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

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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 Codex 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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Codex is a tool made by OpenAI.

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You might know their famous tool called ChatGPT.

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OpenAI is the main company behind ChatGPT 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,

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which is a system that can solve human problems.

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In the products section, you can see tools like ChatGPT, Codex, Atlas and Prism.

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ChatGPT 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, Airtable, Booking.com, Canva, Spotify and more.

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Now let us look at OpenAI Codex.

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Codex 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

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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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Codex is also inside ChatGPT, so you can use it directly.

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

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We will see how Codex 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 Codex.

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CLI means Command Line Interface. It is a text-based 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

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text-based user interface used to interact with the software, operating system and on

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your keyboard instead of using a mouse to click on visual items and press enter to make

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them work.

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We will learn how to use this CLI.

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Codex 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

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language.

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Codex can analyse the database identifying files, proposed changes and generate limitation

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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 codex discussion.

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In this course we will talk about daily development, prompting, making agents and using codex to

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for a long time. We will cover all of these important topics together.

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So, moving on, the next critical discussion is primarily related to exactly

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how we are going to securely install codecs on our machine. First, well before

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actually installing it anywhere else, we will practically use the standard

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command-line interface to get things started. But right before that specific

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step, we can smoothly download the dedicated version specifically meant for Windows operating

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systems. Now, I already have the necessary Codex installer fully ready to go here. I

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simply open up the main system downloads folder right now. Then, I firmly run the executable

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installer directly as a system administrator. The core software immediately starts to install

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itself smoothly. Simultaneously, the Microsoft Store seamlessly begins its essential download

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process. Finally, when the entire download completely finishes, Codex will successfully

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run. Interestingly, we can certainly also manage to install it safely across multiple

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different computer systems. As we smoothly scroll further down the main page, you will

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clearly see three distinct setup options presented. The very first one is the

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standard standalone app. If we really want to use a code editor we can install it

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directly within our preferred IDE. Fortunately we already have Visual Studio

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code fully set up. Right inside VS Code a highly helpful AI is fully available. It

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

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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 Codex 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 ChatGPT+, Pro, Business, Education and Enterprise plans.

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First and foremost we absolutely must carefully check our specific ChatGPT subscription plan.

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I will officially open up the ChatGPT 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

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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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Codex 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 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 Codex.

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We basically add Codex as a dedicated side panel within VS Code to seamlessly chat, intuitively

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edit and carefully check all our changes.

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Then, we can confidently use Codex directly in the cloud, sending massive jobs straight

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to it.

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Moving gracefully to the very next step, we simply need to safely sign in using our primary

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ChatGPT account credentials.

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

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workspace.

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Now, the third available setup option is to actually install this directly inside our

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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 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.

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Within PowerShell itself, we formally install the OpenAI Codex 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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Codex 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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settings menu there are actually many different customisable options

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available. I specifically navigate over to the appearance tab in order to make

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some visual interface changes. First, I completely change the overall display

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theme to a comfortable dark mode. Next, I noticeably increase the base system UI

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size for better visibility. We then carefully choose our preferred font

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style and slightly adjust the visual contrast. Initially, I confidently write

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in 32 for the primary font size, however upon seeing it, 32 is admittedly just a bit too

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big for my screen. So I quickly change it down to exactly 24. Honestly, 24 is a genuinely

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comfortable size for long coding sessions. For the dedicated code font, we firmly use

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size 20. Moving on, we strategically turn off the reduce motion option. We ensure we

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use standard pointer cursors and gently lower the screen contrast. Everything is working

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

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made those crucial visual tweaks, the default text font was incredibly small and honestly

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hard to read. We absolutely had to step in and make the font significantly bigger for

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basic clarity. I truly believe that 24 and 20 are excellent, highly optimized sizes for

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our daily coding tasks.

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Now if we quickly navigate over to the General Configuration Settings menu, we can clearly

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see multiple distinct operational modes available to choose from. I promise that I will carefully

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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 OpenAI codex 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 NPM installation status alongside the available AI models.

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

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I simply type NPM codex directly into the prompt.

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The resulting codex CLI version currently shows up as 0.139.0.

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

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to code. We type codex right into the system environment. A brand new security message

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suddenly appears on the screen. It clearly asks, do you currently trust the exact contents

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of this specific directory? Working directly with untrusted contents definitely carries

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inherent security risks or potential prompt injections. Trusting that directory directly

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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,

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we now finally have our direct working option ready to go.

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We have the full power of the OpenAI codex 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 System32.

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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,

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it impressively replies back almost automatically.

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I simply write out,

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can you explicitly 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, 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 7,939 tokens used.

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The initial input strictly 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

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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

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off.

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If I suddenly decide that I want to completely change the underlying AI model, we currently

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have three distinct options available.

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Next is GPT 5.5, which is essentially the frontier model specifically built for complex

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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.

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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, Codex immediately shows a complete, highly

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detailed working menu of commands.

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First and foremost, we can fully configure how Codex 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 context.

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We actively have detail permissions to precisely choose exactly what codecs can or cannot do

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safely.

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We have dedicated key maps specifically 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 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 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 Read Only setting strictly means that Codex can only safely read active files located

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within the current workspace environment.

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It absolutely requires your direct manual approval before it can ever attempt to edit

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files or directly access the live internet.

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The Ask for Approval setting actually serves as the standard default mode, where Codex

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can seamlessly run, read or even edit files inside the current workspace and fully read

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the active command prompt. Still, explicit manual approval is completely required to

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permanently edit files or access the internet. Approved for me intelligently only asks for

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explicit permission when it encounters potentially unsafe system actions. Full access simply

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means Codex can freely edit files far outside the designated workspace and easily access

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the internet without ever asking for prior approval. Exercise extreme caution and ask

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vital questions when using this. I explicitly choose the Approve for me setting. Our updated

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permissions are cleanly applied. I press Enter and transition to the Keymap 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

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some incredibly useful direct operational options.

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What we can actually do here is utilise the basic left and right keyboard arrow keys to

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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

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dash symbol to quickly unbind an active key, and the Escape key to easily close out the

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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

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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

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here.

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We actually changed our primary AI model twice today.

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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 Control-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

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across every single linked application environment.

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Thankfully, the powerful Codex 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

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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

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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

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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 index.html.

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

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

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The generated Codex AI response will 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,

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the comprehensive onboarding bug log and of course, our preferred dark mode visual theme.

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We will consistently get highly accurate direct 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 personalisation, advanced MCP servers, webhook

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integrations, system usage and active billing.

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We absolutely need to check these panels timely and consistently to perfectly know exactly

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how we are efficiently carrying all these things forward.

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We can chat and utilise 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

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configuration tabs right at the top.

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We absolutely also have detail personalization settings, custom keyboard shortcuts, active

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usage limits and standard billing information.

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

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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 codex usage capabilities

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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

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seamless browser connections,

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broad computer use permissions and robust MCP servers.

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The core coding section beautifully includes active webhooks, secure remote connections,

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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 module.

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You probably remember that we previously ran our Codex 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

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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

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and intentionally make the system font slightly smaller for better viewing.

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We gracefully go over to the visual appearance tab

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and actively change the primary tech size down from 24 to precisely 20.

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Now, the overall tech size is just so much better and more manageable.

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I will clearly explain to you generally what these advanced cloud-based development environments actually are.

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We will deeply understand this entire concept right here today.

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You absolutely should know right up front that this is essentially a pre-configured, entirely remotely hosted software workspace.

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It actively contains your preferred IDE alongside all your necessary background tools.

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Modern developers can effortlessly code, rigorously test and smoothly deploy complex software straight from the web browser.

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The acronym CDE specifically stands for Cloud Development Environment.

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It effectively solves that highly frustrating, age-old problem

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when a specific piece of code miraculously only works on one specific person's local computer.

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Brand new software engineers can easily start actively coding in mere minutes.

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This is our dedicated cloud system.

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Now, let's take a moment to talk about Codex itself.

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Codex fundamentally has some massive, undeniably big advantages here.

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Codex genuinely works absolute best when it can safely access the entire full code repository.

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It impressively also has powerful built-in deployment tools.

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A cloud environment safely lets Codex seamlessly talk directly to remote code repositories.

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It can reliably run terminal commands, execute unit tests and thoroughly check projects.

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It safely makes automated code changes.

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The biggest overall benefit is undeniable, absolute consistency.

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In significantly older traditional local development environments,

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various developers constantly use completely different underlying operating systems

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and vastly different local machine settings.

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settings. This inherently creates the infamous, frustrating, well, it perfectly works on my

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machine problem. Modern, streamlined cloud environments completely remove these highly

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annoying problems entirely. Absolutely everything that we actively do right here, for example,

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the previously pinned chat log specifically about making a functional calculator application,

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all our deep technical discussions are safely stored permanently in this robust cloud system.

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We can effortlessly and rapidly review our collective past work right here at any given time.

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Other incredibly massive benefits strictly include nearly instant team onboarding,

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highly consistent underlying tool setups, absolute hardware independence and reliable

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long-term session persistence.

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Now, moving forward, we will thoughtfully choose a specific cloud development platform to use.

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I will happily show you some excellent real-world examples shortly.

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First and foremost, we will take a very close look at GitHub Codespaces today.

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It is a remarkably secure, highly robust cloud development environment used by many.

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If we genuinely do not want to use this specific one, we can alternatively utilise Gitpod.

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We actually use the Gitpod platform quite a lot in our daily workflows.

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It is a fantastic, strictly on-demand, highly scalable development environment.

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For massively big enterprise companies, we consistently have the AWS Cloud9 infrastructure safely available.

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for our larger, more complex coding tasks.

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It is basically a fully complete cloud-based integration development environment from Amazon.

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It is truly a complete, fully featured IDE right in your browser.

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We can effortlessly write, smoothly run and quickly fix our complex code directly inside it.

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These are a few older, very solid examples.

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Now, I will explicitly search the web to see if Codex itself is officially classified as a cloud-based development environment.

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It confidently says, yes.

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Codex, created by OpenAI, is officially a cloud-based AI software engineering agent.

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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.

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This essentially means that the powerful tool we are actively utilising right now acts almost exactly like a completely standalone, fully robust cloud-based development environment in itself.

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I strongly suggest that we consistently use this incredible tool to intentionally make

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a highly secure, deeply isolated remote workspace.

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There are honestly quite a lot of highly technical back-end things actively running here.

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I will quickly hop back and change the UI font size once again, because it simply does

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not look visually right on this display.

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I will purposefully make it just a little bit bigger, strictly for the sake of our video

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course clarity. Now we simply go straight back into our main codex application. Everything

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visually looks exceptionally good now. We have our advanced reasoning engine and other

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vital backend things running. We will take a complete comprehensive look at this next.

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This perfectly shows how we put things into a complete cloud-based setup.

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Now, moving smoothly forward, our very next crucial task is to securely connect our remote

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GitHub repositories directly.

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We absolutely need to establish a solid link to our GitHub account directly within the

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main codec system.

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Inside our primary GitHub platform, a tremendous amount of distinct configurable options are

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always readily available.

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You can clearly see the active status regarding the connection with GitHub right here on the

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interface.

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If I cautiously go over to the main settings panel, specifically looking closely in the

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Connections option area, there is currently absolutely no active connection established.

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The standard SSH and secure Git credential options similarly show that there are simply

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no active connections present.

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Furthermore, down in the Remote Servers and Local Browser tab, there is similarly no connection.

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In the Computer Use section, we can alternatively use the Google Chrome browser extension.

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So, our primary GitHub repository profile is clearly not effectively connected to the system just yet.

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I will intentionally just type out the specific query.

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Is GitHub firmly connected to Codex right now?

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to quickly see if we actually get a reassuring green verification tick.

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This built-in diagnostic tool will thoroughly check the back-end systems

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and explicitly tell us if our GitHub account is successfully connected or not.

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Simultaneously, I will efficiently search for the precise phrasing

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GitHub and official codex integration securely online.

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This highly powerful system connection can miraculously be added directly without any significant friction.

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It prominently includes highly advanced automated pull request code reviews,

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a dedicated co-pilot AI coding agent and deeply integrated GitHub workflow actions.

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We will comprehensively discuss absolutely all of these incredible back-end setup options in extreme detail.

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The diagnostic system now clearly shows that the official GitHub integration plugin

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is indeed fully available directly within the primary codex plugin section.

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But, unfortunately, this specific local workspace folder

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is actually not initialised as a valid Git repository right now.

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A brand new Git tracking folder is quickly being created in the background.

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Now, if we explicitly click the prominent plus button on the user interface,

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we can clearly see the GitHub icon safely listed in the available plugins directory.

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But we critically want to verify exactly which specific user account is currently connected directly to our active GitHub plugin extension.

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We currently cannot seem to find our primary GitHub profile, so we will manually initiate a deep search for it.

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When we effectively run the search, the official GitHub authentication app finally appears.

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The application safely requests broad permission to actively access repositories, track software issues and manage pull requests.

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But we have simply not fully connected it just yet.

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So we will proceed to log securely into our main GitHub account.

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This is our dedicated primary account explicitly named metabrains-del.

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It undeniably has many repositories and we have done a lot of work here.

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We will now meticulously connect this specific GitHub account directly to our active Codex

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system workspace.

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When I confidently click the connect button, it explicitly asks for final permission to

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securely connect to GitHub servers.

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It safely allows the underlying ChatGPT engine to carefully read our previous chats and stored

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memories to consistently give significantly better, context-aware answers.

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It clearly states that your deep personal privacy permissions are heavily respected,

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and you are always completely in control.

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It does warn that external connectors may possibly introduce some slight security risk.

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I will boldly open up our Direct GitHub Developer Dashboard.

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You can visually see that the secure GitHub app authorisation connection is actively starting

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in the background.

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Absolutely all our ongoing critical development work is safely housed right here.

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We will press firmly to continue onward to GitHub so we can comfortably go straight to

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our main profile account.

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It will naturally take a little bit of processing time to fully connect.

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A basic connection will form.

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You can see it is connected.

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I open plugins again.

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Now you will actively see that our dedicated GitHub plugin is finally working precisely

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as intended.

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It smoothly works specifically because it is successfully connected to the backend.

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If it is ever mysteriously not connected, we can easily check our credentials again to see if we can actively reconnect it.

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We currently have our active user login, but unfortunately, adding the specific external link just failed.

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Why exactly did it suddenly fail here?

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We must remember that this is our specific ChatGPT Plus tier account.

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You absolutely must remember this vital detail because it impacts our permissions.

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Now we will purposefully open up the completely alternative ChatGPT account instead.

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We will securely bring our dedicated Michael DuPont user account right here into the active workspace to try again.

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Our premium ChatGPT plus subscription tier is fully available right here.

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Now we will carefully attempt to securely connect the integration system once again.

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It will systematically connect our main chat GPT interface to the repository.

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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.

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We obviously also have the standard option to immediately disconnect the authorization any time.

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We will gracefully proceed straight directly over to the main GitHub authorisation portal.

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Now it will successfully build the required connection directly in our correct targeted application.

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It strictly demands highly secure multi-factor user authentication.

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We will comfortably utilise the standard Authenticator mobile app to handle this.

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The mobile Authenticator app will swiftly finish processing our deep security verification.

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Now you can clearly see that our primary GitHub profile is finally directly connected perfectly.

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I will quickly pivot back over to our main codex interface.

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You can clearly see that our secure software link is now fully established and solidly connected.

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If we carefully look directly at our active system plugins list right now,

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absolutely all our relevant GitHub integration tasks have delightfully started showing up directly in there.

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We will smoothly navigate back over to our main chat terminal interface.

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00:37:25,417 --> 00:37:33,417
You can very clearly see our dedicated GitHub functionality is directly added and fully available right there.

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We will quickly go back over to the plugins tab and our GitHub features will be permanently included in the active workflow loop.

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It will effortlessly come directly into our daily software development work.

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Ultimately, we have incredibly successfully added our robust Codex AI tool to perfectly

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sync with our remote GitHub code repositories.

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Moving logically to the very next crucial step, we will thoroughly talk about the highly

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specific agents.md configuration file.

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This incredibly important file is primarily used for organising massively big software

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development projects. We specifically utilise it whenever we happen to have

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many complex automated tasks or a full highly detailed business use case to

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carefully look at. I will intentionally open it up right here on the screen so

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you can clearly see exactly where these vital agent configuration files

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naturally come from and exactly where to easily find them. It will reliably give

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00:38:41,517 --> 00:38:45,937
us the system response directly and accurately.

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00:38:45,937 --> 00:38:52,717
The dedicated agents.md file immensely helps us to deeply inspect and standardise our overall

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00:38:52,717 --> 00:38:55,237
project architecture.

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You can clearly see it actively looking deep inside our raw project files.

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Here, it explicitly states that the active workspace is entirely empty right now.

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There is absolutely no agents.md file found.

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It checked the temporary scratch space and verified there is no file.

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To successfully create one from scratch, we absolutely must make a brand new, correctly

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formatted Agents.md file.

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I will manually go ahead and create a brand new foundational file right here for you.

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This incredibly efficient way, we can consistently see absolutely all the necessary high level

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production details firmly embedded safely within this specific file.

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First, the core Structured Agents file is quickly drafted out.

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Right after that initial phase, we can comfortably make far more highly nuanced text changes

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to this preliminary draft.

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In this specific advanced technical setup, we usually really need to carefully check

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if our highly specific basic operational rules or distinct business use cases are actually

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working properly.

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00:40:13,918 --> 00:40:18,698
successfully and directly created an excellent base foundational agent file

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right here for us. If we carefully review the generated file we can clearly see

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its intended core purpose. Besides the purpose there is a clear project

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00:40:30,738 --> 00:40:37,698
overview. We also see a working agreement, a layout and editing rules. We can

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00:40:37,698 --> 00:40:42,118
actively cross-check all of these fundamental operational rules precisely

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here in the document. I will also make sure to explicitly tell you exactly where

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this specialized configuration file is typically used. We consistently use the

460
00:40:53,698 --> 00:40:58,738
specialized agents.md file to effectively establish strict working

461
00:40:58,738 --> 00:41:04,998
boundaries and core rules for literally any AI agent operating in the workspace.

462
00:41:04,998 --> 00:41:10,198
There are basically no other bizarre tasks or unrelated work explicitly meant

463
00:41:10,198 --> 00:41:17,458
for it. Sometimes, unfortunately, we literally have to go deep down into our underlying operating

464
00:41:17,458 --> 00:41:24,958
system just to manually set up the complex agents.md file perfectly. This tedious manual

465
00:41:24,958 --> 00:41:30,958
process admittedly takes quite a lot of valuable development time. We essentially have to carefully

466
00:41:30,958 --> 00:41:37,138
look at so many different distinct things, like our strict project requirements, core team work

467
00:41:37,138 --> 00:41:44,418
ethics and several other highly detailed technical options. We absolutely need to fully know how to

468
00:41:44,418 --> 00:41:50,318
properly handle these nuanced things. But for massively big projects, we only deliberately

469
00:41:50,318 --> 00:41:58,178
include our basic setup requirements here. Moving right along, next we will deeply discuss exactly

470
00:41:58,178 --> 00:42:04,178
how to effectively use this incredibly vital agents.md file in standard practice.

471
00:42:04,178 --> 00:42:14,358
Deeply understanding this specific core concept is an undeniably very important foundational part of the entire development process

472
00:42:14,358 --> 00:42:23,358
We absolutely need to fully know exactly how to actively create the underlying file directly from absolute scratch

473
00:42:24,478 --> 00:42:30,738
Now we purposefully transition and move seamlessly right over to the very next important part

474
00:42:30,738 --> 00:42:42,558
We will fundamentally learn exactly how to appropriately handle highly complex things and deeply understand them right after actively creating the foundational file.

475
00:42:43,498 --> 00:42:48,898
This is fundamentally a highly special, deeply vital system instruction file.

476
00:42:49,898 --> 00:42:57,618
It consistently provides invaluable deep guidance and much needed environmental context directly for our automated work.

477
00:42:57,618 --> 00:43:05,158
It can absolutely also be used incredibly effectively, exactly like a traditional readme developer file.

478
00:43:06,298 --> 00:43:12,158
You might vividly remember that standard software developers constantly use structured readme files.

479
00:43:12,978 --> 00:43:15,998
In the exact same way, we can use this file.

480
00:43:15,998 --> 00:43:30,438
I have created a basic agents.md file, but incredibly, we can undoubtedly also meticulously make a highly reusable foundational agents.md configuration template right here in the workspace.

481
00:43:31,158 --> 00:43:39,078
We can comfortably and securely include absolutely all of our strict foundational base development requirements firmly inside it.

482
00:43:39,658 --> 00:43:45,298
This proactive step will flawlessly kickstart our broader automation work immediately.

483
00:43:45,998 --> 00:43:52,238
I will gladly proceed to show you an excellent, highly structured example right now.

484
00:43:52,238 --> 00:43:57,998
I will purposely open up Microsoft Word or a standard blank doc text document.

485
00:43:57,998 --> 00:44:02,698
I am deliberately using a blank doc right now, strictly so we can comfortably start

486
00:44:02,698 --> 00:44:06,118
a fresh, entirely new, empty document.

487
00:44:06,118 --> 00:44:12,318
Here, you can very clearly see exactly what critical structural things are highly recommended

488
00:44:12,318 --> 00:44:13,878
and available.

489
00:44:13,878 --> 00:44:19,538
First, we logically have the high-level project overview section.

490
00:44:19,538 --> 00:44:24,878
This clearly tells us exactly what core deliverables we strictly need in the project.

491
00:44:24,878 --> 00:44:32,158
Next, we definitely have the strict team coding standards that we must absolutely follow.

492
00:44:32,158 --> 00:44:38,758
After that, we discuss repository structures, testing requirements, security rules and large-scale

493
00:44:38,758 --> 00:44:40,858
systems.

494
00:44:40,858 --> 00:44:46,138
We will practically use a fully functional, highly complete, overarching working system

495
00:44:46,138 --> 00:44:47,138
here.

496
00:44:47,138 --> 00:44:53,858
Our strictly prohibited, highly restricted system areas will absolutely also be meticulously

497
00:44:53,858 --> 00:44:57,898
explicitly listed right here for immense safety.

498
00:44:57,898 --> 00:45:04,858
Then, our highly nuanced, deeply specific primary AI operational instructions will be

499
00:45:04,858 --> 00:45:07,798
thoroughly included next.

500
00:45:07,798 --> 00:45:13,198
Right after all the comprehensive AI baseline instructions, we will seamlessly have all

501
00:45:13,198 --> 00:45:18,758
our broader, full-feature architectural options carefully documented.

502
00:45:18,758 --> 00:45:24,078
This is essentially exactly what we traditionally call a comprehensive, well-structured readme

503
00:45:24,078 --> 00:45:26,978
file in standard development.

504
00:45:26,978 --> 00:45:32,958
It practically has all our complete, strict baseline instructions deeply hard-coded and

505
00:45:32,958 --> 00:45:36,118
built directly right into it.

506
00:45:36,118 --> 00:45:41,758
After this section is successfully completed, the very next essential technical thing dynamically

507
00:45:41,758 --> 00:45:47,258
available is dealing with our sensitive back-end environment variables.

