WEBVTT

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Hi everyone and a very warm welcome to this course on codeex.

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Really excited to have you here today and hope to learn a lot of things together.

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We will learn how to use codeex for enterprise how to use codeex for enterprise development.

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We will see how it works as a coding assistant and its many functions in different situations.

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Codeex is a tool made by openai.

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You might know their famous tool called chat GPT.

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OpenAI is the main company behind chat GPT and they handle all the AI generation and work.

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First I will show you the OpenAI website.

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On their website they say their research will lead to artificial general intelligence which is a system that can solve human problems.

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In the product section you can see tools like chat GPT codeex atlas and prism.

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Chat GPT is a very large tool that includes images, deep research and GPTs, codecs, multiple applications and libraries.

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If we talk about apps, we have multiple apps connection.

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You can connect it with popular apps like Adobe, Air Table, Booking.com, Canva, Spotify and more.

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Now let us look at OpenAI codeex.

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Codeex is an AI software engineering agent.

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It helps developers write, understand, change, test, and ship code easily.

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It is not just a simple chatbot that only answers questions.

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It works directly with your project files and helps with the whole repository structure and can make the changes, run commands, and assists with development cycles.

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It gives developers real engineering results.

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Codeex is also inside chat GPT, so you can use it directly.

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There is a specific app for codeex and you can download it for Windows.

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We will see how codeex makes real engineering work faster from planning and building the features to fixing and releases and cross-checking.

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There is also a command line interface or CLI on GitHub for codecs.

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CLI means command line interface.

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It is a textbased interface used to talk to software and computers.

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Instead of clicking buttons with a mouse on visual icons, you type text commands and the textbased user interface used to interact with the software operating system and on your keyboard instead of using a mouse to click on visual items

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and press enter to make them work.

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We will learn how to use this CLI.

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Codeex helps what a developer wants to do and turns it into engineering output.

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You can describe a bug or a new feature, test environment, documentation, task in natural language.

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Codeex can analyze the database, identifying files, propose changes and generate limitation steps.

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This makes it useful not only for the writer but also for navigating unfamiliar systemd.

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Here we have codeex discussion.

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In this course, we will talk about daily development, prompting, making agents and using codecs for a long time.

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We will cover all of these important topics will cover all of these important topics together.

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So moving on, the next critical discussion is primarily related to exactly how we are going to securely install codeex on our machine.

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first well before actually installing it anywhere else.

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We will practically use the standard command line interface to get things started.

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But right before that specific step, we can smoothly download the dedicated version specifically meant for Windows operating systems.

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Now I already have the necessary codeex installer fully ready to go here.

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I simply open up the main system downloads folder right now.

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Then I firmly run the executable installer directly as a system administrator.

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The core software immediately starts to install itself smoothly.

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Simultaneously, the Microsoft Store seamlessly begins its essential download seamlessly begins its essential download process.

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Finally, when the entire download completely finishes, codeex will successfully run.

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Interestingly, we can certainly also manage to install it safely across multiple different computer systems.

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As we smoothly scroll further down the main page, you will clearly see three distinct setup options presented.

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The very first one is the standard standalone app.

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If we really want to use a code editor, we can install it directly within our preferred IDE.

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Fortunately, we already have Visual Studio Code fully set up right inside VS Code.

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A highly helpful AI is fully available.

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It is completely automated and we can easily use various models right here.

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To successfully add this to our daily workflow, we simply need to install it in VS Code.

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We securely click allow in VS Code and Codeex will seamlessly open.

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Essentially, it is OpenAI's powerful coding agent that constantly works with you.

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It is fully included in chat GPT plus pro, business, education, and enterprise plans.

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First and foremost, we absolutely must carefully check our specific chat GPT subscription plan.

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I will officially open up the chat GPT interface right open up the chat GPT interface right now.

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As you can clearly see, we currently have the plus version fully activated.

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Looking closely in the dedicated upgrade plan section, you clearly see our active billing plan.

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It is indeed the standard plus plan.

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This essentially means all our ongoing coding work is completely safe and secure.

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Codeex is fully available to use today.

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The strictly required language model is situated right here.

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Moving back into VS Code, we will effectively start the complete software effectively start the complete software installation.

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It securely installs just like a standard web extension.

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First, we smoothly pair it directly with First, we smoothly pair it directly with codeex.

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We basically add codeex as a dedicated side panel within VS Code to seamlessly chat, intuitively edit, and carefully check all our changes.

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Then we can confidently use Codeex directly in the cloud, sending massive jobs straight to it.

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Moving gracefully to the very next step, we simply need to safely sign in using our primary chat GPT account credentials.

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Once fully authenticated, our main application will automatically install directly into the workspace.

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Now the third available setup option is to actually install this directly inside our system terminal.

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For this specific method, just look closely at the keep going in the terminal prompt section.

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We carefully copy this exact command string to our copy this exact command string to our clipboard.

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Following that, we explicitly open up the system command prompt, making sure to run it strictly as an administrator.

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The Windows PowerShell interface naturally opens up within PowerShell itself.

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We formally install the OpenAI codeex tool utilizing the npm package manager.

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Naturally, it will definitely take a little bit of time to fully install properly.

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The underlying system will sequentially gather necessary data in a much better way.

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Codeex is actively installing and we have our app ready.

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Now we go to settings.

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We purposefully open the main application settings directly from the main dashboard.

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Once inside the comprehensive settings menu, there are actually many different customizable options available.

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I specifically navigate over to the appearance tab in order to make some visual interface changes.

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First, I completely change the overall display theme to a comfortable dark display theme to a comfortable dark mode.

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Next, I noticeably increase the base system UI size for better visibility.

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We then carefully choose our preferred font style and slightly adjust the visual contrast.

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Initially, I confidently write in 32 for the primary font size.

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However, upon seeing it, 32 is admittedly just a bit too big for my screen.

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So, I quickly change it down to exactly 24.

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Honestly, 24 is a genuinely comfortable size for long coding sessions.

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For the dedicated code font, we firmly use size 20.

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Moving on, we strategically turn off the reduce motion option.

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We ensure we use standard pointer cursors and gently lower the screen cursors and gently lower the screen contrast.

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Everything is working well.

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Honestly, the overall reading experience is just so much better right now.

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Before we made those crucial visual tweaks, the default text font was incredibly small and honestly hard to read.

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We absolutely had to step in and make the font significantly bigger for basic clarity.

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I truly believe that 24 and 20 are excellent, highly optimized sizes for our daily coding tasks.

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Now, if we quickly navigate over to the general configuration settings menu, we can clearly see multiple distinct operational modes available to choose from.

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I promise that I will carefully explain all of these specific working modes in much greater detail a little bit later on.

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Right now, all our required system packages are successfully installed.

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The powerful Open AI codeex itself is completely installed.

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Now we just essentially need to forcefully run it one more time.

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I smoothly tab back over to the chat GPT window.

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I explicitly type out and clearly ask.

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I have basically run this command in the terminal.

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What do I do next to start it?

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We will now officially start the require process right here within our local system terminal.

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The entire background installation procedure is completely finished.

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It successfully managed to add two vital software packages in just about 36 seconds total.

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The software carefully checks the current MPM installation status alongside the available AI models.

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First and foremost, we must verify the active codeex version.

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I simply type MPM codeex directly into the prompt.

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The resulting Codeex CLI version currently shows up as Codeex CLI version currently shows up as 0.139.0.

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Next, we actively run Codeex, so we can finally start to code.

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We type codeex right into the system environment.

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A brand new security message suddenly appears on the screen.

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It clearly asks, "Do you currently trust the exact contents of this specific directory?"

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Working directly with untrusted contents definitely carries inherent security risks or potential prompt injections.

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Trusting that directory directly allows for reading local configuration settings.

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I confidently click yes and smoothly continue.

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After successfully getting that required yes confirmation, we now finally have our direct working option ready to go.

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We have the full power of the open AI codeex at our fingertips.

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Our specifically selected AI model is currently GPT 5.5.

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Our active working directory is listed safely as system 32.

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We can comfortably make direct code changes right here in this space.

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If I quickly send over a very simple introductory message, it impressively replies back almost automatically.

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I simply write out, "Can you explicitly help me in generating some basic HTML help me in generating some basic HTML code?"

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It quickly gives a remarkably short, concise response.

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It plainly says, "Yes, concise response.

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It plainly says, "Yes, absolutely.

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Just tell me exactly what you want the final HTML page to do or what you want it to look like.

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Paste any existing code snippets you might already have.

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If you happen to start entirely from scratch, I can easily create a simple HTML framework for you.

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Our coding journey begins.

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I press Ctrl C to pause.

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It shows the response.

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The interface clearly displays our complete token usage statistics right on the screen.

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The grand total comes out to exactly The grand total comes out to exactly 7,939 tokens used.

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The initial input strictly accounted for 7,881 accounted for 7,881 tokens.

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Meanwhile, the generated output was a remarkably short 58 tokens.

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To seamlessly continue this exact same chat session, we carefully copy the provided resume command.

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I smoothly paste that specific command right back in here.

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Instantly, the previous conversation thread beautifully continues right where we left off.

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If I suddenly decide that I want to completely change the underlying AI model, we currently have three distinct options available.

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First is GPT 5.5, which is essentially the Frontier model specifically built for complex coding tasks.

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Next is GPT 5.4, the strongest overall model strictly meant for everyday standard coding.

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Finally, we have the incredibly lightweight GPT 5.4 Mini.

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We also have very handy slash commands completely ready to use. we will clearly show exactly how to effectively use them moving forward.

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Let's use slash commands.

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When I proactively type out a forward slash, codeex immediately shows a complete, highly detailed working menu of commands.

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First and foremost, we can fully configure how codeex strictly operates.

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We have the primary model selection option available.

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We also have the specific fast option explicitly listed.

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We have the IDE integration to easily include currently open files and broader include currently open files and broader context.

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We actively have detailed permissions to precisely choose exactly what codecs can or cannot do safely.

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We have dedicated key maps specifically designed for setting custom keyboard designed for setting custom keyboard shortcuts.

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We have Vim mode strictly intended for our main code composer.

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We logically have the sandbox add to directory feature ready.

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Finally, we have the experimental feature section.

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I intentionally select the very first configuration option to explore the available models.

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I ultimately choose the GPT 5.4 mini I ultimately choose the GPT 5.4 mini variant.

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Now we selectively choose the preferred reasoning level.

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We specifically select low reasoning instead of the standard low reasoning instead of the standard medium.

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We can carefully view current IDE sessions and files.

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Next, we review permissions.

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There are several highly specific model permissions carefully listed here.

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The readonly setting strictly means that Codeex can only safely read active files located within the current workspace environment.

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It absolutely requires your direct manual approval before it can ever attempt to edit files or directly access the live internet.

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The ask for approval setting actually serves as the standard default mode where Codeex can seamlessly run, read, or even edit files inside the current workspace and fully read the active command prompt.

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Still, explicit manual approval is completely required to permanently edit files or access the internet.

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Approve for me intelligently only asks for explicit permission when it encounters potentially unsafe system encounters potentially unsafe system actions.

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Full access simply means Codeex can freely edit files far outside the designated workspace and easily access the internet without ever asking for prior approval.

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Exercise extreme caution and ask vital questions when using this.

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I explicitly choose the approve for me I explicitly choose the approve for me setting.

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Our updated permissions are cleanly applied.

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I press enter and transition to the key map configuration.

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In keymap, we have our transcript, external editor, clear terminal, and more options.

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We practically have multiple distinct configuration options readily available right here alongside some incredibly useful direct operational options.

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What we can actually do here is utilize the basic left and right keyboard arrow keys to smoothly navigate and group items.

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We firmly use the enter key whenever we strictly need to modify or edit an existing shortcut.

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We smartly use the star symbol strictly for creating completely custom shortcuts, the dash symbol to quickly unbind an active key, and the escape key to easily close out the menu entirely.

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I simply press escape right now to smoothly go back to the previous screen.

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Right after successfully configuring our system permissions, we logically have our custom key maps fully sorted out.

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Next up, we carefully review our active system approvals.

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You can transparently see absolutely all the recent system changes we manually made right here.

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We actually changed our primary AI model twice today.

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We closely reviewed the IDE context We closely reviewed the IDE context settings.

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We officially updated our security permissions to approve for me.

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Finally, I press Ctrl C.

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Executing that specific command officially closes out the active chat session entirely.

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It is crucial to note that this specific underlying configuration genuinely remains the exact same across every single linked application environment.

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Thankfully, the powerful codeex tool is readily available right here, too.

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We can practically do so many different amazing things with it.

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If we smartly decide to switch over to the exclusive pre-release software version, absolutely all the newest experimental features become instantly available.

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I am going to intentionally open up a brand new dedicated project folder officially named Metabrains for our officially named Metabrains for our work.

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We carefully select this exact folder directory and smoothly open up our fresh chat interface.

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I explicitly confirm that I fully trust the verified authors operating in this specific environment.

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I smoothly close this secondary pop-up window.

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I promptly open up a brand new code file appropriately named code file appropriately named index.html.

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You can distinctly see the familiar codeex logo right inside this document.

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We can now finally start to actively write out our core underlying code write out our core underlying code snippets.

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The generated codeex AI response will seamlessly appear right here on the seamlessly appear right here on the interface.

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We will be able to clearly see our active IDE connection, the linked source repository, the comprehensive onboarding bug log, and of course our preferred dark mode visual theme. we will consistently get highly accurate direct

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responses moving forward.

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Now, we need to take a very close look at our overall system usage metrics.

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I purposefully navigate back over to the main settings page.

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The exact same user account is actively being used uniformly everywhere.

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We can easily modify our deeper codec software settings right here.

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You clearly see broad configurations, custom personalization, advanced MCP servers, web hook integrations, system usage, and active integrations, system usage, and active billing.

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We absolutely need to check these panels timely and consistently to perfectly know exactly how we are efficiently carrying all these things forward.

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We can chat and utilize commands.

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We can switch models and connect apps.

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Inside the primary settings menu, we prominently have the visual appearance and core system configuration tabs.

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Right at the top, we absolutely also have detailed personalization settings, custom keyboard shortcuts, active usage limits, and standard billing limits, and standard billing information.

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The general designated application usage limit strictly caps out at exactly 5 limit strictly caps out at exactly 5 hours.

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Currently, we happily have a massive 99% of that time left available.

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The broader weekly limit currently shows 100% completely left over.

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We have successfully expanded our overall codeex usage capabilities alongside the powerful GPT 5.5 deep thinking mode.

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We can effortlessly purchase an additional credit balance whenever needed.

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Supported system integrations proudly include seamless browser connections, broad computer use permissions, and robust MCP servers.

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The core coding section beautifully includes active web hooks, secure remote connections, complete git source control, safe isolated environments, and managed work trees.

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Our foundational setup phase is now entirely complete.

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The highly anticipated direct usage strictly begins right now.

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We will now efficiently set up highly secure cloud-based development environments right here in this specific environments right here in this specific module.

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You probably remember that we previously ran our codeex agent directly here on the local machine.

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Absolutely all of our core operational functions were safely contained directly inside it.

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Now, however, we will purposefully run our advanced cloud-based development environment securely integrated directly within our main codec setup.

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First things first, I will quickly navigate back over to the main settings panel and intentionally make the system font slightly smaller for better font slightly smaller for better viewing.

00:23:44.240 --> 00:23:53.590
We gracefully go over to the visual appearance tab and actively change the primary text size down from 24 to precisely 20.

00:23:53.600 --> 00:23:58.870
Now, the overall tech size is just so much better and more manageable.

00:23:58.880 --> 00:24:05.669
I will clearly explain to you generally what these advanced cloud-based development environments actually are.

00:24:05.679 --> 00:24:10.074
We will deeply understand this entire concept right here today.

00:24:10.074 --> 00:24:19.590
You absolutely should know right up front that this is essentially a preconfigured, entirely remotely hosted software workspace.

00:24:19.600 --> 00:24:26.149
It actively contains your preferred IDE alongside all your necessary background alongside all your necessary background tools.

00:24:26.159 --> 00:24:35.269
Modern developers can effortlessly code, rigorously test, and smoothly deploy complex software straight from the web complex software straight from the web browser.

00:24:35.279 --> 00:24:42.710
The acronym CDE specifically stands for cloud development environment.

00:24:42.720 --> 00:24:54.549
It effectively solves that highly frustrating age-old problem when a specific piece of code miraculously only works on one specific person's local works on one specific person's local computer.

00:24:54.559 --> 00:25:00.070
Brand new software engineers can easily start actively coding in mere minutes.

00:25:00.080 --> 00:25:03.510
This is our dedicated cloud system.

00:25:03.520 --> 00:25:07.590
Now let's take a moment to talk about codeex itself.

00:25:07.600 --> 00:25:13.830
Codeex fundamentally has some massive, undeniably big advantages here.

00:25:13.840 --> 00:25:21.110
Codeex genuinely works absolute best when it can safely access the entire full code repository.

00:25:21.120 --> 00:25:25.621
It impressively also has powerful built-in deployment tools.

00:25:25.621 --> 00:25:32.070
A cloud environment safely lets codec seamlessly talk directly to remote code talk directly to remote code repositories.

00:25:32.080 --> 00:25:39.190
It can reliably run terminal commands, execute unit tests, and thoroughly check execute unit tests, and thoroughly check projects.

00:25:39.200 --> 00:25:42.950
It safely makes automated code changes.

00:25:42.960 --> 00:25:47.887
The biggest overall benefit is undeniable absolute consistency.

00:25:47.887 --> 00:26:00.710
In significantly older traditional local development environments, various developers constantly use completely different underlying operating systems and vastly different local machine and vastly different local machine settings.

00:26:00.720 --> 00:26:08.310
This inherently creates the infamous frustrating well it perfectly works on my machine problem.

00:26:08.320 --> 00:26:14.950
Modern streamlined cloud environments completely remove these highly annoying problems entirely.

00:26:14.960 --> 00:26:18.123
Absolutely everything that we actively do right here.

00:26:18.123 --> 00:26:25.430
For example, the previously pinned chat log specifically about making a functional calculator about making a functional calculator application.

00:26:25.440 --> 00:26:33.510
Absolutely all our deep technical discussions are safely stored permanently in this robust cloud system.

00:26:33.520 --> 00:26:39.830
We can effortlessly and rapidly review our collective past work right here at any given time.

00:26:39.830 --> 00:26:55.909
Other incredibly massive benefits strictly include nearly instant team on boarding, highly consistent underlying tool setups, absolute hardware independence, and reliable long-term session persistence.

00:26:55.919 --> 00:27:01.835
Now moving forward, we will thoughtfully choose a specific cloud development platform to use.

00:27:01.835 --> 00:27:07.190
I will happily show you some excellent real world examples some excellent real world examples shortly.

00:27:07.200 --> 00:27:12.950
First and foremost, we will take a very close look at GitHub code spaces today.

00:27:12.960 --> 00:27:19.110
It is a remarkably secure, highly robust cloud development environment used by cloud development environment used by many.

00:27:19.120 --> 00:27:26.149
If we genuinely do not want to use this specific one, we can alternatively utilize gitpod.

00:27:26.159 --> 00:27:30.959
We actually use the git pod platform quite a lot in our daily workflows.

00:27:30.959 --> 00:27:37.269
It is a fantastic strictly ondemand, highly scalable development environment.

00:27:37.279 --> 00:27:46.310
For massively big enterprise companies, we consistently have the AWS Cloud9 infrastructure safely available.

00:27:46.320 --> 00:27:51.990
We can seamlessly use it directly for our larger, more complex coding tasks.

00:27:52.000 --> 00:27:58.950
It is basically a fully complete cloud-based integration development environment from Amazon.

00:27:58.960 --> 00:28:04.789
It is truly a complete fully featured IDE right in your browser.

00:28:04.799 --> 00:28:13.029
We can effortlessly write smoothly run and quickly fix our complex code directly inside it.

00:28:13.039 --> 00:28:17.269
These are a few older very solid These are a few older very solid examples.

00:28:17.279 --> 00:28:25.990
Now I will explicitly search the web to see if Codeex itself is officially classified as a cloud-based development classified as a cloud-based development environment.

00:28:26.000 --> 00:28:29.269
It confidently says yes.

00:28:29.279 --> 00:28:37.430
Codeex created by OpenAI is officially a cloud-based AI software engineering cloud-based AI software engineering agent.

00:28:37.440 --> 00:28:51.350
It remarkably handles incredibly complex programming tasks, consistently fixes highly stubborn software bugs, and smoothly proposes absolutely all the necessary fundamental work changes for your review.

00:28:51.360 --> 00:29:04.310
This essentially means that the powerful tool we are actively utilizing right now acts almost exactly like a completely standalone, fully robust cloud-based development environment in itself.

00:29:04.320 --> 00:29:13.661
I strongly suggest that we consistently use this incredible tool to intentionally make a highly secure, deeply isolated remote workspace.

00:29:13.661 --> 00:29:18.499
There are honestly quite a lot of highly technical backend things actively running here.

00:29:18.499 --> 00:29:26.789
I will quickly hop back and change the UI font size once again because it simply does not look visually right on this display.

00:29:26.799 --> 00:29:33.590
I will purposefully make it just a little bit bigger strictly for the sake of our video course clarity.

00:29:33.600 --> 00:29:38.149
Now we simply go straight back into our main codeex application.

00:29:38.159 --> 00:29:40.608
Everything visually looks exceptionally good.

00:29:40.608 --> 00:29:45.899
Now we have our advanced reasoning engine and other vital backend things running.

00:29:45.899 --> 00:29:50.726
We will take a complete comprehensive look at this.

00:29:50.726 --> 00:29:57.750
Nextly shows how we put things into a complete cloud-based setup.

00:29:57.760 --> 00:30:06.950
Now moving smoothly forward, our very next crucial task is to securely connect our remote GitHub repositories directly.

00:30:06.960 --> 00:30:17.115
We absolutely need to establish a solid link to our GitHub account directly within the main codec system inside our primary GitHub platform.

00:30:17.115 --> 00:30:22.630
A tremendous amount of distinct configurable options are always readily configurable options are always readily available.

00:30:22.640 --> 00:30:29.029
You can clearly see the active status regarding the connection with GitHub right here on the interface.

00:30:29.039 --> 00:30:41.029
If I cautiously go over to the main settings panel, specifically looking closely in the connections option area, there is currently absolutely no active connection established.

00:30:41.039 --> 00:30:49.669
The standard SSH and secure git credential options similarly show that there are simply no active connections there are simply no active connections present.

00:30:49.679 --> 00:30:57.029
Furthermore, down in the remote servers and local browser tab, there is similarly no connection.

00:30:57.039 --> 00:31:04.070
In the computer use section, we can alternatively use the Google Chrome browser extension.

00:31:04.080 --> 00:31:11.099
So, our primary GitHub repository profile is clearly not effectively connected to the system just yet.

00:31:11.099 --> 00:31:14.401
I will intentionally just type out the specific query.

00:31:14.401 --> 00:31:23.909
Is GitHub firmly connected to codeex right now? to quickly see if we actually get a reassuring green verification tick.

00:31:23.919 --> 00:31:34.230
This built-in diagnostic tool will thoroughly check the backend systems and explicitly tell us if our GitHub account is successfully connected or not.

00:31:34.240 --> 00:31:44.310
Simultaneously, I will efficiently search for the precise phrasing GitHub and official codeex integration securely and official codeex integration securely online.

00:31:44.320 --> 00:31:51.901
This highly powerful system connection can miraculously be added directly without any significant friction.

00:31:51.901 --> 00:32:04.070
It prominently includes highly advanced automated pull request code reviews, a dedicated co-pilot AI coding agent, and deeply integrated GitHub workflow deeply integrated GitHub workflow actions.

00:32:04.080 --> 00:32:11.509
We will comprehensively discuss absolutely all of these incredible back-end setup options in extreme back-end setup options in extreme detail.

00:32:11.519 --> 00:32:21.756
The diagnostic system now clearly shows that the official GitHub integration plugin is indeed fully available directly within the primary codeex plug-in section.

