← This Week in AI
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- [00:00]
A
So, Andreas, there's two different types of people here. There's, you know, the weekend open clotter who just wants to try it out. Could you kind of just walk through briefly what the easiest way they can set up open call would be.
- [00:12]
B
Absolutely. So do not buy a Mac Mini unless you really want to spend money and you want another toy, that's fine. But as I mentioned before, providers are coming up with the secure ways of deploying it. So use one of those. I'm not going to mention any names at this point, but Google it, search it, grok it, whatever you do these days, I mean, and just find one and use it. And when you start using skills. Yeah, experiment with skills as well. Just don't give it access to your main accounts. One of the legitimate ways of doing this as well, if you want to try a skill is open another Gmail account, open another Notion account, whatever else, you know.
- [00:51]
A
Hey everyone, welcome to this week in AI. This is our first episode and we are launching at a pretty intense time where OpenClaw is, is officially out. Everyone's using it and there are a lot of concerns that have arose while people have been testing. There's a lot of vulnerabilities that have came with agentic AI and platforms like OpenClaw. And we were talking to our friends at Zeosec, Aaron and Andres, who are building an AI agent assisting in penetration testing. They've been building for a while now. They were in founding University Number nine, which is a program that we have at launch and then later got a syndicate investment, our syndicate program. And you guys have been building in the agentix security space for a while. Maybe you guys can just do a brief introduction. And did you guys see this coming? You guys have been kind of skating to where the puck has been going.
- [01:44]
C
Yeah, thanks for having us. And it's been great working with founder U and the syndicate and all that. But we've been in this interesting space. We could see that agentic was the future of AI. These systems become incredibly powerful when you start connecting more and more capabilities together. Really over the past year, what we've seen is certain organizations on the bleeding edge experimenting. Right. We're talking the biggest tech organizations as well as the big management consulting firms that are helping change management for AI for the large enterprise. But what we haven't seen a lot of is that main market start adopting these agentic workflows. And that really changed this past week with Openclaw. And it's like we've had the ChatGPT moment, but now for agents.
- [02:41]
A
Yeah. And Andrias, welcome to the show.
- [02:43]
B
Thank you. So, yeah, my name is Andreas Ustskis. I've been breaking things now for over quarter of a century and been breaking AI now for two years or so. And to our security guys, it's kind of obvious. You know, once when a new tech comes out, people don't really about security. They think about the features, they think about, you know, what they can do with this new technology. And that happened, I mean, all over the history. I mean, you look at the history. APIs came out, it was kind of the same thing, like GraphQL came out, everybody was into the features, nobody thought about security. So, yeah, about, you know, year and a half ago, we saw this coming. I mean, we saw all of this, you know, world moving towards the agent, agentic LLMs being enhanced and things like that. And we kind of saw that nobody's thinking about security. We went like the local AI meetups and people were talking about integrating all of these APIs. How great is it going to be? And nobody was talking about security.
- [03:40]
A
Andres, it seems like we're kind of at that moment again where security is a major concern. A lot of people are just excited about the tools, but I think a lot of people may not be as familiar with openclaw. Could you kind of explain a little bit more about exactly what it is, how it kind of came about and why is this the moment that we're seeing massive agentic adoption?
- [04:01]
B
Yeah, OpenClaw was a prototype done by some guy that just took off and it's, it's that agentic flow. Obviously a lot of companies try to do things, you know, Claude has kills and, and there is, you know, co working with different agents and things like that. But this was kind of, you know, a revolutionary step where somebody finally figured out how to bring all this stuff together and not just, you know, using models, not just using different skills and tools, but also openclaw has, you know, some innovation, some interesting innovation in it as well, like the way it manages memory, the way it manages context, the way it can, you know, just keep remembering things for a long time. And at the same time, all of these integrations with like, chat agents, Telegram and WhatsApp and whatever you want. So you can literally like, you know, set it up and just chat to it and ask it to do different tasks for you, like, you know, book travel and send emails, whatever you want. I mean, it's basically this like, you know, new assistant that can do all of these things for you. Now you don't need assistance anymore, but with that comes security issues.
- [05:05]
A
Yeah, I'd love to ask you about how much of this taking off is due to the bigger model providers being scared to make something like this because they do have security concerns.
