Name: GitHub for Startups 101
Uploaded: 2025-02-27T05:31:05.872Z
Duration: 43 min 44 s
Description: GitHub for Startups 101

Transcript for "GitHub for Startups 101": Good morning, folks. This is Rahul. I am startup program manager with GitHub for Startups APAC. First of all, thank you very much for dialing in today, for the GitHub for Startups one zero one session. Our topic for today is supercharge your DevOps with AI and security. Along with me, I have Faten, who's the senior manager for field services at GitHub based out of Sydney. We also have Lakshya joining in, from India. Before we start, can you just type in where you are joining in from? It would be great to know where the audience is from. So I'll start over. I'll start here with mine. Lovely. We have someone from Hyderabad. Nice. Well, it's 10AM on a Thursday morning. Thank you guys for joining in. You can also mention what companies you're from. If you're if you are working for a start up, we'd love to know more about what you're doing, in the chat session. If you can go to the next slide, I'll just brief you quickly about what GitHub for Startups program is. GitHub for Startups program is relatively new. We've been there for three years. We have over 30,000 startups across 45 countries in the program. We support startups for two year program, giving them access to GitHub enterprise and, getting giving them access to GitHub advanced security. In case if you are not part of the program, please use scan this QR code, and mention the, the referral code as GFS101APAC so that we can get you onto the program. With this, I will pass on this, conversation to Faten and Lakshya to walk you through to the agenda and the session today. Thank you, Rahul. Thanks for the introduction, and thanks everyone for joining us. We are very excited to be here today with you. Let's dive into the agenda for today. So our session is about supercharging your DevOps with AI and security, similar to launching Arrowkit, where we will start by exploring the power of GitHub platform and how it can enhance your development workflow. Then we will focus on security securing your code with GitHub Advanced Security. And finally, we'll delve into the AI capabilities of GitHub Copilot, which is the main superpower here. So we'll see how AI can supercharge your developer's experience. As you can see, so the session is structured to take you from understanding the platform to securing the code, and then I will be passing it to Lakshya so he can, show us how we can leverage AI to boost the productivity. Let's get started. Before we get started, we also have a small surprise for you. So we will have a game during the session today where some of you might win some prizes. During the session, we will be asking three questions. And the first one to respond with the right answer in the chat window will win a GitHub voucher from our shop where you can go and get some nice swag. Okay. Let's talk about the first one. And before we talk about the GitHub platform, we wanna talk a little bit about the DevOps challenges. And we know that companies across the globe, from startups to large enterprises, they all rely on DevOps to fuel their growth and drive innovation. However, DevOps can be sometimes a bit a complex landscape. And we're all aware of lots of these different challenges. I'm not gonna go through these challenges, but just to name few, we can talk about the loss of productivity. We can talk about silos. We can talk about where, for example, developers are using different tools, and they have to move from one tool to another. We can also talk about the security risk as depending on the size of your, startup. Some of you might have, developers. Some of you might have also security professional. Usually, the ratio is, like, one security professional is aligned to support the code that gets generated by, like, a hundred developers. It's a very big responsibility, and that's one of them. So the security risk is another one. One of the main pain point is often overlooked, which is, with all of these issues, we can name heaps of them, that will create a very poor developer experience. And at GitHub, we believe that experience makes a big difference. A strong focus on the optimal experience for the developer will provide them with more time and energy, for the team so they can focus on creating solution for the for the problems that you're putting in front of them, leading more innovation and more. So that will lead to faster shifts, and all of that will combined will % go and benefit your company. Now how can we help to unlock these benefits? First of all, by offering this single integrated enterprise ready platform with industry best collaborative tools, security features wrapped in every single step of the development process, and not forgetting the superpower. So all of that is powered by AI, supercharging every interaction so your developers can move quickly, efficiently, and confidently. Here we go. This is our AI powered developer platform. This is the GitHub enterprise platform, AI powered developer platform. So it consists of compromise of four main layers, collaboration, productivity, security, scale, and every single layer is powered by AI. You're gonna hear me saying that over and over and over during this session. So, you can see on top of that, we've got the integration where we've got built in integration and API. So GitHub enterprise