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If you're in SF: Join us for the Claude Plays Pokemon hackathon this Sunday!If you're not: Fill out the 2025 State of AI Eng survey for $250 in Amazon cards!We are SO excited to share our conversation with Dharmesh Shah, co-founder of HubSpot and creator of Agent.ai.A particularly compelling concept we discussed is the idea of "hybrid teams" - the next evolution in workplace organization where human workers collaborate with AI agents as team members. Just as we previously saw hybrid teams emerge in terms of full-time vs. contract workers, or in-office vs. remote workers, Dharmesh predicts that the next frontier will be teams composed of both human and AI members. This raises interesting questions about team dynamics, trust, and how to effectively delegate tasks between human and AI team members.The discussion of business models in AI reveals an important distinction between Work as a Service (WaaS) and Results as a Service (RaaS), something Dharmesh has written extensively about. While RaaS has gained popularity, particularly in customer support applications where outcomes are easily measurable, Dharmesh argues that this model may be over-indexed. Not all AI applications have clearly definable outcomes or consistent economic value per transaction, making WaaS more appropriate in many cases. This insight is particularly relevant for businesses considering how to monetize AI capabilities.The technical challenges of implementing effective agent systems are also explored, particularly around memory and authentication. Shah emphasizes the importance of cross-agent memory sharing and the need for more granular control over data access. He envisions a future where users can selectively share parts of their data with different agents, similar to how OAuth works but with much finer control. This points to significant opportunities in developing infrastructure for secure and efficient agent-to-agent communication and data sharing.Other highlights from our conversation* The Evolution of AI-Powered Agents – Exploring how AI agents have evolved from simple chatbots to sophisticated multi-agent systems, and the role of MCPs in enabling that.* Hybrid Digital Teams and the Future of Work – How AI agents are becoming teammates rather than just tools, and what this means for business operations and knowledge work.* Memory in AI Agents – The importance of persistent memory in AI systems and how shared memory across agents could enhance collaboration and efficiency.* Business Models for AI Agents – Exploring the shift from software as a service (SaaS) to work as a service (WaaS) and results as a service (RaaS), and what this means for monetization.* The Role of Standards Like MCP – Why MCP has been widely adopted and how it enables agent collaboration, tool use, and discovery.* The Future of AI Code Generation and Software Engineering – How AI-assisted coding is changing the role of software engineers and what skills will matter most in the future.* Domain Investing and Efficient Markets – Dharmesh's approach to domain investing and how inefficiencies in digital asset markets create business opportunities.* The Philosophy of Saying No – Lessons from "Sorry, You Must Pass" and how prioritization leads to greater productivity and focus.Timestamps* 00:00 Introduction and Guest Welcome* 02:29 Dharmesh Shah's Journey into AI* 05:22 Defining AI Agents* 06:45 The Evolution and Future of AI Agents* 13:53 Graph Theory and Knowledge Representation* 20:02 Engineering Practices and Overengineering* 25:57 The Role of Junior Engineers in the AI Era* 28:20 Multi-Agent Systems and MCP Standards* 35:55 LinkedIn's Legal Battles and Data Scraping* 37:32 The Future of AI and Hybrid Teams* 39:19 Building Agent AI: A Professional Network for Agents* 40:43 Challenges and Innovations in Agent AI* 45:02 The Evolution of UI in AI Systems* 01:00:25 Business Models: Work as a Service vs. Results as a Service* 01:09:17 The Future Value of Engineers* 01:09:51 Exploring the Role of Agents* 01:10:28 The Importance of Memory in AI* 01:11:02 Challenges and Opportunities in AI Memory* 01:12:41 Selective Memory and Privacy Concerns* 01:13:27 The Evolution of AI Tools and Platforms* 01:18:23 Domain Names and AI Projects* 01:32:08 Balancing Work and Personal Life* 01:35:52 Final Thoughts and ReflectionsTranscriptAlessio [00:00:04]: Hey everyone, welcome back to the Latent Space podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of Small AI.swyx [00:00:12]: Hello, and today we're super excited to have Dharmesh Shah to join us. I guess your relevant title here is founder of Agent AI.Dharmesh [00:00:20]: Yeah, that's true for this. Yeah, creator of Agent.ai and co-founder of HubSpot.swyx [00:00:25]: Co-founder of HubSpot, which I followed for many years, I think 18 years now, gonna be 19 soon. And you caught, you know, people can catch up on your HubSpot story elsewhere. I should also thank Sean Puri, who I've chatted with back and forth, who's been, I guess, getting me in touch with your people. But also, I think like, just giving us a lot of context, because obviously, My First Million joined you guys, and they've been chatting with you guys a lot. So for the business side, we can talk about that, but I kind of wanted to engage your