Agentic AI SOC introduction

0:00 You're not only going to have to know those security things and like personal network and all that, but you're going to have to know how to like leverage AI on top of that to be effective at your job and get hired and like maintain your position for future roles. And it's my mission to try to help everybody stay ahead of the curve as much as possible and introduce things that will be useful for your future interviews and future jobs and all that stuff.

0:23 So this course we're basically going to build a cyber security agentic AI like an AI sock analyst that does like threat hunting and can like take action and stuff like this. But in order to do that we need to build up our foundation. Uh so this course is going to be in three parts. The first part being the basics of Python. So you can do this like even if you have zero programming experience like anyone can start doing this.

0:46 And then the second part of the course is going to be using Python to uh interact with the open AI API cuz this is going to be heavily leveraged when we actually build the agent in the third part of the course. So after completing the course um not only going to be able to build an agentic AI like an AI sock analyst, you're going to have a really good understanding of how LLM APIs function and how to interact with them.

1:09 And this will open up a literal world of possibilities for you. Like once you know how to program and you understand how APIs work and you understand how to interact with uh the API for like chat GPD for instance, you can do like a lot of stuff. And the future of cyber security is very likely going to include some kind of orchestration of agentic AIS like orchestration of like AI sock analysts. Another way you can think about it and going through this course and doing everything will give you a really good understanding of how an AI agent might think and make decisions and how it interacts with a model and everything like that.

1:55 Like the purpose of this course is not to like you know be able to like build an agentic AI and like go and like sell the product or something cuz what we're making is like relatively simple rather it's to help you understand how everything works and give you a good mental foundation and expand your mind basically. And this course was originally created for the cyber range my community. It's a a long series of like many different videos and we just stitched them together and put it on YouTube.

2:19 And eventually you'll get to a point where you need to have access to the organic uh log database from the cyber range cuz a lot of organic and attack traffic gets put in there. And then we're going to use that uh log repository to do threat hunting and that type of stuff. But you'll be able to get through like seven hours of the course and like learn how to use the OpenAI API and like all the stuff before we even get to there.

2:41 But when we get to that point, um you just need access to the cyber range in order to use the logs. But if you want, I can provide um some like sample like real logs, but I'll provide them in samples for you that you can use with your code. But I recommend joining the Cyber anyway. Uh the community support is basically unparalleled and it's a really really high quality environment with enterprise tools and a nice production platform.

3:04 It's just really really good. And all the links and everything you need and like bookmarks and stuff are down below like when we start getting to the actual like interacting with the OpenAI API, you're going to have to be using like different code and I'm just going to provide all those down below in some links. And a quick note before we actually get into the course, I'm going to give you a a quick demo of the agent in action like the cyber security agentic AI agent and it might look like a bit intimidating because there's a lot of code and stuff, but eventually when we get through the course and like learn all this stuff, it will look a lot less intimidating and it will make a lot more sense.

3:26 But when you're watching the demo, just try to make sense of it and just try to understand it at a superficial level and like understand what I'm saying. And of course, if you have questions, just ask in the comments. I'll do my best to answer them. But again uh I spend most of my time in the community and I I dedicate like few hours a day just to answering community posts in there. So if you if you join the cyber range like instead of leaving YouTube comments just like leave a comment in the cyber range and tag me and I'll I'll like definitely respond to it or one of the staff will respond.

3:48 Don't stress. Just do your best to absorb things and work through it slowly and you'll get to the end. Just be consistent. Yeah. Best of luck. Ask any questions if you get stuck and we will see you in the next video. Hey everybody, welcome to the Agentic Cyber Security AI and Python course. Um, if you didn't already know, Agentic AI is just like an AI agent that can do something and then take some kind of action on its own with minimal or no uh input from humans.

4:11 And if you mix cyber security into that, you get aentic cyber security AI. And then you can imagine things like um automatically remediating something that it found like maybe isolating a virtual machine based on logs that analyzed or like remediating some vulnerability or like turning off a VM notifying somebody like the AI can actually like do something beyond just some kind of analysis. So in this course, we're going to build an agent that can do that stuff.