is ready to meet your business where you are. Okay. Let's move now that we talked about the GitHub enterprise. What are the what's the problem that we're trying to solve here? And these are the different layers. Let's go through them one by one. The first one is collaboration. And when it comes to collaboration, GitHub, GitHub enterprise and GitHub in general is focused on collaboration at its core. GitHub is based like, you know, the home of the open source. So we take lots of the lessons from the open source community and create an inner source inner source perspective where you can take these lessons from developing open source software and applying them to the way your companies develop software internally. So in other words, it's like apply application of these open source principles within your organization. Inner source is very key and is in the at the core of, GitHub Enterprise. So that will help provide your developers with the right tools to allow collaboration, and that will happen, effortlessly. They don't have to make a big effort because all of that available for them within the platform. We've got, like, GitHub Project, GitHub Issues, repos, pull requests. All of that will help the developers, the project managers, anyone involved in the development life cycle. Second one is productivity. And I know that when it comes to productivity, especially for, startups, GitHub Enterprise has been instrumental in helping startups to accelerate their development and bring new product to market faster. And this is the one of the main goals for you is, you don't have to reinvent the wheel in lots of places where you can use some of the existing code. You can prioritize reusing instead of inventing. You don't have to, go and create anything from scratch. You will have somewhere where you can start your developers will be able to start building these applications. That's the whole idea, similar to what we were talking before with the inner source and open source. On top of that, we've got also, less tools to manage, and you wanna focus more on the development, on what's really matter for you. All of that, we talked about collaboration. We want teams to collaborate. We want to make sure that we are being productive and prod fast, but security has to be in mind all the time. We want our developer to collaborate, to be more productive. At the same time, we wanna make sure that they're doing it in a secure way. So with GitHub Enterprise, we provide you with a secure compliant platform without having to sacrifice, like, speed. And that's why we say GitHub Enterprise is secured by design here. So we've got lots of different built in, security features, especially when it comes, when it comes, about governance and policies and all of that at the enterprise level for you. Next is scale. As a startup, you know that GitHub is a reliable platform. So as your business grow, potentially, you might expand to thousands of developer in the future. You wanna make sure that you have the peace of mind knowing that GitHub will support your needs at every single step along the way. GitHub is the largest developer community. So we've got GitHub.com, the hundred million hundred million developers on GitHub.com. That means that we are ready to scale with your business. So we this is the unique advantage that we have at GitHub as we have got this GitHub place where you've got the open source and do scaling for all of the hundred million of developers on GitHub.com. We've done it before. We can do it with your business as well within within your GitHub enterprise umbrella. Okay. Now time for our first game. We spoke about GitHub platform and our first part of this session. Let's go to the first game. Now, I'm gonna put the question. It's gonna be the first one to answer the right, the give the right answer in the chat window. The question is, what is GitHub? A, complete AI powered plat developer platform. B, version control system only. CICD product only. And your code monkey playground. So I think we've got our winner. A is the right answer. That's correct. And I think the the first one to put it is, Subramanian, if I'm saying it right. If I'm saying it wrong, I'm sorry. But that says the winner for today. We will get in touch with you post the session so to make sure that we will send you your evouchers from GitHub. Thank you for playing with us. Okay. Now we let's, shift gears and talk about shifting security left. So we spoke about the platform, the benefit that you can get from the GitHub and sorry. Okay. Maybe that was my mistake. I'll continue. If there's anything, please put I just wanna mention at any time, please put your questions in the q and a section. So between Lakshya and I, we will all always keep an eye on the q and a and answer the questions. So we'll be talking about GitHub Advanced Security. So GitHub Advanced Security, it's the additional add on on top of GitHub Enterprise. And here, it's, consists of three main, pillars. The first one is from SCA side from, software composition analysis. So this is how we can scan for any libraries for any dependencies that your, your code is using. Sorry. Your is using any loggers depending on that. This is using dependable to make sure that you are not using any version of a third party log in that's vulnerable. The second one is the SaaS side where we are securing the custom code, the code that your developer are writing