CTO, agent, engineer side of things. So how did you get agent religion?Dharmesh [00:01:00]: Let's see. So I've been working, I'll take like a half step back, a decade or so ago, even though actually more than that. So even before HubSpot, the company I was contemplating that I had named for was called Ingenisoft. And the idea behind Ingenisoft was a natural language interface to business software. Now realize this is 20 years ago, so that was a hard thing to do. But the actual use case that I had in mind was, you know, we had data sitting in business systems like a CRM or something like that. And my kind of what I thought clever at the time. Oh, what if we used email as the kind of interface to get to business software? And the motivation for using email is that it automatically works when you're offline. So imagine I'm getting on a plane or I'm on a plane. There was no internet on planes back then. It's like, oh, I'm going through business cards from an event I went to. I can just type things into an email just to have them all in the backlog. When it reconnects, it sends those emails to a processor that basically kind of parses effectively the commands and updates the software, sends you the file, whatever it is. And there was a handful of commands. I was a little bit ahead of the times in terms of what was actually possible. And I reattempted this natural language thing with a product called ChatSpot that I did back 20...swyx [00:02:12]: Yeah, this is your first post-ChatGPT project.Dharmesh [00:02:14]: I saw it come out. Yeah. And so I've always been kind of fascinated by this natural language interface to software. Because, you know, as software developers, myself included, we've always said, oh, we build intuitive, easy-to-use applications. And it's not intuitive at all, right? Because what we're doing is... We're taking the mental model that's in our head of what we're trying to accomplish with said piece of software and translating that into a series of touches and swipes and clicks and things like that. And there's nothing natural or intuitive about it. And so natural language interfaces, for the first time, you know, whatever the thought is you have in your head and expressed in whatever language that you normally use to talk to yourself in your head, you can just sort of emit that and have software do something. And I thought that was kind of a breakthrough, which it has been. And it's gone. So that's where I first started getting into the journey. I started because now it actually works, right? So once we got ChatGPT and you can take, even with a few-shot example, convert something into structured, even back in the ChatGP 3.5 days, it did a decent job in a few-shot example, convert something to structured text if you knew what kinds of intents you were going to have. And so that happened. And that ultimately became a HubSpot project. But then agents intrigued me because I'm like, okay, well, that's the next step here. So chat's great. Love Chat UX. But if we want to do something even more meaningful, it felt like the next kind of advancement is not this kind of, I'm chatting with some software in a kind of a synchronous back and forth model, is that software is going to do things for me in kind of a multi-step way to try and accomplish some goals. So, yeah, that's when I first got started. It's like, okay, what would that look like? Yeah. And I've been obsessed ever since, by the way.Alessio [00:03:55]: Which goes back to your first experience with it, which is like you're offline. Yeah. And you want to do a task. You don't need to do it right now. You just want to queue it up for somebody to do it for you. Yes. As you think about agents, like, let's start at the easy question, which is like, how do you define an agent? Maybe. You mean the hardest question in the universe? Is that what you mean?Dharmesh [00:04:12]: You said you have an irritating take. I do have an irritating take. I think, well, some number of people have been irritated, including within my own team. So I have a very broad definition for agents, which is it's AI-powered software that accomplishes a goal. Period. That's it. And what irritates people about it is like, well, that's so broad as to be completely non-useful. And I understand that. I understand the criticism. But in my mind, if you kind of fast forward months, I guess, in AI years, the implementation of it, and we're already starting to see this, and we'll talk about this, different kinds of agents, right? So I think in addition to having a usable definition, and I like yours, by the way, and we should talk more about that, that you just came out with, the classification of agents actually is also useful, which is, is it autonomous or non-autonomous? Does it have a deterministic workflow? Does it have a non-deterministic workflow? Is it working synchronously? Is it working asynchronously? Then you have the different kind of interaction modes. Is it a chat agent, kind of like a customer support agent would be? You're having this kind of back and forth. Is it a workflow agent that just does a discrete number of steps? So there's all these different flavors of agents. So if I were to draw it in a Venn diagram, I would draw a big circle that says, this is agents, and then I have a bunch of circles, some