508
00:45:47,258 --> 00:45:53,298
We will deeply see precisely how we can effectively, securely manage these highly critical system

509
00:45:53,298 --> 00:45:55,718
environment variables.

510
00:45:55,718 --> 00:46:03,898
Now, our next incredibly critical technical discussion is primarily about handling robust

511
00:46:03,898 --> 00:46:11,578
backend environment variables. These are essentially highly dynamic, configurable key values operating

512
00:46:11,578 --> 00:46:17,418
in the background. We can actively store them either directly or indirectly deep within

513
00:46:17,418 --> 00:46:23,538
our underlying operating system infrastructure. We can comfortably and securely utilise them

514
00:46:23,538 --> 00:46:31,138
later for absolutely all of our other automated complex coding tasks. Usually, we deeply involve

515
00:46:31,138 --> 00:46:38,318
our complete, highly systematic overall workflow process directly here to explicitly see exactly

516
00:46:38,318 --> 00:46:44,118
how a full, robust software system is successfully constructed.

517
00:46:44,118 --> 00:46:49,498
These are highly dynamic back-end key values that are stored strictly and directly inside

518
00:46:49,498 --> 00:46:55,618
the native operating system, kept entirely safely outside of our vulnerable, raw source

519
00:46:55,618 --> 00:47:02,858
code files. They heavily detect and dictate precisely how the running process fundamentally

520
00:47:02,858 --> 00:47:09,918
behaves. This brilliant system effortlessly allows developers to incredibly safely store

521
00:47:09,918 --> 00:47:17,258
highly sensitive security credentials. What exactly are sensitive credentials? It is highly

522
00:47:17,258 --> 00:47:24,818
vital to see this clearly. If we fail to understand this, our work suffers. Sometimes developers

523
00:47:24,818 --> 00:47:30,258
are understandably incredibly afraid that their highly sensitive personal or corporate

524
00:47:30,258 --> 00:47:36,438
information will eventually accidentally leak to the dangerous public internet.

525
00:47:36,438 --> 00:47:39,838
Why exactly does this enormous fear exist?

526
00:47:39,838 --> 00:47:45,818
Basically, because our complete interconnected development environment inherently has some

527
00:47:45,818 --> 00:47:48,938
deeply guarded secrets.

528
00:47:48,938 --> 00:47:54,698
These highly confidential items definitely include things like private API keys, secure

529
00:47:54,698 --> 00:47:58,658
admin account usernames and highly encrypted user passwords.

530
00:47:59,801 --> 00:48:03,581
We absolutely have to carefully look closely at them and protect them.

531
00:48:04,661 --> 00:48:11,441
Now we officially pivot to selectively talk about the massive, overarching enterprise operational level.

532
00:48:11,441 --> 00:48:17,181
What exactly inherently happens operating at the massive enterprise scale level?

533
00:48:18,061 --> 00:48:23,661
Let us quickly intentionally open up a brand new, fresh, isolated chat window.

534
00:48:24,661 --> 00:48:30,061
At the highest enterprise level, actively managing profound structural secrets properly

535
00:48:30,061 --> 00:48:36,001
is absolutely critical for safely protecting tremendously sensitive proprietary information.

536
00:48:37,241 --> 00:48:40,841
Secrets routinely may include remote cloud access keys,

537
00:48:40,841 --> 00:48:47,841
massive database passwords, complex encryption keys, vital third-party API credentials,

538
00:48:48,641 --> 00:48:51,161
and various access authentication tokens.

539
00:48:52,521 --> 00:48:56,001
Handling environment variables securely with codecs is important.

540
00:48:56,481 --> 00:49:04,061
These specific, crucial security items are undeniably very important to actively manage appropriately right here.

541
00:49:04,061 --> 00:49:11,061
Usually, wildly different distinct deployment environments inherently fundamentally require

542
00:49:11,061 --> 00:49:14,281
completely different sets of unique configuration values.

543
00:49:15,501 --> 00:49:19,801
We can intelligently deploy and actively utilise them safely over there.

544
00:49:21,201 --> 00:49:28,321
Let me clearly tell you, whenever I actively try to perform a direct system search for standard environment variables,

545
00:49:28,321 --> 00:49:35,521
you immediately see our primary system environment variables are visibly available precisely right here.

546
00:49:36,521 --> 00:49:45,541
You will undeniably see that absolutely all of our current environment variables are entirely accessible and available literally right now.

547
00:49:46,821 --> 00:49:51,301
Sometimes it happens to merely be the static number of active system processors.

548
00:49:52,681 --> 00:49:56,481
Sometimes it is a highly confidential external API key.

549
00:49:56,481 --> 00:50:02,821
We can smoothly dive deep directly right into the back-end system variables menu,

550
00:50:03,701 --> 00:50:06,661
carefully enter the specific custom variable name

551
00:50:06,661 --> 00:50:12,241
and its corresponding strict value directly and permanently safely store it.

552
00:50:13,561 --> 00:50:19,461
So, the next time we run a use case, all variables are automatically set perfectly.

553
00:50:20,601 --> 00:50:25,961
How exactly is this properly handled inside a secure underlying database architecture?

554
00:50:26,481 --> 00:50:33,241
As you can visibly observe precisely here, located deep inside the primary configuration

555
00:50:33,241 --> 00:50:41,081
interface, we purposely actively include a dedicated corporate company database link.

556
00:50:41,081 --> 00:50:47,561
If there happens to clearly be a specific network port required, we firmly include it.

557
00:50:47,561 --> 00:50:53,241
If there explicitly is an overarching master application configuration requirement, we

558
00:50:53,241 --> 00:51:00,241
we safely add the core app environment variable alongside the specific designated app port.

559
00:51:00,241 --> 00:51:08,701
Secure, highly confidential API credentials will absolutely come directly right here.

560
00:51:08,701 --> 00:51:15,821
For one clear example, if we genuinely want to safely utilise an external OpenAI API authentication

561
00:51:15,821 --> 00:51:20,261
key, we securely do it precisely here.

562
00:51:20,261 --> 00:51:25,881
We can undoubtedly also clearly see secure encrypted payment gateway keys stored right

563
00:51:25,881 --> 00:51:26,881
here.

564
00:51:26,881 --> 00:51:33,401
Then, there are massive authentication backend settings designed purely to store multiple

565
00:51:33,401 --> 00:51:36,081
dynamic secrets.

566
00:51:36,081 --> 00:51:43,341
These environment variables brilliantly enable large organisations to safely manage app configurations.

567
00:51:43,341 --> 00:51:47,601
It prevents leaking sensitive information.

568
00:51:47,601 --> 00:51:54,481
handles keys safely too without hard coding. I will definitively also sincerely tell you

569
00:51:54,481 --> 00:51:59,821
that strict environment variables frankly may not initially actively seem incredibly

570
00:51:59,821 --> 00:52:04,761
very important right now when we merely successfully create basic simple software,

571
00:52:05,641 --> 00:52:10,701
absolutely like a fundamental basic calculator or standard normal terminal tools.

572
00:52:10,701 --> 00:52:17,601
however the exact moment when we actively rigorously try to fundamentally change our

573
00:52:17,601 --> 00:52:23,981
massive software architecture or alter major things safely on a significantly much larger

574
00:52:23,981 --> 00:52:31,041
incredibly massive corporate scale literally many distinct individual things wildly realistically

575
00:52:31,041 --> 00:52:38,021
start changing aggressively side by side simultaneously we immediately rapidly actively

576
00:52:38,021 --> 00:52:44,241
see literally multiple deep cascading fundamental code structural changes happening.

577
00:52:45,141 --> 00:52:52,461
Now, moving confidently right forward seamlessly, we will deeply, actively, rigorously, explicitly

578
00:52:52,461 --> 00:52:59,141
discuss all of these major systematic fundamental software changes and deeply integrated highly

579
00:52:59,141 --> 00:53:01,581
complex AI functions directly later.

580
00:53:02,081 --> 00:53:05,041
We will explore this in the next sections perfectly.

581
00:53:08,021 --> 00:53:16,021
Authentication and access configuration is a critical part of using OpenAI codecs in an enterprise development environment.

582
00:53:17,021 --> 00:53:23,021
Authentication verifies the identity of the user or system attempting to use codecs,

583
00:53:23,021 --> 00:53:29,021
while access configuration defines what that user or system is allowed to do.

584
00:53:29,021 --> 00:53:42,801
Together, these controls ensure that only authorised developers, teams and automation tools can interact with repositories, environments, APIs and sensitive project resources.

585
00:53:43,781 --> 00:53:55,781
In enterprise software development, Codex usually works with cloud-based development environments, GitHub repositories, CI-cd pipelines and internal tools.

586
00:53:55,781 --> 00:54:07,041
Because these systems may contain confidential source code, credentials, customer data and deployment configurations, access must be carefully managed.

587
00:54:08,441 --> 00:54:17,061
A weak authentication setup can expose the organisation to unauthorised code access, accidental changes or security breaches.

588
00:54:17,061 --> 00:54:25,981
Therefore, enterprises commonly rely on identity providers, single sign-on, role-based access

589
00:54:25,981 --> 00:54:32,901
control and audit logging. The authentication process normally begins when a developer signs

590
00:54:32,901 --> 00:54:40,581
in using an approved identity provider. This may include enterprise login systems such as SSO,

591
00:54:40,581 --> 00:54:48,461
OAuth or multi-factor authentication. Once the user identity is confirmed, the

592
00:54:48,461 --> 00:54:52,341
system checks whether the user has permission to access Codex, the

593
00:54:52,341 --> 00:54:57,981
development workspace and the connected repositories. This ensures that Codex

594
00:54:57,981 --> 00:55:03,821
activities are tied to a verified user and can be tracked for accountability.

595
00:55:03,821 --> 00:55:09,921
Access configuration determines the scope of Codex's permissions. For example,

596
00:55:09,921 --> 00:55:18,921
codecs may be allowed to read a repository, analyse code, create a branch, run tests or open a pull request.

597
00:55:18,921 --> 00:55:25,921
In some cases, it may not be allowed to directly merge code or access production secrets.

598
00:55:25,921 --> 00:55:29,921
These permissions should follow the principle of least privilege,

599
00:55:29,921 --> 00:55:35,921
meaning codecs and users should receive only the access required to complete their assigned tasks.

600
00:55:35,921 --> 00:55:43,361
Repository access is especially important. Codecs must often inspect project files,

601
00:55:43,361 --> 00:55:50,321
understand dependencies and modify code. However, not every repository should be

602
00:55:50,321 --> 00:55:56,421
accessible to every user or AI workflow. Enterprises should configure repository

603
00:55:56,421 --> 00:56:00,361
permissions based on teams, projects and business sensitivity.

604
00:56:01,665 --> 00:56:07,025
For example, a front-end developer may receive access to UI repositories

605
00:56:07,025 --> 00:56:10,865
but not to payment infrastructure or identity management services.

606
00:56:10,865 --> 00:56:15,865
Environment variables and secrets also require strict control.

607
00:56:15,865 --> 00:56:22,865
Codecs may need to understand variable names, configuration patterns or runtime requirements,

608
00:56:22,865 --> 00:56:26,865
but it should not expose or hard code secret values.

609
00:56:26,865 --> 00:56:33,865
Sensitive credentials should be stored in secure secret managers and injected only when required.

610
00:56:33,865 --> 00:56:42,465
This prevents accidental leakage of API keys, tokens, database passwords or cloud credentials

611
00:56:42,465 --> 00:56:45,185
into source code.

612
00:56:45,185 --> 00:56:51,485
Auditability is another major requirement in enterprise access configuration.

613
00:56:51,485 --> 00:56:56,705
Organisations should be able to review who accessed codecs, which repositories were used,

614
00:56:56,705 --> 00:57:01,545
what tasks were performed and what changes were generated.

615
00:57:01,545 --> 00:57:07,605
logs help security teams investigate incidents, enforce governance policies, and demonstrate

616
00:57:07,605 --> 00:57:11,705
compliance with internal or regulatory standards.

617
00:57:11,705 --> 00:57:18,145
A well-designed authentication and access configuration model allows enterprises to use codecs safely

618
00:57:18,145 --> 00:57:20,285
and efficiently.

619
00:57:20,285 --> 00:57:26,865
It protects sensitive assets while still enabling developers to benefit from AI-assisted coding.

620
00:57:26,865 --> 00:57:33,045
By combining strong identity verification, scoped permissions, secure secret handling

621
00:57:33,045 --> 00:57:38,985
and continuous monitoring, organisations can create a controlled environment where Codex

622
00:57:38,985 --> 00:57:43,205
improves productivity without increasing operational risk.

623
00:57:43,205 --> 00:57:46,205
We discuss Codex workflows now.

624
00:57:46,205 --> 00:57:49,745
We want to see how Codex uses large workflows.

625
00:57:49,745 --> 00:57:53,865
We look at complete software solutions and workability.

626
00:57:53,865 --> 00:57:57,645
Sometimes we must see how the whole process grows over time.

627
00:57:57,645 --> 00:58:02,045
For this, we change and improve code on a large scale.

628
00:58:02,045 --> 00:58:06,105
After these changes, we check the overall process understanding.

629
00:58:06,105 --> 00:58:09,645
I will tell you about Codex workflows.

630
00:58:09,645 --> 00:58:13,305
Codex helps developers in the software development lifecycle.

631
00:58:13,305 --> 00:58:15,365
It does repeating tasks.

632
00:58:15,365 --> 00:58:18,105
It makes the coding environment fast.

633
00:58:18,105 --> 00:58:21,625
It helps us understand how to fix different problems.

634
00:58:21,625 --> 00:58:25,125
It helps us understand different work processes.

635
00:58:25,125 --> 00:58:29,285
The most important discussion is how we use codecs.

636
00:58:29,285 --> 00:58:31,005
We start with a prompt.

637
00:58:31,005 --> 00:58:33,385
We can add details in the prompt.

638
00:58:33,385 --> 00:58:35,725
This helps software work well.

639
00:58:35,725 --> 00:58:40,505
We use prompts to make software processes easy, fast.

640
00:58:40,505 --> 00:58:42,085
We start with the prompt.

641
00:58:42,085 --> 00:58:44,585
We can add details in the prompt.

642
00:58:44,585 --> 00:58:48,125
The important thing in the prompt is a defined objective.

643
00:58:48,125 --> 00:58:51,145
We must have a defined objective.

644
00:58:51,145 --> 00:58:55,065
We bring this objective into our software and working process.

645
00:58:55,065 --> 00:58:58,185
First, we take the generation process.

646
00:58:58,185 --> 00:59:01,405
We understand the process on a large scale.

647
00:59:01,405 --> 00:59:04,365
We see how we generate everything.

648
00:59:04,365 --> 00:59:06,885
We have one big question.

649
00:59:06,885 --> 00:59:10,425
The question is how to define the objective.

650
00:59:10,425 --> 00:59:12,625
We look at things to define it.

651
00:59:12,625 --> 00:59:15,945
We will see how these things work together.

652
00:59:15,945 --> 00:59:18,925
This is a very strong and important point.

653
00:59:18,925 --> 00:59:23,825
We must know how to set up objectives for large generation.

654
00:59:23,825 --> 00:59:27,205
After we set the objective, we look at the next steps.

655
00:59:27,205 --> 00:59:30,205
The next step is feature development.

656
00:59:30,205 --> 00:59:34,025
Feature development is a process in our pipeline.

657
00:59:34,025 --> 00:59:38,725
After development, the next thing is software defect identification.

658
00:59:38,725 --> 00:59:43,445
We must make this defect identification process strong.

659
00:59:43,445 --> 00:59:46,845
After we find defects, we move to next steps.

660
00:59:46,845 --> 00:59:50,125
The next steps are refactoring and optimization.

661
00:59:50,125 --> 00:59:53,605
First, we must define a task.

662
00:59:53,605 --> 00:59:57,245
We must have a clear task definition.

663
00:59:57,245 --> 01:00:01,045
After we define the task, we provide background context.

664
01:00:01,045 --> 01:00:04,685
We provide this context on a large scale.

665
01:00:04,685 --> 01:00:07,085
I will explain this process to you.

666
01:00:07,085 --> 01:00:10,605
I will use a flow diagram to show how things work.

667
01:00:10,605 --> 01:00:13,845
First, we have the task definition.

668
01:00:13,845 --> 01:00:17,145
Next, we have Task Context.

669
01:00:17,145 --> 01:00:20,805
We must know how to add the context.

670
01:00:20,805 --> 01:00:24,345
After the context, we need a detailed prompt.

671
01:00:24,345 --> 01:00:27,285
Then we connect our main codecs.

672
01:00:27,285 --> 01:00:30,725
We connect codecs with our own codebases.

673
01:00:30,725 --> 01:00:35,945
We connect codecs with our codebases to show complete analysis.

674
01:00:35,945 --> 01:00:39,965
After analysis, we must have Solution Generation.

675
01:00:39,965 --> 01:00:43,025
Solution Generation must be available.

676
01:00:43,025 --> 01:00:47,225
After solution generation, the next step is review.

677
01:00:47,225 --> 01:00:50,265
I tell you we need these things in our prompt.

678
01:00:50,265 --> 01:00:53,745
When we have these things, our prompt starts.

679
01:00:53,745 --> 01:00:58,245
Inside this prompt, our solution generation process starts.

680
01:00:58,245 --> 01:01:01,245
Here we have our solution generation.

681
01:01:01,245 --> 01:01:04,225
After we generate the solution, we review it.

682
01:01:04,225 --> 01:01:07,545
We check everything in the review step.

683
01:01:07,545 --> 01:01:10,285
After the review, another process starts.

684
01:01:10,285 --> 01:01:17,285
We call this new process testing. Testing is very important here. In testing we include

685
01:01:17,285 --> 01:01:25,185
debugging. Both testing and debugging must happen together. We need both in our workflow.

686
01:01:25,185 --> 01:01:30,745
They help us find and fix problems. These steps make the software better and ready for

687
01:01:30,745 --> 01:01:36,765
final stages. Both testing and debugging must be present.

688
01:01:36,765 --> 01:01:39,845
The last step available here is refinement.

689
01:01:39,845 --> 01:01:43,345
We call this refinement process iteration.

690
01:01:43,345 --> 01:01:46,765
We do refinement to make software better.

691
01:01:46,765 --> 01:01:49,885
After the refinement step, we commit changes.

692
01:01:49,885 --> 01:01:52,785
We save all the changes we made.

693
01:01:52,785 --> 01:01:55,345
This is the complete process.

694
01:01:55,345 --> 01:01:58,045
At the end, our workflow closes.

695
01:01:58,045 --> 01:02:00,865
It closes at the deployment stage.

696
01:02:00,865 --> 01:02:02,785
We go to deployment.

697
01:02:02,785 --> 01:02:06,065
We deploy our project into our system.

698
01:02:06,065 --> 01:02:08,905
These steps are helpful on a large scale.

699
01:02:08,905 --> 01:02:11,265
They help us create a better score.

700
01:02:11,265 --> 01:02:14,985
They help us create a better decision tree for work.

701
01:02:14,985 --> 01:02:18,845
This is how the complete workflow operates from start to finish.

702
01:02:18,845 --> 01:02:22,405
We follow these simple rules to make good software.

703
01:02:22,405 --> 01:02:25,945
Every step is important for the final product.

704
01:02:25,945 --> 01:02:28,265
Deployment is the final goal of this journey.

705
01:02:28,265 --> 01:02:31,085
Our next talk is about codecs.

706
01:02:31,085 --> 01:02:34,365
We will learn about our projects in codecs.

707
01:02:34,365 --> 01:02:39,525
Project navigation is a very important AI skill in modern software development.

708
01:02:39,525 --> 01:02:44,765
In big business places, developers work with big repositories often.

709
01:02:44,765 --> 01:02:47,785
These repositories have thousands of files.

710
01:02:47,785 --> 01:02:50,965
We can see our multiple services directly.

711
01:02:50,965 --> 01:02:57,365
It also sees big documentation, complex dependencies and multiple servers.

712
01:02:57,365 --> 01:03:02,305
Understanding these projects by hand needs much time and effort.

713
01:03:02,305 --> 01:03:09,665
helps developers understand the project structures well. It finds correct files, traces dependencies,

714
01:03:09,665 --> 01:03:16,065
and locates our implementation details. I go to the project menu directly. I click

715
01:03:16,065 --> 01:03:23,345
Start from scratch. I name the new project Metabrains. I start one project directly here.

716
01:03:24,065 --> 01:03:30,225
I save it. Now we have a new project. There is no chat available yet in the project.

717
01:03:30,225 --> 01:03:33,225
You see our Explorer and Object options.

718
01:03:33,225 --> 01:03:37,225
If we turn on the Explorer, our file opens automatically.

719
01:03:37,225 --> 01:03:41,225
You can see we have no document available yet.

720
01:03:41,225 --> 01:03:45,225
With time, we will make many additions and changes.

721
01:03:45,225 --> 01:03:49,225
Automatically, our response and style will change.

722
01:03:49,225 --> 01:03:51,225
I will start from the beginning.

723
01:03:51,225 --> 01:03:55,225
We will look at all the changes we make from start to now.

724
01:03:55,225 --> 01:03:59,225
Along with changes, we will also see the time.

725
01:03:59,627 --> 01:04:04,147
Along with changes we will also see the time. We will see how much time one full cycle takes.

726
01:04:04,147 --> 01:04:09,467
We can look at the complete process directly. Sometimes we must approve things directly

727
01:04:09,467 --> 01:04:15,907
to understand them, I will tell you. I will type what things should be in our project.

728
01:04:15,907 --> 01:04:25,387
I write create an agent.md file. We will create the agent.md file here. This makes our agent

729
01:04:25,387 --> 01:04:31,627
work in a much better way. I type because this is a corporate sales manager and content

730
01:04:31,627 --> 01:04:38,307
creator project. It will do the first step of our project here. First of all, we give

731
01:04:38,307 --> 01:04:44,867
the context and our details. We are making the employee do these things here. We will

732
01:04:44,867 --> 01:04:50,787
include this directly for our approval. I tell you that a complete process discussion

733
01:04:50,787 --> 01:04:58,307
is very important here. In this, we have to involve all our details. We must involve our

734
01:04:58,307 --> 01:05:04,987
full working process here. You can see it will take some time, obviously. It is working

735
01:05:04,987 --> 01:05:13,847
in our exact folder. If I refresh our folder here, you will see the agent.md file is created.

736
01:05:13,847 --> 01:05:20,347
We can directly review it here. It created the agent.md file with a tailored operating

737
01:05:20,347 --> 01:05:27,827
brief. This is for the corporate sales manager and content project. The agent.md file is

738
01:05:27,827 --> 01:05:34,667
made here. You can see our exact source code and other things are available. We can open

739
01:05:34,667 --> 01:05:41,467
it directly in our VS code. We can open it in the default application. We can also open

740
01:05:41,467 --> 01:05:48,167
it in our terminal. These things are much better here. We have a complete system environment.