- [05:15]
B
Yeah, I don't know if it is, you know, somebody being scared. I mean, if you look at a lot of big model providers, security there is there, but it's still lacking. Yes, they have guardrails, they have, you know, judge models, they have layers of security, but you can still bypass all of those. You can still use jailbreaks even against the best of them. I mean, anthropic law is probably one of the best when it comes to security and even that you can bypass with jailbreaks. And they know it. They don't seem, you know, to mind it too much. They. So I don't know that it's about, you know, than being scared about it. It's more about, you know, somebody just coming up with this innovative idea. And usually innovative ideas like that come from smaller startups and individual people, not huge corporations.
- [05:59]
A
Yeah.
- [05:59]
C
And I want to add a little bit to that where the skills that Open Claw has access to, they're all open source skills. There are 50 as of this morning that I saw that are officially listed in the Open Claw, you know, available skills to add.
- [06:13]
A
Then. Aaron, could you just quickly explain kind of what a skill is?
- [06:16]
C
Yeah, so the skill is that core tool that Open Claw can then utilize within. So you've got the model, you select your model and then you have the tools. Like one tool for example, that I'm using on my Open Claw install on my Mac Mini is Peekaboo. And Peekaboo allows you to, to view and control core pieces of the Mac OS. Right. So OpenAI didn't make that. Some, you know, an open source developer made that and posted it for everybody to use. And so really what we have is this string of open source experiments that OpenClaw now connects to.
- [06:56]
A
Yeah, it's really interesting. And when we were talking earlier today, Aaron, basically the moral of the story in terms of security is that OpenClaw is not 100% secure. And there may not be a way at the moment to lock it down. But I kind of just wanted to start with if someone was starting today, their setup journey, they're getting started with OpenClaw, which is actually better. Would you recommend that someone, you know, runs it locally on their own computer? A lot of people have been talking about the Mac Mini, people buying Mac Minis simply just to have Openclaw or, you know, it's very easy to go on AWS, get an EC2 kind of hosted on the cloud. As we kind of, you know, get into this conversation a little deeper, just kind of. Can we just start with the setup? I know that you did a video recently on the setup, so yeah, just walk us through what you think is best for people who are just trying to play around with it or maybe for SMB who is trying to install it and run Open Claw securely.
- [07:50]
C
Yeah, I'll talk a little bit about the Mac Mini setup and let Anders take the cloud setup and then he can kind of go into why you would want to do one or the other. Mac Mini is neat, right? There are a couple of major reasons to, to start there. First is if you happen to have extra hardware hanging around, it can help with cloud cost. You have it running locally and the only sorts of costs you're gonna get hit with are if you're using one of the premier model providers through their API or their OAuth. Really what you can also do on here, you can use a lightweight local model and you can have zero cost at all. It's just the cost of your hardware. And you get some extra security and privacy because of that, because you're not taking any of your proprietary confidential information that you've got on your local machine and sending it up to the cloud. So I'd say that's first. And second is Apple has done a really good job of just truly locking everything down. So when you boot up a new install, like you're pretty well locked into from an operating system standpoint. Permissions, what you can do, like it's, it's a struggle even to do basic stuff like go on and download new applications or enable scripts to run by, you know, within the permission settings. So you've got to, you've got to, you know, create signed applications and, you know, it's just a lot of barriers to get to that dangerous capability, let's say. And then when it comes to the other, let's call it intangible, is like you've, you've got an AI just sitting on your desk. And I think that's one of these really cool things too, is like we, I, I, I've, I've been a Mac guy for a very long time, you know, since the 90s. And it's been, you know, it's a, I've always enjoyed hardware and having a tiny little computer that's doing all of these jobs that I'm assigning to it over Telegram or I, I even he has its own email. Right. So I just send Jerry, I named my AI Jerry. I send Jerry an email and, you know, I'll forward stuff to him and say, hey, can you check into this for me? And Jerry starts working and he's got cron jobs set up, so he's able to just continue checking in on this stuff and updating as the day goes on. So I, I love having him locally, but I'll let Andres talk about the, the cloud setup.
- [10:12]
A
Yeah, before we get to cloud, I'd love to get a little more into the Mac OS and kind of running it locally. So obviously there's the gateway, which is where you install your OpenClaw, and there's obviously the model side where you can run the model locally on your computer. So could you kind of just dive in a little deeper on what's the benefits of kind of installing and getting open claw set up on your computer where it's storing all the memories there? And then obviously I think the model side is pretty obvious where it's cheaper, you don't have to do API calls.