4:34 And the reality is with all the advent of the crazy AI and GPT and like all this stuff that's coming out these days, it's getting really really good and you know like businesses want to minmax and like save as much money as possible and like make money and all this stuff. So of course they're going to try to automate away as much as they can and what this means for cyber security is for sure a lot of those like low-end like what you know now as those like tier one sock analyst jobs that that's definitely going to get automated away eventually.

5:19 It's not going to be like today or maybe even this year, but um as people adopt AI more, those like entry- level jobs are going to kind of go away and um it's going to create new other positions that heavily leverage AI um AI agents to do those kind of cyber security operations things. It's kind of raising the bar in cyber security. You can think about it that way. like the lower-end jobs are going to kind of go away and then there's going to be other jobs that are like engineering the agents like orchestrating the sock, orchestrating the agents, like fine-tuning them and stuff like this.

5:42 So, we kind of have to like build on top of the foundation we already have and like learn these new uh AI related skills. And the whole reason for making this course is I just want people to get ahead of it. Like I don't want the jobs to like start going away in like you know 2027 or whatever and then people are like oh I have to like learn how to deal with cyber security agents at that time.

6:06 It's better to just like do it now. So we're going to build one from scratch and then we're going to learn the inner workings of it and everything. So by the time like even now like when you start interviewing it's going to be really really strong. Um when it comes to like your resume and like during the interview you're what you're going to be able to talk about is going to look really really good. But by the time we have to start actually like using these like fully developed SAS applications that use AI agents, um you'll have like a really good idea and a good intuition for how those work.

6:27 So you should be like, you know, much better off than the average person who's like not doing anything about it yet. In the next video, I'm going to show you a demo of the thing that we're actually going to build. Um I'll probably update that video, you know, as we build out the agent, but basically um it's a AI sock analyst agent. It will take a prompt from a user, decide where to search for the data, collect and analyze the logs, hunt for potential threats, generate a report, and then take some kind of action based on its findings.

6:51 And you'll see like what I mean by like the level one sock analyst positions are eventually going to go away because the agent um if it's built correctly, it functions at like 3 to 500 times the speed as a human does. And the way this course is structured, um there's going to be kind of maybe three main sections. The first section is just uh Python fundamentals. It's not really related to AI or anything, but we we're going to be using Python quite a bit.

7:15 And I'm not going to teach it in the sense that I just like cover all the theory. I'm going to cover it um in a way to kind of help you understand the specific components of Python that we need when we actually go to build agent. And the second portion of the course uh Python plus AI basics um we talk about how to combine Python with AI tools and different APIs like how to use Python and interact with the chat GPT API and how to use Python to interact with like our log analytics workspace and and this type of stuff the next level building blocks to build the AI agent.

8:02 And then the third part of the course um we're going to actually put everything together and then build our own intelligent um AI sock analyst that can actually do the threat hunting and like do those autonomous actions. And then the requirements for this course um as of right now uh everybody needs to have their own open AI account. Uh it's not really expensive. Um we'll kind of cover that later but we need to use the chat GPT API.

8:25 So we have to like register that account. It's relatively cheap and um it's kind of like pay as you go. The second thing is um you need to or rather I highly recommend you have completed the security operations course inside the cyber brains because it kind of provides you that foundation that threat hunting security operations foundation where we go over the logs and like learn how to use KQL and like all that stuff cuz we're going to build on top of that.

8:49 And then the third thing you need is access to the cyber range. Um the reason for this is there's like ton of organic traffic and logs inside of there that we're going to use to actually build our agent with. So, it's important to have these three things. Yeah, welcome to the course. We'll see you in the next video. Welcome back and welcome to the introduction to Chat GPT. And I just wanted to make this video real quick in case people like didn't know what chat GPT was or someone who has like heard about it or maybe you haven't used it yet.

9:13 Basically, you can use it for free. Um, I think you might have to sign up for it in order to like send more than X number of messages to it, but you can sign up to it for free and just kind of like use it with this demo if you want. just go to chat2pb.com. But the best way to think about this is like a super hyper intelligent alien that you're having a conversation with that happens to know all about humanity.