741
01:05:49,707 --> 01:05:56,227
Automatically, we see all divisions and working ability here. Sometimes, this working ability

742
01:05:56,227 --> 01:06:03,547
or complete process causes problems. It causes problems on a big scale. We see many issues

743
01:06:03,547 --> 01:06:10,207
in our work. We usually create our complete empty MD file at the very start of the project

744
01:06:10,207 --> 01:06:18,347
setup. So, on a big scale, if any issue happens later, we can understand it early. We can

745
01:06:18,347 --> 01:06:25,087
do things early according to our system. This is a basic discussion now. We see how complete

746
01:06:25,087 --> 01:06:32,187
generation happens. We see how we take a complete process or understanding with us. After the

747
01:06:32,187 --> 01:06:38,627
agent.md file we will directly look at our project structure. I will go into the exact

748
01:06:38,627 --> 01:06:44,727
same folder. I will include a new folder here. This is from a previously created section.

749
01:06:45,627 --> 01:06:51,007
You can see our portfolios are available here. I will do all the portfolio discussion here.

750
01:06:51,927 --> 01:06:59,167
I will now analyse our repository. I write analyse this repository and provide a comprehensive

751
01:06:59,167 --> 01:07:05,827
overview of the project structure. It includes the main purpose of the application. Then we have

752
01:07:05,827 --> 01:07:12,947
high-level architecture. Then we have important directories. Then we have all options for

753
01:07:12,947 --> 01:07:20,287
important directories on a big scale. After major frameworks, we have entry points. After entry

754
01:07:20,287 --> 01:07:27,567
points, we have configuration files. Then we have deployment-related files. Then we have testing

755
01:07:27,567 --> 01:07:32,567
structure. Then it says present the information in a structured format,

756
01:07:32,567 --> 01:07:37,667
suitable for onboarding a new developer. We can take our things directly in

757
01:07:37,667 --> 01:07:43,007
developer onboarding too. We can involve them. This is a complete structured

758
01:07:43,007 --> 01:07:47,847
repository layout that we use here. Sometimes we must see some changes in

759
01:07:47,847 --> 01:07:52,767
this too. In this we also involve multiple repositories and options

760
01:07:52,767 --> 01:07:58,827
directly. When I enter this it will directly go to our folder. The index file

761
01:07:58,827 --> 01:08:05,127
is inside. You can see this is like our index file. When the index file opens a

762
01:08:05,127 --> 01:08:10,647
complete portfolio website is available. Now we will see how to enhance and

763
01:08:10,647 --> 01:08:15,887
understand this portfolio website on a big scale. This will happen in our codex

764
01:08:15,887 --> 01:08:23,147
here. It understood the child item here. After that it showed our files. It has

765
01:08:23,147 --> 01:08:30,707
shown the key pattern too. We have one HTML document. We have one style sheet. We

766
01:08:30,707 --> 01:08:37,307
have one script bundle. Then we have some static assets. We also have all other

767
01:08:37,307 --> 01:08:43,787
things available to use directly. Now I will take our details. I will see how our

768
01:08:43,787 --> 01:08:50,687
process runs. I will see how all direct discussions and details run. With this we

769
01:08:50,687 --> 01:08:55,607
will take our setup. Usually this needs a lot of time if we take these things in

770
01:08:55,607 --> 01:09:01,527
another environment but here our things are much simpler now. We can include much

771
01:09:01,527 --> 01:09:07,547
better things and accounts here. I will look at our direct use case now. It read

772
01:09:07,547 --> 01:09:12,727
out our whole folder here. After that it told us there are no platform specific

773
01:09:12,727 --> 01:09:17,407
deployment manifests checked into the repository. The deployment guidance is

774
01:09:17,407 --> 01:09:23,287
document only. After that we have a testing structure. Then all other things

775
01:09:23,287 --> 01:09:28,867
have come. Now we have gone inside our project. We have seen how we will include

776
01:09:28,867 --> 01:09:34,487
our system. Now I will see what entry points are available there. I will write

777
01:09:34,487 --> 01:09:39,307
to find the entry points. If we want to look at something other than entry points

778
01:09:39,307 --> 01:09:42,687
we will involve all user authentication features here.

779
01:09:43,267 --> 01:09:45,087
We will see how we can look at them.

780
01:09:46,047 --> 01:09:49,647
Along with this, we will get a direct response from the complete system.

781
01:09:50,407 --> 01:09:53,847
We will see how we take things directly in our system first.

782
01:09:54,847 --> 01:09:59,327
I will type to locate and explain the implementation of the user authentication feature.

783
01:10:00,027 --> 01:10:02,967
I will identify all the components involved here.

784
01:10:03,707 --> 01:10:06,047
Then I will look at the authentication flow.

785
01:10:06,047 --> 01:10:09,507
Then I will look at the authentication middleware

786
01:10:09,507 --> 01:10:12,327
Then I will look at password handling

787
01:10:12,327 --> 01:10:15,967
Then I will look at the token generation process

788
01:10:15,967 --> 01:10:19,527
Then I will look at the session or token management

789
01:10:19,527 --> 01:10:25,447
Then I will provide a step-by-step explanation of how the application starts

790
01:10:25,447 --> 01:10:30,687
Then I will process the requests from login to successful authentication

791
01:10:30,687 --> 01:10:33,887
These things bring all our details here

792
01:10:33,887 --> 01:10:36,587
All our handling has come here now.

793
01:10:37,747 --> 01:10:43,287
Generating code from requirements is one of the most practical uses of OpenAI codecs in everyday development.

794
01:10:44,347 --> 01:10:49,127
Instead of translating every single business requirement into working code by hand,

795
01:10:49,787 --> 01:10:53,587
developers can provide codecs with a vast amount of information or context.

796
01:10:54,787 --> 01:10:58,427
We can include clear instructions, behaviours and context.

797
01:10:59,207 --> 01:11:02,027
We have multiple forms of languages available to use.

798
01:11:02,027 --> 01:11:05,027
Let me open Excalibur here.

799
01:11:05,027 --> 01:11:09,027
As you can see, we have some business languages.

800
01:11:09,027 --> 01:11:19,027
For example, we can allow users to export reports as CSV or involve role-based access control, also known as RBAC.

801
01:11:19,027 --> 01:11:23,027
Codex helps bridge the gap between these requirements and implementations

802
01:11:23,027 --> 01:11:29,027
by identifying relevant files, suggesting changes, creating new components,

803
01:11:29,027 --> 01:11:33,027
updating APIs, and adding tests where needed.

804
01:11:33,027 --> 01:11:39,027
However, Codex works best when the requirements are very specific in nature.

805
01:11:39,027 --> 01:11:43,027
Let me show you how to include basics in Codex right from the start.

806
01:11:43,027 --> 01:11:48,027
Suppose you want a plan mode, and after that you want to pursue a goal.

807
01:11:48,027 --> 01:11:51,027
Then you might want to create a document.

808
01:11:51,027 --> 01:11:56,027
After document creation, you might want to include photos.

809
01:11:56,027 --> 01:11:59,027
You have multiple plugins that you can use side by side.

810
01:12:00,701 --> 01:12:06,281
browser plugin you can use that one too. If you have specific content to use that

811
01:12:06,281 --> 01:12:12,481
can be utilized as well. For instance we can go to documents or downloads, select

812
01:12:12,481 --> 01:12:15,641
Select an available document and use it.

813
01:12:15,641 --> 01:12:18,421
After that we select our model.

814
01:12:18,421 --> 01:12:24,241
This latency is quite important, therefore I will use a latest model here.

815
01:12:24,241 --> 01:12:29,541
With that latest model, we can increase speed and manage latency well.

816
01:12:29,541 --> 01:12:33,921
After this, our prompt should contain very detailed options.

817
01:12:33,921 --> 01:12:38,801
First of all, a well-set prompt has some specific elements available within it.

818
01:12:38,801 --> 01:12:41,321
I will explain these elements to you.

819
01:12:41,321 --> 01:12:45,321
A good prompt includes all these necessary components.

820
01:12:45,321 --> 01:12:52,541
The very first thing is context, followed by the role, details, and then the requirements.

821
01:12:52,541 --> 01:12:57,521
When discussing requirements, it is a crucial point because codex works better when the

822
01:12:57,521 --> 01:12:59,781
requirements are specific.

823
01:12:59,781 --> 01:13:04,261
A vague prompt may produce incomplete or misaligned code.

824
01:13:04,261 --> 01:13:10,761
A strong prompt includes the feature goal, affected users, input and output behaviour,

825
01:13:10,761 --> 01:13:16,521
or modules to consider, coding standards, test expectations and what our codex

826
01:13:16,521 --> 01:13:21,321
should avoid changing. Developers should treat the codex generated code as a

827
01:13:21,321 --> 01:13:26,081
first draft so we get a complete response right from the very start of it.

828
01:13:26,081 --> 01:13:32,061
Next, after the requirements, we need to establish our acceptance criteria. This

829
01:13:32,061 --> 01:13:36,801
defines the standard our response must maintain when we receive it. At the end

830
01:13:36,801 --> 01:13:42,561
we sometimes use a negative prompt. In a negative prompt we specify the things

831
01:13:42,561 --> 01:13:47,561
that we do not need. In the rest of the prompt we list all the necessary things

832
01:13:47,561 --> 01:13:53,241
that we want. However, in a negative prompt we mention all those exact things

833
01:13:53,241 --> 01:13:58,761
that are not required for our output at all. For example, let me show you a sample

834
01:13:58,761 --> 01:14:03,681
prompt right here in this section. We can go into Codex and type out our prompt.

835
01:14:03,681 --> 01:14:12,341
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.

836
01:14:13,561 --> 01:14:17,821
This defines our role. The complete task is outlined in plain words.

837
01:14:18,721 --> 01:14:25,901
After the task, you can see our functional requirements are discussed, such as adding an Export CSV button near the Reports table.

838
01:14:26,881 --> 01:14:30,521
Towards the end, all the detailed steps we need to perform are available.

839
01:14:31,141 --> 01:14:33,341
This is our acceptance criteria.

840
01:14:33,681 --> 01:14:36,681
The export button appears on the report page.

841
01:14:36,681 --> 01:14:39,681
Clicking the button downloads a valid CSV file,

842
01:14:39,681 --> 01:14:43,681
and the CSV contains the same rows displayed on the table.

843
01:14:43,681 --> 01:14:47,681
It will take data straight from the browser, commit the repository in GitHub,

844
01:14:47,681 --> 01:14:50,681
and provide the response in document form.

845
01:14:50,681 --> 01:14:56,681
Generating code from requirements with Codex improves overall development speed.

846
01:14:56,681 --> 01:15:00,681
When our prompts are better, the final results we get will also be much better,

847
01:15:00,681 --> 01:15:06,801
better, which we can then utilise today. Clear requirements, a defined scope and

848
01:15:06,801 --> 01:15:11,841
strong acceptance criteria help codecs produce code that is easier to review,

849
01:15:11,841 --> 01:15:17,921
test and merge in big enterprise teams. We are discussing how big enterprise

850
01:15:17,921 --> 01:15:23,001
teams can incorporate these modern features on a larger scale today. Our

851
01:15:23,001 --> 01:15:26,781
next discussion will be related to editing and refactoring existing code

852
01:15:26,781 --> 01:15:33,781
We have generated this exact code as an example project where we are utilising all these core elements in real time.

853
01:15:33,781 --> 01:15:38,781
Now, suppose our initial code is generated and ready.

854
01:15:38,781 --> 01:15:45,781
To demonstrate this point well, I will show you a custom calculator code from our older previous generations.

855
01:15:45,781 --> 01:15:55,781
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.

856
01:15:55,781 --> 01:16:02,201
today. Now we will discuss editing or refactoring the code. Here you can see

857
01:16:02,201 --> 01:16:06,641
that we asked to create a calculator code. It took a quick look and made a

858
01:16:06,641 --> 01:16:11,681
plan for us. After making the plan it implemented the calculator in the

859
01:16:11,681 --> 01:16:17,741
calculator.py file. This is our calculator. Everything in it is

860
01:16:17,741 --> 01:16:22,421
functional from start to finish. If we want to run it we will see that the

861
01:16:22,421 --> 01:16:28,461
verification passed using the bundled Python runtime. Note that Python and py

862
01:16:28,461 --> 01:16:34,301
are not on our system path, so if we want to use it in our environment we need all

863
01:16:34,301 --> 01:16:40,481
these requirements. I will open PowerShell here or I will just open the

864
01:16:40,481 --> 01:16:46,781
command prompt. In the command prompt we will give this command. When I press enter

865
01:16:46,781 --> 01:16:51,941
you will see that we have a complete response included here. Now I will

866
01:16:51,941 --> 01:16:58,301
include it here. There is an issue in the first line of our code. So we will run it

867
01:16:58,301 --> 01:17:04,881
from here to here. I will copy this. After copying I will go back to the command

868
01:17:04,881 --> 01:17:11,321
prompt. Here is the command prompt. Now we will include it in the command prompt.

869
01:17:11,321 --> 01:17:16,881
When we include it you can see that because this file is very old our file

870
01:17:16,881 --> 01:17:23,121
is not available here. But we can still run it in our browser. Now we will look

871
01:17:23,121 --> 01:17:28,161
at our editing and refactoring here. Usually this is the most valuable

872
01:17:28,161 --> 01:17:33,741
capability of our OpenAI codecs for enterprise software development. While

873
01:17:33,741 --> 01:17:38,841
generating new code is useful, developers spend a lot of time improving,

874
01:17:38,841 --> 01:17:45,061
maintaining and modernizing existing applications. Codecs can analyze the

875
01:17:45,061 --> 01:17:52,141
current code base. It can understand relationships between files, identify code smells and suggest

876
01:17:52,141 --> 01:17:58,681
improvements for better readability. First I will explain the first thing. This is what

877
01:17:58,681 --> 01:18:06,221
we call refactoring code. This is a process of restructuring the existing code. It improves

878
01:18:06,221 --> 01:18:13,421
readability, maintainability and internal design without changing its external behaviour.

879
01:18:13,421 --> 01:18:16,941
We primarily involve this in our code review.

880
01:18:16,941 --> 01:18:22,621
If I go to Excalordraw, I can tell you that after refactoring, the next thing is restructuring

881
01:18:22,621 --> 01:18:23,621
or editing.

882
01:18:23,621 --> 01:18:26,361
That is very simple.

883
01:18:26,361 --> 01:18:31,441
It is simple because we can come into our code, include any line here, and include things

884
01:18:31,441 --> 01:18:33,421
by giving a local comment.

885
01:18:33,421 --> 01:18:39,741
Or, if we want to do overall refactoring, I can say to make this into an HTML file that

886
01:18:39,741 --> 01:18:42,541
I can run in VS Code.

887
01:18:42,541 --> 01:18:46,481
Here you can see that now it will directly take our prompt.

888
01:18:46,481 --> 01:18:49,421
The code was previously available.

889
01:18:49,421 --> 01:18:55,921
Now it will connect our Python calculator into a browser-friendly HTML version.

890
01:18:55,921 --> 01:18:59,641
Alternatively I will open our VS Code.

891
01:18:59,641 --> 01:19:05,481
You might remember that we already included codecs in Visual Studio Code before, so this

892
01:19:05,481 --> 01:19:10,041
will also be available for us to use in a much easier way.

893
01:19:10,041 --> 01:19:15,041
Along with this, in Visual Studio Code where everything else is, we will automatically

894
01:19:15,041 --> 01:19:18,501
include our calculator file.

895
01:19:18,501 --> 01:19:19,501
Codex is open.

896
01:19:19,501 --> 01:19:23,521
All our generations and things are available in it.

897
01:19:23,521 --> 01:19:27,341
Now you will see that our codex file has arrived here.

898
01:19:27,341 --> 01:19:31,681
In the codex file, all our things are directly included.

899
01:19:31,681 --> 01:19:36,761
Now you can see that if we want, we can directly open the calculator in the browser, or we

900
01:19:36,761 --> 01:19:40,581
We can copy its link and go to another browser.

901
01:19:40,581 --> 01:19:44,641
If we copy its link, we just have to go here.

902
01:19:44,641 --> 01:19:49,481
When we open it here, the calculator will open in our browser.

903
01:19:49,481 --> 01:19:52,061
This is a very simple calculator.

904
01:19:52,061 --> 01:19:57,201
If we want to open it in the internal browser of Codex, that is also possible.

905
01:19:57,201 --> 01:20:00,081
will load and run our calculator in the Codex browser.

906
01:20:01,264 --> 01:20:05,904
Here you can see that if we want, we can directly use this file in our VS Code

907
01:20:05,904 --> 01:20:07,744
from the options.

908
01:20:07,744 --> 01:20:11,104
We can include annotations. If we want,

909
01:20:11,104 --> 01:20:15,584
we can save a screenshot here. After saving the screenshot here,

910
01:20:15,744 --> 01:20:18,744
we can also use it in another browser.

911
01:20:18,744 --> 01:20:21,744
We can come here and use it here too.

912
01:20:21,744 --> 01:20:26,744
So, if we want to make any design changes, we can do that directly.

913
01:20:26,744 --> 01:20:33,744
When working with legacy systems, developers often face challenges such as inconsistent coding styles.

914
01:20:33,744 --> 01:20:37,744
Here, the coding we have is AI-based coding.

915
01:20:37,744 --> 01:20:43,744
However, if we talk about legacy systems, they are systems where we manually write all the code.

916
01:20:43,744 --> 01:20:48,184
We make all the changes and alterations in that code ourselves.

917
01:20:48,184 --> 01:20:55,504
There, sometimes there are outdated frameworks, poor documentation and tightly coupled components.

918
01:20:55,504 --> 01:21:02,064
Codex can help developers understand the purpose of existing code before making modifications.

919
01:21:02,064 --> 01:21:06,544
It does this by analysing the related files and dependencies.

920
01:21:06,544 --> 01:21:13,504
It can recommend safer refactoring strategies and identify areas where changes may have downstream

921
01:21:13,504 --> 01:21:20,004
effects. This significantly reduces the time required to understand unfamiliar code bases.

922
01:21:20,004 --> 01:21:27,224
Despite these advantages, developers should carefully review all refactoring changes before

923
01:21:27,224 --> 01:21:32,384
merging them into the production branches. Even when functionality appears unchanged,

924
01:21:32,384 --> 01:21:38,944
modifications can introduce unintended side effects. Now, I will work on our code here.

925
01:21:38,944 --> 01:21:45,064
I will go to our codex. In codex we will write a prompt that you are working as a

926
01:21:45,064 --> 01:21:49,744
senior software engineer in this repository. The task is to refactor the

927
01:21:49,744 --> 01:21:54,264
existing code without changing its functionality. We will improve the code

928
01:21:54,264 --> 01:21:58,684
readability and maintainability and remove duplicate logic with simple

929
01:21:58,684 --> 01:22:04,264
complex methods. There is a lot of detail here. The general overview of this

930
01:22:04,264 --> 01:22:08,344
detail is that we should make our code readability and maintainability better.

931
01:22:08,344 --> 01:22:13,544
As soon as I improve this, we start getting our response.

932
01:22:13,544 --> 01:22:15,704
We can directly include this response.

933
01:22:15,704 --> 01:22:19,164
First, it will look at the current state.

934
01:22:19,164 --> 01:22:24,984
The main refactor target is that we will slightly change the HTML file.

935
01:22:24,984 --> 01:22:28,724
First of all, we will include the keyboard handling.

936
01:22:28,724 --> 01:22:33,324
After that, we will see multiple changes in this HTML file.

937
01:22:33,324 --> 01:22:37,384
If we want to review it, our changes will automatically appear wherever changes are

938
01:22:37,384 --> 01:22:43,704
being made in our file. You will see that the refactor is done in one focused pass.

939
01:22:43,704 --> 01:22:50,024
I am validating both sides now. Python behaviour should still pass, and the HTML script should

940
01:22:50,024 --> 01:22:54,504
still calculate and respond to the button and keyboard actions. Here our checks have

941
01:22:54,504 --> 01:23:02,684
passed. Now, if we reload our calculator, many changes will be included in our calculator.

942
01:23:02,684 --> 01:23:05,764
Now we have another very important thing.

943
01:23:05,764 --> 01:23:08,564
It is not just doing a simple check.

944
01:23:08,564 --> 01:23:11,864
It also performed a Python check.

945
01:23:11,864 --> 01:23:18,984
If I show you the working, after the Python check it also included HTML behaviour checks.

946
01:23:18,984 --> 01:23:22,444
The refactored HTML is built here.

947
01:23:22,444 --> 01:23:25,484
It has only 123 lines.

948
01:23:25,484 --> 01:23:29,704
I can say that our workability is much easier now.

949
01:23:29,704 --> 01:23:33,944
If we look at the code review, it changed many lines in the code.

950
01:23:33,944 --> 01:23:40,824
For example, instead of display value 0, it has set the display value to the default value.

951
01:23:40,824 --> 01:23:44,864
Overall, it showed our functionality in depth.

952
01:23:44,864 --> 01:23:49,704
It directly changed the error coming in the display into show error.

953
01:23:49,704 --> 01:23:54,764
Here too, it changed set display error to show error.

954
01:23:54,764 --> 01:24:01,004
In simple words, it improved our code maintainability and nullified the error-causing paths on a

955
01:24:01,004 --> 01:24:02,984
large scale.

956
01:24:02,984 --> 01:24:07,204
It manipulated the errors into the ShowError function.

957
01:24:07,204 --> 01:24:12,544
Exactly here too, the SetDisplayError was changed to ShowError.

958
01:24:12,544 --> 01:24:17,644
This means, in simple words, our code maintainability has improved.

959
01:24:17,644 --> 01:24:21,424
It has removed the paths that cause errors on a large scale.

960
01:24:21,424 --> 01:24:27,804
we will discuss context windows and scope. Context window is a new topic. People do not

961
01:24:27,804 --> 01:24:34,824
discuss it much. I will tell you what a context window is. A context window is the maximum

962
01:24:34,824 --> 01:24:42,284
text an AI model can hold at one time. It works as the AI's memory. Everything inside

963
01:24:42,284 --> 01:24:49,144
this window, like prompts, history or files, is seen by the model. Before explaining how

964
01:24:49,144 --> 01:24:55,424
it works, I will give you a simple example. For a simple example, I will go to ChatGPT.

965
01:24:56,524 --> 01:25:03,784
First, I write a message in ChatGPT. I say, hi, I want to work with AI and HTML.

966
01:25:04,784 --> 01:25:10,644
If I continue this conversation, it will write the code. This is simple prompting.

967
01:25:11,164 --> 01:25:18,084
We get our answer through it. But if we do something else, if we give a very long prompt

968
01:25:18,084 --> 01:25:25,464
again and again. You will see a message. The message says it is too long. Let us see the

969
01:25:25,464 --> 01:25:32,444
size of the context window in ChatGPT. I will search for the context window of ChatGPT.

970
01:25:32,444 --> 01:25:40,144
It will show the context window size. Usually the model has a 128,000 token window. This

971
01:25:40,144 --> 01:25:47,104
This means it takes 96,000 words or 250 to 300 pages of text.

972
01:25:47,104 --> 01:25:50,704
I will copy this text and paste it many times.

973
01:25:50,704 --> 01:25:54,044
I will do this until the prompt becomes too long.

974
01:25:54,044 --> 01:25:58,324
I will copy it and go to a word counter website.

975
01:25:58,324 --> 01:26:00,584
It is a famous word counter.