overlapping, because they're not mutually exclusive. And so I think that's what's interesting, and we're seeing development along a bunch of different paths, right? So if you look at the first implementation of agent frameworks, you look at Baby AGI and AutoGBT, I think it was, not Autogen, that's the Microsoft one. They were way ahead of their time because they assumed this level of reasoning and execution and planning capability that just did not exist, right? So it was an interesting thought experiment, which is what it was. Even the guy that, I'm an investor in Yohei's fund that did Baby AGI. It wasn't ready, but it was a sign of what was to come. And so the question then is, when is it ready? And so lots of people talk about the state of the art when it comes to agents. I'm a pragmatist, so I think of the state of the practical. It's like, okay, well, what can I actually build that has commercial value or solves actually some discrete problem with some baseline of repeatability or verifiability?swyx [00:06:22]: There was a lot, and very, very interesting. I'm not irritated by it at all. Okay. As you know, I take a... There's a lot of anthropological view or linguistics view. And in linguistics, you don't want to be prescriptive. You want to be descriptive. Yeah. So you're a goals guy. That's the key word in your thing. And other people have other definitions that might involve like delegated trust or non-deterministic work, LLM in the loop, all that stuff. The other thing I was thinking about, just the comment on Baby AGI, LGBT. Yeah. In that piece that you just read, I was able to go through our backlog and just kind of track the winter of agents and then the summer now. Yeah. And it's... We can tell the whole story as an oral history, just following that thread. And it's really just like, I think, I tried to explain the why now, right? Like I had, there's better models, of course. There's better tool use with like, they're just more reliable. Yep. Better tools with MCP and all that stuff. And I'm sure you have opinions on that too. Business model shift, which you like a lot. I just heard you talk about RAS with MFM guys. Yep. Cost is dropping a lot. Yep. Inference is getting faster. There's more model diversity. Yep. Yep. I think it's a subtle point. It means that like, you have different models with different perspectives. You don't get stuck in the basin of performance of a single model. Sure. You can just get out of it by just switching models. Yep. Multi-agent research and RL fine tuning. So I just wanted to let you respond to like any of that.Dharmesh [00:07:44]: Yeah. A couple of things. Connecting the dots on the kind of the definition side of it. So we'll get the irritation out of the way completely. I have one more, even more irritating leap on the agent definition thing. So here's the way I think about it. By the way, the kind of word agent, I looked it up, like the English dictionary definition. The old school agent, yeah. Is when you have someone or something that does something on your behalf, like a travel agent or a real estate agent acts on your behalf. It's like proxy, which is a nice kind of general definition. So the other direction I'm sort of headed, and it's going to tie back to tool calling and MCP and things like that, is if you, and I'm not a biologist by any stretch of the imagination, but we have these single-celled organisms, right? Like the simplest possible form of what one would call life. But it's still life. It just happens to be single-celled. And then you can combine cells and then cells become specialized over time. And you have much more sophisticated organisms, you know, kind of further down the spectrum. In my mind, at the most fundamental level, you can almost think of having atomic agents. What is the simplest possible thing that's an agent that can still be called an agent? What is the equivalent of a kind of single-celled organism? And the reason I think that's useful is right now we're headed down the road, which I think is very exciting around tool use, right? That says, okay, the LLMs now can be provided a set of tools that it calls to accomplish whatever it needs to accomplish in the kind of furtherance of whatever goal it's trying to get done. And I'm not overly bothered by it, but if you think about it, if you just squint a little bit and say, well, what if everything was an agent? And what if tools were actually just atomic agents? Because then it's turtles all the way down, right? Then it's like, oh, well, all that's really happening with tool use is that we have a network of agents that know about each other through something like an MMCP and can kind of decompose a particular problem and say, oh, I'm going to delegate this to this set of agents. And why do we need to draw this distinction between tools, which are functions most of the time? And an actual agent. And so I'm going to write this irritating LinkedIn post, you know, proposing this. It's like, okay. And I'm not suggesting we should call even functions, you know, call them agents. But there is a certain amount of elegance that happens when you say, oh, we can just reduce it down to one primitive, which is an agent that you can combine in complicated ways to kind of raise the level of abstraction and accomplish