for your variables or that you're always using a particular style for like tabbing, and things like that that it's going to follow along with that as well. So the suggestions that it makes are going to follow along with that.

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So, if you're already using um some a set of requirements, like maybe you're using Pepe, let's say in in Python and you're writing your code, then GitHub pilot will typically follow along with that, because it's going to see that context, so there isn't necessarily a way to go. Hey always do this, but if you've got code, that's already following those patterns that structure then GitHub called pilot is going to uh typically follow right along with that as uh as well.

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um How many ask the question: will it work the same way in Visual Studio, 2022, um I I'm, not exactly sure what it is. So let me answer that in two different ways: first, up when it comes to the current version of GitHub copilot, yes, that it's going to work in line and as I'm doing my thing, all of that will behave the exact same way when it comes to copilot chat.

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As of right now, copilot chat is specific to visual studio code that will eventually find its way to other Ides, as it continues to mature and and hopefully gets released out, but again, there's no timelines on on any of that. At uh at the moment, Adam asked question assume there is embedded embedding of local code stored somewhere and then semantic search performed to inject context into the prompt. It's very cool. But one question is where the embedded searches performed.

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I'm not entirely sure, and at least based on my understanding of the way that GitHub pilot works I, don't think that that's exactly how that works so that the way that I understand it is that that context, that's being sent up, that's all of your files uh uh that that are open. That's the code that you're! Currently writing. That's!

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What's going to be sent up, and then the suggestions are generated in the cloud sent back and again all of this winds up going away so I don't think that there's necessarily anything that's stored locally I could be wrong on that, but that's at least my understanding of the way that GitHub copilot works. I, don't I, don't have the the perfect answer to that, or at least the the way that I understand the way that works doesn't necessarily work that way.

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um uh No there's a setting on the GitHub called pilot page allow GitHub to use my code Snippets to improve product improvements, not sure how this plays into uh uh if there's a difference between individual and business. Okay, so Justin asked this question and I'm going to summarize this here. Real quick there is do I. Have the slide on this.

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I, don't have a slide on it, that's fine! Okay! um All right can I just do this.

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Sorry, just trying to there we go all right come on there. We go all right so uh just to ask a question: um if you go into copilot, you might notice. Hey I want to allow my uh my my interactions to improve Copilot with the current version of GitHub copilot, there's actually two skus, so two subsets, if you will of it, and that is get up call pilot for individuals in GitHub co-pilot for business with GitHub copilot for business, so specifically the business SKU, specifically the business product.

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This transaction right here context being sent up suggesting going back down. That is ephemeral, so that is a one-time shot. That's it! None of your code. None of the suggestions are ever ever ever ever ever ever used to update to retrain to improve the model. None of that is being stored for copilot for individual that's different and that now becomes an option for the individual. So the individual can say yes, I want this to be stored and I want this to be used to improve, or they can choose not so for business.

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We just make that answer, and that answer is always going to be. No, so that answer is this is always going to be ephemeral for individual. It then does become up to the individual to decide whether or not they want that to to happen, or not so totally up to the individual there. So that's one of the biggest differences between the individual and the business version of that. Beyond that, the business version uh does include a couple of other features.

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Part of it, of course, uh will be user management, so you can control who has access to it, who doesn't have access to it? What orgs have access to it and eventually even what repos are going to be allowed to use it and not use it? You also do have an option for co-pilot for business to choose whether or not you want to block or allow suggestions to be made that match publicly available code. So you can choose whether or not you want that to just be hidden or if you want that to be shown.

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So that's another option that you get inside of inside of copilot for business. That's a that's a great question! Thank you for bringing that up. Justin! Please! Forgive me. If I mispronounced, that name, are there plans to make chat available in Vim as well. A question applies to the rest of the products you're showing us today. So there are I, don't think. I have the slide on on this one.

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For the current version of GitHub co-pilot, there are plugins available for neovim for the jetbrain suite of Ides visual studio and visual studio code, so that is the current version of GitHub copilot for copilot chat, which would be the one that would be most applicable to having a plug-in right.