00:32:21.756 --> 00:32:29.914
But unfortunately, this specific local workspace folder is actually not initialized as a valid Git repository right now.

00:32:29.914 --> 00:32:34.710
A brand new Git tracking folder is quickly being created in the background.

00:32:34.720 --> 00:32:45.350
Now, if we explicitly click the prominent plus button on the user interface, we can clearly see the GitHub icon safely listed in the available plugins directory.

00:32:45.360 --> 00:32:53.917
But we critically want to verify exactly which specific user account is currently connected directly to our active GitHub plug-in extension.

00:32:53.917 --> 00:32:58.310
We currently cannot seem to find our primary GitHub profile.

00:32:58.320 --> 00:33:02.470
So, we will manually initiate a deep search for it.

00:33:02.480 --> 00:33:08.950
When we effectively run the search, the official GitHub authentication app finally appears.

00:33:08.960 --> 00:33:17.391
The application safely requests broad permission to actively access repositories, track software issues, and manage pull requests.

00:33:17.391 --> 00:33:21.489
But we have simply not fully connected it just yet.

00:33:21.489 --> 00:33:25.697
So we will proceed to log securely into our main GitHub account.

00:33:25.697 --> 00:33:32.070
This is our dedicated primary account explicitly named Metabrains-dell.

00:33:32.080 --> 00:33:37.460
It undeniably has many repositories and we have done a lot of work here.

00:33:37.460 --> 00:33:45.350
We will now meticulously connect this specific GitHub account directly to our active codec system workspace.

00:33:45.360 --> 00:33:53.750
When I confidently click the connect button, it explicitly asks for final permission to securely connect to GitHub permission to securely connect to GitHub servers.

00:33:53.760 --> 00:34:05.750
It safely allows the underlying chat GPT engine to carefully read our previous chats and stored memories to consistently give significantly better contextaware answers.

00:34:05.760 --> 00:34:12.820
It clearly states that your deep personal privacy permissions are heavily respected and you are always completely in control.

00:34:12.820 --> 00:34:18.634
It does warn that external connectors may possibly introduce some slight security risk.

00:34:18.634 --> 00:34:23.349
I will boldly open up our direct GitHub developer up our direct GitHub developer dashboard.

00:34:23.359 --> 00:34:30.629
You can visually see that the secure GitHub app authorization connection is actively starting in the background.

00:34:30.639 --> 00:34:35.278
Absolutely all our ongoing critical development work is safely housed right here.

00:34:35.278 --> 00:34:43.109
We will press firmly to continue onward to GitHub so we can comfortably go straight to our main profile account.

00:34:43.119 --> 00:34:47.509
It will naturally take a little bit of processing time to fully connect.

00:34:47.509 --> 00:34:49.354
A basic connection will form.

00:34:49.354 --> 00:34:51.493
You can see it is connected.

00:34:51.493 --> 00:34:53.349
I open plugins again.

00:34:53.359 --> 00:34:59.900
Now you will actively see that our dedicated GitHub plugin is finally working precisely as intended.

00:34:59.900 --> 00:35:04.233
It smoothly works specifically because it is successfully connected to the back end.

00:35:04.233 --> 00:35:12.544
If it is ever mysteriously not connected, we can easily check our credentials again to see if we can actively reconnect it.

00:35:12.544 --> 00:35:20.310
We currently have our active user login, but unfortunately adding the specific external link just adding the specific external link just failed.

00:35:20.320 --> 00:35:23.589
Why exactly did it suddenly fail here?

00:35:23.599 --> 00:35:28.908
We must remember that this is our specific chat GPT plus tier account.

00:35:28.908 --> 00:35:35.109
You absolutely must remember this vital detail because it impacts our detail because it impacts our permissions.

00:35:35.119 --> 00:35:41.190
Now we will purposefully open up the completely alternative chat GPT account completely alternative chat GPT account instead.

00:35:41.200 --> 00:35:49.109
We will securely bring our dedicated Michael Deont user account right here into the active workspace to try again.

00:35:49.119 --> 00:35:55.227
Our premium chat GPT plus subscription tier is fully available right here.

00:35:55.227 --> 00:35:59.811
Now we will carefully attempt to securely connect the integration system once again.

00:35:59.811 --> 00:36:06.069
It will systematically connect our main chat GPT interface to the our main chat GPT interface to the repository.

00:36:06.079 --> 00:36:15.349
If we ever eventually want to completely remove it for security reasons, we can easily uninstall it and quickly reinstall it from scratch later again.

00:36:15.359 --> 00:36:21.381
We obviously also have the standard option to immediately disconnect the authorization any time.

00:36:21.381 --> 00:36:27.990
We will gracefully proceed straight directly over to the main GitHub authorization over to the main GitHub authorization portal.

00:36:28.000 --> 00:36:34.470
Now it will successfully build the required connection directly in our correct targeted application.

00:36:34.480 --> 00:36:39.910
It strictly demands highly secure multiffactor user authentication.

00:36:39.920 --> 00:36:45.270
We will comfortably utilize the standard authenticator mobile app to handle this.

00:36:45.280 --> 00:36:51.750
The mobile authenticator app will swiftly finish processing our deep security verification.

00:36:51.760 --> 00:36:59.030
Now you can clearly see that our primary GitHub profile is finally directly connected perfectly.

00:36:59.040 --> 00:37:03.589
I will quickly pivot back over to our main codeex interface.

00:37:03.599 --> 00:37:09.910
You can clearly see that our secure software link is now fully established and solidly connected.

00:37:09.920 --> 00:37:21.351
If we carefully look directly at our active system plugins list right now, absolutely all our relevant GitHub integration tasks have delightfully started showing up directly in there.

00:37:21.351 --> 00:37:26.470
We will smoothly navigate back over to our main chat terminal interface.

00:37:26.480 --> 00:37:34.230
You can very clearly see our dedicated GitHub functionality is directly added and fully available right there.

00:37:34.240 --> 00:37:41.328
We will quickly go back over to the plugins tab and our GitHub features will be permanently included in the active workflow loop.

00:37:41.328 --> 00:37:47.109
It will effortlessly come directly into our daily software development work.

00:37:47.119 --> 00:37:58.710
Ultimately, we have incredibly successfully added our robust codeex AI tool to perfectly sync with our remote GitHub code repositories.

00:37:58.720 --> 00:38:08.790
Moving logically to the very next crucial step, we will thoroughly talk about the highly specific agents.mmd configuration file.

00:38:08.800 --> 00:38:16.710
This incredibly important file is primarily used for organizing massively big software development projects.

00:38:16.720 --> 00:38:27.498
We specifically utilize it whenever we happen to have many complex automated tasks or a full highly detailed business use case to carefully look at.

00:38:27.498 --> 00:38:40.310
I will intentionally open it up right here on the screen so you can clearly see exactly where these vital agent configuration files naturally come from and exactly where to easily find them.

00:38:40.320 --> 00:38:45.750
It will reliably give us the system response directly and accurately.

00:38:45.760 --> 00:38:55.030
The dedicated agents.mmd file immensely helps us to deeply inspect and standardize our overall project standardize our overall project architecture.

00:38:55.040 --> 00:39:00.630
You can clearly see it actively looking deep inside our raw project files.

00:39:00.640 --> 00:39:06.077
Here it explicitly states that the active workspace is entirely empty right now.

00:39:06.077 --> 00:39:11.349
There is absolutely no agents.mmd file found.

00:39:11.359 --> 00:39:17.270
It checked the temporary scratch space and verified there is no file.

00:39:17.280 --> 00:39:27.006
To successfully create one from scratch, we absolutely must make a brand new correctly formatted agents.mmd file.

00:39:27.006 --> 00:39:32.870
I will manually go ahead and create a brand new foundational file right here for you.

00:39:32.880 --> 00:39:45.270
This incredibly efficient way, we can consistently see absolutely all the necessary high-level production details firmly embedded safely within this specific file.

00:39:45.280 --> 00:39:50.263
First, the core structured agents file is quickly drafted out.

00:39:50.263 --> 00:39:59.670
Right after that initial phase, we can comfortably make far more highly nuanced text changes to this preliminary draft.

00:39:59.680 --> 00:40:13.750
In this specific advanced technical setup, we usually really need to carefully check if our highly specific basic operational rules or distinct business use cases are actually working business use cases are actually working properly.

00:40:13.760 --> 00:40:21.430
It successfully and directly created an excellent base foundational agent file right here for us.

00:40:21.440 --> 00:40:28.150
If we carefully review the generated file, we can clearly see its intended core purpose.

00:40:28.160 --> 00:40:32.710
Besides the purpose, there is a clear project overview.

00:40:32.720 --> 00:40:37.396
We also see a working agreement, a layout, and editing rules.

00:40:37.396 --> 00:40:44.790
We can actively cross-check all of these fundamental operational rules precisely here in the document.

00:40:44.800 --> 00:40:52.230
I will also make sure to explicitly tell you exactly where this specialized configuration file is typically used.

00:40:52.240 --> 00:41:05.829
We consistently use the specialized agents.mmd file to effectively establish strict working boundaries and core rules for literally any AI agent operating in the workspace.

00:41:05.839 --> 00:41:12.069
There are basically no other bizarre tasks or unrelated work explicitly meant for it.

00:41:12.079 --> 00:41:23.670
Sometimes, unfortunately, we literally have to go deep down into our underlying operating system just to manually set up the complex agents.mmd file perfectly.

00:41:23.680 --> 00:41:28.931
This tedious manual process admittedly takes quite a lot of valuable development time.

00:41:28.931 --> 00:41:41.910
We essentially have to carefully look at so many different distinct things like our strict project requirements, core team work ethics, and several other highly detailed technical several other highly detailed technical options.

00:41:41.920 --> 00:41:47.197
We absolutely need to fully know how to properly handle these nuance things.

00:41:47.197 --> 00:41:54.470
But for massively big projects, we only deliberately include our basic setup requirements here.

00:41:54.480 --> 00:41:55.800
Moving right along.

00:41:55.800 --> 00:42:05.750
Next, we will deeply discuss exactly how to effectively use this incredibly vital agents.md file in standard practice.

00:42:05.760 --> 00:42:15.589
Deeply understanding this specific core concept is an undeniably very important foundational part of the entire development process.

00:42:15.599 --> 00:42:25.030
We absolutely need to fully know exactly how to actively create the underlying file directly from absolute scratch.

00:42:25.040 --> 00:42:31.990
Now we purposefully transition and move seamlessly right over to the very next important part.

00:42:32.000 --> 00:42:44.069
We will fundamentally learn exactly how to appropriately handle highly complex things and deeply understand them right after actively creating the foundational after actively creating the foundational file.

00:42:44.079 --> 00:42:50.150
This is fundamentally a highly special deeply vital system instruction file.

00:42:50.160 --> 00:42:58.790
It consistently provides invaluable deep guidance and much needed environmental context directly for our automated work.

00:42:58.800 --> 00:43:06.304
It can absolutely also be used incredibly effectively, exactly like a traditional readme developer file.

00:43:06.304 --> 00:43:13.006
You might vividly remember that standard software developers constantly use structured readme files.

00:43:13.006 --> 00:43:16.819
In the exact same way, we can use this file.

00:43:16.819 --> 00:43:31.750
I have created a basic agents.mmd file, but incredibly we can undoubtedly also meticulously make a highly reusable foundational agents.mmd configuration template right here in the workspace.

00:43:31.760 --> 00:43:40.175
We can comfortably and securely include absolutely all of our strict foundational base development requirements firmly inside it.

00:43:40.175 --> 00:43:46.390
This proactive step will flawlessly kickstart our broader automation work immediately.

00:43:46.400 --> 00:43:50.309
I will gladly proceed to show you an excellent highly structured example.

00:43:50.319 --> 00:43:57.910
Right now I will purposely open up Microsoft Word or a standard blank dock text document.

00:43:57.920 --> 00:44:06.630
I am deliberately using a blank doc right now strictly so we can comfortably start a fresh entirely new empty start a fresh entirely new empty document.

00:44:06.640 --> 00:44:14.470
Here you can very clearly see exactly what critical structural things are highly recommended and available.

00:44:14.480 --> 00:44:19.193
First, we logically have the high-level project overview section.

00:44:19.193 --> 00:44:25.349
This clearly tells us exactly what core deliverables we strictly need in the project.

00:44:25.359 --> 00:44:31.910
Next, we definitely have the strict team coding standards that we must absolutely coding standards that we must absolutely follow.

00:44:31.920 --> 00:44:40.790
After that, we discuss repository structures, testing requirements, security rules, and large scale systems.

00:44:40.800 --> 00:44:47.314
We will practically use a fully functional, highly complete overarching working system here.

00:44:47.314 --> 00:44:58.470
Our strictly prohibited, highly restricted system areas will absolutely also be meticulously explicitly listed right here for immense safety.

00:44:58.480 --> 00:45:07.670
Then our highly nuanced, deeply specific primary AI operational instructions will be thoroughly included next.

00:45:07.680 --> 00:45:18.630
Right after all the comprehensive AI baseline instructions, we will seamlessly have all our broader full feature architectural options carefully feature architectural options carefully documented.

00:45:18.640 --> 00:45:26.870
This is essentially exactly what we traditionally call a comprehensive well ststructured readme file in standard ststructured readme file in standard development.

00:45:26.880 --> 00:45:34.659
It practically has all our complete strict baseline instructions deeply hardcoded and built directly right into it.

00:45:34.659 --> 00:45:47.190
After this section is successfully completed, the very next essential technical thing dynamically available is dealing with our sensitive backend environment variables.

00:45:47.200 --> 00:45:57.750
We will deeply see precisely how we can effectively securely manage these highly critical system environment variables.

00:45:57.760 --> 00:46:06.950
Now our next incredibly critical technical discussion is primarily about handling robust backend environment handling robust backend environment variables.

00:46:06.960 --> 00:46:12.726
These are essentially highly dynamic configurable key values operating in the background.

00:46:12.726 --> 00:46:21.190
We can actively store them either directly or indirectly deep within our underlying operating system within our underlying operating system infrastructure.

00:46:21.200 --> 00:46:29.109
we can comfortably and securely utilize them later for absolutely all of our other automated complex coding tasks.

00:46:29.119 --> 00:46:43.910
Usually we deeply involve our complete highly systematic overall workflow process directly here to explicitly see exactly how a full robust software system is successfully constructed.

00:46:43.920 --> 00:46:57.510
These are highly dynamic backend key values that are stored strictly and directly inside the native operating system, kept entirely safely outside of our vulnerable raw source code files.

00:46:57.520 --> 00:47:04.630
They heavily detect and dictate precisely how the running process fundamentally behaves.

00:47:04.640 --> 00:47:13.270
This brilliant system effortlessly allows developers to incredibly safely store highly sensitive security store highly sensitive security credentials.

00:47:13.280 --> 00:47:16.630
What exactly are sensitive credentials?

00:47:16.640 --> 00:47:19.670
It is highly vital to see this clearly.

00:47:19.680 --> 00:47:23.750
If we fail to understand this, our work If we fail to understand this, our work suffers.

00:47:23.760 --> 00:47:36.390
Sometimes developers are understandably incredibly afraid that their highly sensitive personal or corporate information will eventually accidentally leak to the dangerous public internet.

00:47:36.400 --> 00:47:40.550
Why exactly does this enormous fear Why exactly does this enormous fear exist?

00:47:40.560 --> 00:47:48.710
basically because our complete interconnected development environment inherently has some deeply guarded inherently has some deeply guarded secrets.

00:47:48.720 --> 00:47:59.829
These highly confidential items definitely include things like private API keys, secure admin account usernames, and highly encrypted user usernames, and highly encrypted user passwords.

00:47:59.839 --> 00:48:05.190
We absolutely have to carefully look closely at them and protect them.

00:48:05.200 --> 00:48:12.870
Now we officially pivot to selectively talk about the massive overarching enterprise operational level.

00:48:12.880 --> 00:48:18.710
What exactly inherently happens operating at the massive enterprise scale level?

00:48:18.720 --> 00:48:26.950
Let us quickly intentionally open up a brand new fresh isolated chat window at the highest enterprise level.

00:48:26.960 --> 00:48:37.589
Actively managing profound structural secrets properly is absolutely critical for safely protecting tremendously sensitive proprietary information.

00:48:37.599 --> 00:48:52.470
Secrets routinely may include remote cloud access keys, massive database passwords, complex encryption keys, vital third-party API credentials, and various access authentication tokens.

00:48:52.480 --> 00:48:56.611
Handling environment variables securely with codecs is important.

00:48:56.611 --> 00:49:05.510
These specific crucial security items are undeniably very important to actively manage appropriately right here.

00:49:05.520 --> 00:49:15.430
Usually wildly different distinct deployment environments inherently fundamentally require completely different sets of unique configuration different sets of unique configuration values.

00:49:15.440 --> 00:49:21.270
We can intelligently deploy and actively utilize them safely over there.

00:49:21.280 --> 00:49:36.950
Let me clearly tell you whenever I actively try to perform a direct system search for standard environment variables, you immediately see our primary system environment variables are visibly available precisely right here.

00:49:36.960 --> 00:49:46.870
You will undeniably see that absolutely all of our current environment variables are entirely accessible and available literally right now.

00:49:46.880 --> 00:49:52.710
Sometimes it happens to merely be the static number of active system static number of active system processes.

00:49:52.720 --> 00:49:57.829
Sometimes it is a highly confidential external API key.

00:49:57.839 --> 00:50:13.750
We can smoothly dive deep directly right into the backend system variables menu carefully enter the specific custom variable name and its corresponding strict value directly and permanently safely store it.

00:50:13.760 --> 00:50:21.270
So the next time we run a use case, all variables are automatically set variables are automatically set perfectly.

00:50:21.280 --> 00:50:27.670
How exactly is this properly handled inside a secure underlying database inside a secure underlying database architecture?

00:50:27.680 --> 00:50:40.950
As you can visibly observe precisely here, located deep inside the primary configuration interface, we purposely actively include a dedicated corporate company database link.

00:50:40.960 --> 00:50:46.788
If there happens to clearly be a specific network port required, we firmly include it.

00:50:46.788 --> 00:51:00.870
If there explicitly is an overarching master application configuration requirement, we safely add the core app environment variable alongside the specific designated app alongside the specific designated app port.

00:51:00.880 --> 00:51:08.630
Secure, highly confidential API credentials will absolutely come directly right here.

00:51:08.640 --> 00:51:20.150
For one clear example, if we genuinely want to safely utilize an external OpenAI API authentication key, we securely do it precisely here.

00:51:20.160 --> 00:51:27.750
We can undoubtedly also clearly see secure encrypted payment gateway keys stored right here.

00:51:27.760 --> 00:51:35.829
Then there are massive authentication backend settings designed purely to store multiple dynamic secrets.

00:51:35.839 --> 00:51:43.190
These environment variables brilliantly enable large organizations to safely manage app configurations.

00:51:43.200 --> 00:51:47.190
It prevents leaking sensitive It prevents leaking sensitive information.

00:51:47.200 --> 00:51:50.903
Codeex handles keys safely too without hard coding.

00:51:50.903 --> 00:52:07.349
I will definitively also sincerely tell you that strict environment variables frankly may not initially actively seem incredibly very important right now when we merely successfully create basic simple software absolutely like a fundamental

00:52:07.359 --> 00:52:12.150
basic calculator or standard normal terminal tools.

00:52:12.160 --> 00:52:28.390
However, the exact moment when we actively rigorously try to fundamentally change our massive software architecture or alter major things safely on a significantly much larger, incredibly massive corporate scale, literally many

00:52:28.400 --> 00:52:35.750
distinct individual things wildly realistically start changing aggressively side by side aggressively side by side simultaneously.

00:52:35.760 --> 00:52:49.034
We immediately rapidly actively see literally multiple deep cascading fundamental code structural changes fundamental code structural changes happening now moving confidently right forward seamlessly.

00:52:49.034 --> 00:53:01.733
We will deeply actively rigorously explicitly discuss all of these major systematic fundamental software changes and deeply integrated highly complex AI functions directly later.

00:53:01.733 --> 00:53:08.549
We will explore this in the next sections perfectly.

00:53:08.559 --> 00:53:17.430
Authentication and access configuration is a critical part of using open AI codecs in an enterprise development codecs in an enterprise development environment.

00:53:17.440 --> 00:53:29.670
Authentication verifies the identity of the user or system attempting to use codecs while access configuration defines what that user or system is allowed to do.

00:53:29.680 --> 00:53:44.470
Together, these controls ensure that only authorized developers, teams, and automation tools can interact with repositories, environments, APIs, and sensitive project resources.

00:53:44.480 --> 00:53:57.109
In enterprise software development, codeex usually works with cloud-based development environments, GitHub repositories, CI/CD pipelines, and internal tools.

00:53:57.119 --> 00:54:08.390
Because these systems may contain confidential source code, credentials, customer data, and deployment customer data, and deployment configurations, access must be carefully managed.

00:54:08.400 --> 00:54:18.790
A weak authentication setup can expose the organization to unauthorized code access, accidental changes, or security access, accidental changes, or security breaches.

00:54:18.800 --> 00:54:29.349
Therefore, enterprises commonly rely on identity providers, single sign on, role-based access control, and audit role-based access control, and audit logging.

00:54:29.359 --> 00:54:36.549
The authentication process normally begins when a developer signs in using an approved identity provider.

00:54:36.559 --> 00:54:45.829
This may include enterprise login systems such as SSO, OOTH, or multiffactor authentication.

00:54:45.839 --> 00:54:56.710
Once the user identity is confirmed, the system checks whether the user has permission to access codeex, the development workspace and the connected development workspace and the connected repositories.

00:54:56.720 --> 00:55:04.470
This ensures that codeex activities are tied to a verified user and can be tracked for accountability.

00:55:04.480 --> 00:55:09.349
Access configuration determines the scope of codeex's permissions.

00:55:09.359 --> 00:55:20.069
For example, codecs may be allowed to read a repository, analyze code, create a branch, run tests, or open a pull a branch, run tests, or open a pull request.

00:55:20.079 --> 00:55:27.109
In some cases, it may not be allowed to directly merge code or access production directly merge code or access production secrets.

00:55:27.119 --> 00:55:37.670
These permissions should follow the principle of least privilege, meaning codecs and users should receive only the access required to complete their assigned tasks.

00:55:37.680 --> 00:55:40.485
Repository access is especially important.

00:55:40.485 --> 00:55:47.445
Codecex must often inspect project files, understand dependencies, and modify code.

00:55:47.445 --> 00:55:54.549
However, not every repository should be accessible to every user or AI workflow.

00:55:54.559 --> 00:56:01.829
Enterprises should configure repository permissions based on teams, projects, and business sensitivity.

00:56:01.839 --> 00:56:12.390
For example, a front-end developer may receive access to UI repositories, but not to payment infrastructure or identity management services.

00:56:12.400 --> 00:56:17.190
Environment variables and secrets also require strict control.

00:56:17.200 --> 00:56:28.150
Codeex may need to understand variable names, configuration patterns, or runtime requirements, but it should not expose or hardcode secret values.

00:56:28.160 --> 00:56:35.109
Sensitive credentials should be stored in secure secret managers and injected only when required.

00:56:35.119 --> 00:56:45.030
This prevents accidental leakage of API keys, tokens, database passwords or cloud credentials into source code.

00:56:45.040 --> 00:56:50.630
Auditability is another major requirement in enterprise access requirement in enterprise access configuration.

00:56:50.640 --> 00:57:01.270
Organizations should be able to review who accessed codecs, which repositories were used, what tasks were performed, and what changes were generated.

00:57:01.280 --> 00:57:11.670
Audit logs help security teams investigate incidents, enforce governance policies, and demonstrate compliance with internal or regulatory compliance with internal or regulatory standards.

00:57:11.680 --> 00:57:20.150
A well-designed authentication and access configuration model allows enterprises to use codec safely and enterprises to use codec safely and efficiently.