976
01:26:00,584 --> 01:26:05,364
When I paste the words here, you will see the website become slow.

977
01:26:05,364 --> 01:26:10,604
This is because there are 9,776 words in total.

978
01:26:10,604 --> 01:26:12,804
We put this in our prompt.

979
01:26:12,804 --> 01:26:16,184
It has 76,000 characters.

980
01:26:16,184 --> 01:26:19,124
Now suppose I paste the last text here.

981
01:26:19,124 --> 01:26:20,984
You will see a message.

982
01:26:20,984 --> 01:26:24,104
It says the long text is added as a file.

983
01:26:24,104 --> 01:26:26,324
The text will show up here.

984
01:26:26,324 --> 01:26:30,324
I will write that if I put this file in the chat it cannot process it.

985
01:26:30,324 --> 01:26:32,784
The message is too long.

986
01:26:32,784 --> 01:26:36,664
We want to see the context window size of ChatGPT.

987
01:26:36,664 --> 01:26:38,424
It will take time.

988
01:26:38,424 --> 01:26:41,824
You will see that the context window depends on the model.

989
01:26:41,824 --> 01:26:47,324
OpenAI does not always show the exact limit, but if you see the message it means the text

990
01:26:47,324 --> 01:26:55,564
is too long for one input, the file is too big, or the user interface has strict limits.

991
01:26:55,564 --> 01:26:59,564
If we use fewer words, we will get our answer.

992
01:26:59,564 --> 01:27:03,364
In the same way, when we go to Codex we can see limits.

993
01:27:03,364 --> 01:27:05,784
In the new chat we have limits.

994
01:27:05,784 --> 01:27:08,484
Wait a minute, I will open it here.

995
01:27:08,484 --> 01:27:10,964
We know that Codex has some limits.

996
01:27:10,964 --> 01:27:16,004
Even if we add many images, files and documents there are still limits.

997
01:27:16,004 --> 01:27:22,364
In real business projects, apps have thousands of files and millions of lines of code.

998
01:27:22,364 --> 01:27:26,284
No AI can read all the code at once.

999
01:27:26,284 --> 01:27:30,504
Devils must help codecs focus on important information.

1000
01:27:30,504 --> 01:27:32,844
Scope sets the limits of a task.

1001
01:27:32,844 --> 01:27:36,784
It includes files, modules and features.

1002
01:27:36,784 --> 01:27:39,744
Setting the right scope stops bad changes.

1003
01:27:39,744 --> 01:27:43,164
It helps codecs focus on the right parts.

1004
01:27:43,164 --> 01:27:45,404
Now I will tell you directly.

1005
01:27:45,404 --> 01:27:47,484
Suppose we get an answer.

1006
01:27:47,484 --> 01:27:49,764
How will a full developer work?

1007
01:27:49,764 --> 01:27:53,444
For example, we will take an e-commerce store.

1008
01:27:53,444 --> 01:27:56,244
In our example we have an e-commerce store.

1009
01:27:56,244 --> 01:27:59,264
A developer wants to add a discount box to a product page.

1010
01:28:02,073 --> 01:28:10,273
Codex. He only shares the product model, service, controller, form and tests. This limits the

1011
01:28:10,273 --> 01:28:15,553
context. Codex can focus on the updates. It will not make bad changes in other

1012
01:28:15,553 --> 01:28:22,873
places. Where do we use this? When we make changes this is very helpful. We can

1013
01:28:22,873 --> 01:28:28,893
modify things easily. You will see two or three options here. We can open it in VS

1014
01:28:28,893 --> 01:28:35,873
code. We have a full MetaBrain's project here. It has all our files. We can run

1015
01:28:35,873 --> 01:28:42,053
the index file here. On the side we have our chat. Our codex is also running

1016
01:28:42,053 --> 01:28:48,413
directly. Besides codex we have an agents option. We can use agents to do

1017
01:28:48,413 --> 01:28:54,953
our work directly. Now we will verify our GitHub account. Do you remember how I did

1018
01:28:54,953 --> 01:29:01,933
GitHub authentication? We will authorize VS code directly. Our workflow and

1019
01:29:01,933 --> 01:29:08,433
personal details will be added here. This works for public and private projects.

1020
01:29:08,433 --> 01:29:13,613
We can include this directly. If I show you the sign in again, authorisation

1021
01:29:13,613 --> 01:29:20,753
comes directly. We can confirm it. Suppose we want to verify using email.

1022
01:29:20,753 --> 01:29:27,033
The email will come automatically. We will confirm the email here. These emails

1023
01:29:27,033 --> 01:29:34,853
run through a base setup. We got the code here. Then we will verify it. Our VS code

1024
01:29:34,853 --> 01:29:42,973
will sign in and connect automatically. After signing in, MetaBrainz connects with our co-pilot.

1025
01:29:42,973 --> 01:29:49,373
We are running many windows. In one place we run the agent. In another place we use

1026
01:29:49,373 --> 01:29:59,253
our IDE. In a third place, we use it as a chatbot. So, we must manage our context carefully.

1027
01:29:59,253 --> 01:30:04,753
Context window and scope management are very important for AI software development. By

1028
01:30:04,753 --> 01:30:11,913
giving the right information and clear boundaries, developers help codecs. It creates accurate,

1029
01:30:11,913 --> 01:30:17,533
good and reliable code. We must look at these important things carefully.

1030
01:30:17,533 --> 01:30:22,233
Now, our discussion is about reviewing our AI-generated code.

1031
01:30:22,233 --> 01:30:27,473
In the AI-generated code, we want to see how we previously used codes like

1032
01:30:27,473 --> 01:30:32,413
CreateCalculator multiple times, as you can see.

1033
01:30:32,413 --> 01:30:39,133
We have created the calculator here, and you can see that all our changes are also available here.

1034
01:30:39,133 --> 01:30:45,413
For these AI-generated changes, we first need to understand two or three things.

1035
01:30:45,413 --> 01:30:51,213
First, in this complete software we are using, whenever there are changes, the red values

1036
01:30:51,213 --> 01:30:56,393
will be all our previous values, and the green values will be our new possible changes that

1037
01:30:56,393 --> 01:30:58,693
we have used here.

1038
01:30:58,693 --> 01:31:05,013
If you look here, you can first see the set display error, but now in our new code, some

1039
01:31:05,013 --> 01:31:07,433
things have expanded.

1040
01:31:07,433 --> 01:31:13,373
Let us suppose I directly include a prompt here saying, I want a scientific calculator.

1041
01:31:13,373 --> 01:31:18,293
Now, a scientific calculator will be created here.

1042
01:31:18,293 --> 01:31:23,053
Usually we have this one code and we can call it version 1.

1043
01:31:23,053 --> 01:31:28,693
Automatically, this version of ours will be applied here, and along with this version,

1044
01:31:28,693 --> 01:31:33,493
if we have any other versions available here, they will be used.

1045
01:31:33,493 --> 01:31:38,173
First of all, it will take some time to think about what things were discussed in the previous

1046
01:31:38,173 --> 01:31:40,013
context.

1047
01:31:40,013 --> 01:31:44,053
It will review what discussions we were having previously.

1048
01:31:44,053 --> 01:31:49,773
After all those discussions, our code will automatically start generating here.

1049
01:31:49,773 --> 01:31:53,193
Alright, it is reconnecting with our work.

1050
01:31:53,193 --> 01:31:58,313
Our connection with the model is being created to see how a complete connection will be generated

1051
01:31:58,313 --> 01:32:01,573
and how our thinking will work on a larger scale.

1052
01:32:01,573 --> 01:32:06,813
Usually, when we are looking at such a code, we have to do validation.

1053
01:32:06,813 --> 01:32:10,273
We can separate our unified difference from here.

1054
01:32:10,273 --> 01:32:14,613
We call this split and we call the other one unified.

1055
01:32:14,613 --> 01:32:20,353
In the split view, our complete previous codebase is on one side and our new code is included

1056
01:32:20,353 --> 01:32:22,293
on the other side.

1057
01:32:22,293 --> 01:32:27,413
In the previous one, you can see the display error and here you can see how much our error

1058
01:32:27,413 --> 01:32:29,813
evaluation is available now.

1059
01:32:29,813 --> 01:32:34,313
Similarly, our if action is also available here.

1060
01:32:34,313 --> 01:32:40,153
We can see how much if action we had previously, and after that, how many evaluations are coming

1061
01:32:40,153 --> 01:32:41,973
in our run action.

1062
01:32:41,973 --> 01:32:47,473
Alright, so all these things are being directly included in our system.

1063
01:32:47,473 --> 01:32:50,253
We are looking at multiple changes here.

1064
01:32:50,253 --> 01:32:54,033
You can see that our connection is being created once again here.

1065
01:32:54,033 --> 01:32:59,453
We can change the model to a very simple one, make the speed fast, and also change the reasoning

1066
01:32:59,453 --> 01:33:00,453
here.

1067
01:33:00,453 --> 01:33:08,033
Now, besides all these things, we have two options available here, Review and Undo.

1068
01:33:08,033 --> 01:33:13,653
In the Review option, we can directly review our code once in the first scenario.

1069
01:33:13,653 --> 01:33:17,633
And Undo works exactly like our version control system.

1070
01:33:17,633 --> 01:33:21,493
It keeps multiple versions in our adopted system.

1071
01:33:21,493 --> 01:33:26,053
Here you can see that our system is now running, and it is telling us that it is upgrading

1072
01:33:26,053 --> 01:33:28,253
the existing HTML.

1073
01:33:28,253 --> 01:33:33,493
Now, let us suppose I take you to this HTML file.

1074
01:33:33,493 --> 01:33:36,273
I will show all the differences here.

1075
01:33:36,273 --> 01:33:40,713
They are here now and we will also enable the rich preview.

1076
01:33:40,713 --> 01:33:44,173
Now you can see that this is our newer file.

1077
01:33:44,173 --> 01:33:49,053
Even after the newer file, when we make changes again, those changes will also be visible

1078
01:33:49,053 --> 01:33:50,473
here.

1079
01:33:50,473 --> 01:33:54,653
You will see plus 32 and minus 21.

1080
01:33:54,653 --> 01:33:59,053
This shows how many lines of code were removed and how many lines of code were added to our

1081
01:33:59,053 --> 01:34:01,153
total system.

1082
01:34:01,153 --> 01:34:06,913
When both these things work together, we automatically start getting our response and work results.

1083
01:34:06,913 --> 01:34:09,173
It shows how we are managing things.

1084
01:34:09,173 --> 01:34:14,453
Alright, so this is our very detailed working process.

1085
01:34:14,453 --> 01:34:17,133
Here you can see all the changes.

1086
01:34:17,133 --> 01:34:23,173
For a simple example, as we are reviewing now, the title was previously Calculator, but now

1087
01:34:23,173 --> 01:34:27,673
Now our new title has become Scientific Calculator.

1088
01:34:27,673 --> 01:34:33,033
Alright, if we look here now, all the design changes of our calculator are shown here with

1089
01:34:33,033 --> 01:34:35,053
plus and minus signs.

1090
01:34:35,053 --> 01:34:41,673
Also, you can see that if we want to add something here, we can directly include a local comment.

1091
01:34:41,673 --> 01:34:45,693
For example, I can say here, I want round buttons.

1092
01:34:45,693 --> 01:34:49,633
Okay, so now we want our round buttons.

1093
01:34:49,633 --> 01:34:53,913
As soon as I post this comment, you can see it is included here.

1094
01:34:53,913 --> 01:34:56,453
Now this comment is added, alright?

1095
01:34:56,453 --> 01:35:01,393
Similarly, if we go here, I will say, I want more buttons.

1096
01:35:01,393 --> 01:35:04,893
I am making very simple changes in front of you.

1097
01:35:04,893 --> 01:35:06,813
I will add the comment.

1098
01:35:06,813 --> 01:35:09,893
Now there are two comments here, alright?

1099
01:35:09,893 --> 01:35:14,153
In the same way, at the end of this file, I will say that we need simpler functionality

1100
01:35:14,153 --> 01:35:15,153
here.

1101
01:35:15,153 --> 01:35:18,953
Okay, I will say, simple functionality please.

1102
01:35:20,293 --> 01:35:22,453
Alright, this comment is added here.

1103
01:35:23,473 --> 01:35:26,813
After that, we can go to the end or just go to the start.

1104
01:35:27,773 --> 01:35:29,973
In the start, I will change our name here.

1105
01:35:30,713 --> 01:35:33,173
Change the name as MetaBrainzCal.

1106
01:35:33,993 --> 01:35:36,013
Okay, MetaBrainzCal.

1107
01:35:37,033 --> 01:35:39,473
Alright, now our comment is added.

1108
01:35:40,413 --> 01:35:43,073
You can see that three or four comments are here now.

1109
01:35:43,073 --> 01:35:50,073
In our calculator, we have a comment in row number 46 and a comment in row number 102.

1110
01:35:50,073 --> 01:35:56,073
After that, there is a comment in row number 200 and then a comment in row number 6.

1111
01:35:57,306 --> 01:36:05,046
Now what we have to do here is I can say make the possible changes asked. Okay what will happen here

1112
01:36:05,046 --> 01:36:10,246
is that based on the changes we included in these comments the changes will happen at those exact

1113
01:36:10,246 --> 01:36:15,366
points. I will only show you this one change that we demanded at the end in the comments.

1114
01:36:16,086 --> 01:36:19,686
We will see how it changes the name of our scientific calculator here,

1115
01:36:20,326 --> 01:36:26,886
and this is a very advanced feature. We are reviewing our complete AI generated changes

1116
01:36:26,886 --> 01:36:31,366
to see how our reviews can be applied on a larger scale and how we can include them.

1117
01:36:32,406 --> 01:36:37,286
It will take some time to think. Obviously you can see that it is thinking here,

1118
01:36:37,286 --> 01:36:41,246
and after that it says, I will apply the review comments directly.

1119
01:36:42,406 --> 01:36:44,946
First of all, our name will be changed to MetaBrainz.

1120
01:36:45,766 --> 01:36:48,326
After that, the calculator buttons will be made circular.

1121
01:36:49,286 --> 01:36:52,066
A few practical scientific buttons will be included.

1122
01:36:53,186 --> 01:36:54,726
Here you can see our calculation.

1123
01:36:55,886 --> 01:36:57,626
MetaBrainzCal is written here.

1124
01:36:58,606 --> 01:37:02,906
After that, we also included a comment here that we want our buttons to be rounded.

1125
01:37:02,906 --> 01:37:09,906
So, you can see that by including height, aspect ratio, border radius and all these things,

1126
01:37:09,906 --> 01:37:13,906
it has provided us with some rounded buttons that we can directly see here.

1127
01:37:13,906 --> 01:37:18,906
Alright, so all these things are greatly included in our working process here.

1128
01:37:18,906 --> 01:37:23,906
And through this, we can include it in our system, and it will work here.

1129
01:37:23,906 --> 01:37:26,906
Now we will get all our changes here.

1130
01:37:26,906 --> 01:37:29,906
You can see that whatever visual changes we have,

1131
01:37:29,906 --> 01:37:34,666
it has included some lines in a file and showed us the changes here.

1132
01:37:34,666 --> 01:37:36,946
We can also open that here.

1133
01:37:36,946 --> 01:37:43,246
OK, after that, for the next changes it makes, you can see our thinking process here.

1134
01:37:43,246 --> 01:37:48,366
In the thinking process, as it is including our constants and other values, these files

1135
01:37:48,366 --> 01:37:51,826
will automatically come here side by side.

1136
01:37:51,826 --> 01:37:54,006
Now it has updated our file.

1137
01:37:54,006 --> 01:37:56,046
We have all the commands here.

1138
01:37:56,046 --> 01:38:01,046
As soon as we open this in our browser, all our discussed changes are here, like Metabrains

1139
01:38:01,046 --> 01:38:02,346
Cal.

1140
01:38:02,346 --> 01:38:04,826
Our buttons have become rounded.

1141
01:38:04,826 --> 01:38:09,686
And now, if we include anything here, that thing will automatically be directly included

1142
01:38:09,686 --> 01:38:10,686
here.

1143
01:38:10,686 --> 01:38:13,026
OK, our error came here.

1144
01:38:13,026 --> 01:38:14,726
We are seeing everything working.

1145
01:38:14,726 --> 01:38:20,066
Alright, if we suppose we need the value of pi here, we get our pi value.

1146
01:38:20,066 --> 01:38:23,986
If we need the value of log8, we can directly input it here.

1147
01:38:23,986 --> 01:38:29,626
Also, you can see that this delete option is working directly here too.

1148
01:38:29,626 --> 01:38:35,186
If we look at all the signs here, every sign that we have is working very easily.

1149
01:38:35,186 --> 01:38:39,066
We can directly enter all our values here.

1150
01:38:39,066 --> 01:38:43,726
If there is no responsiveness, we can go ahead and directly include responsiveness in our

1151
01:38:43,726 --> 01:38:45,786
code later.

1152
01:38:45,786 --> 01:38:50,266
But code review is the main thing that I have discussed with you.

1153
01:38:50,266 --> 01:38:54,426
After this, our next discussion is related to our prompt hints.

1154
01:38:54,426 --> 01:38:58,166
Next we discuss the main usage of a prompt library.

1155
01:38:58,166 --> 01:39:02,786
We will see how we can use it and where more options are included.

1156
01:39:02,786 --> 01:39:04,466
First I come here.

1157
01:39:04,466 --> 01:39:09,946
Instead of using everything, I will search the prompt library in Codex.

1158
01:39:09,946 --> 01:39:12,866
Here you see Codex prompting.

1159
01:39:12,866 --> 01:39:18,366
First I tell you this is a built-in collection of reusable workflows, templates and skills

1160
01:39:18,366 --> 01:39:22,506
in OpenAI Codecs and Agentic CLI.

1161
01:39:22,506 --> 01:39:26,806
When I go to prompting, you see we often use prompts.

1162
01:39:26,806 --> 01:39:31,986
You interact with the codecs by sending prompts that describe what you want.

1163
01:39:31,986 --> 01:39:34,586
Example prompts are shown here.

1164
01:39:34,586 --> 01:39:36,686
Thread is a single session.

1165
01:39:36,686 --> 01:39:41,646
It has your prompt plus the model outputs and tool calls that follow.

1166
01:39:41,646 --> 01:39:44,606
A thread can include multiple prompts.

1167
01:39:44,606 --> 01:39:48,146
We use a chain of process to take things forward.

1168
01:39:48,146 --> 01:39:52,606
I will explain this exact process right here in our codex.

1169
01:39:52,606 --> 01:39:56,706
In codex, we go to our main user settings.

1170
01:39:56,706 --> 01:40:00,486
Inside these settings we have personalization.

1171
01:40:00,486 --> 01:40:05,266
In personalization, our own custom instructions are included.

1172
01:40:05,266 --> 01:40:10,606
We can also switch our AI personality from pragmatic to friendly.

1173
01:40:10,606 --> 01:40:14,086
Both of these personalization options are here.

1174
01:40:14,086 --> 01:40:19,466
In custom instructions, we can include all custom-made, personalised instructions that

1175
01:40:19,466 --> 01:40:21,766
we want in our tool.

1176
01:40:21,766 --> 01:40:25,366
It is quite simple to include our text responses.

1177
01:40:25,366 --> 01:40:31,086
But sometimes, we must see our clear deviation and how we are working on stuff, and how these

1178
01:40:31,086 --> 01:40:33,806
custom instructions work.

1179
01:40:33,806 --> 01:40:39,086
We have our memory, which we can induce right here in our experimental form.

1180
01:40:39,086 --> 01:40:45,386
We see how our things can be included and how we can take our many processes forward.

1181
01:40:45,386 --> 01:40:50,166
Our standard options show how we will best include our own memory.

1182
01:40:50,166 --> 01:40:53,206
First is the main Enable Memories.

1183
01:40:53,206 --> 01:40:56,846
Second is our Good Tool Assisted Memories.

1184
01:40:56,846 --> 01:41:02,146
We can also involve Tool Assisted Memories and involve all our process or workability

1185
01:41:02,146 --> 01:41:04,306
in it.

1186
01:41:04,306 --> 01:41:07,626
Next thing is our own custom prompt libraries.

1187
01:41:07,626 --> 01:41:10,126
What is a good prompt library?

1188
01:41:10,126 --> 01:41:15,566
I will tell you first that our prompt library is a great reusable prompt hub.

1189
01:41:15,566 --> 01:41:19,466
In this we can do our text discussion multiple times.

1190
01:41:19,466 --> 01:41:22,946
We can do multiple workings for our single tool.

1191
01:41:22,946 --> 01:41:26,146
We must see one more thing here.

1192
01:41:26,146 --> 01:41:31,286
From the ChatGPT side, there is no prompt library available here yet.

1193
01:41:31,286 --> 01:41:34,726
We have clear information about basic prompting.

1194
01:41:34,726 --> 01:41:39,186
But if I talk about the Claude code, there is a distinct prompt library available.

1195
01:41:39,186 --> 01:41:45,326
We can go there and see the many prompts are collected from the various Anthropic guides.

1196
01:41:45,326 --> 01:41:50,926
This includes our common workflows and best practices, and how Anthropic teams take Claude

1197
01:41:50,926 --> 01:41:53,386
code forward.

1198
01:41:53,386 --> 01:41:57,966
If I want, we can also see the core understand prompts.

1199
01:41:57,966 --> 01:42:04,486
We see how we can use our own prompts if we need a new prompt for git, release, data,

1200
01:42:04,486 --> 01:42:06,486
automate or product.

1201
01:42:06,486 --> 01:42:11,486
A set number of proper prompts are available for every single thing.

1202
01:42:11,486 --> 01:42:14,486
We can reuse them multiple times over.

1203
01:42:14,486 --> 01:42:19,486
We can utilise multiple variations or our many functions.

1204
01:42:19,486 --> 01:42:23,486
This very same thing is available here in our Claude,

1205
01:42:23,486 --> 01:42:31,486
but if we go to our codex, then until now we do not have these full prompt libraries available.

1206
01:42:31,486 --> 01:42:37,006
We can do one other good thing here. We can come right here and ask a prompt question.

1207
01:42:37,966 --> 01:42:43,006
If we go into ChatGPT and for our codecs we include our own best prompts,

1208
01:42:43,646 --> 01:42:47,326
I can say I want a whole new prompt library for my codecs.

1209
01:42:48,446 --> 01:42:52,926
It will then give a good reusable clean codecs prompt library.

1210
01:42:54,046 --> 01:43:01,326
Inside it we have all our good useful prompts. We have our bug fixes, text test generator,

1211
01:43:01,326 --> 01:43:11,006
code review, refactoring, feature builder, API design, performance optimization and security audit prompt.

1212
01:43:12,046 --> 01:43:14,606
All these things will involve in that exact thing.

1213
01:43:15,886 --> 01:43:22,126
From there we will take and use it well. These various things are included in our entire core

1214
01:43:22,126 --> 01:43:29,166
system on a large scale. We must look at all these many things on a large scale to see how we can

1215
01:43:29,166 --> 01:43:35,646
reuse them. We will copy it and come inside this main system to use all our many prompts.

1216
01:43:36,686 --> 01:43:42,846
We will not use these exact things but besides this we have all our 12 core prompts.