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Now, it's solely for visual studio code uh I assume that eventually it will become available on the other Ides, but right now it's just Visual Studio code now specific to Vim, uh if you're just using them, unfortunately uh not available there, uh even GitHub co-pilot, uh it's going to be neovim. So if you're looking for at least something there, that's that's the way that that would work um perfect, okay, slab! Thank you. Thank you. Thank you.

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Thank you um and asked the question: um can we specify which files to look for the use case would be to create a back-end API for a specific form? Let's say context JS in the front end fantastic question, so the the direct answer is sort of I love that that was my direct answer. My direct answer is sort of uh the direct answer is sort of so when uh copilot is looking to generate its context, it's going to look, of course, at the file that you currently have and at the files that are currently open.

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So, let's talk a little bit about what GitHub co-pilot is is trying to do here. It's really trying to walk a very fine line between giving you the best possible suggestions, but to do so as quickly as possible. So if we have like and I'm going to over exaggerate here- but let's say, we've got like a five second latency, so I type out a comment, and then it takes five seconds to get a response back from Copilot.

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Quite frankly, at that point, co-pilot's useless to me that it's just not going to be able to keep up that if I'm having to wait five seconds to get a response.

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I'm already out of the Zone, like my brain, has already moved on to on to the next thing, so we need to make sure that that latency is as low as possible.

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So we want to get those answers back like near instantaneous, but of course we want to at the same time make sure that we're giving you the best possible quality that we can and that's where the trade-off comes into play, because the more information that we send up and the longer that we're going to take to process the the greater the latency is going to be, but at the same time, the more information that we send up the more time that we take the better the responses are going to be so there's there's a trade-off to be made here.

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So the way that copilot works is it's going to focus its attention on the files that you have open. So it is not, for example, like let's say that I am referencing a file somewhere else like I've, got a link to a file somewhere else inside of an app that I'm building.

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um It's not going to follow that link. So it's not going to be doing like an awful lot of work on the file system and trying to get everything that it possibly can about your project to then in turn, give you the suggestion, because doing that is going to slow things down again. We've got, we've got that trade-off there. So the way that it's optimized is it's going to look at the file that you have and it's going to look at the files that you currently have open.

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So, if you have, let's say you know, context.js, there's my form and now I want to create the back end for that open that file and that now will be used by copilot as part of its context. So you're not able to specifically say, hey, go look at this file, but if you open the file, if you have that open on the tab, then that will help it out and help point it in in the right direction.

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Now for me personally, if, if you're anything like me and I know, I am I, have a propensity to just open up a whole bunch of files. Just keep a whole bunch of files open and I'm. Just kind of doing my thing so I find that naturally, I will have the files open that are related to whatever it is that I'm working on so I think it's relatively rare um I'm not going to say never because I'm sure that I have at one point, but it's relatively rare, where I've ever had to stop and go.

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Oh, let me open up another file and kind of help. Co-Pilot out point it in the right direction, because I just find that as I'm doing my normal development, that I will have the files open that are going to help co-pilot out there. So so the direct answer to the question is there isn't a way to just go? Hey use this, but if you have the file open, that's going to help it out uh with that, but again I.

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Don't want to like Hammer that point home too much, because sometimes when I say hey, you know open up the files and that's going to help co-pilot out. A lot of people will just then get tunnel visioned on that and they'll start to think. Oh, my gosh now I really have to think about all the files that I have open, and things like that and my answer to that is probably not that just through the normal course of your development that you're just going to find that you'll have the right files open.

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You know, like think about how you you do development or think about like how you your phone, that chances are when you use an app and you decide hey I'm, going to close this you're, not just like you know, closing out all the apps on your phone you're. Just you know. Moving on to the next one kind of the same thing here that when you work on a file, uh chances are you're going to uh kind of keep doing your uh your same thing. There, okay, cool cool, let's see um and then Thomas asked.

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The question um seems like a bit of a waste that larger organizations are not able to use Federated learning model or appending to extend local copilot models. Great question. Thank you. Thomas um blue I want I want to go back here. Okay, so I'm back on copilot next I'm, going to scroll down on copilot next and I want right here, uh GitHub copilot for your code base.