in house to make sure that they're not introducing any security vulnerability, and we will get make sure that these will get picked before they make it to production. So it's integrated within the developer workflow. It's built in. It's powered by CodeQL. So CodeQL is our static code analysis tool. So it's a semantic code analysis engine. And the the the thing about it is that it will help get higher true positive rate than any traditional, code scanning tool. And we will also talk a little bit later about the AI powered remediation here with GitHub Autofix. The third one is secret scanning, where we wanna make sure that you are not you don't have any secrets in the code. And then the developers sometimes, by mistake, they will go and add any token, any secrets, any password into the code. So this will make sure that there's no secrets secret leaked into your, your repos. Now these are the three main pillars, and we've got the security overview. So the security overview will give your security professional a place where they can have a single page to view anything related to security within your GitHub enterprise, account. So that means that anything coming any alerts coming from secret scanning, from the code scanning, from, Dependabot, they will all be in one single view for the, security professionals to go through with lots of insights to help them to with the triaging and getting that vision. And the one at the bottom right hand side, to make sure that it's extensible, we mentioned where we don't want the developers to go and switch between different tools. So even if, let's say, for example, for, container scanning, you're using a different tool, you can also get these results integrated into GitHub Advanced Security, and you can view the results from one single place within your GitHub, GitHub and GitHub, Advanced Security. Okay. So this is the high level of GitHub Advanced Security and what's available. The first one that we mentioned is Dependabot. This is for the supply chain. So the idea here is that, if you're using any library, you wanna make sure that this library is not available. And if it is, it will go and, notify you that you will need to upgrade this library to a newer version that's not available. And the second one, the dependency review, this is where we spoke about shifting security left, where at the pull request, at the PR level, this is where we are telling the developer that if you're gonna go ahead and, merge this code change, merge this pull request, it's gonna introduce it's it's using a library that's vulnerable. So we are identifying that and notifying the developer at the PR level. That's from the SCA side. The second one is with the secret scanning. So secret scanning, if anyone on github.com public repos, if you try to to commit any secret, it will get flagged straight away. And what happens is that we've got partnership with lots of the different, secret and token providers like AWS, Google, Atlassian, all of them, and hundreds of them. And what we do is we get that flagged. It gets remediated straight away. So this is if you try to do that to a publicly. If you wanna do that, if you try to commit a secret to a private one, it will also get picked up straight away. The only difference is that you have more authority on what to do with this, with this, notification as, like, you're using it. It's not gonna go and get remediated straight away. It you will have the option to choose what you wanna do with this one. You've got all of the different, the secret patterns that we have out of the box, and you can also create your own custom secret pattern. So it should be like a regex specific format that you are using within an internal application, and you can specify that in, for secret scanning as well. The big, plus the big advantage that we've got here is the push protection. So this is push protection helps customers avoid the cost and complexity of having to remediate a secret. And we all know that it can be very, very expensive. So even when the developer is still at the commit level, they can get flagged, and that way they will be aware of it before it gets into the code. So this is the prevention that we're doing with the push product protection. So secrets we spoke about Dependabot. We spoke about secret scanning. And the third one, which is the code scanning. And the big highlight for us with code scanning is found means fix. And this is a big one and big plus or benefit from GitHub Advanced Security when it comes to code scanning. And, via what we call GitHub Copilot Autofix. It's it's amazing. And you can see here from some of the figures where people even from the beginning when it was still not during the beta, they found that fixing things three times faster, seven times faster when fixing cross site scripting vulnerabilities, and 12 times faster fixing SQL injection vulnerabilities. This is amazing. So if you wanna put that, let's say let's just take, into context. Let's just take an example, cross site scripting vulnerability, for example. And then if you are taking twenty two minutes, it's taking them to get it fixed compared to, three hours, almost three hours previously when that was done manually. So these are amazing benefit. Now that we've seen it here, I would like to jump into a quick demo for advanced security. The first one, because we're still talking about autofix, is to show you the autofix at the