9:37 Basically, don't use it like it's Google. You can say like full-on sentences to it. For example, like um give me a, you know, carrot cake recipe for my son's only parents birthday. They are allergic to gluten. I'm I'm spelling stuff wrong, but it doesn't matter cuz it's really smart. gluten flour and they are a hyper militant vegan. They like the color white when it comes to food. You you can say like crazy stuff like this like all kinds of things.

9:59 Um and it will it will give you a decent recipe and this probably especially with the latest versions of GPT this will probably end up being pretty good if you were to cook it. Say this is like too long for example you can you can say something like okay that's too many ingredients whatever and then it will it will simplify it a bit for you can pretty much change the way it communicates with you like you can say even if you're like learning English for the you know it's not your first language you can say [snorts] like u I'm ESL I'm an English second language learner whatever can you use a bit easier English for Okay.

10:45 And then it will it will do it right. And you can say like you know please put this in table format and make it easier to understand still and it will do it. This is called like prompt engineering uh where you you craft oh by the way okay the the thing that you send to chat GPT this message this is called a prompt and then prompt engineering is when you craft this message you send to GPT in a certain way where it you know in I don't I don't want to say entices but it gets GPT to respond to you in like a certain format like for example um our prompts resulted in like easier English, like a shorter recipe with less ingredients and then in table format basically.

11:33 So you can say things like you know explain photosynthesis in simple terms or like explain something in an easy to understand way. Explain like I'm five like explain how an uh atom bomb works as if I'm 3 years old. It's going to say something ridiculous. I don't know if a three-year-old can understand this, but you kind of like get the idea, right? And if you want to do something like really really specific, like you have a question about the law, you can say something like, "Okay, now you are a lawyer, whatever who specializes.

12:25 I'm spelling stuff wrong, but whatever. Specializes in uh whatever. I don't know if this is a thing. Housing law in Washington State. My landlord is not fixing the mold the mold for and weeks. Which RFC's are they violating? Can you can do something like this, right? And it has like a big big model, big brain model with like it's been trained on like pretty much everything on the internet basically. So it it pretty much like knows everything, right?

12:50 And then you can ask it stuff. You can give it context for like how you want it to think and how you want it to respond and you can ask it like all kinds of like arbitrary stuff like this. You can even say something like cuz it knows about the internet and it knows about like people on the internet and it can also search the internet. I think the free one can do this. I'm not really sure but you can say like um okay like I just bought a service from Josh Mator.

13:13 What are the chances that I'm left feeling disappointed? Please give me a straightforward answer based in reality. I don't know what this is going to say. I assume it's going to say something like good because uh I try not to make bad stuff. Well, if you don't know, then go out and search. Well, it did say something. Let me see. I don't have a specific personal personal knowledge reviews. It's telling me to like check reviews. Shut up.

13:59 You do it. It It can go out and do it for you. And it did. It checked like Reddit and apparently what else? Course report. Reddit YouTube course report. Uh, and it said based on the available information. Um, I'm not going to read this. I'm just going to include it in the dictionary in the video. I don't like reading like too many texts, but you kind of like can get the idea. Order the YouTube. Okay. Out of all the YouTubers which are most likely to scam you.

14:21 And sometimes um okay, I'll say order them 1 through 10. Sometimes it will answer stuff like this, but sometimes if it's like too unethical or like it's like I don't want to smear anyone, it it like won't answer, right? So, you can some kind of like you can sometimes bait it into answering stuff. Um, if you're trying to like you frame it in a certain way, like I'm trying to like figure out the best thing for my son to watch or something like this, you can bait it into doing stuff.

14:45 But basically, um, I just want to like introduce Chad DBT as a hyper smart, you know, super intelligent alien that will do all kinds of stuff. And you can, the more context you give it for what you want it to do, like the better an answer it's going to formulate for you. So, we're actually going to use this to help us with threat hunting, but we're not going to like paste stuff in here like this. We're going to use it programmatically on the back end.