higher order goals. Anyway, that's my answer. I'd say that's a success. Thank you for coming to my TED Talk on agent definitions.Alessio [00:09:54]: How do you define the minimum viable agent? Do you already have a definition for, like, where you draw the line between a cell and an atom? Yeah.Dharmesh [00:10:02]: So in my mind, it has to, at some level, use AI in order for it to—otherwise, it's just software. It's like, you know, we don't need another word for that. And so that's probably where I draw the line. So then the question, you know, the counterargument would be, well, if that's true, then lots of tools themselves are actually not agents because they're just doing a database call or a REST API call or whatever it is they're doing. And that does not necessarily qualify them, which is a fair counterargument. And I accept that. It's like a good argument. I still like to think about—because we'll talk about multi-agent systems, because I think—so we've accepted, which I think is true, lots of people have said it, and you've hopefully combined some of those clips of really smart people saying this is the year of agents, and I completely agree, it is the year of agents. But then shortly after that, it's going to be the year of multi-agent systems or multi-agent networks. I think that's where it's going to be headed next year. Yeah.swyx [00:10:54]: Opening eyes already on that. Yeah. My quick philosophical engagement with you on this. I often think about kind of the other spectrum, the other end of the cell spectrum. So single cell is life, multi-cell is life, and you clump a bunch of cells together in a more complex organism, they become organs, like an eye and a liver or whatever. And then obviously we consider ourselves one life form. There's not like a lot of lives within me. I'm just one life. And now, obviously, I don't think people don't really like to anthropomorphize agents and AI. Yeah. But we are extending our consciousness and our brain and our functionality out into machines. I just saw you were a Bee. Yeah. Which is, you know, it's nice. I have a limitless pendant in my pocket.Dharmesh [00:11:37]: I got one of these boys. Yeah.swyx [00:11:39]: I'm testing it all out. You know, got to be early adopters. But like, we want to extend our personal memory into these things so that we can be good at the things that we're good at. And, you know, machines are good at it. Machines are there. So like, my definition of life is kind of like going outside of my own body now. I don't know if you've ever had like reflections on that. Like how yours. How our self is like actually being distributed outside of you. Yeah.Dharmesh [00:12:01]: I don't fancy myself a philosopher. But you went there. So yeah, I did go there. I'm fascinated by kind of graphs and graph theory and networks and have been for a long, long time. And to me, we're sort of all nodes in this kind of larger thing. It just so happens that we're looking at individual kind of life forms as they exist right now. But so the idea is when you put a podcast out there, there's these little kind of nodes you're putting out there of like, you know, conceptual ideas. Once again, you have varying kind of forms of those little nodes that are up there and are connected in varying and sundry ways. And so I just think of myself as being a node in a massive, massive network. And I'm producing more nodes as I put content or ideas. And, you know, you spend some portion of your life collecting dots, experiences, people, and some portion of your life then connecting dots from the ones that you've collected over time. And I found that really interesting things happen and you really can't know in advance how those dots are necessarily going to connect in the future. And that's, yeah. So that's my philosophical take. That's the, yes, exactly. Coming back.Alessio [00:13:04]: Yep. Do you like graph as an agent? Abstraction? That's been one of the hot topics with LandGraph and Pydantic and all that.Dharmesh [00:13:11]: I do. The thing I'm more interested in terms of use of graphs, and there's lots of work happening on that now, is graph data stores as an alternative in terms of knowledge stores and knowledge graphs. Yeah. Because, you know, so I've been in software now 30 plus years, right? So it's not 10,000 hours. It's like 100,000 hours that I've spent doing this stuff. And so I've grew up with, so back in the day, you know, I started on mainframes. There was a product called IMS from IBM, which is basically an index database, what we'd call like a key value store today. Then we've had relational databases, right? We have tables and columns and foreign key relationships. We all know that. We have document databases like MongoDB, which is sort of a nested structure keyed by a specific index. We have vector stores, vector embedding database. And graphs are interesting for a couple of reasons. One is, so it's not classically structured in a relational way. When you say structured database, to most people, they're thinking tables and columns and in relational database and set theory and all that. Graphs still have structure, but it's not the tables and columns structure. And you could wonder, and people have made this case, that they are a better representation of knowledge for LLMs and for AI