1217
01:43:44,046 --> 01:43:51,406
As we go forward our prompt library will increase even more. From 1 to 12 our many different options

1218
01:43:51,406 --> 01:43:58,366
will be used and we will include them. These things are used very much inside the entire system.

1219
01:43:59,813 --> 01:44:04,053
With this, we have a lot of great automation in our work on a large scale.

1220
01:44:04,753 --> 01:44:06,153
We can use that well.

1221
01:44:07,113 --> 01:44:11,133
I will tell you, we also have cool automations here on the side.

1222
01:44:11,133 --> 01:44:16,673
We can run our day brief, week review or smart project monitor.

1223
01:44:17,873 --> 01:44:22,353
But besides that, if we look at our cool templates, we have very many.

1224
01:44:22,813 --> 01:44:24,953
Now our next discussion relates to integration.

1225
01:44:25,913 --> 01:44:30,053
We will see how to perform AI-enhanced CI slash CD.

1226
01:44:30,993 --> 01:44:35,333
First, I will explain the full definition of CI slash CD.

1227
01:44:36,353 --> 01:44:38,913
CI stands for continuous integration.

1228
01:44:38,913 --> 01:44:43,033
CD stands for continuous delivery and deployment.

1229
01:44:44,333 --> 01:44:49,073
Usually, when enterprise-level workflow loops run, we have multiple projects.

1230
01:44:49,953 --> 01:44:57,553
We have standalone projects, collaborative projects, or autonomous projects connected to multiple companies, industries, and businesses.

1231
01:44:58,413 --> 01:45:01,493
For them, we must look at integration and deployment.

1232
01:45:02,033 --> 01:45:07,613
This is a DevOps methodology that automates building, testing, and releasing software.

1233
01:45:07,613 --> 01:45:10,413
We can discuss this as automation.

1234
01:45:11,413 --> 01:45:17,093
This pipeline allows development teams to ship code updates frequently, safely and reliably,

1235
01:45:17,533 --> 01:45:19,933
while catching bugs early in the development cycle.

1236
01:45:21,113 --> 01:45:26,893
Usually we do CI slash CD at an industrial or enterprise level where we need automation.

1237
01:45:28,013 --> 01:45:30,273
First we have continuous integration.

1238
01:45:31,273 --> 01:45:35,533
It is a practice where developers regularly merge their code into a central repository

1239
01:45:35,533 --> 01:45:42,093
like GitHub or GitLab. Every time code is merged, an automated system builds the application

1240
01:45:42,093 --> 01:45:48,293
and runs tests until the integration finishes. This ensures that the new code does not break

1241
01:45:48,293 --> 01:45:55,793
the existing code base. It allows teams to catch errors instantly. Then we have continuous delivery

1242
01:45:55,793 --> 01:46:04,173
versus continuous deployment. How can we use CI slash CD? First, it gives a faster time to market.

1243
01:46:04,173 --> 01:46:09,733
New features and bug fixes reach users in hours instead of weeks or months.

1244
01:46:10,733 --> 01:46:14,853
There are fewer bugs, easier rollbacks and better developer productivity.

1245
01:46:16,133 --> 01:46:23,773
CI slash CD pipelines can be used in GitHub Actions, GitLab CI, Jenkins and Circle CI.

1246
01:46:24,573 --> 01:46:27,173
I will search for codecs on Google now.

1247
01:46:27,173 --> 01:46:34,633
For example, if I share here that I want this in Codex, then we can also do that, how it becomes possible.

1248
01:46:35,933 --> 01:46:42,973
Integrating the Codex command line into the pipeline enables OpenAI Codex to automatically evaluate build failures.

1249
01:46:43,973 --> 01:46:49,513
It analyses vulnerability scans and proposes minimal changes required to make the tests pass.

1250
01:46:50,133 --> 01:46:52,653
It executes code quality checks directly.

1251
01:46:52,653 --> 01:46:56,633
It also generates remediation patches or pull requests.

1252
01:46:57,173 --> 01:47:03,873
Usually, when we talk about our process, we can perform CI slash CD in multiple forms

1253
01:47:03,873 --> 01:47:06,113
inside our projects.

1254
01:47:06,113 --> 01:47:11,173
Here in this interface and outside it, if I go directly to the terminal, I can run the

1255
01:47:11,173 --> 01:47:14,593
CI slash CD pipeline.

1256
01:47:14,593 --> 01:47:16,053
How can I do this?

1257
01:47:16,053 --> 01:47:20,013
First, I will search for Codex CLI.

1258
01:47:20,013 --> 01:47:24,093
The developer platform will open, which we can access directly.

1259
01:47:24,093 --> 01:47:26,033
Here we must install it.

1260
01:47:26,033 --> 01:47:29,593
I will come here and command the system to install Codex.

1261
01:47:29,593 --> 01:47:32,493
We will copy and paste the required command.

1262
01:47:32,493 --> 01:47:35,693
You will see that Codex is already set up here.

1263
01:47:35,693 --> 01:47:39,053
Because of this, we do not need to install it again.

1264
01:47:39,053 --> 01:47:43,153
We simply type our Codex command and it will start running.

1265
01:47:43,153 --> 01:47:45,233
You have seen this here too.

1266
01:47:45,233 --> 01:47:50,093
Whenever we give a command, we have a terminal option available on the side.

1267
01:47:50,093 --> 01:47:54,493
Inside this, we can automatically initiate our working process.

1268
01:47:54,493 --> 01:47:59,253
We also have a browser option to run CI-cd pipelines.

1269
01:47:59,253 --> 01:48:05,253
Usually, continuous integration and continuous deployment have become a foundation of modern

1270
01:48:05,253 --> 01:48:07,253
software engineering.

1271
01:48:07,253 --> 01:48:14,833
Traditional CI-cd pipelines automate the building, testing and deployment processes.

1272
01:48:14,833 --> 01:48:19,633
This reduces manual effort and ensures consistent software delivery.

1273
01:48:19,633 --> 01:48:27,093
With the introduction of AI-powered development tools like OpenAI, Enhanced CI and CD introduces

1274
01:48:27,093 --> 01:48:31,393
a new layer of intelligence into the software delivery lifecycle.

1275
01:48:31,393 --> 01:48:37,093
Instead of merely reporting failures, AI systems can investigate the root cause.

1276
01:48:37,093 --> 01:48:42,333
They propose correlations and create pull requests containing fixes.

1277
01:48:42,333 --> 01:48:47,133
This dramatically reduces the time developers spend troubleshooting failed builds.

1278
01:48:47,133 --> 01:48:52,073
It allows engineering teams to focus on high value work such as feature development and

1279
01:48:52,073 --> 01:48:54,573
architectural improvement.

1280
01:48:54,573 --> 01:48:57,013
Let me show you a simple example.

1281
01:48:57,013 --> 01:48:59,373
We can take any system here.

1282
01:48:59,373 --> 01:49:03,333
When we give a prompt, you can see our working process begins.

1283
01:49:03,333 --> 01:49:07,233
We get options to debug an issue or review a plan.

1284
01:49:07,233 --> 01:49:12,013
I will select GitHub and ask it to review the newest repository.

1285
01:49:12,013 --> 01:49:13,933
The newest repository will appear.

1286
01:49:13,933 --> 01:49:17,933
Then, I will command it to analyse the latest pull request.

1287
01:49:17,933 --> 01:49:20,933
It must generate unit tests for newly added functions,

1288
01:49:20,933 --> 01:49:23,933
modified business logic and edge cases

1289
01:49:23,933 --> 01:49:26,933
to improve our error handling completely.

1290
01:49:26,933 --> 01:49:28,933
As soon as I include this,

1291
01:49:28,933 --> 01:49:31,933
the error handling scenarios will become much better.

1292
01:49:31,933 --> 01:49:36,933
The other responses will also appear here for us to analyse directly.

1293
01:49:36,933 --> 01:49:39,933
Usually, the GitHub workflow is infused here.

1294
01:49:39,933 --> 01:49:45,933
Inside the GitHub workflow, we can directly use our other generations or processes.

1295
01:49:45,933 --> 01:49:49,933
Our other regions and our understanding will also appear.

1296
01:49:49,933 --> 01:49:52,933
Side by side, I must tell you another thing.

1297
01:49:52,933 --> 01:49:58,933
We usually face a concern about how to check our processes inside out on a larger scale.

1298
01:49:58,933 --> 01:50:01,933
We will see that in a much better form now.

1299
01:50:01,933 --> 01:50:07,933
In the CI slash CD pipeline, you can see the local workspace is empty.

1300
01:50:07,933 --> 01:50:13,133
The GitHub account is authenticated, but Git is not available.

1301
01:50:13,133 --> 01:50:18,773
If we set up these things, we can cross-check our CI slash CD pipelines.

1302
01:50:18,773 --> 01:50:23,853
We prepare a repository and use the CI slash CD pipeline perfectly.

1303
01:50:23,853 --> 01:50:28,013
Here, I will give you the example of a pipeline.

1304
01:50:28,013 --> 01:50:33,053
If you prepare a pipeline of build, which have a request, it has many stage such as

1305
01:50:33,053 --> 01:50:36,413
names and tests will appear here.

1306
01:50:36,413 --> 01:50:41,873
If you connect codecs here, then our AI tasks can work side by side with it.

1307
01:50:41,873 --> 01:50:46,613
Our next topic is putting codecs into our work process.

1308
01:50:46,613 --> 01:50:50,033
This means adding codecs to our build system.

1309
01:50:50,033 --> 01:50:53,933
When we do this, the system helps us find problems.

1310
01:50:53,933 --> 01:50:59,933
If a build stops working or a task breaks, the tool sees the code quality issues.

1311
01:50:59,933 --> 01:51:04,853
Before, people had to look at every single problem by hand.

1312
01:51:04,853 --> 01:51:08,613
Now the system looks at the failures for us.

1313
01:51:08,613 --> 01:51:12,493
It gives ideas to fix them and creates tests.

1314
01:51:12,493 --> 01:51:16,093
It can even make pull requests with good answers.

1315
01:51:16,093 --> 01:51:20,173
In a normal process, a person sends code to GitHub.

1316
01:51:20,173 --> 01:51:24,833
Then our complete system starts running automatically.

1317
01:51:24,833 --> 01:51:27,453
Things begin to work on their own.

1318
01:51:27,453 --> 01:51:30,373
We usually watch these actions in our deployment area.

1319
01:51:30,373 --> 01:51:34,733
For enterprises, this saves a lot of time.

1320
01:51:34,733 --> 01:51:38,793
do not have to fix the same small problems again.

1321
01:51:38,793 --> 01:51:42,473
The Codex Assistant helps keep the work active.

1322
01:51:42,473 --> 01:51:46,173
It understands the whole process of how things run.

1323
01:51:46,173 --> 01:51:49,553
We like having a place without mistakes.

1324
01:51:49,553 --> 01:51:52,613
Now let us look at consistency.

1325
01:51:52,613 --> 01:51:55,973
This is a very important benefit.

1326
01:51:55,973 --> 01:51:59,373
Sometimes working directly with these pipelines can be hard.

1327
01:52:01,754 --> 01:52:08,754
First, I will go to our plugins section. We can see the GitHub plugin here.

1328
01:52:08,754 --> 01:52:13,174
Next, I will search for codecs in the bar.

1329
01:52:13,174 --> 01:52:18,254
We see many results, but I want to find it in the profile settings.

1330
01:52:18,254 --> 01:52:24,994
I look at the list of options like packages, co-pilot, pages and security.

1331
01:52:24,994 --> 01:52:27,674
Here I will search for the codecs.

1332
01:52:27,674 --> 01:52:29,954
And here we have our codecs.

1333
01:52:29,954 --> 01:52:33,754
We can also search in GitHub or settings.

1334
01:52:33,754 --> 01:52:36,474
Then I decide to grant access.

1335
01:52:36,474 --> 01:52:39,714
To do this, I open our repository.

1336
01:52:39,714 --> 01:52:43,234
I click on the code button and copy the link.

1337
01:52:43,234 --> 01:52:48,174
I will ask the chat, do you have access to this project?

1338
01:52:48,174 --> 01:52:53,614
The system will now check if it can reach the repository and provide us with it.

1339
01:52:53,614 --> 01:52:58,334
And how we can initiate our working or a larger scale.

1340
01:52:58,334 --> 01:53:01,234
Sometimes we have to look at these details ourselves.

1341
01:53:01,234 --> 01:53:08,234
Also, we can take a complete process out here and our generation will be completed in that.

1342
01:53:08,234 --> 01:53:11,434
This is usually present at a lesser extent.

1343
01:53:11,434 --> 01:53:15,714
But now we will initiate a full-fledged process here.

1344
01:53:15,714 --> 01:53:20,834
You will see that it has told us here that yes, I can access the repository.

1345
01:53:20,834 --> 01:53:24,714
The access to our repository has also arrived here.

1346
01:53:24,714 --> 01:53:30,914
The second thing it said is that our default branch is main, visibility is public and effective

1347
01:53:30,914 --> 01:53:38,154
permissions in the session are admin, maintain, push, pull and triage. I can

1348
01:53:38,154 --> 01:53:43,534
simply say here that we now have to include an agents.md file inside this.

1349
01:53:43,534 --> 01:53:49,394
This will directly include it and give it to us. But the thing is we cannot

1350
01:53:49,394 --> 01:53:55,174
create things inside this. So right now we will only cross-check our agents.md

1351
01:53:55,174 --> 01:54:00,234
file here to see if it is directly available to us or not. These are our

1352
01:54:00,234 --> 01:54:06,534
things. I will now take our full detailed discussion. You will see that directly

1353
01:54:06,534 --> 01:54:13,474
after just one second our agents.md file has been included here. Inside it, as you

1354
01:54:13,474 --> 01:54:20,814
see, git isn't available. So here, after inspecting, it has directly arrived. I can

1355
01:54:20,814 --> 01:54:25,014
give access here to directly push the code to see how we can improve or

1356
01:54:25,014 --> 01:54:30,474
include things on a large scale. Side by side another very important thing is

1357
01:54:30,474 --> 01:54:36,294
running here. Usually in a base pipeline I could not run git push origin here

1358
01:54:36,294 --> 01:54:41,254
because the directory is not a git repository. Git is not installed in our

1359
01:54:41,254 --> 01:54:48,134
current shell. Let us suppose we want to install git. How can we do that? First of

1360
01:54:48,134 --> 01:54:53,774
all we will open our PowerShell here. We come inside this one. Here I say our

1361
01:54:53,774 --> 01:55:00,354
PowerShell. This is our PowerShell window. Coming directly inside PowerShell, we will

1362
01:55:00,354 --> 01:55:06,774
state our Git version here. You are seeing that the Git version is available to us here.

1363
01:55:06,774 --> 01:55:12,114
Let us suppose we want to install our Git. If we use this directly, you are seeing that

1364
01:55:12,114 --> 01:55:17,934
now we will say we want to install Git with our basic widget. Automatically our widget

1365
01:55:17,934 --> 01:55:23,754
will be installed here. On the basis of that widget, we will take our things inside running.

1366
01:55:23,774 --> 01:55:27,774
Usually these things are not explained to us.

1367
01:55:27,774 --> 01:55:31,774
We are just initiating our production and working on a large scale.

1368
01:55:31,774 --> 01:55:34,774
Here it will take some time to install.

1369
01:55:34,774 --> 01:55:37,774
Until it installs we will wait here.

1370
01:55:37,774 --> 01:55:41,774
Now, due to some issues, our Git is not becoming active.

1371
01:55:41,774 --> 01:55:44,774
I tried a lot to activate our Git.

1372
01:55:44,774 --> 01:55:46,774
You are seeing the prefix.

1373
01:55:46,774 --> 01:55:50,774
Branch prefix is working. Everything is working.

1374
01:55:50,774 --> 01:55:59,774
We usually did not include our commit instructions, but still, it is possible that by opening these things, all these items come into working.

1375
01:56:00,774 --> 01:56:08,774
But still, as a matter of fact, the discussion here is that when integrating codecs, organisations start in non-production environments.

1376
01:56:09,774 --> 01:56:13,774
This allows codecs to analyse failures and generate suggestions.

1377
01:56:13,774 --> 01:56:19,934
Once the team gains confidence in the results, they can gradually introduce more advanced workflows.

1378
01:56:21,334 --> 01:56:26,434
These include automated pull request generations and our AI-assisted bug fixing.

1379
01:56:27,634 --> 01:56:34,154
Overall, Codex acts as an intelligent engineering assistant inside our CI-slash-CD pipeline.

1380
01:56:35,074 --> 01:56:37,754
It will overall help us in building all our things.

1381
01:56:38,274 --> 01:56:41,034
These entire matters have been discussed here.

1382
01:56:41,034 --> 01:56:48,154
An autofix workflow begins the moment a developer pushes code to a repository or submits a pull request for a review.

1383
01:56:49,354 --> 01:57:05,374
The CI slash 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.

1384
01:57:05,374 --> 01:57:11,654
In traditional software development environments, any failure in these checks would require

1385
01:57:11,654 --> 01:57:17,254
a developer to manually investigate logs, identify the source of the issue, and implement

1386
01:57:17,254 --> 01:57:17,794
a fix.

1387
01:57:18,414 --> 01:57:23,994
With codex-powered autofix workflows, the process becomes significantly more efficient.

1388
01:57:25,254 --> 01:57:29,914
Instead of merely reporting that something failed, the workflow can immediately begin

1389
01:57:29,914 --> 01:57:32,994
analysing the problem and preparing a potential solution.

1390
01:57:32,994 --> 01:57:41,454
This transforms CI-CD from a passive validation system into an active participant in software

1391
01:57:41,454 --> 01:57:44,714
maintenance and quality assurance.

1392
01:57:44,714 --> 01:57:50,814
Once a failure is detected, Codex examines all available information related to the problem.

1393
01:57:50,814 --> 01:57:57,934
This includes error messages, build logs, test outputs, recently modified files, project

1394
01:57:57,934 --> 01:58:05,834
documentation, repository instructions and any development guidelines defined in agents.md.

1395
01:58:05,834 --> 01:58:10,354
By reviewing these sources together, Codex gains a much broader understanding of the

1396
01:58:10,354 --> 01:58:14,314
issue than a simple rule-based automation tool.

1397
01:58:14,314 --> 01:58:20,554
For example, if a login-related test starts failing after a recent update, Codex can inspect

1398
01:58:20,554 --> 01:58:27,174
the authentication logic, compare the recent code changes, review the affected test cases

1399
01:58:27,174 --> 01:58:31,434
and determine where the behaviour diverged from expectations.

1400
01:58:31,434 --> 01:58:37,834
This contextual understanding is one of the major advantages of AI-assisted development workflows.

1401
01:58:37,834 --> 01:58:43,514
After gathering the necessary information, Codex performs root cause analysis.

1402
01:58:43,514 --> 01:58:47,734
Rather than attempting random modifications until a test passes,

1403
01:58:47,734 --> 01:58:52,014
it tries to determine why the failure occurred in the first place.

1404
01:58:52,014 --> 01:58:55,314
The underlying issue could be a missing import statement,

1405
01:58:55,314 --> 01:58:58,554
a renamed function that was not updated everywhere,

1406
01:58:58,554 --> 01:59:01,154
a changed API response structure,

1407
01:59:01,154 --> 01:59:03,514
an incorrect configuration value,

1408
01:59:03,514 --> 01:59:07,134
a dependency upgrade that introduced breaking changes,

1409
01:59:07,134 --> 01:59:09,274
or a test case that no longer reflects

1410
01:59:09,274 --> 01:59:12,134
the intended application behaviour.

1411
01:59:12,134 --> 01:59:15,094
By identifying the actual source of the problem,

1412
01:59:15,094 --> 01:59:18,134
codecs can generate fixes that are more accurate,

1413
01:59:18,134 --> 01:59:21,574
maintainable, and less likely to introduce new defects

1414
01:59:21,574 --> 01:59:23,834
elsewhere in the system.

1415
01:59:23,834 --> 01:59:29,394
Once the root cause has been identified, Codex generates a proposed solution.

1416
01:59:29,394 --> 01:59:35,094
A well-designed autofix workflow emphasises minimal and focused changes.

1417
01:59:35,094 --> 01:59:39,514
The goal is not to rewrite large portions of the application, but to make the smallest

1418
01:59:39,514 --> 01:59:43,214
possible modification that resolves the failure.

1419
01:59:43,214 --> 01:59:49,434
This approach reduces risk and makes the resulting changes easier for developers to review.

1420
01:59:49,434 --> 01:59:54,974
For example, if a build fails because of an incorrect import path, codecs should update

1421
01:59:54,974 --> 02:00:00,374
only the affected import statement rather than refactoring multiple unrelated files.

1422
02:00:01,865 --> 02:00:06,565
also provide explicit instructions to guide this process, such as requesting

1423
02:00:06,565 --> 02:00:11,305
that only necessary files be modified, preserving existing coding conventions,

1424
02:00:11,305 --> 02:00:16,285
and updating tests only when required to reflect legitimate behaviour changes.

1425
02:00:17,525 --> 02:00:21,625
Following fixed generation, validation becomes the next critical step.

1426
02:00:22,665 --> 02:00:27,525
The proposed solution is tested using the same pipeline checks that originally detected the problem.

1427
02:00:28,605 --> 02:00:36,045
Automated builds, unit tests, integration tests, linting tools and security scans are executed again

1428
02:00:36,045 --> 02:00:38,905
to confirm that the issue has been resolved successfully.

1429
02:00:38,905 --> 02:00:49,885
If the validation process still detects failures, developers can provide additional context or refined instructions and allow codecs to perform another iteration.

1430
02:00:51,285 --> 02:00:58,145
This feedback loop helps improve solution quality while ensuring that every proposed change is verified before moving forward.

1431
02:00:59,365 --> 02:01:04,985
Even when automated validation succeeds, human review remains an essential part of the workflow.

1432
02:01:04,985 --> 02:01:19,885
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.

1433
02:01:21,025 --> 02:01:32,465
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.

1434
02:01:32,465 --> 02:01:38,865
Once the fix has been approved, the changes can be merged into the main branch and included

1435
02:01:38,865 --> 02:01:41,065
in future deployments.

1436
02:01:41,065 --> 02:01:48,505
Over time, teams can analyse recurring issues and improve their development processes accordingly.

1437
02:01:48,505 --> 02:01:56,205
Repository instructions, testing strategies, agents.md guidelines and CI-CD configurations

1438
02:01:56,205 --> 02:02:02,005
can be updated to help codecs handle similar situations more effectively in the future.

1439
02:02:02,005 --> 02:02:07,505
As a result, autofix workflows not only resolve immediate problems, but also contribute to

1440
02:02:07,505 --> 02:02:12,845
continuous improvement across the software development lifecycle, enabling teams to deliver

1441
02:02:12,845 --> 02:02:18,625
higher quality software faster, while reducing the manual effort required to maintain complex

1442
02:02:18,625 --> 02:02:19,625
systems.

1443
02:02:19,625 --> 02:02:25,045
Now, the discussion we have is related to configuring automated bug resolution.

1444
02:02:25,045 --> 02:02:27,585
We can say this on a large scale.