00:57:20.160 --> 00:57:26.710
It protects sensitive assets while still enabling developers to benefit from AI assisted coding.

00:57:26.720 --> 00:57:43.155
By combining strong identity verification, scoped permissions, secure secret handling, and continuous monitoring, organizations can create a controlled environment where codeex improves productivity without increasing operational risk.

00:57:43.155 --> 00:57:45.197
We discuss codeex workflows.

00:57:45.197 --> 00:57:49.356
Now we want to see how codeex uses large workflows.

00:57:49.356 --> 00:57:53.750
We look at complete software solutions and complete software solutions and workability.

00:57:53.760 --> 00:57:57.538
Sometimes we must see how the whole process grows over time.

00:57:57.538 --> 00:58:00.904
For this we change and improve code on a large scale.

00:58:00.904 --> 00:58:06.069
After these changes we check the overall process understanding.

00:58:06.079 --> 00:58:09.270
I will tell you about codeex workflows.

00:58:09.280 --> 00:58:13.150
Codeex helps developers in the software development life cycle.

00:58:13.150 --> 00:58:14.846
It does repeating tasks.

00:58:14.846 --> 00:58:17.491
It makes the coding environment fast.

00:58:17.491 --> 00:58:21.386
It helps us understand how to fix different problems.

00:58:21.386 --> 00:58:25.030
It helps us understand different work processes.

00:58:25.040 --> 00:58:28.561
The most important discussion is how we use codecs.

00:58:28.561 --> 00:58:30.905
We start with a prompt.

00:58:30.905 --> 00:58:33.158
We can add details in the prompt.

00:58:33.158 --> 00:58:35.433
This helps software work well.

00:58:35.433 --> 00:58:40.390
We use prompts to make software processes easy, fast.

00:58:40.400 --> 00:58:41.935
We start with the prompt.

00:58:41.935 --> 00:58:44.213
We can add details in the prompt.

00:58:44.213 --> 00:58:47.621
The important thing in the prompt is a defined objective.

00:58:47.621 --> 00:58:49.810
We must have a defined objective.

00:58:49.810 --> 00:58:51.030
We must have a defined objective.

00:58:51.040 --> 00:58:55.270
We bring this objective into our software and working process.

00:58:55.280 --> 00:58:58.069
First, we take the generation process.

00:58:58.079 --> 00:59:00.689
We understand the process on a large scale.

00:59:00.689 --> 00:59:02.878
We see how we generate scale.

00:59:02.878 --> 00:59:04.230
We see how we generate everything.

00:59:04.240 --> 00:59:06.395
We have one big question.

00:59:06.395 --> 00:59:10.309
The question is how to define the objective.

00:59:10.319 --> 00:59:12.465
We look at things to define it.

00:59:12.465 --> 00:59:15.829
We will see how these things work together.

00:59:15.839 --> 00:59:18.413
This is a very strong and important point.

00:59:18.413 --> 00:59:23.510
We must know how to set up objectives for large generation.

00:59:23.520 --> 00:59:26.655
After we set the objective, we look at the next steps.

00:59:26.655 --> 00:59:29.383
The next step is feature development.

00:59:29.383 --> 00:59:33.750
Feature development is a process in our pipeline.

00:59:33.760 --> 00:59:38.630
After development, the next thing is software defect identification.

00:59:38.640 --> 00:59:43.190
We must make this defect identification process strong.

00:59:43.200 --> 00:59:45.958
After we find defects, we move to next steps.

00:59:45.958 --> 00:59:50.789
The next steps are refactoring and optimization.

00:59:50.799 --> 00:59:53.433
First, we must define a task.

00:59:53.433 --> 00:59:56.950
We must have a clear task definition.

00:59:56.960 --> 01:00:00.554
After we define the task, we provide background context.

01:00:00.554 --> 01:00:04.630
We provide this context on a large scale.

01:00:04.640 --> 01:00:07.197
I will explain this process to you.

01:00:07.197 --> 01:00:11.030
I will use a flow diagram to show how things work.

01:00:11.040 --> 01:00:14.309
First, we have the task definition.

01:00:14.319 --> 01:00:16.805
Next, we have task context.

01:00:16.805 --> 01:00:20.549
We must know how to add the context.

01:00:20.559 --> 01:00:23.365
After the context, we need a detailed prompt.

01:00:23.365 --> 01:00:25.944
Then, we connect our main prompt.

01:00:25.944 --> 01:00:27.190
Then, we connect our main codeex.

01:00:27.200 --> 01:00:29.704
We connect codeex with our own code bases.

01:00:29.704 --> 01:00:35.670
We connect codeex with our code bases to show complete analysis.

01:00:35.680 --> 01:00:39.589
After analysis, we must have solution After analysis, we must have solution generation.

01:00:39.599 --> 01:00:42.710
Solution generation must be available.

01:00:42.720 --> 01:00:47.190
After solution generation, the next step is review.

01:00:47.200 --> 01:00:49.473
I tell you we need these things in our prompt.

01:00:49.473 --> 01:00:53.670
When we have these things, our prompt starts.

01:00:53.680 --> 01:00:57.648
Inside this prompt, our solution generation process starts.

01:00:57.648 --> 01:01:00.950
Here we have our solution generation.

01:01:00.960 --> 01:01:03.530
After we generate the solution, we review it.

01:01:03.530 --> 01:01:07.270
We check everything in the review step.

01:01:07.280 --> 01:01:09.713
After the review, another process starts.

01:01:09.713 --> 01:01:12.052
We call this new process starts.

01:01:12.052 --> 01:01:13.430
We call this new process testing.

01:01:13.440 --> 01:01:16.211
Testing is very important here.

01:01:16.211 --> 01:01:18.862
In testing, we include debugging.

01:01:18.862 --> 01:01:22.187
Both testing and debugging must happen together.

01:01:22.187 --> 01:01:25.109
We need both in our workflow.

01:01:25.119 --> 01:01:28.230
They help us find and fix problems.

01:01:28.240 --> 01:01:32.870
These steps make the software better and ready for final stages.

01:01:32.880 --> 01:01:35.838
Both testing and debugging must be present.

01:01:35.838 --> 01:01:39.196
The last step available here is refinement.

01:01:39.196 --> 01:01:43.190
We call this refinement process iteration.

01:01:43.200 --> 01:01:45.645
We do refinement to make software better.

01:01:45.645 --> 01:01:49.324
After the refinement step, we commit changes.

01:01:49.324 --> 01:01:51.999
We save all the changes we made.

01:01:51.999 --> 01:01:55.190
This is the complete process.

01:01:55.200 --> 01:01:57.976
At the end, our workflow closes.

01:01:57.976 --> 01:02:00.695
It closes at the deployment stage.

01:02:00.695 --> 01:02:02.132
We go to closes at the deployment stage.

01:02:02.132 --> 01:02:02.630
We go to deployment.

01:02:02.640 --> 01:02:05.829
We deploy our project into our system.

01:02:05.839 --> 01:02:08.116
These steps are helpful on a large scale.

01:02:08.116 --> 01:02:10.582
They help us create a better score.

01:02:10.582 --> 01:02:14.393
They help us create a better decision tree for work.

01:02:14.393 --> 01:02:18.244
This is how the complete workflow operates from start to finish.

01:02:18.244 --> 01:02:22.008
We follow these simple rules to make good software.

01:02:22.008 --> 01:02:25.430
Every step is important for the final product.

01:02:25.440 --> 01:02:28.179
Deployment is the final goal of this journey.

01:02:28.179 --> 01:02:30.950
Our next talk is about codecs.

01:02:30.960 --> 01:02:33.326
We will learn about our projects in codecs.

01:02:33.326 --> 01:02:39.094
Project navigation is a very important AI skill in modern software development.

01:02:39.094 --> 01:02:43.270
In big business places, developers work with big repositories.

01:02:43.280 --> 01:02:47.036
Often these repositories have thousands of files.

01:02:47.036 --> 01:02:50.568
We can see our multiple services directly.

01:02:50.568 --> 01:02:56.668
It also sees big documentation, complex dependencies, and multiple servers.

01:02:56.668 --> 01:03:01.088
Understanding these projects by hand needs much time and effort.

01:03:01.088 --> 01:03:06.069
Codeex helps developers understand the project structures well.

01:03:06.079 --> 01:03:13.109
It finds correct files, traces dependencies, and locates our implementation details.

01:03:13.119 --> 01:03:15.752
I go to the project menu directly.

01:03:15.752 --> 01:03:17.782
I click start from scratch.

01:03:17.782 --> 01:03:21.190
I name the new project Metabrains.

01:03:21.200 --> 01:03:24.299
I start one project directly here.

01:03:24.299 --> 01:03:25.263
I save it.

01:03:25.263 --> 01:03:28.069
Now we have a new project.

01:03:28.079 --> 01:03:30.605
There is no chat available yet in the project.

01:03:30.605 --> 01:03:33.212
You see our explorer and object project.

01:03:33.212 --> 01:03:34.470
You see our explorer and object options.

01:03:34.480 --> 01:03:39.029
If we turn on the explorer, our file opens automatically.

01:03:39.039 --> 01:03:41.912
You can see we have no document available yet.

01:03:41.912 --> 01:03:46.230
With time we will make many additions and changes.

01:03:46.240 --> 01:03:50.390
Automatically our response and style will change.

01:03:50.400 --> 01:03:52.427
I will start from the beginning.

01:03:52.427 --> 01:03:55.804
We will look at all the changes we make from start to now.

01:03:55.804 --> 01:03:59.754
Along with changes, we will also see the time.

01:03:59.754 --> 01:04:03.834
We will see how much time one full cycle takes.

01:04:03.834 --> 01:04:07.349
We can look at the complete process directly.

01:04:07.359 --> 01:04:10.870
Sometimes we must approve things directly to understand them.

01:04:10.870 --> 01:04:11.901
I will tell you.

01:04:11.901 --> 01:04:16.133
I will type what things should be in our project.

01:04:16.133 --> 01:04:20.710
I write create an agent MD file.

01:04:20.720 --> 01:04:24.390
We will create the agent.mmd file here.

01:04:24.400 --> 01:04:27.397
This makes our agent work in a much better way.

01:04:27.397 --> 01:04:33.000
I type because this is a corporate sales manager and content creator project.

01:04:33.000 --> 01:04:37.029
It will do the first step of our project here.

01:04:37.039 --> 01:04:41.190
First of all, we give it the context and our details.

01:04:41.200 --> 01:04:44.126
We are making the employee do these things here.

01:04:44.126 --> 01:04:48.309
We will include this directly for our approval.

01:04:48.319 --> 01:04:53.342
I tell you that a complete process discussion is very important here.

01:04:53.342 --> 01:04:57.190
In this we have to involve all our details.

01:04:57.200 --> 01:05:00.014
We must involve our full working process.

01:05:00.014 --> 01:05:03.197
Here you can see it will take some time.

01:05:03.197 --> 01:05:06.800
Obviously it is working in our exact folder.

01:05:06.800 --> 01:05:13.750
If I refresh our folder here you will see the agent ND file is created.

01:05:13.760 --> 01:05:16.531
We can directly review it here.

01:05:16.531 --> 01:05:21.402
It created the agent.mmd file with a tailored operating brief.

01:05:21.402 --> 01:05:25.910
This is for the corporate sales manager and content the corporate sales manager and content project.

01:05:25.920 --> 01:05:29.305
The agent.md file is made here.

01:05:29.305 --> 01:05:33.818
You can see our exact source code and other things are available.

01:05:33.818 --> 01:05:37.046
We can open it directly in our VS code.

01:05:37.046 --> 01:05:40.549
We can open it in the default application.

01:05:40.559 --> 01:05:43.670
We can also open it in our terminal.

01:05:43.680 --> 01:05:46.315
These things are much better here.

01:05:46.315 --> 01:05:49.750
We have a complete system environment.

01:05:49.760 --> 01:05:54.281
Automatically we see all divisions and working ability here.

01:05:54.281 --> 01:05:59.022
Sometimes this working ability or complete process causes problems.

01:05:59.022 --> 01:06:01.826
It causes problems on a big scale.

01:06:01.826 --> 01:06:04.368
We see many issues in our big scale.

01:06:04.368 --> 01:06:05.510
We see many issues in our work.

01:06:05.520 --> 01:06:10.997
We usually create our complete empty MD file at the very start of the project setup.

01:06:10.997 --> 01:06:17.106
So on a big scale if any issue happens later we can understand it early.

01:06:17.106 --> 01:06:20.907
We can do things early according to our system.

01:06:20.907 --> 01:06:23.248
This is a basic discussion.

01:06:23.248 --> 01:06:26.715
Now we see how complete generation happens.

01:06:26.715 --> 01:06:30.692
We see how we take a complete process or understanding with us.

01:06:30.692 --> 01:06:37.430
After the agent MD file we will directly look at our project structure.

01:06:37.440 --> 01:06:39.923
I will go into the exact same folder.

01:06:39.923 --> 01:06:42.536
I will include a new folder here.

01:06:42.536 --> 01:06:45.609
This is from a previously created section.

01:06:45.609 --> 01:06:48.022
You can see our portfolios are available here.

01:06:48.022 --> 01:06:51.730
I will do all the portfolio discussion here.

01:06:51.730 --> 01:06:54.214
I will now analyze our discussion here.

01:06:54.214 --> 01:06:55.349
I will now analyze our repository.

01:06:55.359 --> 01:07:01.519
I write analyze this repository and provide a comprehensive overview of the project structure.

01:07:01.519 --> 01:07:05.190
It includes the main purpose of the application.

01:07:05.200 --> 01:07:08.230
Then we have highlevel architecture.

01:07:08.240 --> 01:07:11.270
Then we have important directories.

01:07:11.280 --> 01:07:15.843
Then we have all options for important directories on a big scale.

01:07:15.843 --> 01:07:19.570
After major frameworks, we have entry points.

01:07:19.570 --> 01:07:22.424
After entry points, we have configuration files.

01:07:22.424 --> 01:07:25.245
Then we have deployment related files.

01:07:25.245 --> 01:07:26.549
Then we have deployment related files.

01:07:26.559 --> 01:07:29.430
Then we have testing structure.

01:07:29.440 --> 01:07:35.753
Then it says present the information in a structured format suitable for onboarding a new developer.

01:07:35.753 --> 01:07:39.664
We can take our things directly in developer onboarding too.

01:07:39.664 --> 01:07:41.670
We can involve them.

01:07:41.680 --> 01:07:46.069
This is a complete structured repository layout that we use here.

01:07:46.079 --> 01:07:48.852
Sometimes we must see some changes in this too.

01:07:48.852 --> 01:07:54.470
In this we also involve multiple repositories and options multiple repositories and options directly.

01:07:54.480 --> 01:07:57.890
When I enter this it will directly go to our folder.

01:07:57.890 --> 01:08:00.549
The index file is inside.

01:08:00.559 --> 01:08:03.510
You can see this is like our index file.

01:08:03.520 --> 01:08:08.789
When the index file opens, a complete portfolio website is available.

01:08:08.799 --> 01:08:13.757
Now we will see how to enhance and understand this portfolio website on a big scale.

01:08:13.757 --> 01:08:16.583
This will happen in our codeex here.

01:08:16.583 --> 01:08:19.441
It understood the child item here.

01:08:19.441 --> 01:08:22.373
After that it showed our files.

01:08:22.373 --> 01:08:25.749
It has shown the key pattern too.

01:08:25.759 --> 01:08:28.169
We have one HTML document.

01:08:28.169 --> 01:08:30.385
We have one stylesheet.

01:08:30.385 --> 01:08:33.189
We have one script bundle.

01:08:33.199 --> 01:08:36.070
Then we have some static assets.

01:08:36.080 --> 01:08:40.630
We also have all other things available to use directly.

01:08:40.640 --> 01:08:42.814
Now I will take our details.

01:08:42.814 --> 01:08:45.317
I will see how our process runs.

01:08:45.317 --> 01:08:49.805
I will see how all direct discussions and details run.

01:08:49.805 --> 01:08:52.647
With this we will take our setup.

01:08:52.647 --> 01:08:57.320
Usually this needs a lot of time if we take these things in another environment.

01:08:57.320 --> 01:09:00.550
But here our things are much simpler now.

01:09:00.560 --> 01:09:03.481
We can include much better things and accounts here.

01:09:03.481 --> 01:09:06.469
I will look at our direct use case now.

01:09:06.469 --> 01:09:09.307
It read out our whole folder here.

01:09:09.307 --> 01:09:16.149
After that it told us there are no platform specific deployment manifests checked into the repository.

01:09:16.159 --> 01:09:19.590
The deployment guidance is document The deployment guidance is document only.

01:09:19.600 --> 01:09:22.229
After that we have a testing structure.

01:09:22.239 --> 01:09:25.110
Then all other things have come.

01:09:25.120 --> 01:09:27.611
Now we have gone inside our project.

01:09:27.611 --> 01:09:29.808
We have seen how we will include our system.

01:09:29.808 --> 01:09:33.696
Now I will see what entry points are available there.

01:09:33.696 --> 01:09:36.553
I will write to find the entry points.

01:09:36.553 --> 01:09:43.113
If we want to look at something other than entry points, we will involve all user authentication features.

01:09:43.113 --> 01:09:45.879
Here we will see how we can look at them.

01:09:45.879 --> 01:09:50.352
Along with this, we will get a direct response from the complete system.

01:09:50.352 --> 01:09:53.590
We will see how we take things directly in our system.

01:09:53.600 --> 01:10:00.202
First I will type to locate and explain the implementation of the user authentication feature.

01:10:00.202 --> 01:10:04.004
I will identify all the components involved here.

01:10:04.004 --> 01:10:07.189
Then I will look at the authentication flow.

01:10:07.199 --> 01:10:10.550
Then I will look at the authentication Then I will look at the authentication middleware.

01:10:10.560 --> 01:10:13.430
Then I will look at password handling.

01:10:13.440 --> 01:10:17.110
Then I will look at the token generation Then I will look at the token generation process.

01:10:17.120 --> 01:10:20.709
Then I will look at the session or token Then I will look at the session or token management.

01:10:20.719 --> 01:10:26.630
Then I will provide a step-by-step explanation of how the application explanation of how the application starts.

01:10:26.640 --> 01:10:31.830
Then I will process the requests from login to successful authentication.

01:10:31.840 --> 01:10:34.790
These things bring all our details here.

01:10:34.800 --> 01:10:37.416
All our handling has come here.

01:10:37.416 --> 01:10:44.116
Now generating code from requirements is one of the most practical uses of OpenAI codeex in everyday development.

01:10:44.116 --> 01:10:54.790
Instead of translating every single business requirement into working code by hand, developers can provide codecs with a vast amount of information or context.

01:10:54.800 --> 01:10:59.510
We can include clear instructions, behaviors, and context.

01:10:59.520 --> 01:11:02.660
We have multiple forms of languages available to use.

01:11:02.660 --> 01:11:04.995
Let me open Excaladraw here.

01:11:04.995 --> 01:11:08.955
As you can see, we have some business languages.

01:11:08.955 --> 01:11:19.510
For example, we can allow users to export reports as CSV or involve RO based access control, also known as RBAC.

01:11:19.520 --> 01:11:33.392
Codeex helps bridge the gap between these requirements and implementations by identifying relevant files, suggesting changes, creating new components, updating APIs, and adding tests where needed.

01:11:33.392 --> 01:11:39.350
However, codeex works best when the requirements are very specific in nature.

01:11:39.360 --> 01:11:43.558
Let me show you how to include basics in codeex right from the start.

01:11:43.558 --> 01:11:48.406
Suppose you want a plan mode and after that you want to pursue a goal.

01:11:48.406 --> 01:11:51.604
Then you might want to create a document.

01:11:51.604 --> 01:11:55.343
After document creation, you might want to include photos.

01:11:55.343 --> 01:11:59.673
You have multiple plugins that you can use side by side.

01:11:59.673 --> 01:12:03.118
Even if you need a browser plugin, you can use that one too.

01:12:03.118 --> 01:12:08.550
If you have specific content to use, that can be utilized as well.

01:12:08.560 --> 01:12:14.766
For instance, we can go to documents or downloads, select an available document and use it.

01:12:14.766 --> 01:12:17.523
After that, we select our model.

01:12:17.523 --> 01:12:20.950
This latency is quite important.

01:12:20.960 --> 01:12:23.404
Therefore, I will use a latest model here.

01:12:23.404 --> 01:12:28.861
With that latest model, we can increase speed and manage latency.

01:12:28.861 --> 01:12:33.497
Well, after this, our prompt should contain very detailed options.

01:12:33.497 --> 01:12:38.738
First of all, a well- set prompt has some specific elements available within it.

01:12:38.738 --> 01:12:41.325
I will explain these elements to you.

01:12:41.325 --> 01:12:44.717
A good prompt includes all these necessary components.

01:12:44.717 --> 01:12:52.390
The very first thing is context followed by the role details and then the requirements.

01:12:52.400 --> 01:12:59.179
When discussing requirements, it is a crucial point because codeex works better when the requirements are specific.

01:12:59.179 --> 01:13:04.148
A vague prompt may produce incomplete or misaligned code.

01:13:04.148 --> 01:13:18.790
A strong prompt includes the feature goal, affected users, input and output behavior, files or modules to consider, coding standards, test expectations, and what our codec should avoid changing.

01:13:18.800 --> 01:13:26.709
Developers should treat the codeex generated code as a first draft so we get a complete response right from the very start of it.

01:13:26.719 --> 01:13:31.990
Next, after the requirements, we need to establish our acceptance criteria.

01:13:32.000 --> 01:13:36.404
This defines the standard our response must maintain when we receive it.

01:13:36.404 --> 01:13:40.070
At the end, we sometimes use a negative prompt.

01:13:40.080 --> 01:13:44.349
In a negative prompt, we specify the things that we do not need.

01:13:44.349 --> 01:13:49.179
In the rest of the prompt, we list all the necessary things that we want.

01:13:49.179 --> 01:13:56.190
However, in a negative prompt, we mention all those exact things that are not required for our output at all.

01:13:56.190 --> 01:14:00.822
For example, let me show you a sample prompt right here in this section.

01:14:00.822 --> 01:14:04.062
We can go into codeex and type out our prompt.

01:14:04.062 --> 01:14:13.322
We will write that you are working in this repository as a senior software engineer with a lot of experience and solid technical background knowledge today.

01:14:13.322 --> 01:14:14.881
This defines our role.

01:14:14.881 --> 01:14:18.250
The complete task is outlined in plain words.

01:14:18.250 --> 01:14:26.757
After the task, you can see our functional requirements are discussed such as adding an export CSV button near the reports table.

01:14:26.757 --> 01:14:31.482
Towards the end, all the detailed steps we need to perform are available.

01:14:31.482 --> 01:14:33.828
This is our acceptance criteria.

01:14:33.828 --> 01:14:36.664
The export button appears on the report page.

01:14:36.664 --> 01:14:43.623
Clicking the button downloads a valid CSV file and the CSV contains the same rows displayed on the table.

01:14:43.623 --> 01:14:46.330
It will take data straight from the browser.

01:14:46.330 --> 01:14:51.910
Commit the repository in GitHub and provide the response in document form.

01:14:51.920 --> 01:14:56.398
Generating code from requirements with codeex improves overall development speed.

01:14:56.398 --> 01:15:04.550
When our prompts are better, the final results we get will also be much better, which we can then utilize today.

01:15:04.560 --> 01:15:16.149
Clear requirements, a defined scope, and strong acceptance criteria help codeex produce code that is easier to review, test, and merge in big enterprise teams.

01:15:16.159 --> 01:15:22.432
We are discussing how big enterprise teams can incorporate these modern features on a larger scale.

01:15:22.432 --> 01:15:27.438
Today our next discussion will be related to editing and refactoring existing code bases.

01:15:27.438 --> 01:15:36.149
We have generated this exact code as an example project where we are utilizing all these core elements in real time.

01:15:36.159 --> 01:15:39.791
Now suppose our initial code is generated and ready.