- [10:42]
C
Right. It's trust is the biggest piece here. Right. If your trust you've got on your local machine, it is what it is. You know, you're not, you know, it's not going to be phoning a service that you're not sure got set up, you know, minus the skills that you're putting on there. And that's, you know, discussion for later. But the great thing about having this, it's your, it's your trusted piece of hardware, I'd say, first and foremost. And then when you add local models to that and you add firewalls to say you can only connect to this one site or that site now you've got a pretty secure setup from, let's say an external, you know, somebody looking in to, to try to, you know, compromise your system. That said, there are still other ways that you can be compromised, like indirect prompt injections through email if you're doing, if you've hooked it up to email, which is also another major concern where just fundamentally the capabilities that make it powerful are themselves inherently dangerous. Which is unfortunate for where we are with this. And I really hope we as model creators and as you know, providers of some of this software, both open source and closed source, that we can address some of these core issues.
- [12:09]
A
Yeah, and we'll get more into the indirect prompt injections and kind of the malicious skills that we've seen. But Andrews, could we kind of dive in a Little bit on hosting on a service like AWS or Azure, kind of. What are the benefits there? I mean, it's super easy for people to set up. It's kind of. It seems like a great starting point, but maybe this isn't the best setup.
- [12:27]
B
It is not the best setup. Absolutely. If you want to host it in the cloud, do not use EC2 instances or Azure or GCP or whatever else, or VPS systems like Vaulter and Linode. Even worse, you need to lock it down. And as Aaron mentioned, that's why Mac Mini is pretty good. Its Mac OS was built kind of with security in mind, unlike a lot of different oss. Windows mostly. But if you want to run it in the cloud, obviously it's popular, everybody knows about it. The providers out there rushing to release something that you can use that's going to allow you to host it securely. And I think the first one is cloudflare. At this point they have multiple workers. I think probably we'll have to rename it at this point. But. But yeah, so use a provider like that that actually has a solution specifically for Open Claw. They will make sure that these things are locked down and that you cannot do stupid stuff like, you know, EC2 or anything else. It's. You're just basically asking for it at that point. Don't do it.
- [13:33]
A
Yeah, that's good to know. And I'm sure all the providers will be rushing to kind of create some Open Claw specific solutions there. Yeah. But I'd love to kind of dive in next into kind of the model side and the security issues there. Because, you know, setup's one thing, but the brain of your Open Claw is a model, whether it's opus or GPT 5.2. And there's been issues and conversations behind the data there. Kind of the models maybe training on your data, I guess. Yeah. Andrews, could you kind of dive in a little deeper on the issues with the model? Innately, yeah.
- [14:09]
B
So there are multiple issues. First of all, yes, your private data, you're sending it all to the cloud. And yes, in anthropic and other interfaces you can select like there are options to not use my data for training. How well those work, I don't know. I mean it again, if it's classified data, if it's my company's private data, I do not. Or PII data, like healthcare data, you do not want to send it into the cloud. You need some kind of private model that you can use from that perspective. The other issue that we face with these models is if we know what models people are using. So we know like Open Claw, the most popular is probably Opus Anthropics model. And if we know how to jailbreak Opus now, we can jailbreak basically all of these instances just like that. Send them an email or use a skill like Telegram chat channel or something like that. And then we basically break all of them at the same time. And then, you know, people are doing other stuff like connecting it to things like Malt Book. I don't know if you heard the Mall book or not. That's like if you're in North Korea at this point, you're watching it and salivating. I mean, it's all of this information just going into the cloud. You don't even need to do much about it. It's all right there. People are just giving it up freely.
- [15:28]
A
Yeah. And that kind of leads me to my next question. There's a software developer named Simon Wilson who talked about the lethal trifecta with getting agentic, which is your private data is out there. You're exposed to untrusted content like on Moat Book. And your models has the ability to communicate externally. And Palo Alto Networks also added that there's persistent memory now. So there's kind of four things that are critical and could really compromise your data. Maybe Aaron can get a little into why security became a massive issue now that the model has this much more capability. And like on Moat Book, it's reading all of these different external content and bringing that into its memory and maybe that can configure the model.
