[Josh Ragland]

When you have the offensive knowledge, you're going to automatically go to the points of initial entry and you're not going to do like 10,000 steps and a checklist to determine something in an investigation. What you are going to do is you're going to look directly at indicators of compromise and you're going to automatically know that this is the way some people and attackers should get in and nine times out of ten you bust down triage time and investigations and sometimes that would actually lead you hours ahead of forensics teams if you're able to catch it in time or if you know what behaviors you're you're looking at.

[Kyser Clark]

Welcome to the Hacker's Cache, the show that decrypts the secrets of cybersecurity one byte at a time. I'm your host Kyser Clark and today we have a returning guest Josh Ragland, if you missed his first appearance. Josh is an OSCP certified cybersecurity analyst with a serious foundation in programming, networking, and blue team operations.

He competed in CTFs, worked in SOC environments, and built hands-on skills with tools like Splunk, Carbon Black, and CrowdStrike. He takes pride in bringing an offensive mindset to defensive security and if you're wondering what episode he was on, previously it was episode number one, do not confuse that with episode zero. So if you want to go back and listen to that, feel free to, but not required to enjoy this episode.

So Josh, thank you so much for coming back on the show. What have you been up to since the last time he was on the show?

[Josh Ragland]

Well thank you for all of that and thank you for inviting me again. I basically just been dabbling in a little bit of everything, working on typical work stuff and reading a ton of books. I decided to return to C programming and I wanted to get more into assembly because I think it's the base foundation of what not only every programmer should know, but at least every red team tool builder.

[Kyser Clark]

Yeah, assembly is, it's from my understanding, super hard to understand and like I looked at assembly and like I haven't touched it and I'm like, I'm like intimidated by any wisdom for anybody that wants to get into assembly. Like any pieces of advice?

[Josh Ragland]

Put your helmet on, I guess for the first part, but I mean after a while it's very, very, very minuscule. Like machine language assembly is something that goes out under the hood. The high level languages help translate into so anything as simple as like, you know, conditions they get put into comparison operators, jump and compare and things of that sort.

So you really start to understand the mechanics on how computers process it and when you get deeper into it with the binary, you learn how the electricity that's running through the computer system starts building up bits and pieces of the data and it's as simple as on and off. It like, it gets really, really, really intricate with things and I think that learning high level languages first before jumping into assembly would probably fare better for people that are newcomers, but for people that already know the languages you probably might as well just put your helmet on and jump right in.

[Kyser Clark]

Yeah, I mean that's the advice for anything I would say. Like if you want to learn something just go in headfirst and just get after it. I like, I like to find a course like a, I'm a, I'm a course kind of person.

I don't really like to go through all the free resources because I like that structured learning, but for me it's like usually I just go get a course and just dive right in for, for learning new topics or grab a book. I like to grab books too. I usually do a video course in a book.

So with assembly, or so other than assembly, you've been working on a lot of other stuff. What has been your primary focus? What's had your most attention?

[Josh Ragland]

So when I started messing around with assembly and I started learning how the electrical components were getting converted into data, I started getting a little bit more into hardware, which is why I had built the PC that I have over there that runs two graphics cards and it is NVIDIA 5060Ti's. I'm running dual on an 870E board, which is a Tomahawk. And I have, I was actually able to get bare metal Kali running on it without a lot of the support that it should have had.

So it was not very easy to get the CUDA cores and everything running, but I had built a hash cracking machine and started getting more into, you know, the C language because I wanted to interface with the difference in devices and things of that sort. So it's just, I got a lot going on and I try to rotate through things a couple hours here, a couple hours there, because if you just dive deep into one thing for so long, you know, you'll get burnt out on it.

[Kyser Clark]

Yeah, I, you know, that was actually gonna be my next question is like, what's your take on, you know, spreading your, your attention across a few different learning areas or focusing on one? Me, I'm under the opinion, so I have a little bit different opinion than you. I like to focus on one thing as like the primary thing and maybe add like one thing on the side to like, like you said, help with the burnout or maybe an auxiliary learning.