01:15:39.791 --> 01:15:46.950
To demonstrate this point, well, I will show you a custom calculator code from our older previous calculator code from our older previous generations.

01:15:46.960 --> 01:15:56.777
In that existing code, we will perform and showcase our past iterations and refactoring processes step by step for all of you to see right here today.

01:15:56.777 --> 01:16:01.510
Now, we will discuss editing or refactoring the code.

01:16:01.520 --> 01:16:04.761
Here you can see that we asked to create a calculator code.

01:16:04.761 --> 01:16:08.027
It took a quick look and made a plan for us.

01:16:08.027 --> 01:16:14.550
After making the plan, it implemented the calculator in the calculator.py file.

01:16:14.560 --> 01:16:16.950
This is our calculator.

01:16:16.960 --> 01:16:19.995
Everything in it is functional from start to finish.

01:16:19.995 --> 01:16:26.870
If we want to run it, we will see that the verification passed using the bundled Python runtime.

01:16:26.880 --> 01:16:30.607
Note that Python and py are not on our system path.

01:16:30.607 --> 01:16:36.709
So if we want to use it in our environment, we need all these our environment, we need all these requirements.

01:16:36.719 --> 01:16:42.231
I will open PowerShell here or I will just open the command prompt.

01:16:42.231 --> 01:16:45.171
In the command prompt, we will give this command.

01:16:45.171 --> 01:16:50.601
When I press enter, you will see that we have a complete response included here.

01:16:50.601 --> 01:16:52.936
Now, I will include it here.

01:16:52.936 --> 01:16:57.350
There is an issue in the first line of our code.

01:16:57.360 --> 01:17:00.544
So, we will run it from here to here.

01:17:00.544 --> 01:17:01.990
I will copy this.

01:17:01.990 --> 01:17:06.085
After copying, I will go back to the command prompt.

01:17:06.085 --> 01:17:08.870
Here is the command prompt.

01:17:08.880 --> 01:17:12.149
Now we will include it in the command Now we will include it in the command prompt.

01:17:12.159 --> 01:17:18.794
When we include it, you can see that because this file is very old, our file is not available here.

01:17:18.794 --> 01:17:22.470
But we can still run it in our browser.

01:17:22.480 --> 01:17:25.784
Now we will look at our editing and refactoring here.

01:17:25.784 --> 01:17:33.590
Usually this is the most valuable capability of our OpenAI codeex for enterprise software codeex for enterprise software development.

01:17:33.600 --> 01:17:43.750
While generating new code is useful, developers spend a lot of time improving, maintaining, and modernizing existing applications.

01:17:43.760 --> 01:17:46.285
Codeex can analyze the current code base.

01:17:46.285 --> 01:17:55.350
It can understand relationships between files, identify code smells, and suggest improvements for better suggest improvements for better readability.

01:17:55.360 --> 01:17:58.229
First, I will explain the first thing.

01:17:58.239 --> 01:18:01.510
This is what we call refactoring code.

01:18:01.520 --> 01:18:05.083
This is a process of restructuring the existing code.

01:18:05.083 --> 01:18:13.350
It improves readability, maintainability and internal design without changing its external behavior.

01:18:13.360 --> 01:18:16.206
We primarily involve this in our code review.

01:18:16.206 --> 01:18:24.070
If I go to Excaladraw, I can tell you that after refactoring, the next thing is restructuring or editing.

01:18:24.080 --> 01:18:26.229
That is very simple.

01:18:26.239 --> 01:18:43.030
It is simple because we can come into our code include any line here and include things by giving a local comment or if we want to do overall refactoring I can say to make this into an HTML file that I can run in VS code here you can

01:18:43.040 --> 01:18:55.990
see that now it will directly take our prompt the code was previously available now it will connect our Python calculator into a browserfriendly HTML calculator into a browserfriendly HTML version.

01:18:56.000 --> 01:18:59.590
Alternatively, I will open our VS Code.

01:18:59.600 --> 01:19:04.223
You might remember that we already included codecs in Visual Studio Code before.

01:19:04.223 --> 01:19:09.910
So, this will also be available for us to use in a much easier way.

01:19:09.920 --> 01:19:18.070
Along with this, in Visual Studio Code, where everything else is, we will automatically include our calculator automatically include our calculator file.

01:19:18.080 --> 01:19:19.307
Codeex is open.

01:19:19.307 --> 01:19:23.187
All our generations and things are available in it.

01:19:23.187 --> 01:19:28.217
Now you will see that our codeex file has arrived here in the codeex file.

01:19:28.217 --> 01:19:31.750
All our things are directly included.

01:19:31.760 --> 01:19:40.390
Now you can see that if we want we can directly open the calculator in the browser or we can copy its link and go to another browser.

01:19:40.400 --> 01:19:44.470
If we copy its link we just have to go If we copy its link we just have to go here.

01:19:44.480 --> 01:19:49.350
When we open it here the calculator will open in our browser.

01:19:49.360 --> 01:19:51.922
This is a very simple calculator.

01:19:51.922 --> 01:19:57.083
If we want to open it in the internal browser of codeex, that is also possible.

01:19:57.083 --> 01:20:01.350
It will load and run our calculator in the codeex browser.

01:20:01.360 --> 01:20:07.398
Here you can see that if we want we can directly use this file in our VS code from the options.

01:20:07.398 --> 01:20:09.205
We can include from the options.

01:20:09.205 --> 01:20:10.229
We can include annotations.

01:20:10.239 --> 01:20:13.990
If we want we can save a screenshot If we want we can save a screenshot here.

01:20:14.000 --> 01:20:19.270
After saving the screenshot here, we can also use it in another browser.

01:20:19.280 --> 01:20:22.533
We can come here and use it here too.

01:20:22.533 --> 01:20:27.750
So if we want to make any design changes, we can do that directly.

01:20:27.760 --> 01:20:34.603
When working with legacy systems, developers often face challenges such as inconsistent coding styles.

01:20:34.603 --> 01:20:38.470
Here the coding we have is AI based coding.

01:20:38.480 --> 01:20:44.575
However, if we talk about legacy systems, they are systems where we manually write all the code.

01:20:44.575 --> 01:20:49.510
We make all the changes and alterations in that code the changes and alterations in that code ourselves.

01:20:49.520 --> 01:20:49.857
there.

01:20:49.857 --> 01:20:56.630
Sometimes there are outdated frameworks, poor documentation, and tightly coupled components.

01:20:56.640 --> 01:21:03.189
Codeex can help developers understand the purpose of existing code before making modifications.

01:21:03.199 --> 01:21:07.590
It does this by analyzing the related files and dependencies.

01:21:07.600 --> 01:21:15.110
It can recommend safer refactoring strategies and identify areas where changes may have downstream effects.

01:21:15.120 --> 01:21:21.430
This significantly reduces the time required to understand unfamiliar code required to understand unfamiliar code bases.

01:21:21.440 --> 01:21:30.229
Despite these advantages, developers should carefully review all refactoring changes before merging them into the production branches.

01:21:30.239 --> 01:21:36.769
Even when functionality appears unchanged, modifications can introduce unintended side effects.

01:21:36.769 --> 01:21:39.473
Now I will work on our code here.

01:21:39.473 --> 01:21:41.396
I will go to our codeex.

01:21:41.396 --> 01:21:48.310
In codeex, we will write a prompt that you are working as a senior software engineer in this repository.

01:21:48.320 --> 01:21:53.270
The task is to refactor the existing code without changing its functionality.

01:21:53.280 --> 01:22:00.551
We will improve the code readability and maintainability and remove duplicate logic with simple complex methods.

01:22:00.551 --> 01:22:02.818
There is a lot of detail here.

01:22:02.818 --> 01:22:09.220
The general overview of this detail is that we should make our code readability and maintainability better.

01:22:09.220 --> 01:22:12.838
As soon as I improve this, we start getting our response.

01:22:12.838 --> 01:22:15.636
We can directly include this response.

01:22:15.636 --> 01:22:18.805
First, it will look at the current state.

01:22:18.805 --> 01:22:23.780
The main refactor target is that we will slightly change the HTML file.

01:22:23.780 --> 01:22:28.112
First of all, we will include the keyboard handling.

01:22:28.112 --> 01:22:33.189
After that, we will see multiple changes in this HTML file.

01:22:33.199 --> 01:22:39.510
If we want to review it, our changes will automatically appear wherever changes are being made in our file.

01:22:39.520 --> 01:22:43.194
You will see that the refactor is done in one focused pass.

01:22:43.194 --> 01:22:45.447
I am validating both sides.

01:22:45.447 --> 01:22:53.667
Now, Python behavior should still pass and the HTML script should still calculate and respond to the button and keyboard actions.

01:22:53.667 --> 01:22:55.796
Here, our checks have passed.

01:22:55.796 --> 01:23:02.629
Now, if we reload our calculator, many changes will be included in our calculator.

01:23:02.639 --> 01:23:05.117
Now, we have another very important thing.

01:23:05.117 --> 01:23:08.103
It is not just doing a simple check.

01:23:08.103 --> 01:23:11.750
It also performed a Python check.

01:23:11.760 --> 01:23:18.640
If I show you the working after the Python check, it also included HTML behavior checks.

01:23:18.640 --> 01:23:22.370
The refactored HTML is built here.

01:23:22.370 --> 01:23:25.189
It has only 123 lines.

01:23:25.189 --> 01:23:28.149
I can say that our workability is much easier.

01:23:28.159 --> 01:23:33.838
Now, if we look at the code review, it changed many lines in the code.

01:23:33.838 --> 01:23:41.270
For example, instead of display value zero, it has set the display value to the default value.

01:23:41.280 --> 01:23:44.144
Overall, it showed our functionality in depth.

01:23:44.144 --> 01:23:49.510
It directly changed the error coming in the display into show error.

01:23:49.520 --> 01:23:54.196
Here too, it changed set display error to show error.

01:23:54.196 --> 01:24:02.208
In simple words, it improved our code maintainability and nullified the error-causing paths on a large scale.

01:24:02.208 --> 01:24:06.761
It manipulated the errors into the show error function.

01:24:06.761 --> 01:24:12.017
Exactly here too the set display error was changed to show error.

01:24:12.017 --> 01:24:16.956
This means in simple words our code maintainability has improved.

01:24:16.956 --> 01:24:21.168
It has removed the paths that cause errors on a large scale.

01:24:21.168 --> 01:24:24.212
Next we will discuss context windows and scope.

01:24:24.212 --> 01:24:27.270
Context window is a new topic.

01:24:27.280 --> 01:24:29.472
People do not discuss it much.

01:24:29.472 --> 01:24:32.870
I will tell you what a context window is.

01:24:32.880 --> 01:24:38.371
A context window is the maximum text an AI model can hold at one time.

01:24:38.371 --> 01:24:40.804
It works as the AI's memory.

01:24:40.804 --> 01:24:47.955
Everything inside this window like prompts, history or files is seen by the model.

01:24:47.955 --> 01:24:52.550
Before explaining how it works, I will give you a simple example.

01:24:52.560 --> 01:24:56.629
For a simple example, I will go to chat For a simple example, I will go to chat GPT.

01:24:56.639 --> 01:24:59.980
First, I write a message in chat GPT.

01:24:59.980 --> 01:25:05.110
I say hi, I want to work with AI and HTML.

01:25:05.120 --> 01:25:08.880
If I continue this conversation, it will write the code.

01:25:08.880 --> 01:25:11.182
This is simple prompting.

01:25:11.182 --> 01:25:14.149
We get our answer through it.

01:25:14.159 --> 01:25:21.595
But if we do something else, if we give a very long prompt again and again, you will see a message.

01:25:21.595 --> 01:25:24.052
The message says it is too long.

01:25:24.052 --> 01:25:28.494
Let us see the size of the context window in chat GPT.

01:25:28.494 --> 01:25:31.137
I will search for the context window of chat GPT.

01:25:31.137 --> 01:25:34.381
It will show the context window size.

01:25:34.381 --> 01:25:39.516
Usually the model has a 128,000 token window.

01:25:39.516 --> 01:25:47.043
This means it takes 96,000 words or 250 to 300 pages of text.

01:25:47.043 --> 01:25:49.611
I will copy this text and paste it many times.

01:25:49.611 --> 01:25:53.801
I will do this until the prompt becomes too long.

01:25:53.801 --> 01:25:58.149
I will copy it and go to a word counter website.

01:25:58.159 --> 01:26:00.326
It is a famous word counter.

01:26:00.326 --> 01:26:05.270
When I paste the words here, you will see the website becomes slow.

01:26:05.280 --> 01:26:10.003
This is because there are 9,776 words in total.

01:26:10.003 --> 01:26:12.373
We put this in our prompt.

01:26:12.373 --> 01:26:15.990
It has 76,000 characters.

01:26:16.000 --> 01:26:18.950
Now suppose I paste the last text here.

01:26:18.960 --> 01:26:20.558
You will see a message.

01:26:20.558 --> 01:26:23.593
It says the long text is added as a file.

01:26:23.593 --> 01:26:25.596
The text will show up here.

01:26:25.596 --> 01:26:29.811
I will write that if I put this file in the chat, it cannot process it.

01:26:29.811 --> 01:26:32.140
The message is too long.

01:26:32.140 --> 01:26:36.550
We want to see the context window size of chat GPT.

01:26:36.560 --> 01:26:37.773
It will take time.

01:26:37.773 --> 01:26:41.830
You will see that the context window depends on the model.

01:26:41.840 --> 01:26:44.651
Open AI does not always show the exact limit.

01:26:44.651 --> 01:26:55.430
But if you see the message, it means the text is too long for one input, the file is too big, or the user interface has strict limits.

01:26:55.440 --> 01:26:59.430
If we use fewer words, we will get our If we use fewer words, we will get our answer.

01:26:59.440 --> 01:27:02.756
In the same way, when we go to codeex, we can see limits.

01:27:02.756 --> 01:27:05.092
In the new chat, we have limits.

01:27:05.092 --> 01:27:06.088
Wait a minute.

01:27:06.088 --> 01:27:07.536
I will open it here.

01:27:07.536 --> 01:27:10.431
We know that codeex has some limits.

01:27:10.431 --> 01:27:15.091
Even if we add many images, files, and documents, there are still limits.

01:27:15.091 --> 01:27:21.796
In real business projects, apps have thousands of files and millions of lines of code.

01:27:21.796 --> 01:27:25.162
No AI can read all the code at once.

01:27:25.162 --> 01:27:30.149
Developers must help codecs focus on important information.

01:27:30.159 --> 01:27:32.786
Scope sets the limits of a task.

01:27:32.786 --> 01:27:36.470
It includes files, modules, and features.

01:27:36.480 --> 01:27:38.976
Setting the right scope stops bad changes.

01:27:38.976 --> 01:27:42.950
It helps codeex focus on the right parts.

01:27:42.960 --> 01:27:45.035
Now I will tell you directly.

01:27:45.035 --> 01:27:46.762
Suppose we get an answer.

01:27:46.762 --> 01:27:48.995
How will a full developer work?

01:27:48.995 --> 01:27:52.873
For example, we will take an e-commerce store.

01:27:52.873 --> 01:27:56.115
In our example, we have an e-commerce store.

01:27:56.115 --> 01:27:59.246
A developer wants to add a discount box to a product page.

01:27:59.246 --> 01:28:03.102
The developer does not share all the code with Codeex.

01:28:03.102 --> 01:28:09.590
He only shares the product model, service, controller, form, and tests.

01:28:09.600 --> 01:28:11.287
This limits the context.

01:28:11.287 --> 01:28:13.356
Codeex can focus on the updates.

01:28:13.356 --> 01:28:17.430
It will not make bad changes in other places.

01:28:17.440 --> 01:28:19.215
Where do we use this?

01:28:19.215 --> 01:28:22.498
When we make changes, this is very helpful.

01:28:22.498 --> 01:28:24.498
We can modify things easily.

01:28:24.498 --> 01:28:27.343
You will see two or three options here.

01:28:27.343 --> 01:28:29.413
We can open it in VS Code.

01:28:29.413 --> 01:28:32.673
We have a full Metabrains project.

01:28:32.673 --> 01:28:35.382
Here it has all our files.

01:28:35.382 --> 01:28:37.649
We can run the index file.

01:28:37.649 --> 01:28:40.524
Here on the side, we have our chat.

01:28:40.524 --> 01:28:43.750
Our codeex is also running directly.

01:28:43.760 --> 01:28:46.398
Besides codeex, we have an agents option.

01:28:46.398 --> 01:28:49.244
We can use agents to do our work option.

01:28:49.244 --> 01:28:50.950
We can use agents to do our work directly.

01:28:50.960 --> 01:28:53.910
Now we will verify our GitHub account.

01:28:53.920 --> 01:28:57.430
Do you remember how I did GitHub Do you remember how I did GitHub authentication?

01:28:57.440 --> 01:29:00.950
We will authorize VS Code directly.

01:29:00.960 --> 01:29:04.294
Our workflow and personal details will be added here.

01:29:04.294 --> 01:29:08.310
This works for public and private projects.

01:29:08.320 --> 01:29:10.790
We can include this directly.

01:29:10.800 --> 01:29:15.391
If I show you the signin again, authorization comes directly.

01:29:15.391 --> 01:29:16.846
We can confirm it.

01:29:16.846 --> 01:29:20.040
Suppose we want to verify using email.

01:29:20.040 --> 01:29:22.217
The email will come using email.

01:29:22.217 --> 01:29:23.510
The email will come automatically.

01:29:23.520 --> 01:29:26.266
We will confirm the email here.

01:29:26.266 --> 01:29:29.339
These emails run through a base setup.

01:29:29.339 --> 01:29:31.410
We got the code here.

01:29:31.410 --> 01:29:33.990
Then we will verify it.

01:29:34.000 --> 01:29:38.310
Our VS Code will sign in and connect Our VS Code will sign in and connect automatically.

01:29:38.320 --> 01:29:42.870
After signing in, Metabrains connects with our co-pilot.

01:29:42.880 --> 01:29:45.177
We are running many windows.

01:29:45.177 --> 01:29:47.761
In one place, we run the agent.

01:29:47.761 --> 01:29:51.189
In another place, we use our IDE.

01:29:51.199 --> 01:29:55.030
In a third place, we use it as a In a third place, we use it as a chatbot.

01:29:55.040 --> 01:29:58.790
So, we must manage our context So, we must manage our context carefully.

01:29:58.800 --> 01:30:04.629
Context window and scope management are very important for AI software very important for AI software development.

01:30:04.639 --> 01:30:10.310
By giving the right information and clear boundaries, developers help clear boundaries, developers help codeex.

01:30:10.320 --> 01:30:13.770
It creates accurate, good and reliable code.

01:30:13.770 --> 01:30:17.466
We must look at these important things carefully.

01:30:17.466 --> 01:30:22.149
Now, our discussion is about reviewing our AI generated code.

01:30:22.159 --> 01:30:30.211
In the AI generated code, we want to see how we previously used codes like create calculator multiple times.

01:30:30.211 --> 01:30:38.973
As you can see, we have created the calculator here and you can see that all our changes are also available here.

01:30:38.973 --> 01:30:45.510
For these AI generated changes, we first need to understand two or three things.

01:30:45.520 --> 01:30:58.550
First, in this complete software we are using, whenever there are changes, the red values will be all our previous values and the green values will be our new possible changes that we have used new possible changes that we have used here.

01:30:58.560 --> 01:31:02.635
If you look here, you can first see the set display error.

01:31:02.635 --> 01:31:07.270
But now in our new code, some things have expanded.

01:31:07.280 --> 01:31:13.990
Let us suppose I directly include a prompt here saying I want a scientific prompt here saying I want a scientific calculator.

01:31:14.000 --> 01:31:17.580
Now a scientific calculator will be created here.

01:31:17.580 --> 01:31:23.110
Usually we had this one code and we can call it version one.

01:31:23.120 --> 01:31:26.576
Automatically this version of ours will be applied here.

01:31:26.576 --> 01:31:33.430
And along with this version, if we have any other versions available here, they will be used.

01:31:33.440 --> 01:31:39.910
First of all, it will take some time to think about what things were discussed in the previous context.

01:31:39.920 --> 01:31:43.830
It will review what discussions we were having previously.

01:31:43.840 --> 01:31:49.750
After all those discussions, our code will automatically start generating will automatically start generating here.

01:31:49.760 --> 01:31:52.275
All right, it is reconnecting with our work.

01:31:52.275 --> 01:32:02.070
Our connection with the model is being created to see how a complete connection will be generated and how our thinking will work on a larger scale.

01:32:02.080 --> 01:32:06.671
Usually when we are looking at such a code we have to do validation.

01:32:06.671 --> 01:32:09.469
We can separate our unified difference from here.

01:32:09.469 --> 01:32:14.470
We call this split and we call the other one unified.

01:32:14.480 --> 01:32:22.235
In the split view our complete previous code base is on one side and our new code is included on the other side.

01:32:22.235 --> 01:32:30.229
In the previous one you can see the display error and here you can see how much our error evaluation is available now.

01:32:30.239 --> 01:32:33.996
Similarly our if action is also available here.

01:32:33.996 --> 01:32:41.916
We can see how much if action we had previously and after that how many evaluations are coming in our run action.

01:32:41.916 --> 01:32:42.931
All right.

01:32:42.931 --> 01:32:46.702
So all these things are being directly included in our system.

01:32:46.702 --> 01:32:49.565
We are looking at multiple changes here.

01:32:49.565 --> 01:32:53.030
You can see that our connection is being created once again.

01:32:53.040 --> 01:32:56.534
Here we can change the model to a very simple one.

01:32:56.534 --> 01:33:01.074
Make the speed fast and also change the reasoning here.

01:33:01.074 --> 01:33:05.974
Now besides all these things, we have two options available here.

01:33:05.974 --> 01:33:07.910
Review and undo.

01:33:07.920 --> 01:33:12.898
In the review option, we can directly review our code once in the first scenario.

01:33:12.898 --> 01:33:17.512
And undo works exactly like our version control system.

01:33:17.512 --> 01:33:21.350
It keeps multiple versions in our adopted system.

01:33:21.360 --> 01:33:29.110
Here you can see that our system is now running and it is telling us that it is upgrading the existing HTML.

01:33:29.120 --> 01:33:32.565
Now let us suppose I take you to this HTML file.

01:33:32.565 --> 01:33:35.844
I will show all the differences here.

01:33:35.844 --> 01:33:40.629
They are here now and we will also enable the rich preview.

01:33:40.639 --> 01:33:43.149
Now you can see that this is our newer file.

01:33:43.149 --> 01:33:50.074
Even after the newer file when we make changes again those changes will also be visible here.

01:33:50.074 --> 01:33:53.301
You will see plus 32 and minus 21.

01:33:53.301 --> 01:34:00.174
This shows how many lines of code were removed and how many lines of code were added to our total system.

01:34:00.174 --> 01:34:06.796
When both these things work together we automatically start getting our response and work results.

01:34:06.796 --> 01:34:09.750
It shows how we are managing things.

01:34:09.760 --> 01:34:10.452
All right.

01:34:10.452 --> 01:34:14.310
So this is our very detailed working process.

01:34:14.320 --> 01:34:17.021
Here you can see all the changes.

01:34:17.021 --> 01:34:27.669
For a simple example as we are reviewing now the title was previously calculator but now our new title has become scientific now our new title has become scientific calculator.

01:34:27.679 --> 01:34:28.433
All right.

01:34:28.433 --> 01:34:35.510
If we look here now all the design changes of our calculator are shown here with plus and minus signs.

01:34:35.520 --> 01:34:41.356
Also you can see that if we want to add something here we can directly include a local comment.

01:34:41.356 --> 01:34:45.971
For example I can say here I want round buttons.

01:34:45.971 --> 01:34:46.489
Okay.

01:34:46.489 --> 01:34:49.247
So now we want our round buttons.

01:34:49.247 --> 01:34:53.287
As soon as I post this comment you can see it is included here.

01:34:53.287 --> 01:34:55.268
Now this comment is added.

01:34:55.268 --> 01:34:56.183
All right.