15:31 So for example, what this look like, what this might look like is we're going to eventually say something like, you know, you are a cyber threat hunter. You are really smart and know everything, whatever. And then we can we're going to say something like uh I suspect X YZ might have happened, but I'm really not sure. And then we're going to say like here are the logs. And then we're going to send like uh you know a bunch of logs in here like ton of logs after this.

15:59 And then GPT is going to read this to get the context of like what we want to do. And then it's going to look at all the logs and it's going to take like you know a minute or 30 seconds or whatever to like analyze them in threat hunt. And it's going to come up with like a bunch of you know recommendations and stuff that it found. Basically is the idea of how we're going to use it.

16:21 It's not exactly like that. It's a bit more like fine-tuned and nuanced but that's the general idea. We're using this like magical blackbox hyper intelligent alien as GPT and then we're just like prompt engineering and crafting it and giving it perfect not perfect but really good context for what we want to do and then we're going to take the output and then do some kind of like actionable uh remediations with it like isolating VMs etc. So yeah let's chat GBT.

16:45 There's like there's like a lot that goes into this and there's a lot of videos on YouTube on like how to use it and stuff. But I just wanted to give this like brief introduction about it in case there was people who like didn't know what it is or didn't really know how to use it. But yeah, we will see you in the next video. Welcome to the AI sock analyst agent demo. I'm just going to kind of show you what it is right now and then give you a sense for what we're actually going to be building.

17:07 likely by the time you get to this, this thing is going to be built out even more. But I'm just going to show you the functionality as it is uh right now today. And again, this course is actually designed for people who are already inside the cyber range. Um so I'm going to reference stuff that they should know about already, but I'll kind of explain about it um as we go. But before we actually launch this, I just want to show you something really quick just so you have like context or some idea.

17:31 basically inside the cyber range um there's like a lot of traffic and a lot of like organic logs and stuff being created and there's a lot of different tables where the different logs are being stored. So for example like audit logs is like if you update an account in Azure active directory like you assign permissions to it delete it or something. Azure activities when you like create virtual machines or create or remove or delete any kind of resource in the portal.

17:54 Um, signin logs is when you like actually go to sign into Azure. All those kind of related activities get put in there. Cy log is like um Linux servers and stuff like this like Linux virtual machines, Ubuntu virtual machines and there's just a ton of different tables in here and they're all like filled with organic like actual traffic from users. There's about a thousand users on here and then a lot of the virtual machines and servers are intentionally exposed to the internet.

18:17 So they they get like a lot of organic uh attack traffic from malicious bots and bad actors. So I just want to like give you a sense for what uh is on the back end. And cyber range members of course you have like access to all this and this is what we're going to actually use to uh build our agent. So we need some kind of like logs to do analysis on. So uh getting right into the demonstration.

18:39 Um I'm not going to like explain all this code right now. All of this is something that's going to be covered eventually but I'm just going to do a quick demo for you. So, I'm going to run this. I'll just say start debugging. And you get like a message down here for what you want to do. And by the way, this can be made into a web UI, but I'm just using on the command line for now for sake of simplicity.

19:02 So, the agent that we're building, it's asking like um stock analyst at your service, what would you like to do? And you can say something like uh I saw on the news yesterday there was a there was a new utility for uh enumerating enumerating and gathering whatever gathering information from Azure tenants. Azure tenants this is just our cloud environment. Uh we are a bit worried that our environment might be compromised. Anything in the last day or so that you can find, please help ASAP.

19:52 You can The idea is you give it some kind of like human sentence like this. And then I'm just going to pause the code and then just run through it. Um I'm not going to let it just go. I'm just going to I'm just going to step through the code so we can kind of slowly see what the AI agent is doing. So it's right now it's looking at our English sentence and then it's using uh GPT endpoint to decide the log search parameters uh based on the user request.

20:17 So it's it's trying to figure out which tables we need to look in. So, for example, do we need to look in audit logs or like operation logs or SIS log or like where do we need to look uh where do we need to start our search and it finished. It decided it needs to look in the sign-in logs and it gave a time range of the last 36 hours and it's going to look at these fields specifically.