generally than other things. So that's kind of thing number one conceptually, and that might be true, I think is possibly true. And the other thing that I really like about that in the context of, you know, I've been in the context of data stores for RAG is, you know, RAG, you say, oh, I have a million documents, I'm going to build the vector embeddings, I'm going to come back with the top X based on the semantic match, and that's fine. All that's very, very useful. But the reality is something gets lost in the chunking process and the, okay, well, those tend, you know, like, you don't really get the whole picture, so to speak, and maybe not even the right set of dimensions on the kind of broader picture. And it makes intuitive sense to me that if we did capture it properly in a graph form, that maybe that feeding into a RAG pipeline will actually yield better results for some use cases, I don't know, but yeah.Alessio [00:15:03]: And do you feel like at the core of it, there's this difference between imperative and declarative programs? Because if you think about HubSpot, it's like, you know, people and graph kind of goes hand in hand, you know, but I think maybe the software before was more like primary foreign key based relationship, versus now the models can traverse through the graph more easily.Dharmesh [00:15:22]: Yes. So I like that representation. There's something. It's just conceptually elegant about graphs and just from the representation of it, they're much more discoverable, you can kind of see it, there's observability to it, versus kind of embeddings, which you can't really do much with as a human. You know, once they're in there, you can't pull stuff back out. But yeah, I like that kind of idea of it. And the other thing that's kind of, because I love graphs, I've been long obsessed with PageRank from back in the early days. And, you know, one of the kind of simplest algorithms in terms of coming up, you know, with a phone, everyone's been exposed to PageRank. And the idea is that, and so I had this other idea for a project, not a company, and I have hundreds of these, called NodeRank, is to be able to take the idea of PageRank and apply it to an arbitrary graph that says, okay, I'm going to define what authority looks like and say, okay, well, that's interesting to me, because then if you say, I'm going to take my knowledge store, and maybe this person that contributed some number of chunks to the graph data store has more authority on this particular use case or prompt that's being submitted than this other one that may, or maybe this one was more. popular, or maybe this one has, whatever it is, there should be a way for us to kind of rank nodes in a graph and sort them in some, some useful way. Yeah.swyx [00:16:34]: So I think that's generally useful for, for anything. I think the, the problem, like, so even though at my conferences, GraphRag is super popular and people are getting knowledge, graph religion, and I will say like, it's getting space, getting traction in two areas, conversation memory, and then also just rag in general, like the, the, the document data. Yeah. It's like a source. Most ML practitioners would say that knowledge graph is kind of like a dirty word. The graph database, people get graph religion, everything's a graph, and then they, they go really hard into it and then they get a, they get a graph that is too complex to navigate. Yes. And so like the, the, the simple way to put it is like you at running HubSpot, you know, the power of graphs, the way that Google has pitched them for many years, but I don't suspect that HubSpot itself uses a knowledge graph. No. Yeah.Dharmesh [00:17:26]: So when is it over engineering? Basically? It's a great question. I don't know. So the question now, like in AI land, right, is the, do we necessarily need to understand? So right now, LLMs for, for the most part are somewhat black boxes, right? We sort of understand how the, you know, the algorithm itself works, but we really don't know what's going on in there and, and how things come out. So if a graph data store is able to produce the outcomes we want, it's like, here's a set of queries I want to be able to submit and then it comes out with useful content. Maybe the underlying data store is as opaque as a vector embeddings or something like that, but maybe it's fine. Maybe we don't necessarily need to understand it to get utility out of it. And so maybe if it's messy, that's okay. Um, that's, it's just another form of lossy compression. Uh, it's just lossy in a way that we just don't completely understand in terms of, because it's going to grow organically. Uh, and it's not structured. It's like, ah, we're just gonna throw a bunch of stuff in there. Let the, the equivalent of the embedding algorithm, whatever they called in graph land. Um, so the one with the best results wins. I think so. Yeah.swyx [00:18:26]: Or is this the practical side of me is like, yeah, it's, if it's useful, we don't necessarilyDharmesh [00:18:30]: need to understand it.swyx [00:18:30]: I have, I mean, I'm happy to push back as long as you want. Uh, it's not practical to evaluate like the 10 different options out there because it takes time. It takes people, it takes, you know, resources, right? Set. That's the first thing. Second thing