PR level. So this is a pull request where I'm making, so that's Lakshya's pull request. He's making some changes. And what you can see here, he's making some changes to the call. And before he even, go ahead and, submit that, what you can see here that you've got the Copilot auto fix with code scanning already picked up that if you were gonna go ahead, it's gonna go and, introduce a vulnerability, and it's giving us all of the details on how to fix it. So Autofix is giving us the details on how to fix this specific vulnerability. It's not just going and telling us about it. So this is the, first one with the auto fix, and it will help the developer a lot because when they lots of different, scanning tools will give them thousand different security vulnerabilities. And the problem is having to triage them to go through all of that will be the last thing that the developer wants to do. And another thing is that if they get, if they get pinged about security vulnerability in a code that they wrote, I'm not gonna say a couple of months ago, a couple of weeks ago, they might also take a long time to go back into the flow to see what I was doing there, try to get a better understanding of the code so they can fix it. So this is all done and helping the developer getting things fixed, found mean fixed way earlier at the earlier stage. Same concept. We have, here, I'm not I'm still committing my code. And what I did here, I just went and added a AWS secret scanner. So secret scan secret access key. So I'm trying to go and commit this change to my branch. I didn't even it's a feature branch. So I'm still committing my code to the feature branch, and you can see the secret scanning push protection already picked it up at this stage before I even the developer commit the code. So it's getting shifting security left to where the developer is working, where they are writing the code, and where they are working. So here you have the they will have the option to say it's a false positive. I'll fix the data. I'll use it. They will have to make their decision. The next one I wanted to show you so we saw the code, code scanning with the Copilot Autofix. We saw the secret scanning push production where it's getting picked at the commit level. And this is the same for the, dependable. So let's say the same way that dependency will give them all the details, all the different libraries, the vulnerable ones that they are using. If I'm going and it's a very simple super simple one, but what I'm doing here is I'm decreasing the number of one of the library libraries that I'm using from eight point five point one to a very old one, one point zero point zero. And you can see here that dependency review is also picking it up at the PR level before I go and push this enable code. Last I know that we're running out of time. Last one I can wanna show you is the security overview. This is the one for the, some of your cofounders where they wanna see what does my enterprise look like from a security perspective. They will be able to get this is a demo environment, so you can see thousands of alerts here. But they will get an idea of the age of some of the alerts that they're getting, how many have been reopened, how many secrets have been bypassed. And at the left hand side, they can get into each one of them from the dependable side, all of the different libraries that we are using, which ones they can filter by the severity to see which one are the ones that they wanna go and focus on. Same concept for the code scanning one. So they can go through these ones with and the secret scanning ones. I'm I'm gonna stop here. If anyone is interested to see more from the GitHub Advanced Security side, we will be also sharing some resources at the end. Now let's go back into our game, our second game for today. And second question, the question is, what are the main three pillars of GitHub Advanced Security? Code scanning, SAST, secret scanning, SCA, software composition analysis will depend about all all of the above. I I'm I'm not sure who which one was the first one, but I can see lots of the right answer. The the right answer wrong, wrong, and the right answer is d. I think Sunita Patel is our first second winner for today. We will get in touch as well after the session. I'm gonna yes. That's, Venkata. I Sunita, that is the answer for the first question. So she answered it direct. One from three three forty one. Yes. Yes. You're right. You're right. Okay. I'll let you I'll let you guys check with the chat which one was the second one. Yeah. You're right. So oh, okay. We gave it a thumbs up. I can see that now. Right? Perfect. Okay. Cool. I'm gonna stop sharing, and I'm gonna pass it to Laksh to go through the third, part of our session, which is GitHub, Copilot. Over to you, Laksh. Thank you, Faten. Hey, everyone. Let us get started. Alright. So so far, we've talked about, the GitHub enterprise platform. We've talked about GitHub advanced security. So I hope you have some idea around how GitHub helps you across the software development life cycle and how you can bring application security at the developer's level itself. Now we're gonna move into GitHub Copilot, which is, if you remember from Faten's earlier slide, we talk about how every step of the way, AI powered is the term that we use across GitHub. Right? And Copilot is what actually brings that AI power. And today, we're gonna cover what