Like, for example, like when I went through OSCP, like it was only OSCP. When I went through OSWA, well, pretty much any offsets are like, it better only be offset. Otherwise, in my opinion, it's going to make it harder.

And that's one of the reasons why I failed OSWA four times, because I was trying to do content, I was moving, I went through a breakup, like I was doing all this other stuff while studying for OSWA. And that's one of the reasons why I failed it three times, I didn't fail four times, I failed it three times past my fourth try. But you know, when I when I finally sat down and like really focused only on OSWA, OSWA, like that's what made me pass.

But I mean, everyone's different. So if you're different, that's fine if you're listening or watching the show. But just know that, you know, I actually recently did a newsletter, and I pretty much called it a hack yourself.

And basically, just learn how you learn, right? Everyone's different, everyone's got different ways of focusing on and prioritizing what's important to them. So do you have any additional wisdom there, Josh?

[Josh Ragland]

Yeah, so basically what you're just touching upon, so when you're talking about learning different things, it's not wise to say, do something like, say, I'm going to do Mellow Dev Academy, and then I'm going to do the CRTO. Some in some cases, in some modules, they might actually overlap, but the learning experience is kind of a little weird, or, you know, you're learning programming, and you're trying to do something that's the total opposite. What I do when I'm learning different things, like C and assembly, they actually go together.

Most of the droppers and executables that are out in the wild, they're going to be either written heavy duty, heavy duty in C, and be able to drop assembly instructions through whatever. So you're working with raw memory addresses, and you have a lot more access to the system than you would have with, say, something like Python or similar languages, because of the fact how you got layered security in the Blue Team Defender, MSI bypasses for PowerShell, different types of ways that loaders work. So even though that they're different things, they all end up making the same pictures.

It's like, you know, math and science are different, but they both can go together. You can use math to figure out the science, or vice versa. So it's, I guess, you choose what you should look at what your end goal is, and then you should see what complements each other, and pair them together in order to have a faster learning experience.

Like, I haven't been able to make it through certifications and do the stuff that I want, because, you know, overworking and being sidetracked with typical family stuff and things of that sort, I don't want, I don't have the time to put into what I want to. But when I went to school, I took four classes at a time, and I strategically overlapped them over multiple degrees, to where I completed more degrees in a shorter time. And at the same time, I retained at least 85% of the knowledge that I had went through and discarded the rest that didn't work.

[Kyser Clark]

Before we dive further in the show, we need to do Security Mad Libs. So a little bit different than last time you was on Josh, we have the basically fill in blank questions. So I'm gonna ask you, I want to speak a sentence.

And then you just first thing comes in your mind. At the end of the sentence, you just say you will have 40 seconds to answer five questions. If you answer all five questions within 40 seconds, you get a bonus, six security Mad Lib, not related to cybersecurity.

So are you ready? I gave it my best shot.

[Josh Ragland]

Josh, the most fun I've ever had hacking was when the most fun I ever had hacking was when I discovered on the OSCP lab and how it was set up.

[Kyser Clark]

You're not a real hacker until you've Oh, those are some dangerous ones.

[Josh Ragland]

But you're not a real hacker unless you actually own something.

[Kyser Clark]

The worst breach I've seen was caused by I'd have to say Conti.

[Josh Ragland]

The one tool I use that no one ever talks about is one tool I use that nobody ever talks about is abuse IPDB.

[Kyser Clark]

The first thing I check after getting a shell is who am I? Good answers. You ran out of time.

That was about 53 seconds. But yeah, over 40. So you don't get the bonus question.

But I appreciate your responses. And yeah, some of those are hard. So don't even worry about your most interesting response out of all those, I would say the most fun I ever had hacking was when OSCP labs.

So why OSCP labs?

[Josh Ragland]

Because it was more or less like a realistic environment to where you're not going to go to prison for abusing out of everything. But you know, I mean, yeah, safe place to actually learn and practice something. And the old lab had three different subnets.