20:40 It decided all this based on our user input and the rationale for it. You can kind of read this the rationale for its decision hunting for potential Azure tenant enumeration uh via cloud signins and app uses and it says this table the sign in logs shows uh xyz blah blah blah. So that's why we're going to look there. So we can keep stepping through this. It built this KQL query. If you've gone through like the security operations course um this will make a lot of sense to you.

21:04 But I'll copy this for example. Now, if I go to log analytics, this is the query it made. So, if I search this, this should be like last 36 hours, but that's okay. It it's going to find a bunch of logs. It looks something like this. And then it's going to use these logs to do its threat hunting and analysis with it returned, 1167 records from the query. It's going to build threat hunting prompt instructions based on the logs it found.

21:31 going to select an adequate and appropriate model. It's going to count up the number of tokens. You'll learn what this means when we actually get into the course. Um because not every model can handle like you know they handle different number of tokens and data like if it's too much we have to use like a different model potentially. Uh agent determined that the token amount was safe. It's within the budget for GPT5. And then it's going to start the threat hunt.

21:54 I'll just press continue. And this is the part that is like 3 to 500 times faster than like a human sock analyst. So I'll let this go. I'll run this threat one more time or this threat hunt one more time but for like some other different scenario. But this time I'll just like let it go all the way through so you can like get a good sense for the speed of it. And while this while this is going u by the way like the Python courses like the fundamentals, the building blocks, etc.

22:16 All of those courses are designed to like help us make sense of all the stuff that's inside of here. And the whole goal of this is to give everyone a really good intuition how this works. And then my hope is that you'll be able to build on top of it and extend it like extend functionality and then be able to kind of do your own thing. Cuz if you really understand how this works and you're able to talk about it in interviews and articulate it like in your profile and stuff, you're going to be like way ahead of way ahead of the average person who just like went through Google Cyber Security or got security plus or something or like even the bachelor's degree, right?

22:40 like a traditional one. You're going to be able to like apply this kind of thing to the real world and like talk about it and it's going to it's going to look really really good. So, the threat hunt is happening right now. Usually, this takes like 1 to 2 minutes. So, it finished. I'll let this continue. It found uh it took about a minute and a about a minute and a half and it found three potential threats.

23:02 So, we'll press enter. I don't know what these are going to and then I paused the code at the very last end or the very last line. So we can kind of take a look at what these threats are. So first one likely account compromise sustained successful login from Kazakhstan with 10 account reconnaissance confidence level high and it kind of explains what it found in the actual this is a cyra user account like an actual one actual IP from Kazakhstan and it kind of explains what it found.

23:49 Uh it includes confidence level MITER attack information um which is tactics techniques and procedures. the very specific log lines that it thought the compromise that that it counted that it considered indicators of compromise. Um it has indicators of compromise here. This is probably a better word a better name for this is probably like malicious entities or something and then tags and recommendations create incident pivot monitor and then some more information. Then threat number two external Gmail account signins to Azure portal from Japan verify guest access.

24:12 This is interesting. Um, it categorized it as a medium. And this is actually me because I'm in Japan right now. I'm not in Fukuoka, but the ISP like probably is. But it just noticed something like interesting because it knows like the the tenant is a login Pacific tenant. Um, but it recognized me logging in from like outside of the US with a non-lo pacific account. So, it flagged it as medium. You can kind of read the through these uh description in the IOC's and stuff if you want.

24:35 Then the last one, uh, idol sign in from hosting VPN IP with multiple MFA challenges than success. So, you can kind of read about this. It just was probably something that it considered unusual of what happened. It's probably not malicious. I'd have to look into this more. Um, but yeah, it was able to like browse through all of those, create this report, um, and figure all this stuff out in like 2 and 1/2 minutes. And that's like significantly faster than a human, right?

25:20 So, I'll let this program finish. Uh, I'm going to run this again without debugging this time. I'll just like let it run all the way through. And then for my new prompt, maybe I'll say something like uh um I think um some maybe malicious traffic has gotten past the firewall today. at least, you know, the last 8 hours or so. I'm not really sure. I'm thinking this because uh an intern disabled some of the firewall rules.