1445
02:02:27,585 --> 02:02:32,345
In our codecs, along with other things, a discussion was going on.

1446
02:02:32,345 --> 02:02:35,765
This is most valuable for enterprise use cases.

1447
02:02:35,765 --> 02:02:42,725
For OpenAI codecs, instead of developers manually investigating every test field, linting error,

1448
02:02:42,725 --> 02:02:49,085
securing warnings or production defects, codecs can analyse the issue, identify the affected

1449
02:02:49,085 --> 02:02:55,265
files, generate a proposed fix and create a pull request for human review.

1450
02:02:55,265 --> 02:03:00,065
This significantly reduces the time spent on repetitive maintenance tasks, while allowing

1451
02:03:00,065 --> 02:03:05,665
focus for engineers to concentrate on high-level architectural business problems.

1452
02:03:05,665 --> 02:03:13,285
In modern software teams, bugs are often discovered through CI-CD pipelines, monitoring systems,

1453
02:03:13,285 --> 02:03:16,845
issue trackers and security scanners.

1454
02:03:16,845 --> 02:03:21,825
Codecs can integrate into these workflows so that when an issue occurs, the AI automatically

1455
02:03:21,825 --> 02:03:27,905
receives the failure logs, repository context, coding standards, and our project instructions.

1456
02:03:29,105 --> 02:03:35,345
Alright, the critical aspect we have for automated bug resolution is defining clear boundaries.

1457
02:03:36,385 --> 02:03:41,425
Enterprise organisations should never allow AI to directly deploy files into production.

1458
02:03:42,305 --> 02:03:48,465
Instead, codecs should generate code changes, execute tests, and create pull requests that

1459
02:03:48,465 --> 02:03:50,965
that require developer approval.

1460
02:03:50,965 --> 02:03:53,565
This maintains governance and accountability

1461
02:03:53,565 --> 02:03:56,465
while still benefiting from automation.

1462
02:03:56,465 --> 02:03:59,005
Human reviewers can remain fully responsible

1463
02:03:59,005 --> 02:04:01,025
for validating the basic logic.

1464
02:04:01,965 --> 02:04:05,465
Now, let me tell you a very important thing.

1465
02:04:05,465 --> 02:04:09,925
Our agents.md file plays a crucial role in the process.

1466
02:04:09,925 --> 02:04:12,805
What happens is they provide our project specifications

1467
02:04:12,805 --> 02:04:15,725
and instructions that guide Codex's decision making

1468
02:04:15,725 --> 02:04:17,845
during bug resolution.

1469
02:04:17,845 --> 02:04:27,245
These instructions define the coding conventions, testing requirements, security constraints, dependency policies and our architectural patterns.

1470
02:04:28,385 --> 02:04:33,985
The more structured the agents.md file is, the more accurate and reliable the fixes become.

1471
02:04:34,965 --> 02:04:40,605
Organisations must look at another thing alongside agents.md – confidence thresholds.

1472
02:04:40,605 --> 02:04:46,805
For example, codecs may automatically fix linting errors and formatting issues, while

1473
02:04:46,805 --> 02:04:53,745
security vulnerabilities or database-related bugs require a mandatory senior engineer review.

1474
02:04:53,745 --> 02:04:58,905
An example of this is that first of all, we have to do this step by step.

1475
02:04:58,905 --> 02:05:03,985
The first part of our process is to identify our bug trigger resources and define where

1476
02:05:03,985 --> 02:05:06,485
the bug reports originate.

1477
02:05:06,485 --> 02:05:12,545
Usually what happens is we see this in our CI slash CD builds, or we can see this in our

1478
02:05:12,545 --> 02:05:18,665
unit tests we perform, or we can see this in our integration test failures.

1479
02:05:18,665 --> 02:05:24,245
Sometimes issues can arise in GitHub, or our security scans can cause an issue.

1480
02:05:24,245 --> 02:05:29,805
Alright, after that we have to identify the AI and look at the AI's fix permissions.

1481
02:05:29,805 --> 02:05:36,425
If, let's suppose, there's a formatting issue, a linting issue, or a unit test failure,

1482
02:05:36,425 --> 02:05:40,725
We'll automatically look at all of them, and a detailed discussion will take place regarding

1483
02:05:40,725 --> 02:05:43,885
production incidents and everything.

1484
02:05:43,885 --> 02:05:48,205
Agents.md is our most important file which I mentioned here.

1485
02:05:48,205 --> 02:05:53,545
What happens in Agents.md is we can see the automated bug resolution rules.

1486
02:05:53,545 --> 02:05:58,285
Whenever we fix a bug, we should minimize the code changes, we should never modify the

1487
02:05:58,285 --> 02:06:04,325
database schemas, we should preserve the API contracts, add our tests for everyone, and

1488
02:06:04,325 --> 02:06:07,405
run all of the affected test suites.

1489
02:06:07,405 --> 02:06:11,945
We must explain the root cause and also create a pull request summary.

1490
02:06:11,945 --> 02:06:17,205
You can see all of this in agents.md, where we address the bugs, and multiple things are

1491
02:06:17,205 --> 02:06:18,205
included.

1492
02:06:18,205 --> 02:06:25,805
Then, if I, let's suppose, perform proper CI slash CD integration, meaning after identifying

1493
02:06:25,805 --> 02:06:29,525
the trigger sources, we've defined our AI.

1494
02:06:29,525 --> 02:06:34,705
Then if I say we want to configure CI slash CD here, what I'll do first is take you to

1495
02:06:34,705 --> 02:06:36,985
the configuration.

1496
02:06:36,985 --> 02:06:42,165
In the configuration workflow, we first discuss the build failure, then we understand our

1497
02:06:42,165 --> 02:06:48,725
codex investigation, generate the fix, run the tests, create the pull request, develop

1498
02:06:48,725 --> 02:06:52,725
our reviews and also then merge our workings.

1499
02:06:52,725 --> 02:06:54,825
So this will come here.

1500
02:06:54,825 --> 02:07:00,065
Then the next and most important process, which will be discussed in our setup here,

1501
02:07:00,065 --> 02:07:02,845
will be our validation of fixes.

1502
02:07:02,845 --> 02:07:09,705
Here we will require our unit tests, integration tests, security scans, code reviews and our

1503
02:07:09,705 --> 02:07:12,065
build verifications.

1504
02:07:12,065 --> 02:07:15,505
These will directly be used to approve our process.

1505
02:07:15,505 --> 02:07:21,385
Alright, now as an example, if I go into Codex and open a new chat, what will happen in our

1506
02:07:21,385 --> 02:07:25,845
chat is I'll say directly that a GitHub action has failed. We'll include the

1507
02:07:25,845 --> 02:07:30,505
repository name directly. We have our failure logs here and the tasks are

1508
02:07:30,505 --> 02:07:35,545
being discussed the most here. Alright, after that we have our unit test

1509
02:07:35,545 --> 02:07:40,445
failure which we will use. After that, whatever automated bug resolution we

1510
02:07:40,445 --> 02:07:45,565
have directly we will configure it. We will discuss a OneGo project today. We

1511
02:07:45,565 --> 02:07:50,905
will direct a full repository in our OneGo project. First we will create all

1512
02:07:50,905 --> 02:07:56,185
project code and details. After that we will check our iterations and possible

1513
02:07:56,185 --> 02:08:00,827
improvements. Then we will use GitHub and Codex.

1514
02:08:01,827 --> 02:08:05,827
Here is our Codex. We open Codex.

1515
02:08:05,827 --> 02:08:09,827
Inside Codex, we generate a full project before using prompts.

1516
02:08:09,827 --> 02:08:13,827
In Codex, we must include the SetAgents file.

1517
02:08:13,827 --> 02:08:17,227
But we will first exit this project.

1518
02:08:17,227 --> 02:08:20,227
Then we will build a new project here.

1519
02:08:20,227 --> 02:08:23,087
I will close this one.

1520
02:08:23,087 --> 02:08:26,627
We close it and build a new project again.

1521
02:08:26,627 --> 02:08:28,987
You see projects are available here.

1522
02:08:28,987 --> 02:08:32,507
I can organise them or start from scratch.

1523
02:08:32,507 --> 02:08:35,827
We will name our project OneGo.

1524
02:08:35,827 --> 02:08:40,847
In this project we will build a complete application with everything.

1525
02:08:40,847 --> 02:08:43,467
First we will pin this project.

1526
02:08:43,467 --> 02:08:46,967
After pinning, we open it in our Explorer.

1527
02:08:46,967 --> 02:08:50,367
Our Explorer has no file inside.

1528
02:08:50,367 --> 02:08:54,327
Later, all generations will come into this file.

1529
02:08:54,327 --> 02:08:57,387
We have our VS Code and Terminal.

1530
02:08:57,387 --> 02:09:01,547
I told you before we can use codecs in our terminal.

1531
02:09:01,547 --> 02:09:04,927
In VS Code, our cursor is available.

1532
02:09:04,927 --> 02:09:07,287
I will first tell you the plan.

1533
02:09:07,287 --> 02:09:09,967
We will open our plan mode.

1534
02:09:09,967 --> 02:09:12,207
We have no plugins yet.

1535
02:09:12,207 --> 02:09:14,887
We will not use the browser much.

1536
02:09:14,887 --> 02:09:18,847
We will use the 5.4 model in our GPT.

1537
02:09:18,847 --> 02:09:22,367
We will use the medium 5.4 model.

1538
02:09:22,367 --> 02:09:26,267
We will use fast speed here, not default speed.

1539
02:09:26,267 --> 02:09:28,647
It will be used here.

1540
02:09:28,647 --> 02:09:31,427
We will not connect GitHub for now.

1541
02:09:31,427 --> 02:09:34,927
I will say in one go that I am going to make a project

1542
02:09:34,927 --> 02:09:37,667
about a health care application.

1543
02:09:37,667 --> 02:09:40,627
Can you plan a project for me?

1544
02:09:40,627 --> 02:09:42,207
Project planning will start here.

1545
02:09:43,207 --> 02:09:45,347
First, it will settle output resources.

1546
02:09:46,467 --> 02:09:47,767
I will not include them now.

1547
02:09:48,807 --> 02:09:50,587
We look at current workspace.

1548
02:09:51,767 --> 02:09:53,607
You see nothing is there in workspace.

1549
02:09:55,207 --> 02:09:58,707
Who is the primary user for the first version of the healthcare app?

1550
02:09:59,367 --> 02:10:01,267
We have patients and doctors.

1551
02:10:02,167 --> 02:10:05,507
I will say, this application is for patients.

1552
02:10:06,367 --> 02:10:09,027
We want to build an application for our patients.

1553
02:10:09,027 --> 02:10:15,487
What kind of first release do you want to plan? MVP or balanced or ambitious?

1554
02:10:16,367 --> 02:10:23,607
I will choose MVP. What is our delivery target? We want to build a web application here.

1555
02:10:24,167 --> 02:10:28,527
I will not build a mobile application. I will build a web app here.

1556
02:10:29,247 --> 02:10:35,547
The current decision is clear. Patient facing, MVP sized and optimised for a web app.

1557
02:10:35,547 --> 02:10:38,807
I still need to lock the feature set.

1558
02:10:40,067 --> 02:10:41,387
Now we have our feature sets.

1559
02:10:42,147 --> 02:10:44,347
Which feature bundle should define the MVP?

1560
02:10:45,527 --> 02:10:46,567
Booking and records?

1561
02:10:47,327 --> 02:10:49,287
We will use this simple option.

1562
02:10:50,787 --> 02:10:53,947
How should the plan treat healthcare compliance in the first version?

1563
02:10:54,867 --> 02:10:58,167
We will use HIPAA ready design, which is recommended.

1564
02:10:59,167 --> 02:11:03,027
We can also use full compliance track or lightweight prototype.

1565
02:11:03,027 --> 02:11:07,447
How much external integration should the first plan include?

1566
02:11:08,727 --> 02:11:11,207
I will say minimal integration will be included.

1567
02:11:12,147 --> 02:11:13,527
These things are recommended here.

1568
02:11:14,347 --> 02:11:16,527
Through them our entire process comes.

1569
02:11:18,007 --> 02:11:19,347
What will be the delivery timeline?

1570
02:11:20,327 --> 02:11:22,847
What will be the delivery timeline for our project?

1571
02:11:23,967 --> 02:11:26,887
I will say I want it in an urgent manner.

1572
02:11:27,867 --> 02:11:30,987
This is a fourth part where we can include what we want.

1573
02:11:30,987 --> 02:11:33,747
What team should this plan assume?

1574
02:11:35,007 --> 02:11:36,147
Our small team is here.

1575
02:11:37,127 --> 02:11:40,327
Instead of a small team, we can choose Solo Builder.

1576
02:11:41,007 --> 02:11:42,967
Our solo builder is here now.

1577
02:11:44,327 --> 02:11:45,627
What kind of plan do you need?

1578
02:11:46,107 --> 02:11:47,947
Build plan or business build?

1579
02:11:48,727 --> 02:11:51,127
We will work with a simple build plan.

1580
02:11:52,107 --> 02:11:54,667
Now it reduces the project scope and other things.

1581
02:11:55,607 --> 02:11:58,107
You see, multiple questions are asked here.

1582
02:11:58,107 --> 02:12:02,907
For a solo builder, what does urgent mean for the first usable release?

1583
02:12:03,847 --> 02:12:05,427
We will answer one week.

1584
02:12:06,327 --> 02:12:07,947
We will include one week here.

1585
02:12:09,007 --> 02:12:10,447
Our plan will come here.

1586
02:12:11,547 --> 02:12:15,327
Build a patient-facing WebMVP for a solo builder

1587
02:12:15,327 --> 02:12:18,327
optimised for one week urgent prototype

1588
02:12:18,327 --> 02:12:22,107
while keeping the design HIPAA aware and future ready

1589
02:12:22,107 --> 02:12:24,047
for real healthcare data handling.

1590
02:12:24,047 --> 02:12:28,267
I will read the plan once, then we will implement it.

1591
02:12:29,267 --> 02:12:31,447
I am saying that we have the entire process.

1592
02:12:32,647 --> 02:12:35,267
We say our product definition is also happening here.

1593
02:12:36,547 --> 02:12:41,387
After product definition, our recommended MVP features have also arrived here.

1594
02:12:42,687 --> 02:12:45,387
Frontend and backend have come in our technical approach.

1595
02:12:46,307 --> 02:12:50,707
I will tell it that I want just a working frontend and minimal backend.

1596
02:12:50,707 --> 02:12:57,627
Also, it should be just HTML and CSS with JS logics.

1597
02:12:57,627 --> 02:13:00,787
We want our product in a simpler way.

1598
02:13:00,787 --> 02:13:02,927
All these things will come here.

1599
02:13:02,927 --> 02:13:05,387
The stack has arrived.

1600
02:13:05,387 --> 02:13:08,207
What should a minimal backend do?

1601
02:13:08,207 --> 02:13:11,567
We can use a tiny mock API.

1602
02:13:11,567 --> 02:13:14,827
We can use a basic form backend.

1603
02:13:14,827 --> 02:13:18,347
We will not use any real backend.

1604
02:13:18,347 --> 02:13:21,147
How should the frontend be structured?

1605
02:13:21,147 --> 02:13:25,907
I can say a multi-page application will be required here.

1606
02:13:25,907 --> 02:13:29,147
What level of frontend quality is needed?

1607
02:13:29,147 --> 02:13:34,167
I will say we need a portfolio quality user interface.

1608
02:13:34,167 --> 02:13:36,727
Our plan is created.

1609
02:13:36,727 --> 02:13:41,447
You can see we have JSON objects and local storage here.

1610
02:13:41,447 --> 02:13:46,687
Key changes are to reframe the project as a frontend prototype, not a production ready

1611
02:13:46,687 --> 02:13:47,687
option.

1612
02:13:47,687 --> 02:13:50,687
Now we can implement this plan.

1613
02:13:50,687 --> 02:13:53,687
During implementation, it will bring our coding.

1614
02:13:53,687 --> 02:13:56,687
It is checking the workspace shape.

1615
02:13:56,687 --> 02:14:01,687
We will look at static app files and shared styles and JavaScript layers here.

1616
02:14:01,687 --> 02:14:06,687
We will also check the open file to see what things are discussed in it.

1617
02:14:06,687 --> 02:14:10,687
First it took basic index HTML.

1618
02:14:10,687 --> 02:14:13,687
We will open our file explorer.

1619
02:14:13,687 --> 02:14:16,687
We will open 1Go from Documents.

1620
02:14:16,687 --> 02:14:22,187
For the time being, we have no file or format available in one go.

1621
02:14:22,187 --> 02:14:25,387
But later our files will appear.

1622
02:14:25,387 --> 02:14:31,687
It has confirmed our HTML pages and state stylesheet and JS layer.

1623
02:14:31,687 --> 02:14:35,007
In plugins, our GitHub is not installed yet.

1624
02:14:35,007 --> 02:14:39,367
I will go to our codec settings to install GitHub once.

1625
02:14:39,367 --> 02:14:41,407
We will go to our settings.

1626
02:14:41,407 --> 02:14:43,947
You can see our connections here.

1627
02:14:43,947 --> 02:14:47,867
In settings, you can see we have our connections.

1628
02:14:47,867 --> 02:14:53,047
Besides connections, we have our MCP servers here which we can use.

1629
02:14:53,047 --> 02:14:56,587
We also use plugins here which we can connect.

1630
02:14:56,587 --> 02:14:58,907
I will go to our plugins.

1631
02:14:58,907 --> 02:15:01,567
You can see our plugins are available.

1632
02:15:01,567 --> 02:15:06,127
Where all our other details are, we will include our direct option.

1633
02:15:06,127 --> 02:15:09,007
In configuration we have our plugins.

1634
02:15:09,007 --> 02:15:11,827
We can use user configuration.

1635
02:15:11,827 --> 02:15:17,227
We have sandbox settings and current version and everything is working.

1636
02:15:17,227 --> 02:15:20,807
In MCP servers our plugins have arrived.

1637
02:15:20,807 --> 02:15:25,887
We can also see our most used plugin here and how it is discussed.

1638
02:15:25,887 --> 02:15:28,867
Then we have plugins inside our hooks.

1639
02:15:28,867 --> 02:15:33,907
And we have our computer use plugin, so any app and our Google Chrome browser has also

1640
02:15:33,907 --> 02:15:35,787
arrived here.

1641
02:15:35,787 --> 02:15:39,147
I will bring our plugins into our settings search.

1642
02:15:39,147 --> 02:15:41,027
These are our plugins.

1643
02:15:41,027 --> 02:15:43,587
I will use GitHub here.

1644
02:15:43,587 --> 02:15:47,447
When I connect GitHub, you can see all details have arrived here.

1645
02:15:47,447 --> 02:15:51,647
Because we are using the Michael DuPont account, we will bring the same Michael DuPont email

1646
02:15:51,647 --> 02:15:53,187
here.

1647
02:15:53,187 --> 02:15:55,707
We click on Add Plugin.

1648
02:15:55,707 --> 02:15:57,767
Adding GitHub will appear.

1649
02:15:57,767 --> 02:15:59,187
It is approved by our admin.

1650
02:15:59,908 --> 02:16:03,828
We will go to Connect and continue to GitHub.

1651
02:16:03,828 --> 02:16:07,908
We will get our detail in our browser, which we will use.

1652
02:16:07,908 --> 02:16:10,708
You will see that GitHub is now connected.

1653
02:16:10,708 --> 02:16:13,828
We can try it out in the chat too.

1654
02:16:13,828 --> 02:16:19,828
In GitHub, we have our repositories and pull requests, and all things have arrived.

1655
02:16:19,828 --> 02:16:22,828
Our GitHub access is now connected.

1656
02:16:22,828 --> 02:16:26,828
We have our repositories and issues, and pull requests inside it.

1657
02:16:26,828 --> 02:16:32,828
We have 97 actions available in the GitHub app related to Read and Write.

1658
02:16:32,828 --> 02:16:36,828
We can use it for Read and Write functions.

1659
02:16:36,828 --> 02:16:40,828
If we want to try it in the chat, we can do that too.

1660
02:16:40,828 --> 02:16:44,988
After this, we go to our healthcare application.

1661
02:16:44,988 --> 02:16:49,248
You will see that a total of 9 files generated here.

1662
02:16:49,248 --> 02:16:52,768
You can see in these files we have our app.js.

1663
02:16:52,768 --> 02:16:57,648
If I go here and reload it, our file structure is still not very strong.

1664
02:16:57,648 --> 02:17:01,948
But you will see that all our assets are available here.

1665
02:17:01,948 --> 02:17:03,908
Index and records.

1666
02:17:03,908 --> 02:17:07,508
And all these files are generated here overall.

1667
02:17:07,508 --> 02:17:12,508
Now it also told us it found a portability issue in the static assets.

1668
02:17:12,508 --> 02:17:16,548
A few non-ASCII characters slipped into the labels.

1669
02:17:16,548 --> 02:17:18,168
It will run them.

1670
02:17:18,168 --> 02:17:20,328
The command is normalised.

1671
02:17:20,328 --> 02:17:23,408
I am loading the normal browser.

1672
02:17:23,408 --> 02:17:26,948
Now we will connect things in our in-app browser.

1673
02:17:26,948 --> 02:17:29,688
You will see I did not give any prompt.

1674
02:17:29,688 --> 02:17:32,868
I did not give any prompt on a large scale.

1675
02:17:32,868 --> 02:17:36,988
I gave a basic prompt that I need a healthcare application.

1676
02:17:36,988 --> 02:17:42,068
It planned it and took multiple recommendations from me during planning.

1677
02:17:42,068 --> 02:17:46,508
In the end it generated all our assets in one go.

1678
02:17:46,508 --> 02:17:51,948
Appointments and dashboard and doctors and index and record files are generated.

1679
02:17:51,948 --> 02:17:55,188
Now browser automation has also arrived.

1680
02:17:55,188 --> 02:17:59,228
We have all files for implementation and we can run prototypes.

1681
02:17:59,228 --> 02:18:02,368
Here is our documentation.

1682
02:18:02,368 --> 02:18:09,748
Now if I open our file explorer and go to documents and one go, our folder is empty right now.

1683
02:18:09,748 --> 02:18:14,788
But if I look at our index.html here in the file explorer, you will see that we have a

1684
02:18:14,788 --> 02:18:17,028
file available.

1685
02:18:17,028 --> 02:18:21,908
If I open this file in our browser, you will see our project has arrived.

1686
02:18:21,908 --> 02:18:24,788
It is a healthcare app prototype.

1687
02:18:24,788 --> 02:18:29,808
We are accessing healthcare here with appointments and records and reminders.

1688
02:18:29,808 --> 02:18:33,048
When we want to enter a dashboard we sign in here.

1689
02:18:33,048 --> 02:18:35,488
Our doctors have arrived in it.

1690
02:18:35,488 --> 02:18:38,268
After doctors our appointments have arrived.

1691
02:18:38,268 --> 02:18:40,628
And our records have arrived.

1692
02:18:40,628 --> 02:18:43,968
This is our whole process as you can see.

1693
02:18:43,968 --> 02:18:47,768
If we want we can confirm any other appointment too.

1694
02:18:47,768 --> 02:18:50,108
I will confirm an appointment.