So you had the one you started out on the IT and admin subnets and you really actually hit the tunnel and pivot through there. And it was a nightmare that actually took me like 42 days to actually complete that whole lab. And in that lab itself is, I guess, similar to a lot of the pro labs that you find on hack the box, but it was a lot bigger.

There were like 66 machines in that lab.

[Kyser Clark]

Yeah, I agree. So that's actually my I would say that would be my most fun as well. And I, I did the old labs and the new labs.

Actually, I was in the middle of the transition transition. So I completed like, I think 17 of the old labs and like 23 of the new labs. So a little bit more on the new labs and old labs.

But yeah, I was in the old labs and in a transition to the new labs. So I got to see both.

[Josh Ragland]

You didn't get to see how some of that stuff was very, very unique. I won't dig too deep into it because I don't want to make offset angry, but there were fishing scenarios in there and you, and it was like a maze. So you had to go through all these different machines.

And you had, it was like you had to find keys and bits and pieces everywhere. So if your post exploitation was weak, you weren't going to go nowhere. So it was like that, that was a really interesting lab.

And if I could do it all over again, I would do it all over again. I just wish that they made their labs more like they did that one.

[Kyser Clark]

Yeah. So, I mean, you got a little, you got a little bit of a opposing opinion. You like the old labs more than like the new labs, I suppose.

I mean, you never did the new labs, but like, like you've heard about the new labs and you know of them and about them. Me, I actually like the new labs more because I didn't like, uh, I like having my own private lab. Like the old lab is like you have shared machines.

And like, if someone crashes the machine, then like while you're on it, it crashes. Or like someone reverse machine while you're on it, like you're just toast. And you said, you told me one time, or maybe you made a post about it, but I remember you saying one time, you're like, that's what makes you good because you have to be fast at the exploitation.

[Josh Ragland]

And you're constantly redoing everything. And see it, not only that, when you were in that shared lab, say you got bored and you wanted someone to tag along and you could sit there and ask that, ask a buddy or something that, you know, is on this, on the same subnet. Cause they give you a group of people and stuff.

You can actually red team it. It's like, here, I'll get in the machine. I'll throw you a show.

Let's do this stuff. It was like, you know, it was an interesting interaction with the way it was and the way that everything was connected together. But it was funny when I would sit there and sometimes put up my HTTP server and I get a hit where it was like, well, what, what machine is that, bro?

That's funny. It was funny too, but it was an interesting, really, it was a really interesting time. And I would never, how do you put it?

I wouldn't change a thing about it. That's why I, but I do like that. I still like that experience way better than what Hack the Box has to offer.

[Kyser Clark]

Makes sense. Yeah. I haven't done a pro lab yet, so I can't, can't really compare, but I heard the pros get out.

We've had other guests on the shows. So high, high regards to the pro labs.

[Josh Ragland]

I really, I haven't really had the time to sit down and play with that. I, but I know I did start Dante at least once and then it meant it reminded me of the OSCP stuff. And then I just, I didn't have the time to finish it.

It was actually pretty nice. It reminded me of that in a way, but I haven't checked out the other ones. A lot of people are saying that they're like really, really hard.

And it's like, I want to see eventually, but up-to-date stuff, Hack the Box, I'd have to go with.

[Kyser Clark]

Last time he was on a show, you mentioned that a red team mindset gives you an edge on blue team tasks like triage and detection. Can you walk us through a real world scenario where offensive knowledge helped you catch something others missed or where you built detections around behaviors most analysts wouldn't recognize?

[Josh Ragland]

Okay. So normally the first thing that you want to do is you're going to pull out the MITRE map. And when you look at MITRE, the first thing you got is normally initial access.

So within this initial access, you only got so much stuff that an attacker can do. They're going to fish you. They're going to look for internet facing like appliances, devices, things of that sort.