25:46 I don't know. I'm just like literally making this up. So, if I say enter, it will take the prompt. will decide which logs to look for like which table to look at and which logs to pull usually takes a few seconds. It decided to look in the Azure networks analytics CL table the rationale it created a query it returned a lot of records and then actually um the er it had an error uh this is built into the program so this is like pretty good so basically like the agent saw that like oh the tokens the amount of logs that got returned is too much to feed into the chat GPT agent all at once because the estimated tokens is you know 345k where GPD5 can only handle 27 72,000 for example and then normally I would like build into this application or into the agent like oh if you exceed too many tokens that exceed what this model can

26:56 handle maybe use a different model right we can build that functionality in but instead I'm just going to like manually set the default model to GPT 4.1 um because I didn't build that into it yet so we'll just like run this we'll debug it again actually I'm going to take uh I'm going to take the same prompt So, and then I'll just like simply run this without debugging again. Same thing, but I switched the model to use GPT 4.1.

27:19 And you see how fast like GPT4.1 is uh compared to GPD5. It's GPT4.1 is like way faster and it can take more tokens, but I think it's analysis is a bit slower because it takes time to like, you know, quote make sure of its findings. So that's that's what's happening right now. So basically it chose this table to look based on my prompt of like you know the firewall rules being disabled chose this table created this this is the KQL it query it this is the KQL query it created so if we copy this for example we go to Azure we can search this and these are the logs that it's going to actually look at like these are like the firewall logs most flow destination IP source port the VM allowed inflows etc and it's going to analyze take all these and then see uh what I can figure out the GP GPT 4.1 selected calculating the tokens 300K out of a possible million so it's about like

28:28 you know a third of the max and then it took 40 only 40 seconds and it found three potential threats so we can say enter and we can look at the threats it found that was like it's really fast right so the first threat uh mass lateral movement and potential command and control exfiltration activity across multiple VMs. This is pro this is probably legit happening inside the cy range cuz it's designed to allow this kind of activity for exactly these scenarios where we can do threat hunts with it.

28:51 It talks about the MITER attack info, tactics, techniques, actual logs or some of the logs. There's like a lot. It says like hundreds of similar lines. Um how it discovered like how it came to the conclusion that this was a malicious activity. Um some of the entities involved in it. Um some tags. C2 means command and control um recommendations etc. Uh threat number two unusual denied flows to public IPs potential external communication attempts. So it found like a lot of probably a lot of blocked outbound flows.

29:16 I'm not sure. I'm not going to read all of this. You can you can read it if you want. And then third one uh confidence level high high volume of repeated SSH RDP and legacy protocol traffic. Um this is probably legit. It's probably either people trying to attack inbound or stuff that got breached inside of the cyber range trying to attack outbound. Um, I can spend more time to look at this if I want. This one's likely legit.

29:40 And then eventually uh this is relatively trivial to do um compared to the rest of it. But we can do things like we can put logic in our agent where like uh if the user query is about a specific virtual machine and there was findings and the confidence is high then we can like create a firewall rule uh isolate the virtual machine shut it down create a report like all this kind of stuff. That's where like the agentic part of agentic AI comes from.

30:05 Like it can actually take action based on the stuff that it found. And that's what we're going to build out and get into. And then again, my hope is people will get a sense for how this works and they'll be able to build out their own custom actions uh that their AI agent can do. But yeah, we'll see you in the next video. Welcome back. In this lesson, I just want to talk about the objective of the Python course.

30:28 So basically um the purpose of this course is I just wanted to help you to build your skill up enough to be able to recognize what some code does and then potentially like augment it and like edit it to get it to do uh what you want to do. I'm not trying to turn everybody into a bunch of like Google software engineers or anything like this. Um I just want you to like get your coding skill up enough to where you can recognize things and then you can understand the output that chat GPT gives you when you when it when you ask it stuff.

30:50 and then you can make the necessary changes to your code. Um, no doubt we're going to deep dive into all the code and I'm going to explain literally what everything does. But basically, these are these are the levels of coding uh in my opinion that people can be at. Um, like level zero up to three is kind of what I hope for for you guys watching this. So like level zero just means like no coding school, like literally zero knowledge.