01:34:56.183 --> 01:35:01.489
Similarly if we go here I will say I want more buttons.

01:35:01.489 --> 01:35:04.311
I am making very simple changes in front of you.

01:35:04.311 --> 01:35:06.645
I will add the comment.

01:35:06.645 --> 01:35:09.016
Now there are two comments here.

01:35:09.016 --> 01:35:09.750
All right.

01:35:09.760 --> 01:35:15.696
In the same way at the end of this file I will say that we need simpler functionality here.

01:35:15.696 --> 01:35:16.247
Okay.

01:35:16.247 --> 01:35:20.310
I will say simple functionality please.

01:35:20.320 --> 01:35:21.182
All right.

01:35:21.182 --> 01:35:23.510
This comment is added here.

01:35:23.520 --> 01:35:27.429
After that we can go to the end or just go to the start.

01:35:27.429 --> 01:35:30.672
In the start I will change our name here.

01:35:30.672 --> 01:35:34.339
Change the name as metabrains cal.

01:35:34.339 --> 01:35:35.091
Okay.

01:35:35.091 --> 01:35:37.350
Metabrains cal.

01:35:37.360 --> 01:35:38.241
All right.

01:35:38.241 --> 01:35:40.445
Now our comment is added.

01:35:40.445 --> 01:35:43.162
You can see that three or four comments are here.

01:35:43.162 --> 01:35:51.350
Now in our calculator we have a comment in row number 46 and a comment in row number 102.

01:35:51.360 --> 01:35:57.350
After that there is a comment in row number 200 and then a comment in row number six.

01:35:57.360 --> 01:36:03.750
Now what we have to do here is I can say make the possible changes asked.

01:36:03.760 --> 01:36:04.006
Okay.

01:36:04.006 --> 01:36:11.173
What will happen here is that based on the changes we included in these comments, the changes will happen at those exact points.

01:36:11.173 --> 01:36:16.080
I will only show you this one change that we demanded at the end in the comments.

01:36:16.080 --> 01:36:20.315
We will see how it changes the name of our scientific calculator here.

01:36:20.315 --> 01:36:23.078
And this is a very advanced feature.

01:36:23.078 --> 01:36:32.608
We are reviewing our complete AI generated changes to see how our reviews can be applied on a larger scale and how we can include them.

01:36:32.608 --> 01:36:34.868
It will take some time to think.

01:36:34.868 --> 01:36:42.470
Obviously you can see that it is thinking here and after that it says I will apply the review comments directly.

01:36:42.480 --> 01:36:45.830
First of all our name will be changed to First of all our name will be changed to metabrains.

01:36:45.840 --> 01:36:49.119
After that the calculator buttons will be made circular.

01:36:49.119 --> 01:36:53.189
A few practical scientific buttons will be included.

01:36:53.199 --> 01:36:55.669
Here you can see our calculation.

01:36:55.679 --> 01:36:58.496
Metabrains cal is written here.

01:36:58.496 --> 01:37:03.910
After that we also included a comment here that we want our buttons to be rounded.

01:37:03.920 --> 01:37:10.188
So you can see that by including height, aspect ratio, border radius and all these things.

01:37:10.188 --> 01:37:14.851
It has provided us with some rounded buttons that we can directly see here.

01:37:14.851 --> 01:37:15.813
All right.

01:37:15.813 --> 01:37:24.149
So all these things are greatly included in our working process here and through this we can include it in our system and it will work here.

01:37:24.149 --> 01:37:27.059
Now we will get all our changes here.

01:37:27.059 --> 01:37:34.156
You can see that whatever visual changes we have it has included some lines in a file and showed us the changes here.

01:37:34.156 --> 01:37:36.347
We can also open that here.

01:37:36.347 --> 01:37:36.855
Okay.

01:37:36.855 --> 01:37:42.763
After that for the next changes it makes you can see our thinking process here.

01:37:42.763 --> 01:37:51.750
In the thinking process as it is including our constants and other values these files will automatically come here side by side.

01:37:51.760 --> 01:37:53.706
Now it has updated our file.

01:37:53.706 --> 01:37:55.675
We have all the commands here.

01:37:55.675 --> 01:38:11.189
As soon as we open this in our browser all our discussed changes are here like metabrains cal our buttons have become rounded and now if we include anything here that thing will automatically be directly included here.

01:38:11.199 --> 01:38:12.793
Okay, our error came here.

01:38:12.793 --> 01:38:15.069
We are seeing everything working.

01:38:15.069 --> 01:38:15.842
All right.

01:38:15.842 --> 01:38:19.707
If we suppose we need the value of pi here, we get our pi value.

01:38:19.707 --> 01:38:24.470
If we need the value of log 8, we can directly input it here.

01:38:24.480 --> 01:38:29.510
Also, you can see that this delete option is working directly here too.

01:38:29.520 --> 01:38:34.349
If we look at all the signs here, every sign that we have is working very easily.

01:38:34.349 --> 01:38:38.950
We can directly enter all our values here.

01:38:38.960 --> 01:38:45.651
If there is no responsiveness, we can go ahead and directly include responsiveness in our code later.

01:38:45.651 --> 01:38:50.000
But code review is the main thing that I have discussed with you.

01:38:50.000 --> 01:38:53.774
After this, our next discussion is related to our prompt hints.

01:38:53.774 --> 01:38:57.557
Next, we discuss the main usage of a prompt library.

01:38:57.557 --> 01:39:02.470
We will see how we can use it and where more options are can use it and where more options are included.

01:39:02.480 --> 01:39:04.038
First, I come here.

01:39:04.038 --> 01:39:09.750
Instead of using everything, I will search the prompt library in codeex.

01:39:09.760 --> 01:39:12.550
Here you see codeex prompting.

01:39:12.560 --> 01:39:22.310
First, I tell you this is a built-in collection of reusable workflows, templates, and skills in OpenAI codeex and Agentic CLI.

01:39:22.320 --> 01:39:26.709
When I go to prompting, you see we often use prompts.

01:39:26.719 --> 01:39:31.590
You interact with the codeex by sending prompts that describe what you want.

01:39:31.600 --> 01:39:34.310
Example prompts are shown here.

01:39:34.320 --> 01:39:36.359
Thread is a single session.

01:39:36.359 --> 01:39:41.111
It has your prompt plus the model outputs and tool calls that follow.

01:39:41.111 --> 01:39:44.195
A thread can include multiple prompts.

01:39:44.195 --> 01:39:48.072
We use a chain of process to take things forward.

01:39:48.072 --> 01:39:52.470
I will explain this exact process right here in our codeex.

01:39:52.480 --> 01:39:56.629
In codeex, we go to our main user In codeex, we go to our main user settings.

01:39:56.639 --> 01:40:00.390
Inside these settings, we have Inside these settings, we have personalization.

01:40:00.400 --> 01:40:05.109
In personalization, our own custom instructions are included.

01:40:05.119 --> 01:40:10.390
We can also switch our AI personality from pragmatic to friendly.

01:40:10.400 --> 01:40:13.185
Both of these personalization options are here.

01:40:13.185 --> 01:40:21.669
In custom instructions, we can include all custommade personalized instructions that we want in our tool.

01:40:21.679 --> 01:40:25.270
It is quite simple to include our text It is quite simple to include our text responses.

01:40:25.280 --> 01:40:32.671
But sometimes we must see our clear deviation and how we are working on stuff and how these custom instructions work.

01:40:32.671 --> 01:40:39.030
We have our memory which we can induce right here in our experimental induce right here in our experimental form.

01:40:39.040 --> 01:40:45.270
We see how our things can be included and how we can take our many processes and how we can take our many processes forward.

01:40:45.280 --> 01:40:49.830
Our standard options show how we will best include our own memory.

01:40:49.840 --> 01:40:53.189
First is the main enable memories.

01:40:53.199 --> 01:40:56.709
Second is our good tool assisted Second is our good tool assisted memories.

01:40:56.719 --> 01:41:03.990
We can also involve tool assisted memories and involve all our process or workability in it.

01:41:04.000 --> 01:41:07.510
Next thing is our own custom prompt Next thing is our own custom prompt libraries.

01:41:07.520 --> 01:41:10.070
What is a good prompt library?

01:41:10.080 --> 01:41:15.430
I will tell you first that our prompt library is a great reusable prompt hub.

01:41:15.440 --> 01:41:19.350
In this we can do our text discussion multiple times.

01:41:19.360 --> 01:41:22.313
We can do multiple workings for our single tool.

01:41:22.313 --> 01:41:27.367
We must see one more thing here from the chat GPT side.

01:41:27.367 --> 01:41:31.266
There is no prompt library available here yet.

01:41:31.266 --> 01:41:33.947
We have clear information about basic prompting.

01:41:33.947 --> 01:41:39.045
But if I talk about the claude code, there is a distinct prompt library available.

01:41:39.045 --> 01:41:45.189
We can go there and see the many prompts are collected from the various anthropic guides.

01:41:45.199 --> 01:41:53.270
This includes our common workflows and best practices and how anthropic teams take clawed code forward.

01:41:53.280 --> 01:41:57.477
If I want, we can also see the core understand prompts.

01:41:57.477 --> 01:42:06.950
We see how we can use our own prompts if we need a new prompt for git, release, data, automate or product.

01:42:06.960 --> 01:42:14.753
A set number of proper prompts are available for every single thing. we can reuse them multiple times over.

01:42:14.753 --> 01:42:20.070
We can utilize multiple variations or our many utilize multiple variations or our many functions.

01:42:20.080 --> 01:42:23.355
This very same thing is available here in our claude.

01:42:23.355 --> 01:42:31.669
But if we go to our codeex then until now we do not have these full prompt libraries available.

01:42:31.679 --> 01:42:34.399
We can do one other good thing here.

01:42:34.399 --> 01:42:37.585
We can come right here and ask a prompt question.

01:42:37.585 --> 01:42:43.410
If we go into chat GPT and for our codeex we include our own best prompts.

01:42:43.410 --> 01:42:48.629
I can say I want a whole new prompt library for my codeex.

01:42:48.639 --> 01:42:54.229
It will then give a good reusable clean codeex prompt library.

01:42:54.239 --> 01:42:57.485
Inside it we have all our good useful prompts.

01:42:57.485 --> 01:43:12.229
We have our bug fixes, text test generator, code review, refactoring, feature builder, API design, performance optimization and security audit prompt.

01:43:12.239 --> 01:43:15.990
All these things will involve in that exact thing.

01:43:16.000 --> 01:43:18.950
From there we will take and use it well.

01:43:18.960 --> 01:43:24.870
These various things are included in our entire core system on a large scale.

01:43:24.880 --> 01:43:30.203
We must look at all these many things on a large scale to see how we can reuse them.

01:43:30.203 --> 01:43:36.790
We will copy it and come inside this main system to use all our many this main system to use all our many prompts.

01:43:36.800 --> 01:43:39.517
We will not use these exact things.

01:43:39.517 --> 01:43:44.149
But besides this, we have all our 12 core besides this, we have all our 12 core prompts.

01:43:44.159 --> 01:43:48.899
As we go forward, our prompt library will increase even more.

01:43:48.899 --> 01:43:54.635
From 1 to 12 are many different options will be used and we will include them.

01:43:54.635 --> 01:44:00.382
These things are used very much inside the entire are used very much inside the entire system with this.

01:44:00.382 --> 01:44:05.030
We have a lot of great automation in our work on a large scale.

01:44:05.040 --> 01:44:07.016
We can use that well.

01:44:07.016 --> 01:44:11.439
I will tell you we also have cool automations here on the side.

01:44:11.439 --> 01:44:17.830
We can run our day brief, week review or smart project monitor.

01:44:17.840 --> 01:44:22.631
But besides that if we look at our cool templates we have very many.

01:44:22.631 --> 01:44:31.350
Now our next discussion relates to integration we will see how to perform AI enhanced we will see how to perform AI enhanced CI/CD.

01:44:31.360 --> 01:44:36.550
First I will explain the full definition of CI/CD.

01:44:36.560 --> 01:44:40.070
CI stands for continuous integration.

01:44:40.080 --> 01:44:44.310
CD stands for continuous delivery and CD stands for continuous delivery and deployment.

01:44:44.320 --> 01:44:49.973
Usually when enterprise level workflow loops run, we have multiple projects.

01:44:49.973 --> 01:44:58.667
We have standalone projects, collaborative projects or autonomous projects connected to multiple companies, industries and businesses.

01:44:58.667 --> 01:45:02.550
For them, we must look at integration and deployment.

01:45:02.560 --> 01:45:08.235
This is a DevOps methodology that automates building, testing and releasing software.

01:45:08.235 --> 01:45:10.861
We can discuss this as automation.

01:45:10.861 --> 01:45:20.502
This pipeline allows development teams to ship code updates frequently, safely, and reliably while catching bugs early in the development cycle.

01:45:20.502 --> 01:45:28.470
Usually, we do CI/CD at an industrial or enterprise level where we need automation.

01:45:28.480 --> 01:45:31.270
First, we have continuous integration.

01:45:31.280 --> 01:45:37.386
It is a practice where developers regularly merge their code into a central repository like GitHub or GitLab.

01:45:37.386 --> 01:45:45.990
Every time code is merged, an automated system builds the application and runs tests until the integration and runs tests until the integration finishes.

01:45:46.000 --> 01:45:50.331
This ensures that the new code does not break the existing code base.

01:45:50.331 --> 01:45:54.070
It allows teams to catch errors instantly.

01:45:54.080 --> 01:45:58.283
Then we have continuous delivery versus continuous deployment.

01:45:58.283 --> 01:46:00.663
How can we use continuous deployment.

01:46:00.663 --> 01:46:01.830
How can we use CI/CD?

01:46:01.840 --> 01:46:05.270
First, it gives a faster time to market.

01:46:05.280 --> 01:46:10.629
New features and bug fixes reach users in hours instead of weeks or months.

01:46:10.639 --> 01:46:16.229
There are fewer bugs, easier rollbacks, and better developer productivity.

01:46:16.239 --> 01:46:25.030
CI/CD pipelines can be used in GitHub actions, GitLab CI, Jenkins, and actions, GitLab CI, Jenkins, and CircleCI.

01:46:25.040 --> 01:46:27.759
I will search for codeex on Google.

01:46:27.759 --> 01:46:35.910
Now, for example, if I share here that I want this in codeex, then we can also do that. how it becomes possible.

01:46:35.920 --> 01:46:43.910
Integrating the codeex command line into the pipeline enables open AI codeex to automatically evaluate build failures.

01:46:43.920 --> 01:46:50.163
It analyzes vulnerability scans and proposes minimal changes required to make the tests pass.

01:46:50.163 --> 01:46:53.432
It executes code quality checks directly.

01:46:53.432 --> 01:46:57.669
It also generates remediation patches or pull generates remediation patches or pull requests.

01:46:57.679 --> 01:47:05.910
Usually when we talk about our process, we can perform CI/CD in multiple forms inside our projects.

01:47:05.920 --> 01:47:14.470
Here in this interface and outside it, if I go directly to the terminal, I can run the CI/CD pipeline.

01:47:14.480 --> 01:47:15.839
How can I do this?

01:47:15.839 --> 01:47:19.910
First, I will search for codeex CLI.

01:47:19.920 --> 01:47:23.779
The developer platform will open which we can access directly.

01:47:23.779 --> 01:47:25.497
Here we must install it.

01:47:25.497 --> 01:47:29.334
I will come here and command the system to install codeex.

01:47:29.334 --> 01:47:32.342
We will copy and paste the required command.

01:47:32.342 --> 01:47:34.887
You will see that codeex is already set up here.

01:47:34.887 --> 01:47:38.552
Because of this, we do not need to install it again.

01:47:38.552 --> 01:47:42.691
We simply type our codeex command and it will start running.

01:47:42.691 --> 01:47:45.109
You have seen this here too.

01:47:45.119 --> 01:47:49.750
Whenever we give a command, we have a terminal option available on the side.

01:47:49.760 --> 01:47:54.296
Inside this, we can automatically initiate our working process.

01:47:54.296 --> 01:47:59.669
We also have a browser option to run CI/CD have a browser option to run CI/CD pipelines.

01:47:59.679 --> 01:48:07.392
Usually, continuous integration and continuous deployment have become a foundation of modern software engineering.

01:48:07.392 --> 01:48:14.639
Traditional CI/CD pipelines automate the building, testing, and deployment processes.

01:48:14.639 --> 01:48:19.510
This reduces manual effort and ensures consistent software delivery.

01:48:19.520 --> 01:48:30.704
With the introduction of AI powered development tools like Open AI, enhanced CI and CD introduces a new layer of intelligence into the software delivery life cycle.

01:48:30.704 --> 01:48:36.575
Instead of merely reporting failures, AI systems can investigate the root cause.

01:48:36.575 --> 01:48:41.319
They propose correlations and create pull requests containing fixes.

01:48:41.319 --> 01:48:46.796
This dramatically reduces the time developers spend troubleshooting failed builds.

01:48:46.796 --> 01:48:54.470
It allows engineering teams to focus on high value work such as feature development and architectural as feature development and architectural improvement.

01:48:54.480 --> 01:48:56.841
Let me show you a simple example.

01:48:56.841 --> 01:48:58.858
We can take any system here.

01:48:58.858 --> 01:49:02.624
When we give a prompt, you can see our working process begins.

01:49:02.624 --> 01:49:06.732
We get options to debug an issue or review a plan.

01:49:06.732 --> 01:49:11.910
I will select GitHub and ask it to review the newest and ask it to review the newest repository.

01:49:11.920 --> 01:49:14.415
The newest repository will appear.

01:49:14.415 --> 01:49:17.847
Then I will command it to analyze the latest pull request.

01:49:17.847 --> 01:49:27.350
It must generate unit tests for newly added functions, modified business logic and edge cases to improve our error handling to improve our error handling completely.

01:49:27.360 --> 01:49:31.773
As soon as I include this, the error handling scenarios will become much better.

01:49:31.773 --> 01:49:37.189
The other responses will also appear here for us to analyze directly.

01:49:37.199 --> 01:49:39.970
Usually the GitHub workflow is infused here.

01:49:39.970 --> 01:49:46.790
Inside the GitHub workflow, we can directly use our other generations or directly use our other generations or processes.

01:49:46.800 --> 01:49:51.511
Our other regions and our understanding will also appear side by side.

01:49:51.511 --> 01:49:53.671
I must tell you another thing.

01:49:53.671 --> 01:49:59.590
We usually face a concern about how to check our processes inside out on a larger scale.

01:49:59.600 --> 01:50:01.669
We will see that in a much better form.

01:50:01.679 --> 01:50:08.392
Now in the CI/CD pipeline, you can see the local workspace is empty.

01:50:08.392 --> 01:50:12.518
The GitHub account is authenticated but git is not available.

01:50:12.518 --> 01:50:18.629
If we set up these things, we can cross-check our CI/CD pipelines.

01:50:18.639 --> 01:50:24.629
We prepare a repository and use the CI/CD pipeline perfectly.

01:50:24.639 --> 01:50:27.198
Here I will give you the example of a pipeline.

01:50:27.198 --> 01:50:35.744
If you prepare a pipeline of build which have a request, it has many stage such as names and tests will appear here.

01:50:35.744 --> 01:50:41.598
If you connect codecs here, then our AI tasks can work side by side with it.

01:50:41.598 --> 01:50:46.151
Our next topic is putting codeex into our work process.

01:50:46.151 --> 01:50:49.751
This means adding codecs to our build system.

01:50:49.751 --> 01:50:53.254
When we do this, the system helps us find problems.

01:50:53.254 --> 01:50:59.829
If a build stops working or a task breaks, the tool sees the code quality issues.

01:50:59.829 --> 01:51:04.870
Before, people had to look at every single problem by hand.

01:51:04.880 --> 01:51:07.577
Now the system looks at the failures for us.

01:51:07.577 --> 01:51:11.772
It gives ideas to fix them and creates tests.

01:51:11.772 --> 01:51:15.809
It can even make pull requests with good answers.

01:51:15.809 --> 01:51:20.310
In a normal process, a person sends code to GitHub.

01:51:20.320 --> 01:51:24.629
Then our complete system starts running Then our complete system starts running automatically.

01:51:24.639 --> 01:51:27.426
Things begin to work on their own.

01:51:27.426 --> 01:51:30.509
We usually watch these actions in our deployment area.

01:51:30.509 --> 01:51:33.961
For enterprises, this saves a lot of time.

01:51:33.961 --> 01:51:38.709
People do not have to fix the same small problems again.

01:51:38.719 --> 01:51:41.634
The codeex assistant helps keep the work active.

01:51:41.634 --> 01:51:45.562
It understands the whole process of how things run.

01:51:45.562 --> 01:51:49.510
We like having a place without mistakes.

01:51:49.520 --> 01:51:52.550
Now let us look at consistency.

01:51:52.560 --> 01:51:55.830
This is a very important benefit.

01:51:55.840 --> 01:51:59.834
Sometimes working directly with these pipelines can be hard.

01:51:59.834 --> 01:52:03.189
The steps become difficult to manage.

01:52:03.199 --> 01:52:06.470
First I will go to our plug-in section.

01:52:06.480 --> 01:52:09.621
We can see the GitHub plugin here.

01:52:09.621 --> 01:52:13.174
Next I will search for codeex in the bar.

01:52:13.174 --> 01:52:17.834
We see many results but I want to find it in the profile settings.

01:52:17.834 --> 01:52:24.709
I look at the list of options like packages copilot pages and security.

01:52:24.719 --> 01:52:27.510
Here I will search for the codeex.

01:52:27.520 --> 01:52:29.752
And here we have our codeex.

01:52:29.752 --> 01:52:33.510
We can also search in GitHub or settings.

01:52:33.520 --> 01:52:36.323
Then I decide to grant access.

01:52:36.323 --> 01:52:39.669
To do this, I open our repository.

01:52:39.679 --> 01:52:42.347
I click on the code button and copy the link.

01:52:42.347 --> 01:52:48.070
I will ask the chat, do you have access to this project?

01:52:48.080 --> 01:52:57.750
The system will now check if it can reach the repository and provide us with it and how we can initiate our working or a larger scale.

01:52:57.760 --> 01:53:02.097
Sometimes we have to look at these details ourselves also.

01:53:02.097 --> 01:53:07.674
We can take a complete process out here and our generation will be completed in that.

01:53:07.674 --> 01:53:11.265
This is usually present at a lesser extent.

01:53:11.265 --> 01:53:14.697
But now we will initiate a full-fledged process here.

01:53:14.697 --> 01:53:20.157
You will see that it has told us here that yes, I can access the repository.

01:53:20.157 --> 01:53:24.629
The access to our repository has also arrived here.

01:53:24.639 --> 01:53:28.314
The second thing it said is that our default branch is main.

01:53:28.314 --> 01:53:37.830
Visibility is public and effective permissions in the session are admin, maintain, push, pull and triage.

01:53:37.840 --> 01:53:43.449
I can simply say here that we now have to include an agents.md file inside this.

01:53:43.449 --> 01:53:47.444
This will directly include it and give it to us.

01:53:47.444 --> 01:53:51.906
But the thing is we cannot create things inside this.

01:53:51.906 --> 01:53:59.591
So right now we will only cross-ch checkck our agents.mmd file here to see if it is directly available to us or not.

01:53:59.591 --> 01:54:01.319
These are our things.

01:54:01.319 --> 01:54:04.904
I will now take our full detailed discussion.

01:54:04.904 --> 01:54:13.223
You will see that directly after just 1 second our agents.md file has been included here inside it.

01:54:13.223 --> 01:54:15.785
As you see git isn't available.

01:54:15.785 --> 01:54:20.470
So here after inspecting it has directly arrived.

01:54:20.480 --> 01:54:28.698
I can give access here to directly push the code to see how we can improve or include things on a large scale side by side.

01:54:28.698 --> 01:54:31.868
Another very important thing is running here.

01:54:31.868 --> 01:54:39.334
Usually in a base pipeline I could not run git push origin here because the directory is not a git repository.