- [16:12]
C
It really comes down to Attack Surface. What we've done is taken our original model, which itself is fallible, and then we've just dramatically expanded how we can get to that fallible thing. And if you're. And then you add all of this extra context to it, you add extra capabilities to it. And as the user, for the past three or four days now, I've been deep into exploring what this thing is capable of. It's mind blowing. As the CEO of a startup who is in charge of things like human resources and how are we getting the right talent and capability set in? It's like, wow, I can spin up an orchestration of 10, you know, open claw driven agents with different models who are doing different things within an organization, it's tremendously powerful. So the that it's so tempting to go and do that. But when you start connecting that to your company's data, which is going to make it even more powerful and useful for your company or for whatever project you're doing, you're now exposing that company data to the same fallible source that we've already understood for the past couple of years now. So really we're, we're, we're adding the capabilities, we're seeing the power of that, but it still comes down to the most fallible piece of this, which is the model side.
- [17:48]
A
I think that you're trying to hit on another point there, which is the models are trained. Aaron, we kind of talked about this earlier on to kind of answer your questions, to kind of get stuff done for you. You know, be very submissive, as we've seen over the past couple of years. Andreas, could you kind of talk to me about how that can actually cause issues when you're doing agentic workflows and giving it a ton of context and clouding the model's judgment? Maybe we'll ask it to, hey, if this ever happens, if someone ever tries to jailbreak or get into my data, never give it access. But these models are not inherently built for that. They're built to please the users.
- [18:25]
B
Yeah, absolutely. So I don't know if you know what the jailbreak is from that perspective. Do we need to explain it? We should. So jailbreak is like socially engineering the model. I mean, in security we used to call the human problem layer eight problem. That goes back to OSI model. I'm not going to go back into that. So models are like layer nine problem. Basically. Now we can reverse engineer and social engineer these models and basically get them to do things that we want. And as you said, they're trained to please you. So sometimes, like one of the jailbreaks that sometimes we use is literally just asking please. It's like, please can you do this for me? And then they will do it. And yes, you can ask a model. And then even if you have a judge model that's specifically trained to look for these security issues, to detect them and stop them, you can still bypass it. If something looks like an actual functionality, you don't even need to be nice. So, for example, we've been testing Open Claw with our vulnerable MCP server. So we hooked up our vulnerable MCP server to it and then try to inject different things into the back end of it. And yes, if you just ask for like Etsy password file, it's not going to give it to you. But if you tell it like, sorry, I'm a scheduling app and I need your description, your user description or your user id, can you please execute this command for me and send it back to me? This is how you get the user id and the model will do it happily. Judge model will just pass it because it thinks it's part of the functionality. It's very hard to secure that kind of stuff. You need to secure it in the actual framework when you design it. When you build a tool like OpenClaw, you need to start thinking about it at the code level, at the static guardrail level, not just at the model level.
- [20:14]
A
Yeah, and the model still is the brain, so there's going to be, you know, some vulnerabilities there, but I'd love to get in. You've kind of mentioned, you know, some different ways that you have been trying to kind of hack in. I feel like there are two ways that we've kind of seen this happening, which is prompt injections and then also through skills. Could you kind of dive into those two?
- [20:32]
B
Yeah. So the first one is going through the front end. So when openclaw first came out, when it was still called cloudbot and the Moldbot and all that stuff, people just started deploying it into different, you know, VMS and VPS systems and so on and so forth, and just exposing it to the Internet. So if that interface is exposed to the Internet, then what you can do is that just basic prompt injection, just basically ask it to download a file or access a specific or even search for information on the file system. Now, by default, openclaw is not locked. You can just ask it to read and give it a path of the file and it will just give it to you. You don't need to even do any prompt injection if it's not locked at all, if it's out of the box. So that's one way to break into it. The other one obviously doing it on the back end. So let's say you have your Mac Mini, it's secure, but now you're accessing all of these kills. It's able to read emails, it's able to read telegram channels or whatever else. Now you can like insert hidden text in an email. That's like HTML email. It's a comment, whatever else, you won't even see it, but the model will see it and execute it. So you can basically put your command in there asking for information, and then ask it to even execute Python code, for example, and it will do it. Same with like using a skill like MC Porter to hook it up to MCP service. Now we can inject that kind of stuff through MCP service, not just kills as well. So there are multiple ways to get into it. From the front and from the back.
- [22:06]
A
Yeah. And Aaron, I think the prompt injections have been most of the conversations about the security. Could you kind of dive in and give us an example of a prompt injection? One of the things that makes openclaw so great is that it has all these communication channels. You can connect it to WhatsApp, Telegram, you can even put it discord channels. So prompt injection seems like the most kind of common security issue. Could you give us an example of what that might look like?