Copilot does. We'll talk about we'll look at a quick demo as well, and, hopefully, you would all, try it out right after the session too. So what is GitHub Copilot, and why should a developer use it? The way we talk about Copilot is that it is an extension of you as a developer where once you've identified your intent, once you've identified your objective, you can have Copilot convert that intent into code. So Copilot essentially writes code for you, whether that's you writing comments on your scripts and converting that into code, whether that's auto filling repetitive code or blanket removing or log statements within your scripts or even showing alternatives. So whether that's refactoring code to turn it from something that is legacy to something that is a bit more current or even optimizing your code so that you can optimize for time complexity, space complexity. These are all things that you can delegate to GitHub Copilot so that you, as a developer, can focus on strategic engineering tasks so that you can focus on design, on architecture, and let Copilot do all of the manual tasks for you. There are many different ways to interact with GitHub, and we look at some of that when we get into a demo as well. But Copilot chat is a very effective way where everything about a ChatGPT style interaction comes to you within the editor. So whether that's you asking questions around, you know, best practices when you're writing code or best practices for a particular language or even just understanding gaps in your knowledge, which every developer really has to do. Where earlier you had to probably open Google and open a hundred different tabs and keep searching to figure out what the answer is, you now get all of that within your editor itself, which means you don't have to context switch. You don't have to break out of your zone, and you can continue to be extremely productive as you're writing code. You also have GitHub on GitHub. So whether that's your CICD, whether that's, application security, or even something as part of your pull request, you can ask Copilot questions every step of the way. So if you want to understand more about a particular repository or you want Copilot to give you a code review for a pull request that you just raised, you can ask Copilot all of these questions. And in many cases, within a single button click, you'll start getting a lot of important insights from Copilot, which is based on accurate context and super, charged for the developers' productivity. And so out of everything that I've covered, our aim here is very straightforward. We want developers to be more productive and spend more time on designing, brainstorming, and iterating over innovative solutions and less time on repetitive tasks and manual tasks such as debugging or writing unit tests. So what you have now is a highly trained, experienced programmer as an extension of you every single day across your workflow and within the editor itself. Now I'm done with the slides. We'll get into a demo straightaway, and I'll show you what GitHub Copilot can do and how you can make it part of your everyday workflow. Alright. So what you should be able to see now is my editor. The most first most important thing whenever you're working with GitHub Copilot or any LLM for that matter is context. With GitHub GitHub Copilot, because it is part of your editor and your everyday workflow, you can pick context in multiple ways from your code and ask GitHub Copilot questions. If I have my cursor on a specific line of code, a few lines above or a few lines below that can be used as context. If I highlight a specific part of my code, that can then be used as context by GitHub Copilot as well. So you can see on the bottom here that lines 37 to 44 are being looked at as context. So whenever I ask questions, GitHub Copilot will use this as a background to understand my intent and give me suggestions. If I have multiple tabs open and I'm working across multiple files as most developers usually do, that could also be used as context, and GitHub Copilot can cross refer between files. But when I now open GitHub Copilot chat, which is what you see in this window right here, you have greater control over how GitHub Copilot picks up context. One of the ways to do that is to use something known as the workspace agent. Often as developers, you need larger, wider project wide understanding of the questions that you're asking. What the workspace agent does is that it gives Copilot access to your entire file system to be picked up as context. Doesn't mean that every single file will now be used as context, but it does mean that based on your prompt, Copilot will identify what files are relevant, use that as a background, look at your question, and then give you a right selection. So let's look at an example of that. I'm gonna say something like I am a new developer. Help me understand this project. And give me a summary of all files. What you will see now is that because Copilot has access to my file system, it will look at references which are relevant from my question's point of view and start giving me a suggestion which I can then use. In this case, you can see I have seven different references, and you get a very granular view into what Copilot is using as context. So if, let's say, you're not satisfied with the suggestion, you can improve upon your prompt. You can be more specific or define your