They're going to run the full methodology through it to see if it's vulnerable. If not, they're going to keep moving on and moving on. So having an attacker's mindset shows that, all right, so when you feel like there's something wrong or something's not behaving right, the first thing you're going to do is you're going to backtrack and trace it.

You're going to run it across that. You're going to see what users affected, what behaviors are going on, what processes are firing. And to make the job a lot more simple, all you really have to do is look at execution and you look at the processes.

If you have the process logs and that, as well as the user source IP address from where they're logged in at or where this behavior is coming from. So when you have the offensive knowledge, you're going to automatically go to the points of initial entry and you're not going to do like 10,000 steps and a checklist to determine something in an investigation. What you are going to do is you're going to look directly at indicators of compromise and you're going to automatically know that this is the way some people and attackers should get in.

And nine times out of 10, you bust down triage time and investigations. And sometimes that would actually lead you hours ahead of forensics teams if you're able to catch it in time or if you know what behaviors you're looking at. Because if you've got red team, you're already playing around with like capture the flags, different attacks.

So you're already doing these attacks. So if you're already doing these attacks, you should just be able to look at something and automatically know what's wrong.

[Kyser Clark]

Yeah, that makes sense. And I mean, I've, I've seen that a little bit. I haven't worked in the real world as a sock analyst, but I do like going through the, the Cisco Cyber Ops certification training and exam and going through the TriHack SAO one exam.

I did do the training. Well, I did some of the training, but not, not much, not all of it. And then doing that exam.

Yeah. Like I could see the alert and I'm like, Oh, that's a directory traversal. I'm just doing things out there.

I'm not saying that's on my exam or anything, but yeah, I would see attacks. I'm like, Oh, I've done this before. And that's what makes it easy for me to, it wasn't, I mean, I did fail the TriHack SAO one on my first try, but on the second try I passed it.

And the only reason why I failed was because of the reporting. It wasn't, I was actually pretty accurate with my, my triaging. So yeah, the, having that red team background or not red team pen testing background really helped me with, with that certification exam.

And I can see how it can a hundred percent correlate into the real world. Probably a little bit more difficult in real world because, you know, that's just an entry level exam, but yeah, that's really cool to hear. And I'm, yeah, I think anybody in this field, if you're on the blue side, learning a little bit about the red side is beneficial.

And if you're on the red side and learning about the blue side is also beneficial. So, you know, since you're a blue teamer with offensive training, how do you test detections or simulate realistic attacks internally, especially without the access to a full red team?

[Josh Ragland]

Okay. So what you would do is you have multiple free stuff. You have Caldera, you have Infection Monkey.

You got all these different types of things, such as Rapid 7. You got all these bone scanners and all this other stuff. So even if you don't have a red team, you can take different tools.

So if it was me personally, normally this is probably not how you do it in a corporate environment, but I would make me a garbage box. I'd open live samples and try to collect logs and the box would be isolated so that these are real events and sequences and leaves all kinds of different things. And I would at least have to analyze the different behaviors to see what triggers, what parts of the registry or even scheduled tasks or any of that kind of stuff.

If it's like based on malware, droppers, loaders, just Trojans, whatever you want, whatever you could think of ransomware. Ransomware is just an encryptor. It's that's garbageware, that's cheatware.

But you know what I mean? It's like you got to see the behaviors, you build the detections and then you test it. So you got C2 frameworks, you got simulator.

There's just all kinds of different things that are out there that you can do it without a red team. But the thing is the red team is always going to be the best. So is the pen testing.

But I still think that they should at least have a little bit more wiggle room on a lot of the rules of engagement. But take a look at that Caldera infection monkey. There are a couple other ones.

But. I mean, you got to run things to get logs and then you look at logs to build detections.

[Kyser Clark]

Yes. So speaking of C2 frameworks, what are some of the key takeaways you've had so far when it comes to building and evading detection with C2 infrastructure?

[Josh Ragland]

So. That one is an interesting question because a lot of the C2s that you have unless you get paid ones like Sliver should be decent. You know, Sliver is workable.