1695
02:18:50,108 --> 02:18:52,528
I will say I have a heart pain.

1696
02:18:52,528 --> 02:18:54,688
I will just include a reason.

1697
02:18:54,688 --> 02:18:58,288
When we include this part our second appointment will come.

1698
02:18:58,288 --> 02:19:00,908
This means our page is loading.

1699
02:19:00,908 --> 02:19:07,008
If we go to records we have our medications and allergies and recent visits available.

1700
02:19:07,008 --> 02:19:11,648
If we go to doctors, all doctors we have are listed here.

1701
02:19:11,648 --> 02:19:13,968
Then comes our dashboard.

1702
02:19:13,968 --> 02:19:18,628
Inside this dashboard we have our current summary showing the plan and conditions and

1703
02:19:18,628 --> 02:19:20,548
recent visits.

1704
02:19:20,548 --> 02:19:26,628
Our insurance card and hydration reminder and medication review are all available.

1705
02:19:26,628 --> 02:19:32,148
Members and unwanted things are available here. If we want we can build a new demo

1706
02:19:32,148 --> 02:19:37,848
account instead of demo credentials. I will close this one. I will give a prompt

1707
02:19:37,848 --> 02:19:42,588
here. I liked my first draft and I want to make this an official app for the

1708
02:19:42,588 --> 02:19:48,548
patients. Add some vibrant health-based colors in the website. Also try to make

1709
02:19:48,548 --> 02:19:53,948
it more real. Our prototype is very much liked. In the prototype our login and

1710
02:19:53,948 --> 02:19:59,388
doctors are very real. But this dashboard has some issues. When I bring it to the phone

1711
02:19:59,388 --> 02:20:05,368
view it does not look special. It has many issues. This dashboard does not go higher

1712
02:20:05,368 --> 02:20:11,808
from here. The second thing is our login panel goes too far back. If we go to our network

1713
02:20:11,808 --> 02:20:18,788
inside the console, nothing special is loading. This means we have no back end. It created

1714
02:20:18,788 --> 02:20:25,208
a working front end for us. I have given a prompt to update our prototype. You see we

1715
02:20:25,208 --> 02:20:31,368
have our browser available in plugins. Due to this we can use it. It says I am updating

1716
02:20:31,368 --> 02:20:37,708
the prototype. It is updating the prototype towards a more launch-oriented Alaska patient

1717
02:20:37,708 --> 02:20:44,148
app. First I am verifying the current front end structure. Then I will replace the mock

1718
02:20:44,148 --> 02:20:50,148
positioning with real Alaska provider data. It will shift the design towards a premium

1719
02:20:50,148 --> 02:20:55,868
Apple adjacent aesthetic without copying Apple owned logos or icons, because we cannot

1720
02:20:55,868 --> 02:21:02,348
copy the icons. But if we want, we can copy aesthetics based on an ecosystem. And we are

1721
02:21:02,348 --> 02:21:08,828
going to do the same thing here. This thing will be induced here. In styles you see we

1722
02:21:08,828 --> 02:21:14,328
we have many changes. It is performing enhancements in our file overall.

1723
02:21:14,328 --> 02:21:21,328
I have included one thing in the OneGo project. I want to run the Apple ecosystem here.

1724
02:21:21,328 --> 02:21:27,708
Apple ecosystem means the user interface enhancements in our MacBook or iPhones. I want to adapt

1725
02:21:27,708 --> 02:21:34,328
them in our project. All those things are happening here. You see what it is doing first.

1726
02:21:34,328 --> 02:21:37,028
I gave this information here.

1727
02:21:37,028 --> 02:21:40,168
Use real doctor information from Alaska.

1728
02:21:40,168 --> 02:21:42,408
I want to launch it there.

1729
02:21:42,408 --> 02:21:45,568
It is taking Alaska doctor profiles from the list.

1730
02:21:45,568 --> 02:21:48,968
First, it read all our files.

1731
02:21:48,968 --> 02:21:52,308
Then it understood index.js file.

1732
02:21:52,308 --> 02:21:56,128
Then it understood all files in data.js.

1733
02:21:56,128 --> 02:21:59,868
After that it is carrying on our research purpose.

1734
02:21:59,868 --> 02:22:04,288
When these things are included, our final website version will come in a better form

1735
02:22:04,288 --> 02:22:12,288
Let me tell you an important thing. In Codex, whatever things are happening now, you can see them all here.

1736
02:22:12,288 --> 02:22:20,288
If we have any output, we can see it too. If we have any source, we can see which source it is utilising here.

1737
02:22:20,288 --> 02:22:25,288
Like here, from a regional hospital list, it is retrieving doctors.

1738
02:22:25,288 --> 02:22:33,288
First, it makes concrete changes, replacing generic healthcare content with Alaska-specific facility and care context.

1739
02:22:33,288 --> 02:22:39,968
Second, it is rebuilding the visual system into a brighter, premium look that feels native

1740
02:22:39,968 --> 02:22:46,088
on iPhone and Mac without copying Apple trademarks or proprietary icon sets.

1741
02:22:46,088 --> 02:22:49,648
All these changes are being created right now here.

1742
02:22:49,648 --> 02:22:54,568
In the Styles section, you can see that we have many changes appearing.

1743
02:22:54,568 --> 02:22:59,248
We are experiencing many changes because it is performing complete enhancements in our

1744
02:22:59,248 --> 02:23:01,368
file overall.

1745
02:23:01,368 --> 02:23:06,468
All the styling updates are being processed to match the ecosystem we requested.

1746
02:23:06,468 --> 02:23:09,208
Our project design is improving to look professional.

1747
02:23:09,208 --> 02:23:13,308
The software implementation has reached the required final stages.

1748
02:23:13,308 --> 02:23:15,228
All web files were edited.

1749
02:23:15,228 --> 02:23:17,788
The main index file is now running.

1750
02:23:17,788 --> 02:23:20,888
The visual brand appears much better now.

1751
02:23:20,888 --> 02:23:24,248
Demo logging credentials exist in the database.

1752
02:23:24,248 --> 02:23:28,048
Entering the main dashboard shows AuroraCare Alaska.

1753
02:23:28,048 --> 02:23:33,888
Navigating to care teams displays available health and vascular care, internal medicine

1754
02:23:33,888 --> 02:23:36,368
and real-time schedules.

1755
02:23:36,368 --> 02:23:42,108
Alaska Regional Cardiology and Providence Primary Care Access Details are visible with exact

1756
02:23:42,108 --> 02:23:45,568
addresses and contact access details.

1757
02:23:45,568 --> 02:23:47,768
We can book a medical appointment here.

1758
02:23:47,768 --> 02:23:52,788
For example, a normal check-up for a child can be scheduled at 10.15.

1759
02:23:52,788 --> 02:23:57,088
A new medical appointment request is submitted for 1.30.

1760
02:23:57,088 --> 02:23:58,928
The system updates the patient schedule.

1761
02:23:59,819 --> 02:24:01,939
The active list shows scheduled visits.

1762
02:24:02,839 --> 02:24:05,139
We can cancel any booked visit from the records.

1763
02:24:06,179 --> 02:24:10,299
Previous health records display current patient medications and known allergies.

1764
02:24:10,299 --> 02:24:14,499
Recent clinical visits and lab reviews are also listed.

1765
02:24:14,499 --> 02:24:19,299
All recommended system features are implemented in this application version.

1766
02:24:19,299 --> 02:24:23,299
All these recommended software features are now complete.

1767
02:24:23,299 --> 02:24:27,299
Next, a brand new change will be adopted.

1768
02:24:27,299 --> 02:24:30,299
A new user profile feature is needed.

1769
02:24:30,299 --> 02:24:37,299
The end user should create a new account, add personal details and access a personalized dashboard.

1770
02:24:37,299 --> 02:24:42,799
Logging out of the current active session brings us to the main screen.

1771
02:24:42,799 --> 02:24:46,299
Clicking on Create a Demo Account opens a new form.

1772
02:24:46,299 --> 02:24:49,299
A new name, Alex, is entered.

1773
02:24:49,299 --> 02:24:53,299
The email address, alex at gmail dot com, is provided.

1774
02:24:53,299 --> 02:24:57,299
A secure password is created for this new account.

1775
02:24:57,299 --> 02:25:00,299
The brand new demo account is accessed.

1776
02:25:00,299 --> 02:25:03,299
Looking at the health records for this new user,

1777
02:25:03,299 --> 02:25:06,899
previous medications and known allergies are still visible.

1778
02:25:06,899 --> 02:25:10,379
The recent clinical visit data is also showing

1779
02:25:10,379 --> 02:25:15,499
old information. This problem happens because synthetic mock data is used.

1780
02:25:15,499 --> 02:25:20,999
When a new user account is created, all personal details should start fresh.

1781
02:25:20,999 --> 02:25:25,539
We need to include actual user inputs instead of synthetic data.

1782
02:25:25,539 --> 02:25:29,079
Even if previous scheduled appointments are cancelled

1783
02:25:29,079 --> 02:25:32,359
they remain in the application database for the new patient.

1784
02:25:32,359 --> 02:25:36,759
This behaviour applies to every new patient profile created.

1785
02:25:36,759 --> 02:25:40,259
New data is not available yet in the interface.

1786
02:25:40,259 --> 02:25:44,859
To solve this issue, new code logic must be introduced.

1787
02:25:44,859 --> 02:25:48,659
A text prompt is written to update the application logic.

1788
02:25:48,659 --> 02:25:51,759
The missing profile fields need to be added

1789
02:25:51,759 --> 02:25:56,639
and displayed on the main dashboard. The user account creation flow must be

1790
02:25:56,639 --> 02:25:57,399
complete from

1791
02:25:57,399 --> 02:26:01,459
end to end. The new user must feel personalized

1792
02:26:01,459 --> 02:26:05,019
without falling back to generic demo data.

1793
02:26:05,019 --> 02:26:08,019
The core application logic is updating.

1794
02:26:08,019 --> 02:26:12,179
Five project files are being edited to implement the changes.

1795
02:26:12,179 --> 02:26:19,299
These code items include data, HTML, dashboard, index and records files.

1796
02:26:19,299 --> 02:26:22,739
More software changes are expected to arrive soon.

1797
02:26:22,739 --> 02:26:25,619
The main project goal is defined now.

1798
02:26:25,619 --> 02:26:30,179
A new created user account must feel custom and personalized.

1799
02:26:30,179 --> 02:26:33,179
It should not fall back to generic demo data.

1800
02:26:33,179 --> 02:26:37,179
The user profile flow is implemented in the source code.

1801
02:26:37,179 --> 02:26:41,179
Syntax checks are running to verify the software changes.

1802
02:26:41,179 --> 02:26:45,179
The main index file now includes a complete sign-up form.

1803
02:26:45,179 --> 02:26:50,179
Logging out again allows us to test the updated demo account creation.

1804
02:26:50,179 --> 02:26:54,179
The new registration form requires comprehensive user details.

1805
02:26:54,179 --> 02:27:03,179
Full name, email, phone number, date of birth, blood type, address and medical insurance information must be provided.

1806
02:27:03,179 --> 02:27:07,179
Emergency contact details are also required to complete the setup.

1807
02:27:07,179 --> 02:27:11,179
These user details will be stored across the application assets.

1808
02:27:11,179 --> 02:27:16,179
The new account registration form is filled with specific user data.

1809
02:27:16,179 --> 02:27:20,179
The first name, Alex, is entered along with the email address.

1810
02:27:20,179 --> 02:27:22,179
A random phone number is provided.

1811
02:27:22,179 --> 02:27:27,579
The proper date of birth is set. The blood type is selected as A positive.

1812
02:27:28,579 --> 02:27:37,919
The user city is entered as Alaska. The geographic region is specified as USA, region, state, Alaska.

1813
02:27:38,959 --> 02:27:42,939
An insurance plan named Master Insure Pro is added.

1814
02:27:44,019 --> 02:27:46,259
An emergency contact number is also provided.

1815
02:27:46,859 --> 02:27:51,179
In the end, a secure password is created to finalise the account.

1816
02:27:52,179 --> 02:27:55,179
The new user account is created.

1817
02:27:55,179 --> 02:28:00,179
Navigating to the medical records section shows the updated patient identity.

1818
02:28:00,179 --> 02:28:05,179
All personal details provided during sign-up are displayed here.

1819
02:28:05,179 --> 02:28:09,179
The scheduled appointments section is now empty and ready for new bookings.

1820
02:28:09,179 --> 02:28:14,179
The care team section reflects the correct operational details.

1821
02:28:14,179 --> 02:28:17,179
The personalised user dashboard is functional.

1822
02:28:17,179 --> 02:28:21,399
Multiple future system changes can be integrated as the project evolves.

1823
02:28:22,619 --> 02:28:24,979
All main project details are configured.

1824
02:28:26,019 --> 02:28:28,919
The next crucial step is to upload the project code.

1825
02:28:30,019 --> 02:28:34,359
A command request is made to push all files into a remote GitHub repository.

1826
02:28:35,599 --> 02:28:40,239
The operating system checks available GitHub capabilities within the active workspace.

1827
02:28:41,219 --> 02:28:44,159
A local system Git installation is not found.

1828
02:28:44,159 --> 02:28:49,159
The active folder is not recognised as a valid Git repository.

1829
02:28:49,159 --> 02:28:54,159
Two concrete system blockers prevent the code push process.

1830
02:28:54,159 --> 02:28:58,159
First, the Git software is not installed on the machine.

1831
02:28:58,159 --> 02:29:03,159
Second, there is no connected remote GitHub repository available.

1832
02:29:03,159 --> 02:29:08,159
Suggested options are provided to resolve these software issues.

1833
02:29:08,159 --> 02:29:12,159
A new public code repository must be created first.

1834
02:29:12,159 --> 02:29:17,159
The main GitHub website is open to create a new online repository.

1835
02:29:17,159 --> 02:29:20,159
The user login credentials are saved.

1836
02:29:20,159 --> 02:29:25,159
A new repository named OneGoProjectHealthcare is created.

1837
02:29:25,159 --> 02:29:28,159
The access visibility is set to public.

1838
02:29:28,159 --> 02:29:31,159
The repository creation process completes.

1839
02:29:31,159 --> 02:29:35,159
The Internet repository link is now available for connection.

1840
02:29:35,159 --> 02:29:40,159
The required remote repository link is copied from GitHub.

1841
02:29:40,159 --> 02:29:46,659
This specific link is pasted into the system prompt to initiate the web connection.

1842
02:29:46,659 --> 02:29:51,659
The active system processes the target online repository URL.

1843
02:29:51,659 --> 02:29:56,999
It checks whether the main GitHub connector has the necessary account access.

1844
02:29:56,999 --> 02:29:59,779
The code push access is verified.

1845
02:29:59,779 --> 02:30:03,499
The current local project files are being read in order.

1846
02:30:03,499 --> 02:30:07,879
The development plan is to publish them into the main code branch.

1847
02:30:07,879 --> 02:30:11,879
This action is done through the built-in GitHub connector.

1848
02:30:11,879 --> 02:30:16,379
The raw text content of all project files is extracted.

1849
02:30:16,379 --> 02:30:19,819
The public code files are prepared for web publishing.

1850
02:30:19,819 --> 02:30:24,739
A small project readme file is also generated for the repository.

1851
02:30:24,739 --> 02:30:28,499
At this moment, the online repository is empty.

1852
02:30:28,499 --> 02:30:33,879
Refreshing the web GitHub page confirms no files are uploaded yet.

1853
02:30:33,879 --> 02:30:37,859
The background publishing application is running the pull request.

1854
02:30:37,859 --> 02:30:43,539
Once the upload process is approved, the new content will be available online.

1855
02:30:43,539 --> 02:30:48,219
The computer system waits for the background publishing process to execute.

1856
02:30:48,219 --> 02:30:51,339
A new approval prompt appears on the screen.

1857
02:30:51,339 --> 02:30:56,339
It requests security permission to allow GitHub to run the file creation tool.

1858
02:30:56,339 --> 02:31:00,979
The required permission is granted by selecting the Allow option.

1859
02:31:00,979 --> 02:31:07,179
This choice ensures automatic file creation without repetitive manual user approvals.

1860
02:31:07,179 --> 02:31:11,639
A subsequent system request asks to create code git blobs.

1861
02:31:11,639 --> 02:31:15,199
This security permission is also allowed to proceed.

1862
02:31:15,199 --> 02:31:21,739
These technical steps are necessary to transfer the local workspace files to the remote web environment.

1863
02:31:21,739 --> 02:31:27,059
If the source code is left in the local workspace, it cannot be shared or deployed.

1864
02:31:27,059 --> 02:31:32,099
Moving it to the online repository ensures the system is integrated.

1865
02:31:32,099 --> 02:31:35,419
Two separate system blockers are identified again.

1866
02:31:35,419 --> 02:31:39,859
the local machine still lacks a local software Git installation.

1867
02:31:39,859 --> 02:31:45,279
The web GitHub integration can read files, but write operations are blocked.

1868
02:31:45,279 --> 02:31:50,799
This problem happens because the integration cannot access the necessary developer tools.

1869
02:31:50,799 --> 02:31:55,979
To resolve this exact issue, a local system installation is required.

1870
02:31:55,979 --> 02:31:57,979
A new internet browser tab is opened.

1871
02:31:59,827 --> 02:32:05,727
install git is executed. The official git software installation page is accessed.

1872
02:32:05,727 --> 02:32:11,187
The Windows desktop operating system option is selected. The standalone

1873
02:32:11,187 --> 02:32:15,947
software installer for Windows is downloaded. The software download process

1874
02:32:15,947 --> 02:32:21,147
will take some time to finish. The installation setup will be executed soon.

1875
02:32:21,147 --> 02:32:27,087
The main git installer file is saved to the computer desktop. The file download

1876
02:32:27,087 --> 02:32:32,027
continues in the background. In the meantime the computer system provides a

1877
02:32:32,027 --> 02:32:36,627
text list of terminal commands. These commands are required to push the

1878
02:32:36,627 --> 02:32:42,327
source code by hand. Before executing them, remote repository permissions must

1879
02:32:42,327 --> 02:32:47,667
be verified. The main GitHub settings page is opened to ensure proper developer

1880
02:32:47,667 --> 02:32:53,907
access rights. The account security and variables section is examined. The account

1881
02:32:53,907 --> 02:32:58,707
moderation options are also visible. Navigating to the repository security

1882
02:32:58,707 --> 02:33:04,227
permissions is necessary to allow new code uploads. The active pull request

1883
02:33:04,227 --> 02:33:08,967
settings are reviewed. The code merge commits and squash merging options are

1884
02:33:08,967 --> 02:33:13,547
enabled by default. The version commit settings and archive features are

1885
02:33:13,547 --> 02:33:18,327
checked. The critical danger zone is avoided to prevent accidental project

1886
02:33:18,327 --> 02:33:23,627
deletion. Everything appears to be configured in a proper state. The git

1887
02:33:23,627 --> 02:33:28,187
software installer download is now complete. The application setup file will

1888
02:33:28,187 --> 02:33:33,047
be executed next to install the software on the computer. The downloaded git

1889
02:33:33,047 --> 02:33:38,147
software installer is executed from the computer desktop. The application setup

1890
02:33:38,147 --> 02:33:42,727
wizard appears on the screen. The standard default installation options are

1891
02:33:42,727 --> 02:33:47,727
selected by clicking the next button multiple times. The default components

1892
02:33:47,727 --> 02:33:52,607
are chosen for the system installation. The default code editor is maintained.

1893
02:33:52,607 --> 02:33:56,727
The initial project branch name configuration is left as a default

1894
02:33:56,727 --> 02:34:02,927
choice. The system path environment is updated. The software installation process

1895
02:34:02,927 --> 02:34:08,447
begins extracting core files. The visual progress bar indicates the current

1896
02:34:08,447 --> 02:34:13,487
installation status. The program installation is completed without errors.

1897
02:34:13,487 --> 02:34:19,847
The active current terminal window is closed. A fresh new terminal session is

1898
02:34:19,847 --> 02:34:24,947
launched to apply the updated installation paths. The specific git

1899
02:34:24,947 --> 02:34:31,007
initialize command is executed again. The operating system initializes an empty

1900
02:34:31,007 --> 02:34:37,087
local git repository. The local development project folder is now tracked by the git tool.

1901
02:34:38,207 --> 02:34:41,567
The next required command is copied from the text instructions.

1902
02:34:42,767 --> 02:34:46,687
The project branch is renamed to main using the active terminal.

1903
02:34:47,887 --> 02:34:50,847
The text command executes without any prompt errors.

1904
02:34:51,967 --> 02:34:58,207
The remote origin target command is copied next. This specific command links the local code

1905
02:34:58,207 --> 02:35:04,567
repository to the new created online GitHub repository. The web link is pasted

1906
02:35:04,567 --> 02:35:09,267
into the terminal and executed. The internet connection is established

1907
02:35:09,267 --> 02:35:14,947
without issues. The next development step requires adding all project files to the

1908
02:35:14,947 --> 02:35:21,247
code staging area. The standard git add command is prepared. An error prompt

1909
02:35:21,247 --> 02:35:26,947
occurs stating access permission is denied. The operating system cannot open

1910
02:35:26,947 --> 02:35:30,567
a distinct application data directory.

1911
02:35:30,567 --> 02:35:33,947
This file access issue must be resolved.

1912
02:35:33,947 --> 02:35:38,307
The access permission denied error halts the running process.

1913
02:35:38,307 --> 02:35:43,327
The operating system attempts to add developer files from the root user directory instead

1914
02:35:43,327 --> 02:35:45,607
of the project folder.

1915
02:35:45,607 --> 02:35:48,467
This behaviour is a crucial mistake.

1916
02:35:48,467 --> 02:35:53,067
The code terminal is operating in the wrong system directory path.

1917
02:35:53,067 --> 02:35:59,707
A new Terminal Application tab must be opened within the exact correct project folder.

1918
02:35:59,707 --> 02:36:03,267
The root user terminal is closed without delay.

1919
02:36:03,267 --> 02:36:09,547
The new command terminal now displays the correct document path for the software project.

1920
02:36:09,547 --> 02:36:14,847
The standard git initialize command is executed again in the right folder.

1921
02:36:14,847 --> 02:36:20,067
An empty code repository is initialized here without any issues.

1922
02:36:20,067 --> 02:36:25,627
The Branch Rename Text command is executed to set the main branch.

1923
02:36:25,627 --> 02:36:32,407
The Remote Origin command is pasted and executed to link the online GitHub repository.

1924
02:36:32,407 --> 02:36:36,167
The correct project folder is now connected.

1925
02:36:36,167 --> 02:36:41,107
The next workflow step is to add all files to the staging area.

1926
02:36:41,107 --> 02:36:46,167
The simple Git Add command is executed without errors this time.

1927
02:36:46,167 --> 02:36:50,767
All main project files are added to the code staging area.

1928
02:36:50,767 --> 02:36:56,267
The standard git commit command is executed with a descriptive message.

1929
02:36:56,267 --> 02:37:01,507
The operating system returns an author identity unknown error.

1930
02:37:01,507 --> 02:37:06,487
The code commit cannot proceed without proper user identification.