outcome a little bit better, and you'll see a different set of references or context being used. So in this case, you'll see Copilot gives me a summary of my project. It tells me what each file is doing and what the summary of some key files in this project are. This is extremely important because as a best practice, we generally say that you wanna follow a funnel line of questioning. Start with a general question and iterate into more specific questions as you move along. Let's look at an example of that as well. So I'm gonna come back to my code, and I will highlight a specific method. So let's look at the get books by title method. And because I've highlighted it, I now do not need to define specific context, and I can just ask Copilot, identify any security vulnerabilities in this code. So, again, I didn't have to specify what this code really means, but Copilot picked up hundred and six to one forty five as lines that I'm referencing. And now you'll see that Copilot identifies that there is SQL injection in this code base, and it gives me recommendations around using prepared statements. So as you're writing code, as you're implementing new features, as you're generating new new code, you can work with Copilot every step of the way to ensure that you can maintain your code quality, to ensure that you can, push, secure code to production, and just make sure that your code is up to the mark of your organizational standards as well. So in this case, we get a suggested fix, which is to use prepared statements. Copilot gives you an entire code block that you can now add, within your code base, and you're good to go. Of course, as a developer, you are the last point of authority, so you want to make sure that you've reviewed this code before it becomes a part of production. Alright. Now let's take a greater example. Right? And for developers, you're rarely ever working on a single file. You will almost always be working across multiple files, adding new methods, removing new old methods, or adding new dependencies all the way. GitHub Copilot helps you with that as well. So what I'm on right now is multifile edit that helps you pick up context from multiple files, generate code in multiple files, and do this all parallelly with a single prompt. And we look at an example of that in just a bit. So I've added two files here to my working set, and I'm gonna say I'm gonna give it a very simple prompt. I'm going to say generate unit tests for these files. And because I like Claude better from a unit test point of view, I'll select Claude and send enter. And while it's generating code, by the way, when you're using GitHub GitHub Copilot, you have the ability to select through multiple models and use the one which best best fits your various use cases, whether that's using the most recently trained models for near live release or more reasoning supporting models for complex business logic related use cases. Alright. So in this case, you'll see now GitHub Copilot is starting to generate code, but I wanna bring your attention to my file system again. Not only did GitHub Copilot add new files to my working set where it's now writing these tests, It also identified specific parts of my directory where these new files need to be created. So GitHub Copilot understood that inside the test directory is where all of my unit tests should go, and it automatically starts creating, new files there, database implementation test or Java, book service test or Java. And within that, I have all of my, new code being generated. Right? So these are all of the unit test that Copilot has generated for me. Now I can, of course, review all of this, make sure that this is in line with what I want to achieve, and I always have the option to accept or discard these suggestions. So, again, as a developer, you are the final point of authority. You get to decide what code becomes a part of your production environment. And, of course, if you wanna add new tests, if you wanna iterate over your prompt, you can do that here again and say something very specific like, write all unit tests for identifying security vulnerabilities or look into a specific mock and make sure that it aligns it aligns with the rest of your project. Alright. So I'm gonna discard this for now. And we've looked at a few things so far. Right? We've looked at asking general questions. We've looked at generating new code. We've also looked at identifying security vulnerabilities or making changes to files across your code base. Let's say you as a developer are now ready to create a pull request and you're good to go. Well, Copilot can help you also do an initial code review just to make sure that the velocity of your pull requests are faster just to make sure that the code that you're finally sending out is of a higher quality. It's very straightforward. I'm simply going to highlight all of my code. I'll right click and ask Copilot to review and comment the code changes that I've made. And what you'll see now is a step by step review that Copilot is going to give to all of my code in this file. It will look at what needs to be improved from a code quality point of view. And, of course, these changes could be specific to, they could be specific to a language. They could be specific to a framework that you're using. But, nevertheless, you'll get great insights. So here you see an example where it says that this should not be a private