Cobalt strikes workable, but you're going to have to build COF and BOF files or whatever you want to call them. And all these different types of encryptors in order to be able to evade stuff, then it's it's like. It's a pain.

I haven't gotten to work on a lot of that stuff yet, but I do have a lot of the knowledge to tamper and play with things like bypassing AMSI, Defender, turning it off, like through some CRTP materials. They show you a little couple things in there. Then you got other stuff that shows you how to do stuff like Model Dev Academy and things of that sort.

But it starts requiring programming when you start getting to EDR evasion and all that. Because EDR, it hooks into a lot of the processes and different things that get loaded for in simpler terms. So that while it's monitoring it, if a program tries to tamper or inject into it, it's going to kill that process.

And then at the same time, it's going to create logs and set off alerts. So things get a little bit crazy when you get to the EDR evasion world.

[Kyser Clark]

Yeah. So when it comes to setting off alerts, you have a lot of experience as a seasoned Sock Analyst with Crosstrike, Splunk, and Carbon Black.

[Josh Ragland]

Carbon Black. And then, yeah. And then you got Sentinel-1 and a couple other things.

I worked with just about everything. I just, I did not feel like filling that out. You'd be sitting here reading for about 30 minutes.

Logarithm is a good one too.

[Kyser Clark]

So these platforms, while they have their place, there's no silver bullet in cybersecurity when it comes to detection and prevention. What are some of the limitations you've seen in these platforms when dealing with advanced or stealthy attacks and how do you get around that?

[Josh Ragland]

So a lot of the things is it's like this. So your setup is only going to be as good as your detections are. You got people that are making the detections, you have default detections, and that's just the basic on everything that's detectable.

So it's not so much as the product's fault. It's more or less the people that are working it because certain things you, so this is where red team, blue team, purple team comes in where you got to make both sides work together. Right?

So the red team is making all the noise running through their safe. They're not going to destroy your environment. So they're leaving logs, they're leaving traces, even if your detections don't pick them up.

So when they hand over the red team report, the blue team goes over it and they see everything that was done and everything that was did. So what you do is you give that to either the detections and engineers, or you have a dedicated person that's familiar with both sides that would translate that report into detections based on all the evidence and mess that was made or that wasn't made and all these other things. So that there's detections for the way that they got in the first time.

[Kyser Clark]

Going into a completely different topic here. So the last time he was on a show, you made a great point about drawing parallels between computing and biology. Do you think there is value across this dis-implicitory study like neuroscience, game theory, or even philosophy?

[Josh Ragland]

Yeah. So you go figure since you got four amino acids, right? A, C, D, and G.

Those four acids bind in consecutive pairs. So when you're looking at like the helix or whatever you want to call it, where it has a person's DNA sequencing, you'll notice that the bits or the sequencing is evened in a certain way where it shares similarities with bits and bytes and all that other structure and binary ones and zeros. So I think eventually that there will be some kind of integration between computing and biology, maybe not right now, but eventually there will be, because I'm pretty sure that there's someone in a lab at a black site right now, that's basically making their own organisms just by using genetic repeats and sequencing and just doing some weird crazy stuff with it.

I mean, it's simple stuff. They already have CRISPR-Cas9 to do editing. So why wouldn't they be able to just code up their organisms and spin it out of a computer already?

[Kyser Clark]

That's definitely an interesting point. And especially since, I mean, I don't know, maybe we're heading for like a cyberpunk future where we're all going to have cybernetics in us and it's like machine and man, this is going to be one. But I don't know, that might be a little off topic for the show, but I mean, that's definitely, like you said, I do feel like you're right.

It is probably going to start blending together biology and computing in the future.

[Josh Ragland]

I mean, it'll be to where people probably are going to end up living forever and you'll be sterile. You won't be able to have kids to keep from overpopulation. I forgot what movie that was off of where something similar happened, but.