1931
02:37:06,487 --> 02:37:11,507
The global user configuration commands must be executed first.

1932
02:37:11,507 --> 02:37:15,687
The terminal command to set the user email is copied.

1933
02:37:15,687 --> 02:37:21,887
The account email address is updated to match the online GitHub account credentials.

1934
02:37:21,887 --> 02:37:25,787
The command is executed without any system errors.

1935
02:37:25,787 --> 02:37:30,387
The terminal command to set the username is copied next.

1936
02:37:30,387 --> 02:37:35,487
The developer username is retrieved from the Web GitHub profile page.

1937
02:37:35,487 --> 02:37:40,387
The target username is pasted into the terminal command line.

1938
02:37:40,387 --> 02:37:44,687
The system configuration is updated without issues.

1939
02:37:44,687 --> 02:37:48,667
The required author identity is now established.

1940
02:37:48,667 --> 02:37:53,367
The standard git commit command is executed once again.

1941
02:37:53,367 --> 02:37:57,507
This specific time, the code commit is a success.

1942
02:37:57,507 --> 02:38:01,887
All modified files are recorded in the local repository.

1943
02:38:01,887 --> 02:38:05,527
The source code is ready for the final push.

1944
02:38:05,527 --> 02:38:12,447
The main commit process includes all necessary application files, the design assets, HTML

1945
02:38:12,447 --> 02:38:17,007
web pages and application data files are secured.

1946
02:38:17,007 --> 02:38:21,707
The final terminal command to push the source code is executed.

1947
02:38:21,707 --> 02:38:28,287
The command terminal requests user authentication to access the remote GitHub repository.

1948
02:38:28,287 --> 02:38:33,267
A new internet browser window opens for the user login process.

1949
02:38:33,267 --> 02:38:37,407
The Sign in with internet browser option is selected.

1950
02:38:37,407 --> 02:38:43,167
The existing active session credentials are used to authorise the upload transaction.

1951
02:38:43,167 --> 02:38:46,907
The access authorisation succeeds without delay.

1952
02:38:46,907 --> 02:38:52,547
Returning to the command terminal confirms the code push process is active.

1953
02:38:52,547 --> 02:38:57,027
The data objects are compressed and written to the remote web server.

1954
02:38:57,027 --> 02:39:01,867
The main code branch is set up to track the remote origin point.

1955
02:39:01,867 --> 02:39:05,447
The entire application project is uploaded.

1956
02:39:05,447 --> 02:39:10,827
The online GitHub repository page is refreshed in the internet browser.

1957
02:39:10,827 --> 02:39:14,807
All local project files are now visible online.

1958
02:39:14,807 --> 02:39:19,667
The assets folder and HTML text documents are listed.

1959
02:39:19,667 --> 02:39:23,927
The code upload process is verified and a success.

1960
02:39:23,927 --> 02:39:30,427
The uploaded index document file is opened on GitHub to verify its code contents.

1961
02:39:30,427 --> 02:39:35,607
The online code matches the local computer version without flaws.

1962
02:39:35,607 --> 02:39:39,527
The source blame and file history options are functional.

1963
02:39:39,527 --> 02:39:43,287
The raw text code can be accessed any time.

1964
02:39:43,287 --> 02:39:46,947
The entire upload process is now concluded.

1965
02:39:46,947 --> 02:39:52,507
The initial project objective was to build a medical healthcare application project.

1966
02:39:52,507 --> 02:39:55,307
A detailed development plan was formulated first.

1967
02:39:58,331 --> 02:40:04,851
basic minimum viable product. The database backend requirements were later removed to

1968
02:40:04,851 --> 02:40:08,471
to focus on the user front-end interface.

1969
02:40:08,471 --> 02:40:15,131
The HTML and CSS design structures were developed with minimal JavaScript logic.

1970
02:40:15,131 --> 02:40:21,771
Various design iterations improved the visual page aesthetics and user experience.

1971
02:40:21,771 --> 02:40:26,851
The personalized user profile creation feature was integrated.

1972
02:40:26,851 --> 02:40:32,351
In the end, the local source code was pushed to a public code repository.

1973
02:40:32,351 --> 02:40:36,571
The application project is stored and accessible.

1974
02:40:36,571 --> 02:40:41,171
Future code modifications can be implemented and tracked through this version repository

1975
02:40:41,171 --> 02:40:43,871
system without effort.

1976
02:40:43,871 --> 02:40:49,031
The detailed software implementation plan proved effective in practice.

1977
02:40:49,031 --> 02:40:55,611
We established a strong code foundation using standard modern web technologies.

1978
02:40:55,611 --> 02:41:02,111
The front-end user interface provides a seamless, smooth experience for clinical patients managing

1979
02:41:02,111 --> 02:41:04,551
their healthcare needs.

1980
02:41:04,551 --> 02:41:11,851
The synthetic mock data limitations were overcome by implementing dynamic user input handling.

1981
02:41:11,851 --> 02:41:17,211
The medical appointment scheduling and user cancellation workflows operate without any

1982
02:41:17,211 --> 02:41:19,351
system errors.

1983
02:41:19,351 --> 02:41:25,831
Essential patient medical records remain accessible on the personalised user dashboard.

1984
02:41:25,831 --> 02:41:31,731
By utilising the Git version control system, the main source code remains protected against

1985
02:41:31,731 --> 02:41:38,591
accidental data loss. The open public repository allows other software developers to review

1986
02:41:38,591 --> 02:41:44,971
the application project structure. This developer workflow demonstrates a practical approach

1987
02:41:44,971 --> 02:41:51,491
to rapid web application development and code deployment. The initial system setup challenges

1988
02:41:51,491 --> 02:41:58,111
regarding local machine software requirements were resolved with great speed. The comprehensive

1989
02:41:58,111 --> 02:42:04,771
command terminal instructions ensured execution of necessary developer commands.

1990
02:42:04,771 --> 02:42:12,571
The final software outcome is a functional, well-documented and versioned front-end application.

1991
02:42:12,571 --> 02:42:15,211
The established project goals are fulfilled.

1992
02:42:15,211 --> 02:42:19,831
The discussion relates to possible iterations we can include here.

1993
02:42:19,831 --> 02:42:25,691
In our use cases, we create projects multiple times, requiring iterations.

1994
02:42:25,691 --> 02:42:30,031
We can include these iterations to see what is possible.

1995
02:42:30,031 --> 02:42:31,831
Iterations start from the beginning.

1996
02:42:31,831 --> 02:42:35,151
We include project details and formats.

1997
02:42:35,151 --> 02:42:38,731
Another option is available after project creation.

1998
02:42:38,731 --> 02:42:42,451
Moving to the end, our index was complete at this step.

1999
02:42:42,451 --> 02:42:49,531
Here, in frontend, backend, appointments and records, our option has arrived.

2000
02:42:49,531 --> 02:42:51,471
Changes are never small.

2001
02:42:51,471 --> 02:42:55,971
For changes, we will include details multiple times.

2002
02:42:55,971 --> 02:43:01,311
Another important thing is working in an environment requiring code changes.

2003
02:43:01,311 --> 02:43:03,591
Iterations become version-based.

2004
02:43:03,591 --> 02:43:07,911
The first website version was quite different from the current version.

2005
02:43:07,911 --> 02:43:12,651
We must understand version histories to see which was more compatible.

2006
02:43:12,651 --> 02:43:16,891
Sometimes we include specific things from a specific version.

2007
02:43:16,891 --> 02:43:20,691
Going into our project, this was the final version.

2008
02:43:20,691 --> 02:43:26,571
Looking at this project, considering the whole use case, the logo is incorrect.

2009
02:43:26,571 --> 02:43:28,571
We can change the logo.

2010
02:43:28,571 --> 02:43:32,851
The dashboard should be a sliding dashboard, not a consistent one.

2011
02:43:32,851 --> 02:43:37,191
Instead of this, some analytics should be involved here.

2012
02:43:37,191 --> 02:43:42,691
Looking here, the card distance and the empty space in the website should be minimal.

2013
02:43:42,691 --> 02:43:45,931
We should fill such spaces beforehand.

2014
02:43:45,931 --> 02:43:51,051
In our website text, search engine optimization is not involved.

2015
02:43:51,051 --> 02:43:53,891
The colors involved here are quite dull.

2016
02:43:53,891 --> 02:43:58,311
We can improve all these things just by giving it some prompts.

2017
02:43:58,311 --> 02:44:01,151
Our iteration will start happening now.

2018
02:44:01,151 --> 02:44:07,951
Alongside iteration, another important thing is making large scale improvements via prompts.

2019
02:44:07,951 --> 02:44:13,451
Since this tool is based on our prompts, any new improvement will be based on prompts.

2020
02:44:13,451 --> 02:44:16,911
there is no other way to improve our stuff.

2021
02:44:16,911 --> 02:44:20,491
These things will be induced here with our ongoing time.

2022
02:44:20,491 --> 02:44:23,851
As our time increases, we must iterate these things

2023
02:44:23,851 --> 02:44:26,891
and see how we are taking them forward.

2024
02:44:26,891 --> 02:44:29,571
Along with this, another important thing

2025
02:44:29,571 --> 02:44:32,571
is that when making improvements based on prompts,

2026
02:44:32,571 --> 02:44:34,891
error chances increase.

2027
02:44:34,891 --> 02:44:38,551
Therefore, we should review our code first.

2028
02:44:38,551 --> 02:44:41,091
After reviewing the code, we should take things

2029
02:44:41,091 --> 02:44:44,651
towards our other generations and discussions.

2030
02:44:44,651 --> 02:44:47,471
Sometimes, within our code itself,

2031
02:44:47,471 --> 02:44:50,971
there are multiple errors we spend time correcting.

2032
02:44:50,971 --> 02:44:54,271
We are focusing on making the dashboard intuitive.

2033
02:44:54,271 --> 02:44:56,931
The layout needs adjustments so upcoming visits

2034
02:44:56,931 --> 02:44:59,331
and active reminders are visible to the user.

2035
02:45:00,351 --> 02:45:02,271
Care teams and appointment sections

2036
02:45:02,271 --> 02:45:04,751
must be integrated together.

2037
02:45:04,751 --> 02:45:07,531
This ensures the entire application functions

2038
02:45:07,531 --> 02:45:11,331
without visual or technical interruptions.

2039
02:45:11,331 --> 02:45:15,851
This completes our entire discussion related to our iteration.

2040
02:45:15,851 --> 02:45:19,291
Along with the iteration, we covered possible improvements

2041
02:45:19,291 --> 02:45:21,691
that needed to be discussed.

2042
02:45:21,691 --> 02:45:25,111
Looking at the bottom section, the reminders and profile

2043
02:45:25,111 --> 02:45:28,691
loaded cards have gaps needing fixes.

2044
02:45:28,691 --> 02:45:32,331
The design should feel premium and responsive.

2045
02:45:32,331 --> 02:45:34,811
The patient readiness items must be tracked

2046
02:45:34,811 --> 02:45:37,631
on one premium dashboard.

2047
02:45:37,631 --> 02:45:40,311
When looking at source options for medical centres,

2048
02:45:40,311 --> 02:45:43,791
like Providence Alaska Medical Centre or Alaska Native Medical

2049
02:45:43,791 --> 02:45:47,851
Centre, information must be displayed.

2050
02:45:47,851 --> 02:45:50,611
The layout structure lacks proper alignment,

2051
02:45:50,611 --> 02:45:53,571
and text blocks feel disconnected.

2052
02:45:53,571 --> 02:45:58,451
We will use specific commands to refine these interface elements.

2053
02:45:58,451 --> 02:46:01,411
Once we apply new styles, the final product

2054
02:46:01,411 --> 02:46:03,811
will look more professional.

2055
02:46:03,811 --> 02:46:11,131
Everything will be committed to the repository, ensuring all changes are saved and tracked for future updates and continuous development.

2056
02:46:11,651 --> 02:46:12,891
Now comes the last part.

2057
02:46:13,791 --> 02:46:16,631
At the end of this course, you saw one main thing.

2058
02:46:17,351 --> 02:46:19,351
It was our GitHub and Codex tools.

2059
02:46:20,211 --> 02:46:21,511
We tried to connect GitHub.

2060
02:46:22,311 --> 02:46:23,971
Then we got many tech issues.

2061
02:46:24,491 --> 02:46:27,771
I will say here I will use our plugin of GitHub now.

2062
02:46:28,431 --> 02:46:31,291
I will start a discussion with the GitHub plugin tool.

2063
02:46:31,291 --> 02:46:35,551
I will ask, can you check if GitHub plugin is working?

2064
02:46:36,451 --> 02:46:38,291
This will test our plugin once.

2065
02:46:38,951 --> 02:46:41,491
We will see if our plugin works in any user case.

2066
02:46:42,111 --> 02:46:45,111
If our plugin is not available, we can check it.

2067
02:46:45,851 --> 02:46:47,971
You can see we have verification now.

2068
02:46:48,871 --> 02:46:50,551
You can see that I have verified it.

2069
02:46:51,331 --> 02:46:53,111
This login account Robert is here.

2070
02:46:53,911 --> 02:46:55,711
You will remember our main account here.

2071
02:46:56,111 --> 02:46:57,291
That is connected here.

2072
02:46:58,191 --> 02:47:00,031
Its user ID has also come.

2073
02:47:00,031 --> 02:47:04,771
that confirm that the plugin is installed, reachable and authenticated.

2074
02:47:05,771 --> 02:47:08,251
Now I can say, what can I do with this?

2075
02:47:08,931 --> 02:47:10,911
This will start giving us a response.

2076
02:47:11,711 --> 02:47:13,751
It will tell us where we can use this plugin.

2077
02:47:14,831 --> 02:47:17,211
This tool is not available on a weak level,

2078
02:47:17,971 --> 02:47:20,551
but still we have to see how our tool can work here.

2079
02:47:21,151 --> 02:47:25,411
You will see here it says you can ask it to read multiple actions.

2080
02:47:26,491 --> 02:47:28,591
In this we also get more recommendations.

2081
02:47:28,591 --> 02:47:32,591
I will suggest to you that we should use multiple plugins.

2082
02:47:32,591 --> 02:47:36,591
Like right now, you are seeing that we can use our windows.

2083
02:47:36,591 --> 02:47:40,591
We have our Chrome and data analytics and product design.

2084
02:47:40,591 --> 02:47:46,591
We also have Apollo and Atio and Carter CRM and Clay and Circleback.

2085
02:47:46,591 --> 02:47:50,591
We have Granola and Otter and Canva.

2086
02:47:50,591 --> 02:47:52,591
We can use all these plugins.

2087
02:47:53,431 --> 02:47:54,811
We have many options.

2088
02:47:55,651 --> 02:47:58,631
If we bring any of these in here, we can use it out.

2089
02:47:59,291 --> 02:48:02,431
For every niche, we have separate options available for us.

2090
02:48:03,031 --> 02:48:07,571
Like for our education and research, we also have options available right here.

2091
02:48:07,571 --> 02:48:10,531
We have our Dow Jones Factiva here.

2092
02:48:10,951 --> 02:48:14,651
We have our GovTribe and we have Life Science Research.

2093
02:48:15,551 --> 02:48:18,691
For finance, we have multiple softwares available right here.

2094
02:48:19,751 --> 02:48:24,411
So what Codex does is on a large scale it gives us multiple plugins to use.

2095
02:48:25,331 --> 02:48:29,691
From these, the used plugin on our developer side is our GitHub plugin.

2096
02:48:30,691 --> 02:48:35,851
But if we want to use multiple plugins on our whole enterprise level, we can do that too.

2097
02:48:35,851 --> 02:48:38,851
With that, our price will increase.

2098
02:48:38,851 --> 02:48:42,851
Our usage cost will also become a cost that is quite high.

2099
02:48:45,851 --> 02:48:50,851
The OpenAI ecosystem is a collection of tools, models and platforms

2100
02:48:50,851 --> 02:48:56,851
that help individuals and organisations use artificial intelligence in practical workflows.

2101
02:48:57,851 --> 02:49:02,851
In this diagram, OpenAI ecosystem is the central idea

2102
02:49:02,851 --> 02:49:06,451
and the main branches show the important parts connected to it.

2103
02:49:07,831 --> 02:49:11,131
ChatGPT is one of the most familiar parts of the ecosystem.

2104
02:49:12,271 --> 02:49:16,611
It helps users write content, explain concepts, solve problems,

2105
02:49:17,251 --> 02:49:19,951
summarise information and support daily work.

2106
02:49:20,771 --> 02:49:25,751
In software development, ChatGPT can help developers understand errors,

2107
02:49:26,331 --> 02:49:31,911
write documentation, plan features and improve prompts before using them with coding tools.

2108
02:49:32,851 --> 02:49:40,451
The OpenAI API allows developers to connect OpenAI models directly into their own applications.

2109
02:49:40,451 --> 02:49:52,411
For example, a company can build a chatbot, document assistant, coding assistant, customer support tool or automation system using the API.

2110
02:49:53,971 --> 02:49:58,351
This makes AI usable inside real business products and enterprise systems.

2111
02:49:59,811 --> 02:50:02,011
Codex is focused on software development.

2112
02:50:02,851 --> 02:50:12,851
It helps developers generate code, refactor files, explain existing code, create tests, debug issues, and work with repositories.

2113
02:50:13,851 --> 02:50:22,851
In an Enterprise course, Codex is important because it shows how AI can support real development workflows instead of only answering questions.

2114
02:50:23,851 --> 02:50:27,851
The Models branch represents the AI models behind the ecosystem.

2115
02:50:27,851 --> 02:50:34,391
These models can work with text, code, images and other types of input depending on the

2116
02:50:34,391 --> 02:50:37,471
product or configuration.

2117
02:50:37,471 --> 02:50:42,351
Better models usually mean better reasoning, better code understanding and more accurate

2118
02:50:42,351 --> 02:50:44,351
responses.

2119
02:50:44,351 --> 02:50:49,651
Finally, enterprise tools are important for organisations.

2120
02:50:49,651 --> 02:50:57,491
Enterprises need security, governance, permissions, auditing and control over how AI is used.

2121
02:50:57,491 --> 02:51:03,511
These tools help companies adopt AI safely while protecting data, managing access and

2122
02:51:03,511 --> 02:51:05,991
following internal policies.

2123
02:51:05,991 --> 02:51:13,131
Overall, the diagram shows that the OpenAI ecosystem is not just one product.

2124
02:51:13,131 --> 02:51:20,631
It includes user-facing tools, developer APIs, coding assistance, advanced models and enterprise

2125
02:51:20,631 --> 02:51:22,131
controls.

2126
02:51:22,131 --> 02:51:28,991
Together, these parts help teams build, automate, learn and develop software more efficiently.

2127
02:51:32,891 --> 02:51:40,411
This conclusion mind map summarises the key lessons learned throughout the OpenAI Codex Enterprise Development course.

2128
02:51:41,191 --> 02:51:48,131
The central idea is that AI-assisted development is becoming an important part of modern software engineering

2129
02:51:48,131 --> 02:51:57,751
and organisations that learn to use these tools effectively can significantly improve productivity, software quality and development speed.

2130
02:51:58,611 --> 02:52:02,511
The first branch focuses on OpenAI Codex itself.

2131
02:52:03,591 --> 02:52:16,091
Throughout the course, learners discovered how Codex helps developers generate code, analyse repositories, refactor applications, create tests and automate repetitive development tasks.

2132
02:52:16,091 --> 02:52:24,571
Rather than replacing developers, Codex acts as an intelligent development assistant that helps teams work more efficiently.

2133
02:52:25,471 --> 02:52:28,791
The next branch highlights the development workflow.

2134
02:52:30,091 --> 02:52:36,171
One of the most important lessons from the course is that AI can support every stage of software development.

2135
02:52:37,391 --> 02:52:44,951
Developers can use Codex during planning, implementation, testing, debugging and deployment preparation.

2136
02:52:46,091 --> 02:52:49,771
Instead of viewing AI as a tool used only for coding,

2137
02:52:49,771 --> 02:52:55,691
organisations can integrate it into the complete software development lifecycle.

2138
02:52:55,691 --> 02:53:01,291
The Enterprise Adoption section emphasises that successful AI implementation

2139
02:53:01,291 --> 02:53:04,651
requires more than technical capability.

2140
02:53:04,651 --> 02:53:07,931
Organisations must establish governance frameworks,

2141
02:53:07,931 --> 02:53:13,611
security controls, compliance processes and collaboration standards.

2142
02:53:13,611 --> 02:53:23,491
Enterprise teams need visibility into how AI is used and must ensure that generated code meets organisational policies and quality requirements.

2143
02:53:24,791 --> 02:53:30,291
The best practices branch represents the habits that produce the best results when working with codecs.

2144
02:53:31,371 --> 02:53:35,311
Effective prompt engineering helps developers communicate requirements clearly.

2145
02:53:36,451 --> 02:53:39,931
Code reviews ensure generated code is maintainable and secure.

2146
02:53:39,931 --> 02:53:46,931
Validation and testing confirm that AI-generated features satisfy business requirements.

2147
02:53:46,931 --> 02:53:51,931
These practices help maximise the value of AI-assisted development.

2148
02:53:51,931 --> 02:53:55,931
Another important area is operational excellence.

2149
02:53:55,931 --> 02:54:04,931
As AI adoption grows, organisations must monitor usage, manage costs, optimise resources and measure performance.

2150
02:54:04,931 --> 02:54:16,311
Understanding token consumption, tracking productivity improvements and evaluating return on investment help organisations scale AI responsibly and efficiently.

2151
02:54:17,271 --> 02:54:22,971
The continuous learning branch reminds learners that AI technologies evolve rapidly.

2152
02:54:24,111 --> 02:54:33,371
Developers should stay informed about new codex capabilities, open AI platform updates, community best practices and industry trends.

2153
02:54:33,371 --> 02:54:41,051
Teams that continuously learn and adapt will gain the greatest long-term benefits from AI-assisted development.

2154
02:54:42,091 --> 02:54:46,451
The Future of Development section looks ahead to emerging trends.

2155
02:54:47,611 --> 02:54:56,831
AI assistants will become more capable, agent-based workflows will become more common, and human-AI collaboration will continue to evolve.

2156
02:54:56,831 --> 02:55:04,831
Developers will increasingly focus on architecture, business logic and strategic decision making,

2157
02:55:04,831 --> 02:55:07,831
while AI handles more implementation tasks.

2158
02:55:07,831 --> 02:55:14,831
Finally, the most important takeaway is that AI augments developers rather than replacing them.

2159
02:55:14,831 --> 02:55:19,831
Human expertise remains essential for understanding business requirements,

2160
02:55:19,831 --> 02:55:28,771
making architectural decisions, reviewing code quality, managing risk and ensuring software meets organisational goals.

2161
02:55:29,951 --> 02:55:38,951
When used effectively, Codex enables developers to deliver better software faster while maintaining quality, security and reliability.

2162
02:55:38,951 --> 02:55:46,531
In summary, the course demonstrates that successful enterprise AI adoption requires a combination

2163
02:55:46,531 --> 02:55:52,571
of technical skills, governance practices, continuous learning, and thoughtful collaboration

2164
02:55:52,571 --> 02:55:54,591
between humans and AI systems.