is your evals are typically on small things and some things only work at scale. Yup. Like graphs. Yup.Dharmesh [00:18:46]: Yup. That's, yeah, no, that's fair. And I think this is one of the challenges in terms of implementation of graph databases is that the most common approach that I've seen developers do, I've done it myself, is that, oh, I've got a Postgres database or a MySQL or whatever. I can represent a graph with a very set of tables with a parent child thing or whatever. And that sort of gives me the ability, uh, why would I need anything more than that? And the answer is, well, if you don't need anything more than that, you don't need anything more than that. But there's a high chance that you're sort of missing out on the actual value that, uh, the graph representation gives you. Which is the ability to traverse the graph, uh, efficiently in ways that kind of going through the, uh, traversal in a relational database form, even though structurally you have the data, practically you're not gonna be able to pull it out in, in useful ways. Uh, so you wouldn't like represent a social graph, uh, in, in using that kind of relational table model. It just wouldn't scale. It wouldn't work.swyx [00:19:36]: Uh, yeah. Uh, I think we want to move on to MCP. Yeah. But I just want to, like, just engineering advice. Yeah. Uh, obviously you've, you've, you've run, uh, you've, you've had to do a lot of projects and run a lot of teams. Do you have a general rule for over-engineering or, you know, engineering ahead of time? You know, like, because people, we know premature engineering is the root of all evil. Yep. But also sometimes you just have to. Yep. When do you do it? Yes.Dharmesh [00:19:59]: It's a great question. This is, uh, a question as old as time almost, which is what's the right and wrong levels of abstraction. That's effectively what, uh, we're answering when we're trying to do engineering. I tend to be a pragmatist, right? So here's the thing. Um, lots of times doing something the right way. Yeah. It's like a marginal increased cost in those cases. Just do it the right way. And this is what makes a, uh, a great engineer or a good engineer better than, uh, a not so great one. It's like, okay, all things being equal. If it's going to take you, you know, roughly close to constant time anyway, might as well do it the right way. Like, so do things well, then the question is, okay, well, am I building a framework as the reusable library? To what degree, uh, what am I anticipating in terms of what's going to need to change in this thing? Uh, you know, along what dimension? And then I think like a business person in some ways, like what's the return on calories, right? So, uh, and you look at, um, energy, the expected value of it's like, okay, here are the five possible things that could happen, uh, try to assign probabilities like, okay, well, if there's a 50% chance that we're going to go down this particular path at some day, like, or one of these five things is going to happen and it costs you 10% more to engineer for that. It's basically, it's something that yields a kind of interest compounding value. Um, as you get closer to the time of, of needing that versus having to take on debt, which is when you under engineer it, you're taking on debt. You're going to have to pay off when you do get to that eventuality where something happens. One thing as a pragmatist, uh, so I would rather under engineer something than over engineer it. If I were going to err on the side of something, and here's the reason is that when you under engineer it, uh, yes, you take on tech debt, uh, but the interest rate is relatively known and payoff is very, very possible, right? Which is, oh, I took a shortcut here as a result of which now this thing that should have taken me a week is now going to take me four weeks. Fine. But if that particular thing that you thought might happen, never actually, you never have that use case transpire or just doesn't, it's like, well, you just save yourself time, right? And that has value because you were able to do other things instead of, uh, kind of slightly over-engineering it away, over-engineering it. But there's no perfect answers in art form in terms of, uh, and yeah, we'll, we'll bring kind of this layers of abstraction back on the code generation conversation, which we'll, uh, I think I have later on, butAlessio [00:22:05]: I was going to ask, we can just jump ahead quickly. Yeah. Like, as you think about vibe coding and all that, how does the. Yeah. Percentage of potential usefulness change when I feel like we over-engineering a lot of times it's like the investment in syntax, it's less about the investment in like arc exacting. Yep. Yeah. How does that change your calculus?Dharmesh [00:22:22]: A couple of things, right? One is, um, so, you know, going back to that kind of ROI or a return on calories, kind of calculus or heuristic you think through, it's like, okay, well, what is it going to cost me to put this layer of abstraction above the code that I'm writing now, uh, in anticipating kind of future needs. If the cost of fixing, uh, or doing under engineering right now. Uh, we'll trend towards zero that says, okay, well, I don't have to get it right right now because even if I get it wrong, I'll run the