01:54:39.334 --> 01:54:42.528
Git is not installed in our current shell.

01:54:42.528 --> 01:54:45.746
Let us suppose we want to install git.

01:54:45.746 --> 01:54:47.750
How can we do that?

01:54:47.760 --> 01:54:50.026
First of all, we will open our PowerShell.

01:54:50.026 --> 01:54:52.254
Here we come inside this one.

01:54:52.254 --> 01:54:54.945
Here I say our PowerShell.

01:54:54.945 --> 01:54:57.529
This is our PowerShell window.

01:54:57.529 --> 01:55:01.847
Coming directly inside PowerShell, we will state our git version.

01:55:01.847 --> 01:55:06.637
Here you are seeing that the git version is available to us here.

01:55:06.637 --> 01:55:09.669
Let us suppose we want to install our git.

01:55:09.679 --> 01:55:16.709
If we use this directly, you are seeing that now we will say we want to install git with our basic widget.

01:55:16.719 --> 01:55:19.527
Automatically our widget will be installed here.

01:55:19.527 --> 01:55:23.980
On the basis of that widget, we will take our things inside running.

01:55:23.980 --> 01:55:27.233
Usually these things are not explained to us.

01:55:27.233 --> 01:55:31.038
We are just initiating our production and working on a large scale.

01:55:31.038 --> 01:55:33.641
Here it will take some time to scale.

01:55:33.641 --> 01:55:34.950
Here it will take some time to install.

01:55:34.960 --> 01:55:37.990
Until it installs, we will wait here.

01:55:38.000 --> 01:55:41.995
Now due to some issues our git is not becoming active.

01:55:41.995 --> 01:55:44.560
I tried a lot to activate our git.

01:55:44.560 --> 01:55:49.030
You are seeing the prefix branch prefix is working.

01:55:49.040 --> 01:55:50.696
Everything is working.

01:55:50.696 --> 01:55:54.188
We usually did not include our commit instructions.

01:55:54.188 --> 01:56:00.790
But still it is possible that by opening these things all these items come into these things all these items come into working.

01:56:00.800 --> 01:56:09.830
But still, as a matter of fact, the discussion here is that when integrating codeex, organizations start in non-production environments.

01:56:09.840 --> 01:56:14.550
This allows codeex to analyze failures and generate suggestions.

01:56:14.560 --> 01:56:21.270
Once the team gains confidence in the results, they can gradually introduce more advanced workflows.

01:56:21.280 --> 01:56:26.870
These include automated pull request generations and our AI assisted bug fixing.

01:56:26.870 --> 01:56:34.101
Overall, codeex acts as an intelligent engineering assistant inside our CI/CD pipeline.

01:56:34.101 --> 01:56:38.768
It will overall help us in building all our things.

01:56:38.768 --> 01:56:41.430
These entire matters have been discussed here.

01:56:41.440 --> 01:56:49.270
An autofix workflow begins the moment a developer pushes code to a repository or submits a pull request for review.

01:56:49.280 --> 01:57:06.709
The CI/CD pipeline automatically starts a series of validation processes such as compiling the application, running automated tests, checking code formatting standards, verifying linting rules, and executing security scans.

01:57:06.719 --> 01:57:18.870
In traditional software development environments, any failure in these checks would require a developer to manually investigate logs, identify the source of the issue, and implement a source of the issue, and implement a fix.

01:57:18.880 --> 01:57:24.535
With codeex powered autofix workflows, the process becomes significantly more efficient.

01:57:24.535 --> 01:57:34.390
Instead of merely reporting that something failed, the workflow can immediately begin analyzing the problem and preparing a potential solution.

01:57:34.400 --> 01:57:44.550
This transforms CI/CD from a passive validation system into an active participant in software maintenance and quality assurance.

01:57:44.560 --> 01:57:50.531
Once a failure is detected, Codeex examines all available information related to the problem.

01:57:50.531 --> 01:58:05.750
This includes error messages, build logs, test outputs, recently modified files, project documentation, repository instructions, and any development guidelines defined in agents.mmd.

01:58:05.760 --> 01:58:14.229
By reviewing these sources together, Codeex gains a much broader understanding of the issue than a simple rule-based automation tool.

01:58:14.239 --> 01:58:29.350
For example, if a login related test starts failing after a recent update, Codeex can inspect the authentication logic, compare the recent code changes, review the affected test cases, and determine where the behavior diverged

01:58:29.360 --> 01:58:31.430
from expectations.

01:58:31.440 --> 01:58:37.910
This contextual understanding is one of the major advantages of AI assisted development workflows.

01:58:37.920 --> 01:58:43.589
After gathering the necessary information, Codeex performs root cause information, Codeex performs root cause analysis.

01:58:43.599 --> 01:58:51.990
Rather than attempting random modifications until a test passes, it tries to determine why the failure occurred in the first place.

01:58:52.000 --> 01:59:08.550
The underlying issue could be a missing import statement, a renamed function that was not updated everywhere, a changed API response structure, an incorrect configuration value, a dependency upgrade that introduced breaking changes, or a test case that no

01:59:08.560 --> 01:59:12.070
longer reflects the intended application longer reflects the intended application behavior.

01:59:12.080 --> 01:59:23.513
By identifying the actual source of the problem, codecs can generate fixes that are more accurate, maintainable, and less likely to introduce new defects elsewhere in the system.

01:59:23.513 --> 01:59:29.504
Once the root cause has been identified, Codeex generates a proposed solution.

01:59:29.504 --> 01:59:34.950
A well-designed autofix workflow emphasizes minimal and focused changes.

01:59:34.960 --> 01:59:43.109
The goal is not to rewrite large portions of the application, but to make the smallest possible modification that resolves the failure.

01:59:43.119 --> 01:59:49.430
This approach reduces risk and makes the resulting changes easier for developers to review.

01:59:49.440 --> 02:00:00.867
For example, if a build fails because of an incorrect import path, codec should update only the affected import statement rather than refactoring multiple unrelated files.

02:00:00.867 --> 02:00:17.430
Developers can also provide explicit instructions to guide this process, such as requesting that only necessary files be modified, preserving existing coding conventions, and updating tests only when required to reflect legitimate behavior changes.

02:00:17.440 --> 02:00:22.537
Following fix generation, validation becomes the next critical step.

02:00:22.537 --> 02:00:28.535
The proposed solution is tested using the same pipeline checks that originally detected the problem.

02:00:28.535 --> 02:00:40.149
Automated builds, unit tests, integration tests, linting tools, and security scans are executed again to confirm that the issue has been resolved successfully.

02:00:40.159 --> 02:00:51.189
If the validation process still detects failures, developers can provide additional context or refined instructions and allow codeex to perform another iteration.

02:00:51.199 --> 02:00:59.350
This feedback loop helps improve solution quality while ensuring that every proposed change is verified before moving forward.

02:00:59.360 --> 02:01:06.229
Even when automated validation succeeds, human review remains an essential part of the workflow.

02:01:06.239 --> 02:01:20.950
Developers examine the AI generated modifications to confirm that the solution is technically correct, aligns with business requirements, follows architectural standards, and does not introduce unintended side effects.

02:01:20.960 --> 02:01:33.669
This review process also provides accountability and governance which are especially important in enterprise environments where compliance, security and maintainability requirements must be carefully enforced.

02:01:33.679 --> 02:01:41.109
Once the fix has been approved, the changes can be merged into the main branch and included in future branch and included in future deployments.

02:01:41.119 --> 02:01:48.070
Over time, teams can analyze recurring issues and improve their development processes accordingly.

02:01:48.080 --> 02:02:01.830
Repository instructions, testing strategies, agents.mmd guidelines, and CI/CD configurations can be updated to help codeex handle similar situations more effectively in the future.

02:02:01.840 --> 02:02:14.310
As a result, autofix workflows not only resolve immediate problems, but also contribute to continuous improvement across the software development [clears throat] life cycle, enabling teams to deliver higher quality software

02:02:14.320 --> 02:02:19.750
faster while reducing the manual effort required to maintain complex systems.

02:02:19.760 --> 02:02:25.025
Now the discussion we have is related to configuring automated bug resolution.

02:02:25.025 --> 02:02:32.100
We can say this on a large scale in our codeex along with other things. a discussion was going on.

02:02:32.100 --> 02:02:37.082
This is most valuable for enterprise use cases for open AI codecs.

02:02:37.082 --> 02:02:55.092
Instead of developers manually investigating every test field, linting error, securing warnings, or production defects, codeex can analyze the issue, identify the affected files, generate a proposed fix, and create a pull request for human review.

02:02:55.092 --> 02:03:05.510
This significantly reduces the time spent on repetitive maintenance tasks while allowing focus for engineers to concentrate on high-level architectural business problems.

02:03:05.520 --> 02:03:16.470
In modern software teams, bugs are often discovered through CI/CD pipelines, monitoring systems, issue trackers, and security scanners.

02:03:16.480 --> 02:03:29.270
Codeex can integrate into these workflows so that when an issue occurs, the AI automatically receives the failure logs, repository context, coding standards, and our project instructions.

02:03:29.280 --> 02:03:29.926
All right.

02:03:29.926 --> 02:03:36.550
The critical aspect we have for automated bug resolution is defining clear boundaries.

02:03:36.560 --> 02:03:42.133
Enterprise organizations should never allow AI to directly deploy files into production.

02:03:42.133 --> 02:03:50.634
Instead, codec should generate code changes, execute tests, and create pull requests that require developer approval.

02:03:50.634 --> 02:03:56.550
This maintains governance and accountability while still benefiting from automation.

02:03:56.560 --> 02:04:01.990
Human reviewers can remain fully responsible for validating the basic responsible for validating the basic logic.

02:04:02.000 --> 02:04:04.994
Now, let me tell you a very important thing.

02:04:04.994 --> 02:04:09.910
Our agents.mmd file plays a crucial role in the process.

02:04:09.910 --> 02:04:17.830
What happens is they provide our project specifications and instructions that guide codeex's decision-making during bug resolution.

02:04:17.840 --> 02:04:27.655
These instructions define the coding conventions, testing requirements, security constraints, dependency policies, and our architectural patterns.

02:04:27.655 --> 02:04:34.950
The more structured the agents.mmd file is, the more accurate and reliable the fixes become.

02:04:34.960 --> 02:04:41.372
Organizations must look at another thing alongside agents.mmd confidence thresholds.

02:04:41.372 --> 02:04:53.196
For example, codecs may automatically fix linting errors and formatting issues while security vulnerabilities or database related bugs require a mandatory senior engineer review.

02:04:53.196 --> 02:04:58.286
An example of this is that first of all we have to do this step by step.

02:04:58.286 --> 02:05:06.390
The first part of our process is to identify our bug trigger resources and define where the bug reports originate.

02:05:06.400 --> 02:05:18.629
Usually what happens is we see this in our CI/CD builds or we can see this in our unit tests we perform or we can see this in our integration test failures.

02:05:18.639 --> 02:05:24.229
Sometimes issues can arise in GitHub or our security scans can cause an issue.

02:05:24.239 --> 02:05:24.936
All right.

02:05:24.936 --> 02:05:29.887
After that, we have to identify the AI and look at the AI's fix permissions.

02:05:29.887 --> 02:05:43.510
If let's suppose there's a formatting issue, a linting issue or a unit test failure, we'll automatically look at all of them and a detailed discussion will take place regarding production incidents and everything.

02:05:43.520 --> 02:05:47.783
Agents.md is our most important file which I mentioned here.

02:05:47.783 --> 02:05:53.106
What happens in agents.md is we can see the automated bug resolution rules.

02:05:53.106 --> 02:05:56.764
Whenever we fix a bug, we should minimize the code changes.

02:05:56.764 --> 02:05:59.522
We should never modify the database schemas.

02:05:59.522 --> 02:06:06.636
We should preserve the API contracts, add our tests for everyone, and run all of the affected test suites.

02:06:06.636 --> 02:06:11.343
We must explain the root cause and also create a pull request summary.

02:06:11.343 --> 02:06:13.394
You can see all of this in summary.

02:06:13.394 --> 02:06:18.794
You can see all of this in agents.md where we address the bugs and multiple things are included.

02:06:18.794 --> 02:06:36.790
Then if I let's suppose perform proper CI/CD integration meaning after identifying the trigger sources we've defined our AI then if I say we want to configure CI/CD here what I'll do first is take you to the I'll do first is take you to the configuration

02:06:36.800 --> 02:06:52.257
in the configuration workflow we first discuss the build failure then we understand our codeex investigation generate the fix run the tests create the pull request test develop our reviews and also then merge our workings.

02:06:52.257 --> 02:06:54.755
So this will come here.

02:06:54.755 --> 02:07:02.550
Then the next and most important process which will be discussed in our setup here will be our validation of fixes.

02:07:02.560 --> 02:07:11.830
Here we will require our unit tests, integration tests, security scans, code reviews and our build verifications.

02:07:11.840 --> 02:07:15.105
These will directly be used to approve our process.

02:07:15.105 --> 02:07:16.160
All right.

02:07:16.160 --> 02:07:24.868
Now as an example, if I go into codeex and open a new chat, what will happen in our chat is I'll say directly that a GitHub action has failed.

02:07:24.868 --> 02:07:27.660
We'll include the repository name directly.

02:07:27.660 --> 02:07:32.813
We have our failure logs here and the tasks are being discussed the most here.

02:07:32.813 --> 02:07:33.444
All right.

02:07:33.444 --> 02:07:37.696
After that, we have our unit test failure which we will use.

02:07:37.696 --> 02:07:42.673
After that, whatever automated bug resolution we have directly, we will configure it.

02:07:42.673 --> 02:07:45.514
We will discuss a onego project today.

02:07:45.514 --> 02:07:49.669
We will direct a full repository in our onego project.

02:07:49.679 --> 02:07:52.796
First we will create all project code and details.

02:07:52.796 --> 02:07:57.830
After that we will check our iterations and possible our iterations and possible improvements.

02:07:57.840 --> 02:08:01.510
Then we will use GitHub and codeex.

02:08:01.520 --> 02:08:03.705
Here is our codeex.

02:08:03.705 --> 02:08:05.430
We open codeex.

02:08:05.440 --> 02:08:10.260
Inside codeex we generate a full project before using prompts.

02:08:10.260 --> 02:08:17.487
In codeex we must include the set agents file but we will first exit this project.

02:08:17.487 --> 02:08:20.553
Then we will build a new project here.

02:08:20.553 --> 02:08:22.297
I will close this one.

02:08:22.297 --> 02:08:25.854
We close it and build a new project again.

02:08:25.854 --> 02:08:28.730
You see projects are available here.

02:08:28.730 --> 02:08:32.390
I can organize them or start from scratch.

02:08:32.400 --> 02:08:35.476
We will name our project one go.

02:08:35.476 --> 02:08:40.353
In this project, we will build a complete application with everything.

02:08:40.353 --> 02:08:43.430
First, we will pin this project.

02:08:43.440 --> 02:08:46.950
After pinning, we open it in our After pinning, we open it in our explorer.

02:08:46.960 --> 02:08:50.390
Our explorer has no file inside.

02:08:50.400 --> 02:08:54.310
Later, all generations will come into this file.

02:08:54.320 --> 02:08:57.222
We have our VS code and terminal.

02:08:57.222 --> 02:09:01.430
I told you before we can use codecs in our you before we can use codecs in our terminal.

02:09:01.440 --> 02:09:05.010
In VS Code, our cursor is available.

02:09:05.010 --> 02:09:07.173
I will first tell you the plan.

02:09:07.173 --> 02:09:09.440
We will open our plan mode.

02:09:09.440 --> 02:09:11.516
We have no plugins yet.

02:09:11.516 --> 02:09:14.790
We will not use the browser much.

02:09:14.800 --> 02:09:18.790
We will use the 5.4 model in our GPT.

02:09:18.800 --> 02:09:22.336
We will use the medium 5.4 model.

02:09:22.336 --> 02:09:24.330
We will use fast speed here.

02:09:24.330 --> 02:09:25.881
Not default speed.

02:09:25.881 --> 02:09:28.550
It will be used here.

02:09:28.560 --> 02:09:31.583
We will not connect GitHub for now.

02:09:31.583 --> 02:09:37.669
I will say in one go that I'm going to make a project about a healthcare make a project about a healthcare application.

02:09:37.679 --> 02:09:40.629
Can you plan a project for me?

02:09:40.639 --> 02:09:43.201
Project planning will start here.

02:09:43.201 --> 02:09:46.470
First it will settle output resources.

02:09:46.480 --> 02:09:48.596
I will not include them.

02:09:48.596 --> 02:09:51.830
Now we look at current workspace.

02:09:51.840 --> 02:09:55.189
You see nothing is there in workspace.

02:09:55.199 --> 02:09:59.686
Who is the primary user for the first version of the healthcare app?

02:09:59.686 --> 02:10:02.550
We have patients and doctors.

02:10:02.560 --> 02:10:06.709
I will say this application is for I will say this application is for patients.

02:10:06.719 --> 02:10:09.224
We want to build an application for our patients.

02:10:09.224 --> 02:10:13.057
What kind of first release do you want to plan?

02:10:13.057 --> 02:10:15.707
MVP or balanced or you want to plan?

02:10:15.707 --> 02:10:16.709
MVP or balanced or ambitious?

02:10:16.719 --> 02:10:19.270
I will choose MVP.

02:10:19.280 --> 02:10:21.750
What is our delivery target?

02:10:21.760 --> 02:10:24.229
We want to build a web application here.

02:10:24.239 --> 02:10:27.192
I will not build a mobile application.

02:10:27.192 --> 02:10:29.669
I will build a web app here.

02:10:29.679 --> 02:10:31.990
The current decision is clear.

02:10:32.000 --> 02:10:36.950
Patientfacing, MVP sized and optimized for a web app.

02:10:36.960 --> 02:10:39.990
I still need to lock the feature set.

02:10:40.000 --> 02:10:42.107
Now we have our feature sets.

02:10:42.107 --> 02:10:47.282
Which feature bundle should define the MVP booking and records?

02:10:47.282 --> 02:10:50.790
We will use this simple option.

02:10:50.800 --> 02:10:55.270
How should the plan treat healthcare compliance in the first version?

02:10:55.280 --> 02:10:59.510
We will use HIPPA ready design which is We will use HIPPA ready design which is recommended.

02:10:59.520 --> 02:11:04.390
We can also use full compliance track or lightweight prototype.

02:11:04.400 --> 02:11:08.709
How much external integration should the first plan include?

02:11:08.719 --> 02:11:11.541
I will say minimal integration will be included.

02:11:11.541 --> 02:11:13.758
These things are recommended here.

02:11:13.758 --> 02:11:16.433
Through them our entire process here.

02:11:16.433 --> 02:11:17.910
Through them our entire process comes.

02:11:17.920 --> 02:11:20.790
What will be the delivery timeline?

02:11:20.800 --> 02:11:24.390
What will be the delivery timeline for our project?

02:11:24.400 --> 02:11:27.243
I will say I want it in an urgent manner.

02:11:27.243 --> 02:11:31.950
This is a fourth part where we can include what we want.

02:11:31.950 --> 02:11:34.950
What team should this plan assume?

02:11:34.960 --> 02:11:36.793
Our small team is here.

02:11:36.793 --> 02:11:41.350
Instead of a small team, we can choose solo builder.

02:11:41.360 --> 02:11:43.903
Our solo builder is here.

02:11:43.903 --> 02:11:46.163
Now, what kind of plan do you need?

02:11:46.163 --> 02:11:48.629
Build plan or business build.

02:11:48.629 --> 02:11:51.856
We will work with a simple build plan.

02:11:51.856 --> 02:11:55.990
Now it reduces the project scope and other things.

02:11:56.000 --> 02:12:00.087
You see multiple questions are asked here for a solo builder.

02:12:00.087 --> 02:12:03.499
What does urgent mean for the first usable release?

02:12:03.499 --> 02:12:06.315
We will answer one week.

02:12:06.315 --> 02:12:09.270
We will include one week here.

02:12:09.280 --> 02:12:11.439
Our plan will come here.

02:12:11.439 --> 02:12:25.270
Build a patient-f facing web MVP for a solo builder optimized for one week urgent prototype while keeping the design hippaware and future ready for real healthcare data handling.

02:12:25.280 --> 02:12:28.660
I will read the plan once then we will implement it.

02:12:28.660 --> 02:12:32.077
I am saying that we have the entire process.

02:12:32.077 --> 02:12:36.520
We say our product definition is also happening here.

02:12:36.520 --> 02:12:42.709
After product definition, our recommended MVP features have also arrived here.

02:12:42.719 --> 02:12:46.629
Front end and backend have come in our technical approach.

02:12:46.639 --> 02:12:51.910
I will tell it that I want just a working front end and minimal back end.

02:12:51.920 --> 02:12:57.510
Also, it should be just HTML and CSS with JS logics.

02:12:57.520 --> 02:13:00.790
We want our product in a simpler way.

02:13:00.800 --> 02:13:02.911
All these things will come here.

02:13:02.911 --> 02:13:05.189
The stack has arrived.

02:13:05.199 --> 02:13:08.034
What should a minimal backend do?

02:13:08.034 --> 02:13:11.510
We can use a tiny mock API.

02:13:11.520 --> 02:13:14.754
We can use a basic form back end.

02:13:14.754 --> 02:13:18.310
We will not use any real backend.

02:13:18.320 --> 02:13:21.109
How should the front end be structured?

02:13:21.119 --> 02:13:25.750
I can say a multi-page application will be required here.

02:13:25.760 --> 02:13:29.109
What level of front-end quality is What level of front-end quality is needed?

02:13:29.119 --> 02:13:34.069
I will say we need a portfolio quality user interface.

02:13:34.079 --> 02:13:36.629
Our plan is created.

02:13:36.639 --> 02:13:40.840
You can see we have JSo objects and local storage here.

02:13:40.840 --> 02:13:47.644
Key changes are to reframe the project as a front-end prototype, not a production ready option.

02:13:47.644 --> 02:13:51.030
Now we can implement this plan.

02:13:51.040 --> 02:13:53.790
During implementation, it will bring our coding.

02:13:53.790 --> 02:13:56.318
It is checking the workspace shape.

02:13:56.318 --> 02:14:01.270
We will look at static app files and shared styles and JavaScript layers.

02:14:01.280 --> 02:14:07.910
Here we will also check the open file to see what things are discussed in it.

02:14:07.920 --> 02:14:11.669
First it took basic index html.

02:14:11.679 --> 02:14:14.086
We will open our file explorer.

02:14:14.086 --> 02:14:17.669
We will open one go from documents.

02:14:17.679 --> 02:14:24.917
For the time being we have no file or format available in one go but later our files will appear.

02:14:24.917 --> 02:14:31.510
It has confirmed our HTML pages and state stylesheet and JS HTML pages and state stylesheet and JS layer.

02:14:31.520 --> 02:14:34.176
In plugins, our GitHub is not installed yet.

02:14:34.176 --> 02:14:38.721
I will go to our codec settings to install GitHub once.

02:14:38.721 --> 02:14:40.757
We will go to our settings.

02:14:40.757 --> 02:14:43.024
You can see our connections here.

02:14:43.024 --> 02:14:47.830
In settings, you can see we have our connections.

02:14:47.840 --> 02:14:53.016
Besides connections, we have our MCP servers here which we can use.

02:14:53.016 --> 02:14:56.708
We also use plugins here which we can connect.

02:14:56.708 --> 02:14:58.440
I will go to our plugins.

02:14:58.440 --> 02:15:03.125
You can see our plugins are available where all our other details are.

02:15:03.125 --> 02:15:06.842
We will include our direct option in configuration.

02:15:06.842 --> 02:15:08.608
We have our plugins.

02:15:08.608 --> 02:15:10.556
We can use user our plugins.

02:15:10.556 --> 02:15:11.750
We can use user configuration.

02:15:11.760 --> 02:15:18.735
We have sandbox settings and current version and everything is working in MCP servers.

02:15:18.735 --> 02:15:20.786
Our plugins have arrived.