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So the question that Thomas asks about being able to train uh GitHub co-pilot on your code base is one of the two or three most common questions that I get asked anytime, that I'm doing a presentation for a business on co-pilot, and this is something that we are looking at implementing that we are trying to build out. So it's something! That's there believe it or not, though this this is something that does become a little bit tricky, that there's a couple of challenges that we will end up facing, the first of which is again.

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This is a large language model and almost sort of like, regardless of how big your code base is. uh The training model that we have is going to be exponentially larger than uh than the amount of code that that you have and in turn it's a large language model, the more that you've got the better. The suggestions are going to wind up being so inherently that generic code base that we have is going to be able to offer better suggestions than training it specific to your code base.

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Now now that being said, where having your code base, be trained can really become helpful, is number one kind of help guide it and point it in a particular direction, but also number two is: if you've got your own custom languages or you've got your own custom Frameworks, then it can help co-pilot get a better understanding for what's going on there, but at the same time, there's also an additional challenge of okay.

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So we're going to use your local code base as well to help Point co-pilot in the right direction, and now there's like some throttling now, there's like some dials to be said of of you know: how much should we favor sort of the generic? If you will copilot versus the co-pilot, that's been trained on on your code base to again try to make sure that we find the best possible suggestions that we can make out there. So it is, it turns out.

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It's a far more challenging of a problem than it might look at at first glance, so it is something that we are investigating. It is something that we are working on, um but right now, I, don't necessarily have any more information um beyond that, but I do want to follow that up. I, don't want to kind of close that out by kind of going back one more time to that context.

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So let's say that you know: we've got: we've got a custom language or our custom Library, rather a custom library that we've built and I need to use that custom Library.

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If I've got two or three files that are already using that Library open those files up, make sure that those files are open and that will then become part of that context. So, as it starts as copilot starts, making those suggestions, it's going to be able to use that context to help guide it through that, so um so yeah. So it's a it's a great question. It turns out that it's a far more challenging of a problem as of right now.

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What you can do again is just keep a couple of files open and that will that will help open it up.

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Yeah, so you know not talking only about trading on local data but more pending the total model, with your local Source, yeah yeah, again like and and I hear, all of that, and and it just it coming relatively tricky, because this is an awful awful lot to try and balance out so right now.

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The way that it's built is it's the files that you have open, the code that you currently have, and that might change over time that you know we're constantly looking for ways to improve the suggestions, ways to improve the model, ways to improve the experience and so over time. That is something that might change, but at least as of right now, that's the way that this is built. That's the way that this is going to work.

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Okay, other questions, I'm loving this. This is great I, don't know if you've noticed, but I I kind of enjoy talking about GitHub Copilot.

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Talk one more sip of coffee here.

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um Thoughts on bias, risks I'm gonna, pass on that question. I'm gonna pass on that question. It's a good question: I'm gonna pass.

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A

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um How would GitHub handle so just to ask a question: how would GitHub handle subscriptions if a user has an individual license and then request a business license from the org uh with the individual subscription um and or privacy settings get canceled out? uh Yes, this is a fantastic question. This is something that comes up quite frequently is um you know, developer goes off, they sign up for get them call pilot on their own, and then their organization goes hey. We really like it. I'm called pilot. Let's get everybody signed up for business.

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The business subscription will override the individual. So if you are, if you're using uh the individuals GitHub accounts or the individual's um handle, then the copilot for business setting will override their individual settings. So that's a great question, that's something that comes up quite frequently.

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um So let me ask the question: what's the most exciting product coming uh with copilot X? In your opinion, oh gosh, um it's almost like asking me to pick my favorite child, even though I don't have any kids, um probably co-pilot chat, probably co-pilot chat, um I I. Think all of them have a little bit to offer. um I do want to talk about the other two here in in a minute here, but um probably.

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Co-Pilot chat with honestly this copilot for for pull request is a really close second, which I'll talk about in a second here, but but yeah. um How about I? Ask the question um our waiting list acceptances for everyone as profile being studied uh prior to approval I.