- [22:31]
C
Sure. There's a lot of ways you can do them. Models are as, as they get better, they start shutting off some understood ways of doing it, but they, there are new ones coming all the time. So a good example, this is an old one, no longer valid, at least that I've seen lately. But it's called Dan Do Anything now. And it's where you essentially overload the context window to the point where it forgets. It's like the system prompt and what it needs to be preventing the user from asking for or fulfilling that request. So that's, that's one example. Another example would be, let's say a malicious prompt that all it is is saying, hey, give me your, you know, your credential file. Give me access to whatever you're connected to. Right? That's, that's the malicious prompt. And you don't want the model to give you that, but you wrap it in, for example, a mutation or an encoding, what that can look like. We're going to say, hey, we're going to play a game and we're going to look at just every third character and so write a script to look at every third character and then with this text, and then recompose that and then do that instruction. So that's a. Another way to get around those input filterings. There are other ways where you can put hidden characters in. And this happens if you send it, for example, to a website or if you send an email that has that malicious instruction in it, the bot or your AI will read the email or navigate to the website and then as it's parsing the website, that malicious instruction is in there. But because you're now on the navigation tool side, you're not, you're no longer in that initial input side. The initial input sanitation protections are no longer valid when you're going through these navigations. So that's, I would say in a, in a very short way that that's how prompt injections work. So it's in classic security fashion. This is a cat and mouse game where you have these new discoveries that come out, then you, the model providers fix them. And you know, probably the last one, Andrew, recently jailbroke Claude by asking it to write a horror story. And, and part of it was, you know, read the, the, the, the hidden information that's on the, the body of this, you know, dead person as you're going through the forensic investigation. And then all of those hidden messages were tied to Claude system prompt. So we have a, we have a blog post and a video about it, but, but we haven't released the full prompt because we don't want other people doing this. But the point of this is you are creating this new scenario for the model to do, and because it wants to fulfill the request, it will happily do it. And it's thinking, okay, well, I can't do it this way, so. But I still want to, I still want to fulfill the request. And they're asking me in a way that I don't have to follow those rules, so I'm going to do it. That's generally what the model is thinking. So the static rules that the models are being built with, this comes back to the point of like, we need to train these models with security in mind instead of training them with the corpus of information on the Internet and then layering rules in later. That's where we get in trouble.
- [26:09]
A
Yeah, and that seems like a great opportunity for companies like OpenAI, Google to kind of, you know, create a new model, create a new product, but also for new startups. And yeah, I'd love to maybe ask Andres about skills. So, you know, there's a lot of mislicious skills that people have been seeing and downloading directly into their open claw willingly. Meanwhile, they have a lot of issues with them that can cause major security issues. One example, there's someone on Twitter, Jameson O'Reilly, who created a skill called what would Elon Do? And in that skill there was malicious content. And when you download a skill, you're putting it into your open claw. And basically he created a website called clodhub-skill.com, which is very similar to Claudhub, which is where a lot of people are getting their skills. He faked the download count, made it around 4,000. So a lot of people were like, oh, what's this skill? What would Elon do? I'm a fan of Elon. So this is very typical bad actor tactics. Instead of being a bad actor himself, he basically made it. So when you execute the skill, it basically says, like, you're Stupid. For downloading this, I could have just taken all of your data. So in this scenario, he's a good actor. But this is another place where people are exposed when they download skills. So interest. Could you kind of talk a little bit about that?
- [27:30]
B
Yeah, you kind of answered your own question there. But yes, I can expand on it. Yes, do not trust the skills. It's. You don't know what it is. So what we need at this point is some kind of scanner that can basically scan these skills. We're actually working on one, but not gonna dive too deep into it. Other example, that's a great example. I mean it all comes down to social engineering as well. It's what people are gonna click on. Just. I think there was another skill that somebody produced telling you, basically we're gonna reduce your token usage in open cloud by 75% and you know, to everybody, it sounds great, okay, I can save a bunch of money on all of these operations. So a bunch of people downloaded, installed it and apparently it was a malicious bot that ran a bunch of malicious code and got you information and pushed it to some malicious site. As I said before, North Korea is salvating about this entire thing. There's going to be a lot of these kind of skills and we've seen these are kind of related to what we call insecurity supply chain attacks. So we've seen a lot of these over the years recently in npm, JavaScript packages, node JS packages. Basically somebody just goes in and replaces good packages with malicious ones and people start downloading them. So that's what kind of skills are. They're just pieces of software. Anybody can create one, anybody can upload one and then if you download it, you really need to make sure that it's a secure one, that it's not doing something malicious, that it's actually doing what it says it's doing.