02:15:20.786 --> 02:15:25.353
We can also see our mostused plug-in here and how it is discussed.

02:15:25.353 --> 02:15:30.988
Then we have plugins inside our hooks and we have our computer use plugin.

02:15:30.988 --> 02:15:34.858
So any app and our Google Chrome browser has also arrived here.

02:15:34.858 --> 02:15:38.872
I will bring our plugins into our settings search.

02:15:38.872 --> 02:15:40.950
These are our plugins.

02:15:40.960 --> 02:15:42.942
I will use GitHub here.

02:15:42.942 --> 02:15:46.991
When I connect GitHub, you can see all details have arrived here.

02:15:46.991 --> 02:15:52.872
Because we are using the Michael Deont account, we will bring the same Michael Deont email here.

02:15:52.872 --> 02:15:54.880
We click on add plugin.

02:15:54.880 --> 02:15:57.334
Adding GitHub will appear.

02:15:57.334 --> 02:16:00.112
It is approved by our admin.

02:16:00.112 --> 02:16:03.990
We will go to connect and continue to will go to connect and continue to GitHub.

02:16:04.000 --> 02:16:08.069
We will get our detail in our browser which we will use.

02:16:08.079 --> 02:16:10.455
You will see that GitHub is now connected.

02:16:10.455 --> 02:16:12.823
We can try it out in the chat connected.

02:16:12.823 --> 02:16:13.990
We can try it out in the chat too.

02:16:14.000 --> 02:16:19.317
In GitHub, we have our repositories and pull requests and all things have arrived.

02:16:19.317 --> 02:16:21.850
Our GitHub access is now arrived.

02:16:21.850 --> 02:16:22.950
Our GitHub access is now connected.

02:16:22.960 --> 02:16:27.814
We have our repositories and issues and pull requests inside it.

02:16:27.814 --> 02:16:33.406
We have 97 actions available in the GitHub app related to read and write.

02:16:33.406 --> 02:16:37.190
We can use it for read and write functions.

02:16:37.200 --> 02:16:41.349
If we want to try it in the chat, we can do that too.

02:16:41.359 --> 02:16:44.870
After this, we go to our healthcare After this, we go to our healthcare application.

02:16:44.880 --> 02:16:48.464
You will see that a total of nine files generated here.

02:16:48.464 --> 02:16:52.648
You can see in these files we have our app.js.JS.

02:16:52.648 --> 02:16:57.859
If I go here and reload it, our file structure is still not very strong.

02:16:57.859 --> 02:17:07.429
But you will see that all our assets are available here index and records and all these files are generated here overall.

02:17:07.439 --> 02:17:12.549
Now it also told us it found a portability issue in the static assets.

02:17:12.559 --> 02:17:16.252
A few non-ASKY characters slipped into the labels.

02:17:16.252 --> 02:17:18.000
It will run them.

02:17:18.000 --> 02:17:19.981
The command is normalized.

02:17:19.981 --> 02:17:23.349
I am loading the normal browser.

02:17:23.359 --> 02:17:26.108
Now we will connect things in our inapp browser.

02:17:26.108 --> 02:17:28.972
You will see I did not give any prompt.

02:17:28.972 --> 02:17:32.345
I did not give any prompt on a large scale.

02:17:32.345 --> 02:17:36.870
I gave a basic prompt that I need a healthcare application.

02:17:36.880 --> 02:17:41.910
It planned it and took multiple recommendations from me during planning.

02:17:41.920 --> 02:17:45.148
In the end, it generated all our assets in one go.

02:17:45.148 --> 02:17:51.830
Appointments and dashboard and doctors and index and record files are generated.

02:17:51.840 --> 02:17:55.110
Now browser automation has also arrived.

02:17:55.120 --> 02:18:00.070
We have all files for implementation and we can run prototypes.

02:18:00.080 --> 02:18:02.309
Here is our documentation.

02:18:02.319 --> 02:18:09.168
Now if I open our file explorer and go to documents and one go our folder is empty right now.

02:18:09.168 --> 02:18:16.870
But if I look at our index html here in the file explorer, you will see that we have a file you will see that we have a file available.

02:18:16.880 --> 02:18:21.713
If I open this file in our browser, you will see our project has arrived.

02:18:21.713 --> 02:18:24.629
It is a healthcare app prototype.

02:18:24.639 --> 02:18:29.589
We are accessing healthcare here with appointments and records and reminders.

02:18:29.599 --> 02:18:32.335
When we want to enter a dashboard, we sign in here.

02:18:32.335 --> 02:18:34.465
Our doctors have arrived in it.

02:18:34.465 --> 02:18:39.793
After doctors, our appointments have arrived and our records have arrived.

02:18:39.793 --> 02:18:43.246
This is our whole process as you can see.

02:18:43.246 --> 02:18:47.657
If we want we can confirm any other appointment too.

02:18:47.657 --> 02:18:49.993
I will confirm an appointment.

02:18:49.993 --> 02:18:52.248
I will say I have a heart pain.

02:18:52.248 --> 02:18:54.227
I will just include a reason.

02:18:54.227 --> 02:18:58.076
When we include this part, our second appointment will come.

02:18:58.076 --> 02:19:00.519
This means our page is loading.

02:19:00.519 --> 02:19:06.870
If we go to records, we have our medications and allergies and recent visits available.

02:19:06.880 --> 02:19:11.119
If we go to doctors, all doctors we have are listed here.

02:19:11.119 --> 02:19:12.940
Then comes our are listed here.

02:19:12.940 --> 02:19:13.910
Then comes our dashboard.

02:19:13.920 --> 02:19:20.455
Inside this dashboard, we have our current summary showing the plan and conditions and recent visits.

02:19:20.455 --> 02:19:26.389
Our insurance card and hydration reminder and medication review are all available.

02:19:26.399 --> 02:19:30.309
Active members and unwanted things are available here.

02:19:30.319 --> 02:19:35.037
If we want, we can build a new demo account instead of demo credentials.

02:19:35.037 --> 02:19:36.616
I will close this one.

02:19:36.616 --> 02:19:38.581
I will give a prompt here.

02:19:38.581 --> 02:19:43.738
I liked my first draft and I want to make this an official app for the patients.

02:19:43.738 --> 02:19:47.847
Add some vibrant health-based colors in the website.

02:19:47.847 --> 02:19:49.522
Also try to make it more real.

02:19:49.522 --> 02:19:51.797
Our prototype is very much liked.

02:19:51.797 --> 02:19:55.849
In the prototype, our login and doctors are very real.

02:19:55.849 --> 02:19:58.284
But this dashboard has some issues.

02:19:58.284 --> 02:20:01.799
When I bring it to the phone view, it does not look special.

02:20:01.799 --> 02:20:03.609
It has many issues.

02:20:03.609 --> 02:20:06.950
This dashboard does not go higher from here.

02:20:06.960 --> 02:20:10.128
The second thing is our login panel goes too far back.

02:20:10.128 --> 02:20:15.058
If we go to our network inside the console, nothing special is loading.

02:20:15.058 --> 02:20:18.230
This means we have no back end.

02:20:18.240 --> 02:20:21.504
It created a working front end for us.

02:20:21.504 --> 02:20:24.034
I have given a prompt to update our prototype.

02:20:24.034 --> 02:20:27.625
You see we have our browser available in plugins.

02:20:27.625 --> 02:20:29.535
Due to this we can use it.

02:20:29.535 --> 02:20:31.911
It says I am updating the use it.

02:20:31.911 --> 02:20:33.510
It says I am updating the prototype.

02:20:33.520 --> 02:20:39.110
It is updating the prototype towards a more launch oriented Alaska patient app.

02:20:39.120 --> 02:20:42.355
First I am verifying the current frontend structure.

02:20:42.355 --> 02:20:47.167
Then I will replace the mock positioning with real Alaska provider data.

02:20:47.167 --> 02:20:57.104
It will shift the design towards a premium Apple adjacent aesthetic without copying Apple owned logos or icons because we cannot copy the icons.

02:20:57.104 --> 02:21:04.950
But if we want we can copy aesthetics based on an ecosystem and we are going to do the same thing here.

02:21:04.960 --> 02:21:08.493
This thing will be induced here in styles.

02:21:08.493 --> 02:21:10.866
You see we have many changes.

02:21:10.866 --> 02:21:12.950
It is performing enhancements in our file.

02:21:12.960 --> 02:21:17.359
Overall, I have included one thing in the one go project.

02:21:17.359 --> 02:21:20.847
I want to run the Apple ecosystem here.

02:21:20.847 --> 02:21:26.491
Apple ecosystem means the user interface enhancements in our MacBook or iPhones.

02:21:26.491 --> 02:21:29.176
I want to adapt them in our project.

02:21:29.176 --> 02:21:31.670
All those things are happening here.

02:21:31.670 --> 02:21:33.398
You see what it is doing.

02:21:33.398 --> 02:21:36.020
First, I gave this information here.

02:21:36.020 --> 02:21:39.455
Use real doctor information from Alaska.

02:21:39.455 --> 02:21:41.555
I want to launch it.

02:21:41.555 --> 02:21:45.372
There it is taking Alaska doctor profiles from the list.

02:21:45.372 --> 02:21:48.573
First it read all our files.

02:21:48.573 --> 02:21:51.912
Then it understood index.js file.

02:21:51.912 --> 02:21:55.910
Then it understood all files in data.js.

02:21:55.920 --> 02:21:59.670
After that it is carrying on our research purpose.

02:21:59.680 --> 02:22:04.421
When these things are included our final website version will come in a better form.

02:22:04.421 --> 02:22:08.473
Let me tell you an important thing in codeex.

02:22:08.473 --> 02:22:12.997
Whatever things are happening now, you can see them all here.

02:22:12.997 --> 02:22:16.230
If we have any output, we can see it too.

02:22:16.230 --> 02:22:21.071
If we have any source, we can see which source it is utilizing here.

02:22:21.071 --> 02:22:25.684
Like here, from a regional hospital list, it is retrieving doctors.

02:22:25.684 --> 02:22:34.710
First, it makes concrete changes, replacing generic healthcare content with Alaska specific facility and care context.

02:22:34.720 --> 02:22:45.445
Second, it is rebuilding the visual system into a brighter, premium look that feels native on iPhone and Mac without copying Apple trademarks or proprietary icon sets.

02:22:45.445 --> 02:22:49.055
All these changes are being created right now.

02:22:49.055 --> 02:22:54.326
Here in the style section, you can see that we have many changes appearing.

02:22:54.326 --> 02:23:00.143
We are experiencing many changes because it is performing complete enhancements in our file.

02:23:00.143 --> 02:23:06.389
Overall, all the styling updates are being processed to match the ecosystem we processed to match the ecosystem we requested.

02:23:06.399 --> 02:23:09.140
Our project design is improving to look professional.

02:23:09.140 --> 02:23:12.877
The software implementation has reached the required final stages.

02:23:12.877 --> 02:23:15.110
All web files were edited.

02:23:15.120 --> 02:23:17.690
The main index file is now running.

02:23:17.690 --> 02:23:20.790
The visual brand appears much better now.

02:23:20.800 --> 02:23:23.497
Demo login credentials exist in the database.

02:23:23.497 --> 02:23:27.804
Entering the main dashboard shows Aurora Care Alaska.

02:23:27.804 --> 02:23:36.389
Navigating to care teams displays available health and vascular care, internal medicine, and real-time schedules.

02:23:36.399 --> 02:23:45.429
Alaska Regional Cardiology and Providence primary care access details are visible with exact addresses and contact access details.

02:23:45.439 --> 02:23:47.750
We can book a medical appointment here.

02:23:47.760 --> 02:23:52.790
For example, a normal checkup for a child can be scheduled at 10:15.

02:23:52.800 --> 02:23:56.870
A new medical appointment request is submitted for 1:30.

02:23:56.880 --> 02:23:59.670
The system updates the patient schedule.

02:23:59.680 --> 02:24:02.710
The active list shows scheduled visits.

02:24:02.720 --> 02:24:05.422
We can cancel any booked visit from the records.

02:24:05.422 --> 02:24:11.429
Previous health records display current patient medications and known current patient medications and known allergies.

02:24:11.439 --> 02:24:15.510
Recent clinical visits and lab reviews are also listed.

02:24:15.520 --> 02:24:20.630
All recommended system features are implemented in this application version.

02:24:20.640 --> 02:24:24.950
All these recommended software features are now complete.

02:24:24.960 --> 02:24:27.542
Next, a brand new change will be adopted.

02:24:27.542 --> 02:24:30.784
A new user profile feature is needed.

02:24:30.784 --> 02:24:38.550
The end user should create a new account, add personal details, and access a personalized dashboard.

02:24:38.560 --> 02:24:42.790
Logging out of the current active session brings us to the main screen.

02:24:42.800 --> 02:24:46.680
Clicking on create a demo account opens a new form.

02:24:46.680 --> 02:24:49.514
A new name, Alex, is entered.

02:24:49.514 --> 02:24:51.358
The email address entered.

02:24:51.358 --> 02:24:53.686
The email address alex@gmail.com is provided.

02:24:53.686 --> 02:24:57.690
A secure password is created for this new account.

02:24:57.690 --> 02:25:00.652
The brand new demo account is accessed.

02:25:00.652 --> 02:25:07.318
Looking at the health records for this new user, previous medications and known allergies are still visible.

02:25:07.318 --> 02:25:11.726
The recent clinical visit data is also showing old information.

02:25:11.726 --> 02:25:16.230
This problem happens because synthetic mock data is used.

02:25:16.240 --> 02:25:21.759
When a new user account is created, all personal details should start fresh.

02:25:21.759 --> 02:25:26.341
We need to include actual user inputs instead of synthetic data.

02:25:26.341 --> 02:25:33.101
Even if previous scheduled appointments are canled, they remain in the application database for the new patient.

02:25:33.101 --> 02:25:37.670
This behavior applies to every new patient profile created.

02:25:37.680 --> 02:25:41.270
New data is not available yet in the New data is not available yet in the interface.

02:25:41.280 --> 02:25:45.108
To solve this issue, new code logic must be introduced.

02:25:45.108 --> 02:25:49.358
A text prompt is written to update the application logic.

02:25:49.358 --> 02:25:54.563
The missing profile fields need to be added and displayed on the main dashboard.

02:25:54.563 --> 02:25:58.955
The user account creation flow must be complete from end to end.

02:25:58.955 --> 02:26:05.190
The new user must feel personalized without falling back to generic demo data.

02:26:05.200 --> 02:26:08.309
The core application logic is updating.

02:26:08.319 --> 02:26:12.309
Five project files are being edited to implement the changes.

02:26:12.319 --> 02:26:19.429
These code items include data, HTML, dashboard, index, and records files.

02:26:19.439 --> 02:26:22.396
More software changes are expected to arrive soon.

02:26:22.396 --> 02:26:25.402
The main project goal is defined now.

02:26:25.402 --> 02:26:30.395
A new created user account must feel custom and personalized.

02:26:30.395 --> 02:26:32.880
It should not fall back to generic demo data.

02:26:32.880 --> 02:26:37.538
The user profile flow is implemented in the source code.

02:26:37.538 --> 02:26:40.875
Syntax checks are running to verify the software changes.

02:26:40.875 --> 02:26:45.190
The main index file now includes a complete signup form.

02:26:45.200 --> 02:26:50.150
Logging out again allows us to test the updated demo account creation.

02:26:50.160 --> 02:26:54.487
The new registration form requires comprehensive user details.

02:26:54.487 --> 02:27:03.670
Full name, email, phone number, date of birth, blood type, address, and medical insurance information must be provided.

02:27:03.680 --> 02:27:08.024
Emergency contact details are also required to complete the setup.

02:27:08.024 --> 02:27:11.566
These user details will be stored across the application assets.

02:27:11.566 --> 02:27:15.968
The new account registration form is filled with specific user data.

02:27:15.968 --> 02:27:20.118
The first name, Alex, is entered along with the email address.

02:27:20.118 --> 02:27:22.537
A random phone number is provided.

02:27:22.537 --> 02:27:24.736
The proper date of birth is set.

02:27:24.736 --> 02:27:28.117
The blood type is selected as a positive.

02:27:28.117 --> 02:27:31.029
The user city is entered as Alaska.

02:27:31.029 --> 02:27:39.270
The geographic region is specified as USA. region, state, Alaska.

02:27:39.280 --> 02:27:43.225
An insurance plan named master insure pro is added.

02:27:43.225 --> 02:27:47.397
An emergency contact number is also provided.

02:27:47.397 --> 02:27:52.469
In the end, a secure password is created to finalize the account.

02:27:52.479 --> 02:27:55.190
The new user account is created.

02:27:55.200 --> 02:28:00.766
Navigating to the medical record section shows the updated patient identity.

02:28:00.766 --> 02:28:04.714
All personal details provided during signup are displayed here.

02:28:04.714 --> 02:28:09.830
The scheduled appointment section is now empty and ready for new bookings.

02:28:09.840 --> 02:28:14.199
The care team section reflects the correct operational details.

02:28:14.199 --> 02:28:17.143
The personalized user dashboard is functional.

02:28:17.143 --> 02:28:23.110
Multiple future system changes can be integrated as the project changes can be integrated as the project evolves.

02:28:23.120 --> 02:28:25.990
All main project details are configured.

02:28:26.000 --> 02:28:29.331
The next crucial step is to upload the project code.

02:28:29.331 --> 02:28:35.510
A command request is made to push all files into a remote GitHub to push all files into a remote GitHub repository.

02:28:35.520 --> 02:28:41.510
The operating system checks available GitHub capabilities within the active GitHub capabilities within the active workspace.

02:28:41.520 --> 02:28:44.510
A local system git installation is not found.

02:28:44.510 --> 02:28:50.230
The active folder is not recognized as a valid git repository.

02:28:50.240 --> 02:28:54.809
Two concrete system blockers prevent the code push process.

02:28:54.809 --> 02:28:59.349
First, the Git software is not installed on the software is not installed on the machine.

02:28:59.359 --> 02:29:04.469
Second, there is no connected remote GitHub repository available.

02:29:04.479 --> 02:29:08.790
Suggested options are provided to resolve these software issues.

02:29:08.800 --> 02:29:12.357
A new public code repository must be created first.

02:29:12.357 --> 02:29:17.990
The main GitHub website is open to create a new online is open to create a new online repository.

02:29:18.000 --> 02:29:21.028
The user login credentials are saved.

02:29:21.028 --> 02:29:26.309
A new repository named one go project healthcare is created.

02:29:26.319 --> 02:29:29.429
The access visibility is set to public.

02:29:29.439 --> 02:29:31.955
The repository creation process completes.

02:29:31.955 --> 02:29:36.790
The internet repository link is now available for connection.

02:29:36.800 --> 02:29:40.436
The required remote repository link is copied from GitHub.

02:29:40.436 --> 02:29:46.550
This specific link is pasted into the system prompt to initiate the web connection.

02:29:46.560 --> 02:29:50.849
The active system processes the target online repository URL.

02:29:50.849 --> 02:29:56.578
It checks whether the main GitHub connector has the necessary account access.

02:29:56.578 --> 02:29:59.237
The code push access is verified.

02:29:59.237 --> 02:30:03.270
The current local project files are being read in order.

02:30:03.280 --> 02:30:07.385
The development plan is to publish them into the main code branch.

02:30:07.385 --> 02:30:11.670
This action is done through the built-in GitHub is done through the built-in GitHub connector.

02:30:11.680 --> 02:30:16.230
The raw text content of all project files is extracted.

02:30:16.240 --> 02:30:19.373
The public code files are prepared for web publishing.

02:30:19.373 --> 02:30:24.550
A small project readme file is also generated for the file is also generated for the repository.

02:30:24.560 --> 02:30:27.692
At this moment, the online repository is empty.

02:30:27.692 --> 02:30:33.646
Refreshing the web GitHub page confirms no files are uploaded yet.

02:30:33.646 --> 02:30:37.551
The background publishing application is running the pull request.

02:30:37.551 --> 02:30:43.349
Once the upload process is approved, the new content will be available online.

02:30:43.359 --> 02:30:48.230
The computer system waits for the background publishing process to background publishing process to execute.

02:30:48.240 --> 02:30:50.659
A new approval prompt appears on the screen.

02:30:50.659 --> 02:30:55.488
It requests security permission to allow GitHub to run the file creation tool.

02:30:55.488 --> 02:31:00.744
The required permission is granted by selecting the allow option.

02:31:00.744 --> 02:31:07.190
This choice ensures automatic file creation without repetitive manual user without repetitive manual user approvals.

02:31:07.200 --> 02:31:11.323
A subsequent system request asks to create code git blobs.

02:31:11.323 --> 02:31:15.190
This security permission is also allowed to proceed.

02:31:15.200 --> 02:31:21.672
These technical steps are necessary to transfer the local workspace files to the remote web environment.

02:31:21.672 --> 02:31:26.557
If the source code is left in the local workspace, it cannot be shared or deployed.

02:31:26.557 --> 02:31:32.150
Moving it to the online repository ensures the system is repository ensures the system is integrated.

02:31:32.160 --> 02:31:35.114
Two separate system blockers are identified again.

02:31:35.114 --> 02:31:39.382
The local machine still lacks a local software git installation.

02:31:39.382 --> 02:31:44.584
The web GitHub integration can read files but write operations are blocked.

02:31:44.584 --> 02:31:50.654
This problem happens because the integration cannot access the necessary developer tools.

02:31:50.654 --> 02:31:55.990
To resolve this exact issue, a local system installation is required.

02:31:56.000 --> 02:31:58.872
A new internet browser tab is opened.

02:31:58.872 --> 02:32:02.790
A search query for install Git is search query for install Git is executed.

02:32:02.800 --> 02:32:06.189
The official Git software installation page is accessed.

02:32:06.189 --> 02:32:10.563
The Windows desktop operating system option is selected.

02:32:10.563 --> 02:32:14.205
The standalone software installer for Windows is downloaded.

02:32:14.205 --> 02:32:17.728
The software download process will take some time to finish.

02:32:17.728 --> 02:32:21.334
The installation setup will be executed soon.

02:32:21.334 --> 02:32:26.230
The main Git installer file is saved to the computer desktop.

02:32:26.240 --> 02:32:29.070
The file download continues in the background.

02:32:29.070 --> 02:32:34.355
In the meantime, the computer system provides a text list of terminal commands.

02:32:34.355 --> 02:32:40.524
These commands are required to push the source code by hand before executing them.

02:32:40.524 --> 02:32:43.929
Remote repository permissions must be verified.

02:32:43.929 --> 02:32:49.577
The main GitHub settings page is opened to ensure proper developer access rights.

02:32:49.577 --> 02:32:52.796
The account security and variables section is examined.

02:32:52.796 --> 02:32:56.501
The account moderation options are also visible.

02:32:56.501 --> 02:33:03.030
Navigating to the repository security permissions is necessary to allow new code uploads.

02:33:03.040 --> 02:33:05.657
The active pull request settings are reviewed.

02:33:05.657 --> 02:33:10.365
The code merge commits and squash merging options are enabled by default.

02:33:10.365 --> 02:33:14.886
The version commit settings and archive features are checked.

02:33:14.886 --> 02:33:19.910
The critical danger zone is avoided to prevent accidental project deletion.

02:33:19.920 --> 02:33:22.743
Everything appears to be configured in a proper state.

02:33:22.743 --> 02:33:26.640
The Git software installer download is now complete.

02:33:26.640 --> 02:33:32.150
The application setup file will be executed next to install the software on the next to install the software on the computer.

02:33:32.160 --> 02:33:37.037
The downloaded Git software installer is executed from the computer desktop.

02:33:37.037 --> 02:33:39.840
The application setup wizard appears on the screen.

02:33:39.840 --> 02:33:46.550
The standard default installation options are selected by clicking the next button multiple times.

02:33:46.560 --> 02:33:50.389
The default components are chosen for the system installation.

02:33:50.399 --> 02:33:53.429
The default code editor is maintained.