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I don't know what the official answer is. My understanding and I could be wrong on this. So please bear that in mind. My understanding is um right now uh copilot for individual.

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uh If you sign up for the waiting list, it is in order, so I do not believe that it's based on the profile uh I believe that it is based on order.

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I could be wrong on that, but what I do know for right now is that copilot for individual is being favored a little bit over uh co-pilot for business for a couple of different reasons, but the one part that I can say with 100 certainty is that if you are already signed up for co-pilot that that is going to get you priority in the waiting list, so keep that in mind. uh Yeah, okay, cool.

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um Let's talk about um uh the other uh two features here with um uh with copilot uh copilot X, so first up is call pilot for pull requests.

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Copilot for pull requests is going to do two big things so number one. Is it's going to be able to detect on a pull request? Whether or not you have unit tests, and if you don't have unit tests, then it will be able to create another pull request that suggests unit tests for the one that you created, which I really appreciate.

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The second is, it can also then suggest and generate both a title and a summary for you of that pull request.

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One of my biggest peeves when it comes to pull requests is a lack of information that you might get a generic title and then like nothing in the description and a lot of times. That title is fixes bug.

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Okay, that's great. That's really helpful, I'm glad that it fixes a bug kind of hope that it would fix a bug, uh but what bug? How did it fix it? How did you detect the bug? How do you, how do you? How are you demonstrating that it now works and that information quite frequently doesn't find its way into the description and do not get me wrong? I get it there isn't a developer in the world that hasn't fought with a bug for hours and hours and hours finally found the fix they got all excited about.

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Finally, effects don't get me wrong, they implement the fix they go to make the pr and now they're, just tired and now they're, just exhausted and now their brain is just not thinking straight, and so they really just want to get that PR made. They just want to get through that process. They want to start running whatever automation, it is. That needs to be run and then that's it, and so that's all they're really focused on, and so now they don't wind up putting in a good description, I get it that happens.

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That's where copilot for pull request comes into play. Is it's going to then make those types of suggestions for you, which is great?

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The other big one is copilot for docs, and this is probably the the one that's I, think least talked about, but one of the most exciting to me I was a technical trainer for many many many many many years, and so, as a result, I have a lot of experience in trying to help individuals learn new skills, learn new languages, learn new Frameworks Etc, and one of the challenges that I always have with documentation is that documentation assumes a certain knowledge level.

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So, let's say, for example, that I've got a a new developer and they know HTML, CSS and JavaScript, and now I want to turn them loose on react and I'm, not picking on react. I could have picked any JavaScript framework. That I just happened to pick react so I'm, not picking on react there.

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If I go into the react docs the react docs are going to assume that I know quite a bit, and quite honestly, what's going to wind up happening? Is I really start to get into those docs? Is that they're going to assume that I know quite a bit about react as I'm digging in with those docs, and this is something that unfortunately, just happens quite quite often inside of documentation?

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Is that a lot of times the people that are writing documentation and I and again, like I'm, not trying to in any way shape or form talk bad about anybody? um But one of the things that just happens is part of human nature. Is that the people who are writing docs?

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Are writing it based on their own experience, they're, writing it from their Viewpoint and so in turn the target audience that they have is themselves and they wind up then sort of assuming a a level of knowledge that not everybody is going to have, and so it makes it very hard for a novice developer to get in and get started on, fill in framework here by going through the documentation. This is where co-pilot for docs is really going to shine, that what you're going to be able to do is specify hey.

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This is the level of developer I have so I could be like an advanced developer, but maybe it's my first time ever using react like maybe I'm an angular developer, so I know angular, but I don't know react at all, then I could go ahead and I could scroll that down and say: hey I, don't know this really well and then over here on the response, but I could say you know you can be a little bit Advanced when you're talking back to me so like I, don't need things explained very low level like you can talk to me here, but I just don't know really anything about react, so I can adjust those sliders here and then I can ask my query and then get a response back based on the profile that I've built right here, and so now it's going to help make that documentation that much more consumable for me as a developer as an experienced developer as a novice developer and what I also really like, and unfortunately I don't have a demo of this.