[Kyser Clark]

I think I saw somewhere where it was like the person, the first person who gets to live forever is already alive today or something like that. Like it's kind of crazy to think about.

[Josh Ragland]

Yeah. I mean, there's a lot of crazy stuff that's out there that people aren't really touching on the topics, especially like the whole computing world where they're storing, what do you call it? I remember what it was.

I think they made a computer out of a brain or something grown in a petri dish or something like that. It was something crazy. And then they got quantum bits and they're storing things to where you get an extra third bit that's in the on and off stage.

So it's like taking that light switch and just putting it in the middle. They got weird stuff going on. I think people are focused on the wrong things at this point in time.

[Kyser Clark]

Yeah, maybe you might be right, but it's interesting nonetheless. So I'm going to ask you the final question a little early because I know you have a huge passion for what you're about to say. So I'm going to give you some extra time here to answer the final question.

And since you're a repeat guest, you're going to get a different final question than everybody else and what you had the first time around. So here is the final question. And like I said, go ahead and unpack this as much as you want.

So what's one key lesson you've learned recently in cybersecurity? Or if you'd prefer, what's a bold prediction you have about the future of this field?

[Josh Ragland]

Well, I think both of those questions are kind of important. So the one key lesson that I learned about cybersecurity is something that you need resilience for. And you need to have very, very strong resolve because this field will tear you apart.

But what I think the future is, well, I'm going to touch up on something that a lot of people are talking about now that don't understand what they're even talking about. So with the whole AI thing, I think the future of cybersecurity is going to start tanking downhill because a lot of companies are looking at automation through learning language models, replacing and throwing like employees out and stuff like that. So what you end up having is you have garbage LLMs that are trained by probably mediocre analysts that are running companies and that are causing a lot more damage than what they are.

There was an article on LinkedIn not too long ago where someone was talking about mass firing. I don't remember the company name, but they were training the AI from the analyst data. The AI got to where it could kind of outdo those analysts from their tasks.

And they fired a lot of the analysts thinking that they were going to save a lot of money. A couple months later, I think that they were hiring or wanting manual overview because they seemed that it wasn't ready type of deal. And the bad part about this LLM and AI stuff is none of this is true AI.

It's not artificial intelligence. It's pattern-based recognition based on interaction type deal LLM. Something that's what I was able to look at and what I played around with.

And it only is capable of doing what it learns. It has no capability of teaching itself. So that LLM is only going to be as good as the people that train it.

So when attackers do start hitting things, that LLM is not going to be able to tell benign activity from expected activity, which is networking and administrative tasks, as well as the rest of the environment. It's going to make, it's just going to flood false positives. Security posture is going to tank.

Everyone's going to go lazy because it's going to switch from learning skills yourself to learning how to use the AI. Instead of using the AI as a teaching tool, everyone's like leaning on it more towards a solution to a problem that it's not even ready to solve at this point. So I think because everything's being LLM or whatever learning language model, and everyone's pushing for it because they think that this is the newest thing.

And I see that the security stuff is going to be very, very, very bad in the future, especially with people that are going to start losing intelligence because of the reliance and not being able to learn things on their own.

[Kyser Clark]

Yeah, I mean, that's a good point. And that's something I mentioned on LinkedIn. I made a post, or I shared someone's post, reposted someone's post, my thoughts.

And, you know, there's a lot of people who are against AI and they are saying, hey, there, well, there was a study done. I forget where, who did it, but there's been probably actually multiple studies done that say like people who use large language models, their intelligence is actually decreasing. And there is evidence behind that, that backs it up.

And my opinion was, you know, I don't, I don't feel like my intelligence went down. I do think less because I can get the answers a lot faster. And I guess for me, like, I'm not concerned with memorizing everything, I guess.

I don't think it's a good use of time to memorize a million things. And if I can just get the answer by asking an LLM, then why not? Right.