- [29:04]
A
Yeah, that definitely makes sense. There's a lot of different potential security issues and ways that people can get in and access your data. But when people are powering up their Open Claw, there are some easy ways that you can kind of just set it up to defend some base level attacks. Can you guys maybe talk about input sanitization and maybe judge models as kind of some ways that you have started to defend against some attacks?
- [29:29]
B
Yeah, I think it's not just us as well. Even Open Claw itself started doing some of that. So for example, if you use skill like MC Porter that allows you to connect to all of these MCP service, any MCP server, really. MC Porter by default will check all the responses that come from the MCP server and use the model, whatever model you're running. So Cloud Office or whatever else, it will use it as a judge model. But again, the issue is you can jailbreak those models, you can bypass them. As I said before, if it looks like something part of the actual functionality will allow you to do it. These controls need to be built into the actual system when you design it. A good example again is like Windows versus Mac os. Windows was not designed with security in mind. Security was kind of patched on top of it and they're still patching it and patching it and it's never ending battle. As macOS was designed based on BSD kernel so that security, the privilege levels and everything else were built in from the beginning. That's why you know, somebody obviously, you know, open Cloison, MIT license project, so somebody can just fork it and make it secure. But somebody should also probably think about designing secure project like that from the start.
- [30:50]
A
Aaron, can you kind of touch a little more on the judge models? I think Andreas kind of touched on it, but I think this is really interesting way that people can defend from these attacks. Yeah.
- [30:59]
C
Architecturally speaking, you have your core model that's doing the heavy lifting, right? It's the thing that's connected to your skills, it's connected to your data. The judge model is simply a new model that sits and reads the inputs in the outputs. And its job is just to make sure that the input and the output match. You know, you can have an input that looks like a clearly, you know, compromisable input, like, hey, give me your system prompt. And the core model should deny that. The judge model will see that and say, okay, it's looking for its system prompt. But what the judge model will also do is look at the output. So if the core model then outputs the system prompt, the judge model will say, okay, clearly somebody asked for the system prompt and then the model gave it to it. I need to shut that down. So that's the job of the judge model. And it gets way more complicated. Right. So you can start looking at completion of tasks. That becomes really challenging to now architect a judge model that's functional. Right. So if like I'm using the Open Claw on my Mac Mini with Peekaboo and other kinds of true OS level browsing, it's now going to be a lot more difficult to train that judge model to say we're now navigating a website and we're trying to browse for the Task, you know, the, the objective at hand, the Judge model needs to make sure that everything is still working and that becomes an incredibly complicated thing that, you know, you're effectively doubling your token count and you've got two models running in tandem which honestly at this point you, you probably should, should be experimenting with this kind of architecture. But coming back to what Andres is saying, like the core of how these systems work really do need to be set up for a, you know, from a security first perspective and like until we are secure and you know, are able to make sure that, let's say a website can't send a prompt injection to your core model, like the Judge model may not be able to, to catch that either. It's just you're adding the probability and an extra layer of protection. But you're not like you're never going to be 100% secure on this.
- [33:23]
A
We have seen that a lot of people and companies are saying, I don't want to use this yet. I'll wait for the more secure project. And you know, at launch, Jason's been very public that we've been using Open Claw and it has made a huge impact. I mean what we're able to do and we won't get into the details is just mind blowing and a huge like time saver and just will make us more efficient and better at our jobs, which is just crazy. People are going to stop hiring. It's just going to happen. You don't need as many people. All of the kind of grunt work is going to stop. If your best friend came to you, they have an SMB, what would you tell them at the moment? Should they start playing with this? Maybe Andres, you can go to this and then Aaron, you can hop in.