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But what I, also really like about copilot for docs is the fact that it will also give me a link to where it found that information. So if I go in and I say hey, how do I create a component or how do I, you know, do something with um oh, why could I not think of.

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Oh relax, that was, that was what I was trying to think of my brain just stopped there for a second like how do I do something with uh you know, react redox or something like that.

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I could go in and I could ask that question and now I'm going to get back a response, I'm going to get back a response, that's going to be targeted for the for the style of developer, that I've specified here and then in turn, I'm going to be able to get links back to the documentation, so I can very quickly see where that information came from I dig deeper into it if I want to and I think. Most importantly is, then it's a great way for me to confirm that.

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Yes, this is in fact the right information that this is in fact, the information that I was looking for. So this is probably the one that's that's slept on most often um and it's one of my absolute favorites and that is uh copilot for docs. So those are the other two components that are part of copilot X um and unfortunately, I don't have demos of of those two, but I I did at least want to uh to highlight those so questions on those and run Applause again for coffee.

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Okay, let's see I want to I want to go back to the slide here there we go okay.

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So, based on sort of the the hush side on the tires assume that's hush, silence, say: hey everything is fantastic: oh uh q, a tab um I've just been focused in on the public.

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um I just saw this q a tab. um Let me kind of go back through this real quick as a GitHub team faced any challenges, development of uh the CLI thus far, um none that I know of or at least none. That's that's been been shared with me. um I hadn't asked that question Thomas. Has the question um I answered that question already and then Marius asked the question: is there going to be a publicly documented, IP uh API rather for building Integrations into Ides? uh That's a great question.

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uh None that I have heard of so as far as I know, there's no plans for that. uh That might change, but at least as of right now, there's no plans uh for that. So yeah Thomas need to go feed the family go enjoy that thanks for the introduce. Thank you for thank you for tuning in cool cool.

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All right, I, want to close with this, uh which is uh copilytics like I mentioned, is a a set of Explorations uh into different areas, where we believe that generative AI can help support developers, and so this is going to be copilot chat, CLI, PRS, docs Etc. Now everything that is under this copilot X umbrella right now, this is part of GitHub next get up. Next is our playground, so anything that's inside of GitHub.

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Next, uh it might get released, it might not be released uh and even if it is released, it might be a single product. It might be rolled into something else. uh Etc uh and there's also as of right now, no roadmap so kind of keep all of that in mind as we're talking about GitHub copilot X.

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If you do want to get signed up for the wait lists, you can check out that little link uh down at the very bottom, um so uh GH, dot, IO, slash, copilot X, go check that out and go sign up.

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The other very big thing that I'm going to strongly recommend that everybody do is go check out, co-pilot for business uh and I'm, suggesting this for two reasons, partly a because if you are already a subscriber for copilot that is going to get you priority on the waitlist, but also number two is something that way you can start to see what it is that co-pilot can do for you that um you know, since the release of copilot X like yes, this is very much like the the the the cool new kid in school I get it and I get why you know it's getting all of the attention, but you know we also need to keep in mind that we've got this really really cool um product back here called GitHub co-pilot.

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That will help support your developers as they're writing code right there inside of their IDE. So don't forget about core GitHub co-pilot, like like I, said at the top here: I have not seen a product. That's had a larger impact on my productivity than GitHub co-pilot. So do remember that that's there definitely go check that out as well, so yeah.

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uh If there are any other questions, please by all means feel free to uh to ask in the comments below uh you can always reach out to us startups at github.com, uh we'll answer your questions there and then keep an eye on the space.

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We are hosting uh these types of monthly talks and if there's a particular topic that you would like to see us cover, please by all means ask that that's how we're going to know uh you know what it is that you want to hear, and then we can make sure that we uh can help uh help you get up and running so yeah. So with that I want to thank everybody for tuning in enjoy. The rest of your uh Tuesday today is Tuesday.

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uh Yesterday was a holiday, so my brain said it was Monday for a second there, so enjoy the rest of your Tuesday. Thank you to everybody for tuning in bye.