I mean, if my intelligence goes down a little bit and my productivity and my efficiency goes up, I think for me, for me personally, that's a net win. But I can definitely see how it would lower your intelligence because like, you're definitely thinking a lot less, you're doing less research. Like when you, like back in the day, it's kind of crazy how I'm saying this back in the day, we used to Google stuff and you know, you'd have to like check out like five, six, seven, eight, nine, 10 different articles.

Sometimes, sometimes I'd go to 30, right. To get a good sample of articles. And now you can just ask LLM and it's just LLM right here.

For those who are on audio, he's, he's got a big book. What is that? C?

[Josh Ragland]

C primer plus.

[Kyser Clark]

What is C? What is that? Like what's.

[Josh Ragland]

That's for C. It takes you through the whole language where it's from beginning to end. Like what you were saying, we have to Google stuff.

So the LLM and yeah, the efficiency and productivity goes up, but it's like, I still use these.

[Kyser Clark]

Yeah. I mean, I like to read too. I for sure.

And I, there are stuff that I have, I got my bookshelf here. It's kind of off camera, but I got my bookshelf back there. And there's a lot of times where I just pull a book off the shelf and open it up.

And cause I know that what I learned a couple of years ago was in those books somewhere. And I I'll do the research real quick, but oftentimes it's faster to check chat GPT, but I still do occasionally pull out the books.

[Josh Ragland]

I use chat GPT for nonsense. It's hilarious. I mean, I, I, I don't, I use it for like troll stuff or just something to argue with because it's hilarious.

But I mean, yeah, like what I noticed, I was just trying to mess around with it because I keep seeing this annoying thing by the coding or something like that. I die laughing. So I try to make this thing, make me some code and it's broken.

I mean, this, it's like, it is so broken, like, but don't get me wrong. It'll spit out some pretty good stuff sometimes, but you got to be specific. So you got to literally know how to know what you're programming and put it in the right order and make it do the right things or whatever.

But you have to be very, very specific to get it to work. And that's, it's hilarious because even then it still comes out broken and you got to sit there and tear it apart, move some things around and fix it. Why do you want to go through all that when like that thing wants to give me like 50 extra lines of nonsense when I can do the same thing and like maybe 10, 15 lines of C.

I mean, it's like, I really hope that this isn't our future because if it is, we're screwed.

[Kyser Clark]

Interesting tape. Yeah. Well, you know, you might be right.

And, uh, it reminds me of the meme I reposted on LinkedIn. It was the, the scene for matrix versus the red pill or blue pill. And he has to pick one or the other.

And the, the caption, what the caption was, um, it had, uh, kind of reads as tech pros. It was like tech, it was like tech pros. And it's like the red pill means the AI is the future blue pill means it's going to destroy humanity.

And then it was like, did you just take both pills? It's like, yes, it is the future and it's going to ruin us at the same time. So, um, yeah, I think it's a pretty normal and pretty healthy to have both outlooks.

I'm an AI optimist, but at the same time, like I understand the risks and, uh, you know, I like to dabble in the doom and gloom. Sometimes, uh, I've definitely talked negative about AI in the past, like, Oh, it's going to take our jobs. If you're not careful, you know, I've definitely said stuff like that.

So yeah, it makes sense. So thanks for sharing those insights and, um, what to take and thanks for your bold predictions. And so where can the audience get you if they want to connect with you?

[Josh Ragland]

They can wherever LinkedIn, whatever they want to send me a message, whatever. Uh, I just hit accept on all the ads.

[Kyser Clark]

The link to his LinkedIn will be in the show notes, guys. Josh, thank you so much for being on the show. Thanks for returning.

And, uh, it's been, it's been a real treat having you again. So thank you so much for being here.

[Josh Ragland]

Not a problem. Anytime you need me, just let me know. I'll come jump on in and audience.

[Kyser Clark]

The best place to get ahold of me is the YouTube comments. So drop a comment and I will reply to you. So hopefully I see you in the comments and hopefully I'll see you in the next episode.

Until then, this is Kyser signing off.