31:13 Like imagine like your great grammar or something like this has like literally no idea. And then level one is code literacy. Like you can kind of read and understand what basic code does. You can figure it out like maybe just by by looking at it. Um level two is code modification. Like you can modify an exist an existing script to fit your needs. Like for example maybe you want to use like you know GPT model like 5.0 instead of 4.1 or GP5 I guess it's called instead of 4.1.

32:01 You can be like okay like I found it. I'm going to like adjust it and then make it work. And then level three is basic coding where you can write relatively like simple code um from scratch and you can automate everyday tasks and you don't have to rely on like GPT for those basic things like loops and conditionals and flow control and stuff like this. If you can get to level three um from the following lessons, that's like more than enough to be to do like, you know, pretty decent and produce something of value, right?

32:23 Especially when it comes to like doing interviews and like creating a nice portfolio and stuff. And the higher level your coding is, the more you're going to be able to leverage GPT. So, this makes sense, right? Somebody who has like level zero coding, they can type something into GPT like make a web page for me and it it will make it, right? but the person doesn't know like they don't know how how to like extend it or edit it or like literally do anything.

32:46 And like the higher you go down this like guess skills list toward level seven like the more useful GPT is going to be for you in terms of like generating code and like being being able to edit it and um identify when GPT like messes up. So your goal is to get to level three. Um, don't as we're going through the tutorials and stuff, don't feel bad if you're like there's no way I could produce this on my own.

33:11 Like you're that's not the goal. Um, right? The goal is to like at least get to level three. You have like a basic understanding. You can write basic stuff on your own. And then when GPT produces something, at least you have enough like knowledge to be able to like kind of identify it and ask the right questions. And coding is just basically like moving around data. It's just like creating, reading, updating, and like deleting or getting rid of stuff.

33:35 You don't have to think about it like in too much depth. It's just moving around data to to do what you want to do from like a business standpoint or like, you know, whatever it is you're trying to do. And I don't want you to like uh get stressed out and try to memorize syntax and like memorize stuff. That's a good way to like stress yourself out. And cuz I I don't memorize anything, but you you will accidentally memorize stuff if you do it enough.

33:59 But the goal is to try to understand what's going on and understand the logic behind the code and I'll try to do a really good job of explaining it and like stepping through the code and everything. So don't worry about it too much. Just work on understanding and just try to understand what we're talking about. And yeah, nobody nobody knows everything, right? I don't I don't know like hardly anything to be honest. I'm like comfortable enough to know that I can figure stuff out.

34:24 So I I just kind of hope other people can get to that level. And you'll likely feel overwhelmed at some point. Um because it's like it is a lot. But it's not like the more you practice, the dumber you're going to get. This doesn't make sense, right? Like the more you expose yourself to it with intent and the more you focus and just the more time and effort you spend on it, you it's just going to make you that much better over time.

34:46 And everyone struggles with coding. Like everyone does. Like even me, I quit compsite the first time I was in it. But just I didn't have like the tools and mindset I have today. So just don't give up and leverage the forum like the community section a lot. Uh leverage chat GPT and just keep trying and you you'll come out better. You'll come out uh better for it. And yeah, finally I just want to say like leverage the community heav he heavily like if you're in the cyber range or cyber community um go to like the community section and make posts and then if you want me to see it just like tag me.

35:09 Um don't DM me directly about code. I I literally like know if not to be like mean or anything but I won't answer it if you DM me about code because it's not scalable and a lot of people are going to be like asking questions. So please use the community cuz when you do that it will give you like reputation points and it will give other people like a chance to understand what's going on and like answer questions um because there's that internship component, right?

35:33 If you provide technical help or a technical solution, you can get points for it if you're doing the internship. So um use the community a lot. Don't DM me about code. Um, just you can DM me still, like DM me. Um, but just make sure it's about stuff that's like, you know, it can't be answered in the community. It's like something specific to me. Um, yeah, I hope to get to the point eventually where I can just go to the community and just like spend a long like block of time answering questions.

35:57 Um, but if it's not me, like somebody else will will get to it eventually. But yeah, um, don't stress out. Remember, we're just