02:33:53.439 --> 02:33:57.453
The initial project branch name configuration is left as a default choice.

02:33:57.453 --> 02:34:00.162
The system path environment is choice.

02:34:00.162 --> 02:34:01.510
The system path environment is updated.

02:34:01.520 --> 02:34:05.763
The software installation process begins extracting core files.

02:34:05.763 --> 02:34:10.790
The visual progress bar indicates the current installation status.

02:34:10.800 --> 02:34:13.951
The program installation is completed without errors.

02:34:13.951 --> 02:34:18.230
The active current terminal window is closed.

02:34:18.240 --> 02:34:23.910
A fresh new terminal session is launched to apply the updated installation paths.

02:34:23.920 --> 02:34:28.550
The specific git initialize command is executed again.

02:34:28.560 --> 02:34:33.510
The operating system initializes an empty local git repository.

02:34:33.520 --> 02:34:38.117
The local development project folder is now tracked by the git tool.

02:34:38.117 --> 02:34:42.870
The next required command is copied from the text required command is copied from the text instructions.

02:34:42.880 --> 02:34:47.990
The project branch is renamed to main using the active terminal.

02:34:48.000 --> 02:34:51.504
The text command executes without any prompt errors.

02:34:51.504 --> 02:34:55.193
The remote origin target command is copied.

02:34:55.193 --> 02:35:03.270
Next, this specific command links the local code repository to the new created online GitHub to the new created online GitHub repository.

02:35:03.280 --> 02:35:07.349
The web link is pasted into the terminal and executed.

02:35:07.359 --> 02:35:11.429
The internet connection is established without issues.

02:35:11.439 --> 02:35:16.696
The next development step requires adding all project files to the code staging area.

02:35:16.696 --> 02:35:20.188
The standard git add command is prepared.

02:35:20.188 --> 02:35:24.136
An error prompt occurs stating access permission is denied.

02:35:24.136 --> 02:35:30.309
The operating system cannot open a distinct application data directory.

02:35:30.319 --> 02:35:33.750
This file access issue must be resolved.

02:35:33.760 --> 02:35:38.150
The access permission denied error halts the running process.

02:35:38.160 --> 02:35:45.349
The operating system attempts to add developer files from the root user directory instead of the project folder.

02:35:45.359 --> 02:35:48.389
This behavior is a crucial mistake.

02:35:48.399 --> 02:35:53.110
The code terminal is operating in the wrong system directory path.

02:35:53.120 --> 02:35:58.856
A new terminal application tab must be opened within the exact correct project folder.

02:35:58.856 --> 02:36:02.796
The root user terminal is closed without delay.

02:36:02.796 --> 02:36:09.510
The new command terminal now displays the correct document path for the software project.

02:36:09.520 --> 02:36:14.858
The standard git initialize command is executed again in the right folder.

02:36:14.858 --> 02:36:19.910
An empty code repository is initialized here without any issues.

02:36:19.920 --> 02:36:25.510
The branch rename text command is executed to set the main branch.

02:36:25.520 --> 02:36:32.309
The remote origin command is pasted and executed to link the online GitHub executed to link the online GitHub repository.

02:36:32.319 --> 02:36:36.070
The correct project folder is now The correct project folder is now connected.

02:36:36.080 --> 02:36:41.030
The next workflow step is to add all files to the staging area.

02:36:41.040 --> 02:36:45.137
The simple git add command is executed without errors.

02:36:45.137 --> 02:36:50.710
This time all main project files are added to the code staging area.

02:36:50.720 --> 02:36:56.150
The standard git commit command is executed with a descriptive message.

02:36:56.160 --> 02:37:01.021
The operating system returns an author identity unknown error.

02:37:01.021 --> 02:37:06.469
The code commit cannot proceed without proper user cannot proceed without proper user identification.

02:37:06.479 --> 02:37:11.510
The global user configuration commands must be executed first.

02:37:11.520 --> 02:37:15.670
The terminal command to set the user email is copied.

02:37:15.680 --> 02:37:21.830
The account email address is updated to match the online GitHub account match the online GitHub account credentials.

02:37:21.840 --> 02:37:25.047
The command is executed without any system errors.

02:37:25.047 --> 02:37:29.798
The terminal command to set the username is copied.

02:37:29.798 --> 02:37:35.429
Next, the developer username is retrieved from the web GitHub profile page.

02:37:35.439 --> 02:37:40.309
The target username is pasted into the terminal command line.

02:37:40.319 --> 02:37:44.630
The system configuration is updated without issues.

02:37:44.640 --> 02:37:48.550
The required author identity is now The required author identity is now established.

02:37:48.560 --> 02:37:52.721
The standard git commit command is executed once again.

02:37:52.721 --> 02:37:57.429
This specific time, the code commit is a success.

02:37:57.439 --> 02:38:01.670
All modified files are recorded in the local repository.

02:38:01.680 --> 02:38:05.349
The source code is ready for the final The source code is ready for the final push.

02:38:05.359 --> 02:38:09.833
The main commit process includes all necessary application files.

02:38:09.833 --> 02:38:16.635
The design assets, HTML web pages, and application data files are secured.

02:38:16.635 --> 02:38:20.926
The final terminal command to push the source code is executed.

02:38:20.926 --> 02:38:28.230
The command terminal requests user authentication to access the remote GitHub repository.

02:38:28.240 --> 02:38:33.190
A new internet browser window opens for the user login process.

02:38:33.200 --> 02:38:37.349
The signin with internet browser option is selected.

02:38:37.359 --> 02:38:43.110
The existing active session credentials are used to authorize the upload are used to authorize the upload transaction.

02:38:43.120 --> 02:38:46.358
The access authorization succeeds without delay.

02:38:46.358 --> 02:38:51.757
Returning to the command terminal confirms the code push process is active.

02:38:51.757 --> 02:38:56.299
The data objects are compressed and written to the remote web server.

02:38:56.299 --> 02:39:01.811
The main code branch is set up to track the remote origin point.

02:39:01.811 --> 02:39:05.349
The entire application project is uploaded.

02:39:05.359 --> 02:39:10.864
The online GitHub repository page is refreshed in the internet browser.

02:39:10.864 --> 02:39:14.710
All local project files are now visible local project files are now visible online.

02:39:14.720 --> 02:39:19.347
The assets folder and HTML text documents are listed.

02:39:19.347 --> 02:39:23.798
The code upload process is verified and a success.

02:39:23.798 --> 02:39:30.309
The uploaded index document file is opened on GitHub to verify its code contents.

02:39:30.319 --> 02:39:35.510
The online code matches the local computer version without flaws.

02:39:35.520 --> 02:39:39.405
The source blame and file history options are functional.

02:39:39.405 --> 02:39:43.227
The raw text code can be accessed any time.

02:39:43.227 --> 02:39:46.870
The entire upload process is now concluded.

02:39:46.880 --> 02:39:51.901
The initial project objective was to build a medical healthcare application project.

02:39:51.901 --> 02:39:55.710
A detailed development plan was formulated first.

02:39:55.710 --> 02:40:00.991
The project scope was defined for a basic minimum viable product.

02:40:00.991 --> 02:40:08.389
The database backend requirements were later removed to focus on the user front-end interface.

02:40:08.399 --> 02:40:15.190
The HTML and CSS design structures were developed with minimal JavaScript logic.

02:40:15.200 --> 02:40:21.670
Various design iterations improved the visual page aesthetics and user visual page aesthetics and user experience.

02:40:21.680 --> 02:40:26.710
The personalized user profile creation feature was integrated.

02:40:26.720 --> 02:40:32.230
In the end, the local source code was pushed to a public code repository.

02:40:32.240 --> 02:40:36.230
The application project is stored and The application project is stored and accessible.

02:40:36.240 --> 02:40:42.997
Future code modifications can be implemented and tracked through this version repository system without effort.

02:40:42.997 --> 02:40:48.395
The detailed software implementation plan proved effective in practice.

02:40:48.395 --> 02:40:55.510
We established a strong code foundation using standard modern web foundation using standard modern web technologies.

02:40:55.520 --> 02:41:04.469
The front-end user interface provides a seamless smooth experience for clinical patients managing their healthcare patients managing their healthcare needs.

02:41:04.479 --> 02:41:11.750
The synthetic mock data limitations were overcome by implementing dynamic user input handling.

02:41:11.760 --> 02:41:18.803
The medical appointmentuling and user cancellation workflows operate without any system errors.

02:41:18.803 --> 02:41:28.686
Essential patient medical records remain accessible on the personalized user dashboard by utilizing the git version control system.

02:41:28.686 --> 02:41:34.230
The main source code remains protected against accidental data loss.

02:41:34.240 --> 02:41:41.510
The open public repository allows other software developers to review the application project structure.

02:41:41.520 --> 02:41:49.590
This developer workflow demonstrates a practical approach to rapid web application development and code application development and code deployment.

02:41:49.600 --> 02:41:56.362
The initial system setup challenges regarding local machine software requirements were resolved with great speed.

02:41:56.362 --> 02:42:04.710
The comprehensive command terminal instructions ensured execution of necessary developer commands.

02:42:04.720 --> 02:42:12.469
The final software outcome is a functional, well doumented and versioned front-end application.

02:42:12.479 --> 02:42:14.774
The established project goals are fulfilled.

02:42:14.774 --> 02:42:19.670
The discussion relates to possible iterations we can include here.

02:42:19.680 --> 02:42:25.590
In our use cases, we create projects multiple times requiring iterations.

02:42:25.600 --> 02:42:29.590
We can include these iterations to see what is possible.

02:42:29.600 --> 02:42:31.864
Iterations start from the beginning.

02:42:31.864 --> 02:42:34.870
We include project details and formats.

02:42:34.880 --> 02:42:38.260
Another option is available after project creation.

02:42:38.260 --> 02:42:42.950
Moving to the end, our index was complete at this step.

02:42:42.960 --> 02:42:48.654
Here in front end, back end, appointments and records, our option has arrived.

02:42:48.654 --> 02:42:51.335
Changes are never small.

02:42:51.335 --> 02:42:55.004
For changes, we will include details multiple times.

02:42:55.004 --> 02:43:00.790
Another important thing is working in an environment requiring code changes.

02:43:00.800 --> 02:43:03.570
Iterations become version based.

02:43:03.570 --> 02:43:07.941
The first website version was quite different from the current version.

02:43:07.941 --> 02:43:12.550
We must understand version histories to see which was more compatible.

02:43:12.560 --> 02:43:16.372
Sometimes we include specific things from a specific version.

02:43:16.372 --> 02:43:20.790
Going into our project, this was the final version.

02:43:20.800 --> 02:43:26.550
Looking at this project, considering the whole use case, the logo is incorrect.

02:43:26.560 --> 02:43:28.240
We can change the logo.

02:43:28.240 --> 02:43:32.575
The dashboard should be a sliding dashboard, not a consistent one.

02:43:32.575 --> 02:43:37.190
Instead of this, some analytics should be involved here.

02:43:37.200 --> 02:43:42.058
Looking here, the card distance and the empty space in the website should be minimal.

02:43:42.058 --> 02:43:44.398
We should fill such spaces minimal.

02:43:44.398 --> 02:43:45.910
We should fill such spaces beforehand.

02:43:45.920 --> 02:43:50.772
In our website text, search engine optimization is not involved.

02:43:50.772 --> 02:43:53.845
The colors involved here are quite dull.

02:43:53.845 --> 02:43:57.750
We can improve all these things just by giving it some prompts.

02:43:57.750 --> 02:44:00.642
Our iteration will start happening.

02:44:00.642 --> 02:44:07.165
Now alongside iteration, another important thing is making large scale improvements via prompts.

02:44:07.165 --> 02:44:13.088
Since this tool is based on our prompts, any new improvement will be based on prompts.

02:44:13.088 --> 02:44:16.270
There is no other way to improve our stuff.

02:44:16.270 --> 02:44:20.389
These things will be induced here with our ongoing time.

02:44:20.399 --> 02:44:26.870
As our time increases, we must iterate these things and see how we are taking them forward.

02:44:26.880 --> 02:44:34.950
Along with this, another important thing is that when making improvements based on prompts, error chances increase.

02:44:34.960 --> 02:44:37.617
Therefore, we should review our code first.

02:44:37.617 --> 02:44:44.630
After reviewing the code, we should take things towards our other generations and discussions.

02:44:44.640 --> 02:44:50.870
Sometimes within our code itself, there are multiple errors we spend time are multiple errors we spend time correcting.

02:44:50.880 --> 02:44:53.456
We are focusing on making the dashboard intuitive.

02:44:53.456 --> 02:45:00.309
The layout needs adjustments, so upcoming visits and active reminders are visible to the user.

02:45:00.319 --> 02:45:04.441
Care teams and appointment sections must be integrated together.

02:45:04.441 --> 02:45:11.269
This ensures the entire application functions without visual or technical interruptions.

02:45:11.279 --> 02:45:15.750
This completes our entire discussion related to our iteration.

02:45:15.760 --> 02:45:21.590
Along with the iteration, we covered possible improvements that needed to be possible improvements that needed to be discussed.

02:45:21.600 --> 02:45:28.550
Looking at the bottom section, the reminders and profile loaded cards have gaps needing fixes.

02:45:28.560 --> 02:45:32.309
The design should feel premium and The design should feel premium and responsive.

02:45:32.319 --> 02:45:37.590
The patient readiness items must be tracked on one premium dashboard.

02:45:37.600 --> 02:45:47.750
When looking at source options for medical centers like Providence Alaska Medical Center or Alaska Native Medical Center, information must be displayed.

02:45:47.760 --> 02:45:53.510
The layout structure lacks proper alignment and text blocks feel alignment and text blocks feel disconnected.

02:45:53.520 --> 02:45:58.469
We will use specific commands to refine these interface elements.

02:45:58.479 --> 02:46:03.830
Once we apply new styles, the final product will look more professional.

02:46:03.840 --> 02:46:11.613
Everything will be committed to the repository, ensuring all changes are saved and tracked for future updates and continuous development.

02:46:11.613 --> 02:46:13.174
Now comes the last part.

02:46:13.174 --> 02:46:17.089
At the end of this course, you saw one main thing.

02:46:17.089 --> 02:46:19.998
It was our GitHub and codeex tools.

02:46:19.998 --> 02:46:22.089
We tried to connect GitHub.

02:46:22.089 --> 02:46:24.238
Then we got many tech issues.

02:46:24.238 --> 02:46:28.073
I will say here I will use our plugin of GitHub.

02:46:28.073 --> 02:46:32.230
Now I will start a discussion with the GitHub plug-in tool.

02:46:32.240 --> 02:46:36.195
I will ask can you check if GitHub plugin is working.

02:46:36.195 --> 02:46:38.477
This will test our plug-in once.

02:46:38.477 --> 02:46:42.074
We will see if our plug-in works in any user case.

02:46:42.074 --> 02:46:46.057
If our plug-in is not available, we can check it.

02:46:46.057 --> 02:46:48.877
You can see we have verification now.

02:46:48.877 --> 02:46:51.387
You can see that I have verified it.

02:46:51.387 --> 02:46:53.679
This login account Robert is here.

02:46:53.679 --> 02:46:57.973
You will remember our main account here that is connected here.

02:46:57.973 --> 02:47:05.990
Its user ID has also come that confirmed that the plug-in is installed, reachable and authenticated.

02:47:06.000 --> 02:47:09.190
Now I can say what can I do with this.

02:47:09.200 --> 02:47:11.695
This will start giving us a response.

02:47:11.695 --> 02:47:14.094
It will tell us where we can use this plug-in.

02:47:14.094 --> 02:47:17.404
This tool is not available on a weak level.

02:47:17.404 --> 02:47:20.753
But still we have to see how our tool can work.

02:47:20.753 --> 02:47:26.024
Here you will see here it says you can ask it to read multiple actions.

02:47:26.024 --> 02:47:29.750
In this we also get more recommendations.

02:47:29.760 --> 02:47:37.123
I will suggest to you that we should use multiple plugins like right now you are seeing that we can use our windows.

02:47:37.123 --> 02:47:40.842
We have our chrome and data analytics and product design.

02:47:40.842 --> 02:47:47.325
We also have Apollo and Atio and Carter CRM and Clay and Circleback.

02:47:47.325 --> 02:47:50.524
We have granola and otter and canva.

02:47:50.524 --> 02:47:53.670
We can use all these plugins.

02:47:53.680 --> 02:47:55.355
We have many options.

02:47:55.355 --> 02:47:59.358
If we bring any of these in here, we can use it out.

02:47:59.358 --> 02:48:02.701
For every niche, we have separate options available for us.

02:48:02.701 --> 02:48:08.267
Like for our education and research, we also have options available right here.

02:48:08.267 --> 02:48:10.588
We have our Dow Jones Factiva.

02:48:10.588 --> 02:48:15.590
Here we have our gov tribe and we have life science research.

02:48:15.600 --> 02:48:19.626
For finance, we have multiple softwares available right here.

02:48:19.626 --> 02:48:26.267
So what codeex does is on a large scale, it gives us multiple plugins to use from these.

02:48:26.267 --> 02:48:30.235
The used plug-in on our developer side is our GitHub plug-in.

02:48:30.235 --> 02:48:36.630
But if we want to use multiple plugins on our whole enterprise level, we can do that too.

02:48:36.640 --> 02:48:39.135
With that, our price will increase.

02:48:39.135 --> 02:48:46.150
Our usage cost will also become a cost that is quite high.

02:48:46.160 --> 02:48:58.309
The open AI ecosystem is a collection of tools, models, and platforms that help individuals and organizations use artificial intelligence in practical artificial intelligence in practical workflows.

02:48:58.319 --> 02:49:07.750
In this diagram, open AI ecosystem is the central idea and the main branches show the important parts connected to show the important parts connected to it.

02:49:07.760 --> 02:49:12.230
Chat GPT is one of the most familiar parts of the ecosystem.

02:49:12.240 --> 02:49:21.269
It helps users write content, explain concepts, solve problems, summarize information, and support daily work.

02:49:21.279 --> 02:49:33.269
In software development, Chat GPT can help developers understand errors, write documentation, plan features, and improve prompts before using them with coding tools.

02:49:33.279 --> 02:49:41.750
The Open AI API allows developers to connect OpenAI models directly into their own applications.

02:49:41.760 --> 02:49:53.990
For example, a company can build a chatbot, document assistant, coding assistant, customer support tool, or automation system using the API.

02:49:54.000 --> 02:49:59.830
This makes AI usable inside real business products and enterprise business products and enterprise systems.

02:49:59.840 --> 02:50:02.605
Codeex is focused on software development.

02:50:02.605 --> 02:50:13.830
It helps developers generate code, refactor files, explain existing code, create tests, debug issues, and work with repositories.

02:50:13.840 --> 02:50:23.990
In an enterprise course, codeex is important because it shows how AI can support real development workflows instead of only answering questions.

02:50:24.000 --> 02:50:28.790
The models branch represents the AI models behind the ecosystem.

02:50:28.800 --> 02:50:37.190
These models can work with text, code, images, and other types of input depending on the product or depending on the product or configuration.

02:50:37.200 --> 02:50:44.469
Better models usually mean better reasoning, better code understanding, and more accurate responses.

02:50:44.479 --> 02:50:49.110
Finally, enterprise tools are important for organizations.

02:50:49.120 --> 02:50:57.269
Enterprises need security, governance, permissions, auditing, and control over how AI is used.

02:50:57.279 --> 02:51:06.550
These tools help companies adopt AI safely while protecting data, managing access, and following internal policies.

02:51:06.560 --> 02:51:13.064
Overall, the diagram shows that the open AI ecosystem is not just one product.

02:51:13.064 --> 02:51:22.550
It includes user-facing tools, developer APIs, coding assistance, advanced models, and enterprise controls.

02:51:22.560 --> 02:51:33.429
Together, these parts help teams build, automate, learn, and develop software more efficiently.

02:51:33.439 --> 02:51:41.750
This conclusion mind map summarizes the key lessons learned throughout the OpenAI codeex enterprise development OpenAI codeex enterprise development course.

02:51:41.760 --> 02:51:56.630
The central idea is that AI assisted development is becoming an important part of modern software engineering and organizations that learn to use these tools effectively can significantly improve productivity, software quality

02:51:56.640 --> 02:51:59.349
and development speed.

02:51:59.359 --> 02:52:02.778
The first branch focuses on OpenAI codeex itself.

02:52:02.778 --> 02:52:17.269
Throughout the course, learners discovered how Codeex helps developers generate code, analyze repositories, refactor applications, create tests, and automate repetitive development tasks.

02:52:17.279 --> 02:52:26.070
Rather than replacing developers, Codeex acts as an intelligent development assistant that helps teams work more assistant that helps teams work more efficiently.

02:52:26.080 --> 02:52:30.070
The next branch highlights the development workflow.

02:52:30.080 --> 02:52:37.349
One of the most important lessons from the course is that AI can support every stage of software development.

02:52:37.359 --> 02:52:46.230
Developers can use codeex during planning, implementation, testing, debugging, and deployment preparation.

02:52:46.240 --> 02:52:55.830
Instead of viewing AI as a tool used only for coding, organizations can integrate it into the complete software development life cycle.

02:52:55.840 --> 02:53:04.870
The enterprise adoption section emphasizes that successful AI implementation requires more than technical capability.

02:53:04.880 --> 02:53:13.830
Organizations must establish governance frameworks, security controls, compliance processes, and collaboration compliance processes, and collaboration standards.

02:53:13.840 --> 02:53:24.630
Enterprise teams need visibility into how AI is used and must ensure that generated code meets organizational policies and quality requirements.

02:53:24.640 --> 02:53:31.269
The best practices branch represents the habits that produce the best results when working with codecs.

02:53:31.279 --> 02:53:35.650
Effective prompt engineering helps developers communicate requirements clearly.

02:53:35.650 --> 02:53:40.950
Code reviews ensure generated code is maintainable and secure.

02:53:40.960 --> 02:53:47.670
Validation and testing confirm that AI generated features satisfy business generated features satisfy business requirements.

02:53:47.680 --> 02:53:52.710
These practices help maximize the value of AI assisted development.

02:53:52.720 --> 02:53:56.084
Another important area is operational excellence.

02:53:56.084 --> 02:54:05.590
As AI adoption grows, organizations must monitor usage, manage costs, optimize resources, and measure costs, optimize resources, and measure performance.

02:54:05.600 --> 02:54:17.750
Understanding token consumption, tracking productivity improvements, and evaluating return on investment help organizations scale AI responsibly and organizations scale AI responsibly and efficiently.

02:54:17.760 --> 02:54:24.070
The continuous learning branch reminds learners that AI technologies evolve learners that AI technologies evolve rapidly.

02:54:24.080 --> 02:54:34.630
Developers should stay informed about new codeex capabilities, open AI platform updates, community best practices, and industry trends.

02:54:34.640 --> 02:54:42.710
Teams that continuously learn and adapt will gain the greatest long-term benefits from AI assisted development.

02:54:42.720 --> 02:54:47.590
The future of development section looks ahead to emerging trends.

02:54:47.600 --> 02:54:50.550
AI assistance will become more capable.

02:54:50.560 --> 02:54:58.150
Agent-based workflows will become more common and human AI collaboration will continue to evolve.

02:54:58.160 --> 02:55:08.710
Developers will increasingly focus on architecture, business logic, and strategic decision-m while AI handles more implementation tasks.

02:55:08.720 --> 02:55:15.690
Finally, the most important takeaway is that AI augments developers rather than replacing them.

02:55:15.690 --> 02:55:29.910
Human expertise remains essential for understanding business requirements, making architectural decisions, reviewing code quality, managing risk, and ensuring software meets organizational goals.

02:55:29.920 --> 02:55:40.630
When used effectively, codeex enables developers to deliver better software faster while maintaining quality, security, and reliability.

02:55:40.640 --> 02:55:57.200
In summary, the course demonstrates that successful enterprise AI adoption requires a combination of technical skills, governance practices, continuous learning, and thoughtful collaboration between humans and AI systems.