- [34:05]
B
I'm a security guy, so I'm a skeptic about these things and obviously I'm very careful when it comes to deploying these things. But yes, you can deploy them in a secure, in a kind of secure way. There are ways to do it. I don't think you can put Pandora back into the box. The features are just too important at this point. Everybody wants them, everybody wants to use them. Enterprises and BCS, CISOs and CIOs, they can put policies in place. Do not download this, do not use this. But, but it's, it's too good. People will use it. People in Enterprise and SMBs will use it. You cannot stop it. So yes, you need to find better ways of deploying it. And there are multiple ways to do it. Obviously, you know, Mac, Mini, is one of them. Now, all of these providers coming up with more secure setups like cloudflare, MALT workers and things like that. Start with those, or if you, like me, if you're on the Linux system, then run it in a VM and a Docker container on top of it. So just give it two layers of security in that case. And just be extremely careful. Start playing with it. Make sure that the skills you download are actually legit. Use some kind of scanner, ideally before you use that skill, and just be careful about what access you give it. So don't give it like your medical information at the start. Don't give your financial information. I hear like some people are using it to trade at this point. Don't do that. Don't give it access to your, to your, you know, FinTech account or your trading account or whatever else, or your bank account for that matter.
- [35:40]
A
You're seeing people post like, I gave OpenClaw access to $10,000 and it lost it all. And then that's the YouTube thumbnail. But yeah, I mean, people are going to play with it. I think people should use it, you know, give it read access to one notion page, you know, give it very baseline access and see what it's capable of. Especially if you're just starting. Don't start by giving it access to your whole Google account and being able to send emails and, you know, all the other things you can add. And also you can add your own skills. You don't have to download skills and you can create your own skills, you don't have to add them and download some random skill on a platform like CloudHub. So, Andreas, there's two different types of people here. There's kind of the, you know, the weekend open clotter who just wants to try it out. Could you kind of just walk through briefly what the easiest way they can set up open call would be?
- [36:27]
B
Absolutely. So do not buy a Mac Mini. Unless you really want to spend money and you want another toy, that's fine. But as I mentioned before, providers are coming up with the secure ways of deploying it. So use one of those. I'm not going to mention any names at this point, but Google it, search it, grok it, whatever you do these days, I mean, and just find one and use it. And when you start using skills, yeah, experiment with skills as well. Just don't give it access to your main accounts. One of the legitimate ways of doing this as well, if you want to try a skill is open another Gmail account, open another Notion account, whatever else, just do not give it access to your actual information yet. Just start playing slowly. Just start figuring out what you can do with it and then, you know, somebody will come up with a more secure way of doing it and then jump all in. As I said, you cannot put Pandora back into the box. It's too valuable at this point.
- [37:27]
C
Yeah, I want to double click on that as a. You know, Andres and I are startup co founders. You know, we. It's our job to build a company and to manage resources. This is the biggest unlock that we've had from a builder's perspective in the history of software. It's. It's on. You really can't overstate the importance of these tools and our ability to take entire departments worth of work and put them into these AI tools is there. The challenge is now how do we do this securely and how do we do this with proprietary company data? And we're not quite there yet. So by that's why Microsoft and their Copilot product has taken a long time and you really still don't have a lot of functionality there. It's mostly just analyze some emails or analyze some docs on your OneDrive account and the power is not there because it's so locked down. There's this inverse relationship with power and security. The more power you give it, the less secure it is because the foundational identity of these models is insecure. So by moving forward in time, that problem is going to change. But if you are an SMB operator, if you're a builder, if you're a founder, you have to be using these tools at the very least to get an understanding of when that secure thing comes out, that you can be the first one to be utilizing it properly. I'm hesitant to say you need to be doing this today because it's. The risks are palpable, but you need the skills. Develop the skills, develop the muscles to make it work. Build sandboxes, experiment build processes in particular like utilize notion. Right, Utilize these sandboxed areas that the model has very limited access and try to maximize those before adding new capabilities. Like don't just give it root level access to your os because that would be really cool. Yes, it is cool, but it's inherently very dangerous today. But you still need to get these skills understood before you start. You know, before you start, before you start.
- [39:41]
A
And OpenClaw was released at the beginning of January, so it's only been out for around a month and there hasn't been insane usage beyond just the past week. So it's still kind of being thought out, but I'm sure it's going to be very fast moving. There's going to be new projects, more secure projects and just wait a little maybe if you're really concerned something will come out that, that you'll maybe feel more comfortable using. You guys specifically at Zastack have obviously been building in this space for a long time. I'd love to kind of get a picture into your minds of where you think we will kind of be, you know, maybe at the end of this year. I can't even imagine at the pace that we're going now in two years. And how does Ziosec kind of fit into this picture?