static final method. Just use private static instead, and you'll even see Copilot, suggesting the actual changes that you need to go need to make. So you can either apply and go next where this will then become a part of your code base, or you can also discard and go next to look at the next suggestion. So, again, what this does is across the board, across your developer teams, it makes sure that you have a faster velocity in creating new features, testing those features, reviewing those features as well before you raise a pull request. And so where, otherwise, your pull request would maybe get stuck for a week, two weeks, or more, here, you'll have a pull request that's ready to go, high quality code which is ready to push into production as well, and, ultimately, with something that's extremely important for start up, which is a faster feedback loop with your customers because your go to market has now been sped up as well. So this is a feature that is available to everybody right now on Versus Code. Highly recommended that you try it out and make it part of your everyday workflow. Now finally, I wanna dive into one more feature, which is how you have access to GitHub GitHub Copilot on github.com. So let's say, again, I, as a developer, made all of the changes, generated new code, did an initial review, and raised a PR. So I'm currently on github.com. I've raised a new PR, which is adding a new method to my code base. I can now use GitHub Copilot every step of the way here as well. So let's take a quick example of that. In my PR summary, where otherwise developers would write maybe a single line and be happy with it and it just simply wouldn't be enough for a reviewer to understand what changes have been made, you can now delegate this task to GitHub Copilot as well. So I can simply ask GitHub Copilot to generate an outline for this PR. And what it will do now is walk through the changes that I've made and give me a complete summary of, improvements or changes to this particular code base. You have references to specific files that have changed as well as a small summary of what that change really is. If I scroll down, you can also use GitHub Copilot to do a code review of the changes that you've made. Right? So in this case, I have a PR overview where GitHub Copilot gives me a summary. As a reviewer, all of this information is extremely important for me because this is key context as I review this code, these changes and make sure that little problems don't slip through, you know, my review. So I get a summary of what reviews have been made. I get specific files and what changes have been made to those files. And then high confidence suggestions from Copilot on what reviews are relevant here and what can be improved in this particular PR. I wanna emphasize that these are all high confidence suggestions. So Copilot will not review or will not give suggestions for something that may not be accurate. We wanna make sure that their developers have the best possible experience when it comes to reviewing their PRs, when it comes to using Copilot on a day to day basis. So here you'll see an example of Copilot telling me that there is a small typo, and issue it by formatting and that I can change this, as well as identifying something major, which in this case, if you recall, we saw this earlier as well, a SQL injection vulnerability in my code and Copilot again leverages prepared statements some as something that I can use. Now for a developer, it's extremely simple. You can simply click on commit suggestion. You add a small comment, and you commit this change to create an entirely new PR, which will go through all of your checks again. It will even mention that it contains changes made by AI, and you now have this loop of using AI across the software development life cycle to make sure that you have a faster execution time when it comes to writing code, testing code, ensuring that it is secure, ensuring that your code quality requirements and standards are met, and finally merging that code into production so that your developers can, so that your customers can try out all of your new features. Alright. So I'm gonna take a pause here. I think this pretty much covers my demo. It is now time for us to dive into our quiz, the third quiz of the day, which is, out of everything that you've seen, what tasks can you delegate to GitHub GitHub Copilot? Can you use GitHub Copilot to generate your tests, document code, do code reviews, or all of the above? Alright. So I think we already have answers. I think Vishal is the, winner there. Awesome. Congratulations, Vishal, on winning. And I will now pass this on to Rahul to maybe take off from here. Thanks, Lakshya and Faten. Thank you folks, for spending these forty five minutes with us. I hope you've learned a lot more about the platform, the capabilities of GitHub Copilot, and how it can help you with your developer productivity. If you are not part of the program, please scan this QR code and use the reference code GFS101APAC. This will give you access to two years of access to the program. We support up to early stage companies up to series b, and thank you for your time today. Thank you, Faten and Lakshya, once again. In case if we have any questions, please put them in the chat. We can answer them. Else, we can call it. Perfect. Thank you, Rahul. Thanks everyone for joining us. Thank you, folks. Have a nice day ahead.