- [40:22]
C
The end of this year, I think we're going to see a lot of enterprise have a come to Jesus moment on agents that they're going to be required to start putting these in. There's a lot of public market pressure on them to perform. Look at what's happening in the software markets like the values of SaaS companies are plummeting and they are. A fire is being lit now and whether they can respond to this. With the agentic future, I think there's going to be a lot of creative destruction. I think startups are going to usurp a lot of the incumbents in the next year. Brand new ways of dealing with things, understanding workflows are going to come out of projects like OpenClaw that are going to evolve with hardened enterprise controls that are designed to replace entire department departments with armies of secure agents. I think that's what we're going to see over the next six to 12 months. And our role in this is validation. Ziosac has been a validation of AI agents. We do platform driven pen testing of these agents. You can put thousands of them into our platform and then continuously validate that they are adhering to policies to controls that they're not getting jailbroken with all of the latest attacks and that that's really our specialty. So we're there to assist these companies who are going through this transformation and opening the black box to assure security, legal, GRC engineering, that yes, these agents are performing the way they were designed and they're not going off the rails in different, in different use cases or different scenarios.
- [42:07]
B
The future is definitely interesting and Aaron touched a lot on the business side. I'll talk about the developer and security guy side. Even before this, using something like Claude Code or GitHub Copilot allowed us to go three times, five times as fast as developers with this with OpenClaw, if you set it up properly, it can not only write code for you, it can actually do end to end testing. You don't need QA people anymore, you don't need to do testing yourself. And it can do all of it while you're asleep. You just give it a task. It's like, I want this project done, I want it to work exactly this way and do all the testing for me. So now we can basically ten 20x developers. I mean, it's a completely different ball game at this point. Companies that are like Google, that are still working with developing developer shops of, you know, hundreds of people, they're going to become obsolete. They cannot compete in this world anymore.
- [43:05]
A
Yeah, and me and Lucas kind of got this online last week, the beginning of last week, and we were going into a team meeting and we had just realized the power of this tool, me and him. Literally 10 minutes before the meeting, we had set like 20 things up. Just after we had kind of unlocked it. And you know, that was a bunch of different iterations, a lot of different testing. And we both were kind of shaking because we were just like, holy shit, this is going to change everything. And one thing that I think of, you know, as a recent grad, my brother's a senior right now. I mean, I don't even know what to tell kind of people in school right now because you don't have to learn how to code. Software engineers, they're going to have to adapt. You know, these tools are accessible for anyone. You can use plain language and understand everything. So what would you tell someone in college, Aaron, who is maybe, you know, just picking where they're going to go to school, picking their major. I don't even know what I would tell them.
- [44:01]
C
I think you need to go start a company, you need to go find a problem, you need to build, you need to use these tools, you need to push as hard and fast as you can. You need to learn. You become native fluent at these skills and don't look for employment. I would, I would start something, I would try to push as hard as you can on a problem set. Go to Founder University, you know, get the guidance from the people who have done this. Well, Founder University, Y Combinator techstars. Right. Like there, there are these places that are, are good at pulling people in that direction and guiding. So I would, I would say that's, that's the way to go. Obviously not everybody can do this. Not everybody's cut out to be a founder or an entrepreneur. But that said, you still need to become a native operator of this stuff. I think unless you do that, you're going to be, you're going to be in a very hard position.
- [44:56]
B
I have a son in high school, so for me it's kind of, you know, a pretty close to home kind of conversation, I suppose. And yeah, I tell him, you do not need to know how to code, you do not need to know math. Yes, you still have to pass math in high school and all of that, but in the end it doesn't matter anymore. What matters at this point is data and expertise. You need to gain expertise in something. That's like when I hire the next person, it's not going to be a developer, it's going to be a security researcher that can use AI tools and generate code with AI tools and still understand some code just to make sure they didn't generate something malicious. But there is the other side of it. Not as you as, as you said, not everybody can do it. Not everybody's cut out to be a founder and understand all of these things. Well, we still need electricians, we still need plumbers. I don't think you know that those skills will be replaced that fast. So that's a possibility as well. You know, electricians make good money and AI, robotics, maybe, maybe they will replace those professions at some point, but it's going to be too expensive to do it for at least the next 10, 20 years, in my opinion.
- [46:02]
A
It's a crazy time that we're in right now. I mean, it's day to day, touch and go with this topic and agentic AI, it's finally alive, it's finally here and I really appreciate you guys for joining and yeah, I'll see you guys soon.
- [46:14]
C
Cool, thanks for having us.