thing for six hours instead of 60 minutes or whatever. It doesn't really matter, right? Like, because that's going to trend towards zero to be able, the ability to refactor a code. Um, and because we're going to not that long from now, we're going to have, you know, large code bases be able to exist, uh, you know, as, as context, uh, for a code generation or a code refactoring, uh, model. So I think it's going to make it, uh, make the case for under engineering, uh, even stronger. Which is why I take on that cost. You just pay the interest when you get there, it's not, um, just go on with your life vibe coded and, uh, come back when you need to. Yeah.Alessio [00:23:18]: Sometimes I feel like there's no decision-making in some things like, uh, today I built a autosave for like our internal notes platform and I literally just ask them cursor. Can you add autosave? Yeah. I don't know if it's over under engineer. Yep. I just vibe coded it. Yep. And I feel like at some point we're going to get to the point where the models kindDharmesh [00:23:36]: of decide where the right line is, but this is where the, like the, in my mind, the danger is, right? So there's two sides to this. One is the cost of kind of development and coding and things like that stuff that, you know, we talk about. But then like in your example, you know, one of the risks that we have is that because adding a feature, uh, like a save or whatever the feature might be to a product as that price tends towards zero, are we going to be less discriminant about what features we add as a result of making more product products more complicated, which has a negative impact on the user and navigate negative impact on the business. Um, and so that's the thing I worry about if it starts to become too easy, are we going to be. Too promiscuous in our, uh, kind of extension, adding product extensions and things like that. It's like, ah, why not add X, Y, Z or whatever back then it was like, oh, we only have so many engineering hours or story points or however you measure things. Uh, that least kept us in check a little bit. Yeah.Alessio [00:24:22]: And then over engineering, you're like, yeah, it's kind of like you're putting that on yourself. Yeah. Like now it's like the models don't understand that if they add too much complexity, it's going to come back to bite them later. Yep. So they just do whatever they want to do. Yeah. And I'm curious where in the workflow that's going to be, where it's like, Hey, this is like the amount of complexity and over-engineering you can do before you got to ask me if we should actually do it versus like do something else.Dharmesh [00:24:45]: So you know, we've already, let's like, we're leaving this, uh, in the code generation world, this kind of compressed, um, cycle time. Right. It's like, okay, we went from auto-complete, uh, in the GitHub co-pilot to like, oh, finish this particular thing and hit tab to a, oh, I sort of know your file or whatever. I can write out a full function to you to now I can like hold a bunch of the context in my head. Uh, so we can do app generation, which we have now with lovable and bolt and repletage. Yeah. Association and other things. So then the question is, okay, well, where does it naturally go from here? So we're going to generate products. Make sense. We might be able to generate platforms as though I want a platform for ERP that does this, whatever. And that includes the API's includes the product and the UI, and all the things that make for a platform. There's no nothing that says we would stop like, okay, can you generate an entire software company someday? Right. Uh, with the platform and the monetization and the go-to-market and the whatever. And you know, that that's interesting to me in terms of, uh, you know, what, when you take it to almost ludicrous levels. of abstract.swyx [00:25:39]: It's like, okay, turn it to 11. You mentioned vibe coding, so I have to, this is a blog post I haven't written, but I'm kind of exploring it. Is the junior engineer dead?Dharmesh [00:25:49]: I don't think so. I think what will happen is that the junior engineer will be able to, if all they're bringing to the table is the fact that they are a junior engineer, then yes, they're likely dead. But hopefully if they can communicate with carbon-based life forms, they can interact with product, if they're willing to talk to customers, they can take their kind of basic understanding of engineering and how kind of software works. I think that has value. So I have a 14-year-old right now who's taking Python programming class, and some people ask me, it's like, why is he learning coding? And my answer is, is because it's not about the syntax, it's not about the coding. What he's learning is like the fundamental thing of like how things work. And there's value in that. I think there's going to be timeless value in systems thinking and abstractions and what that means. And whether functions manifested as math, which he's going to get exposed to regardless, or there are some core primitives to the universe, I think, that the more you understand them, those are what I would kind of think of as like really large dots in your life that will have a higher gravitational pull and value to them that you'll then be able to. So I want him to collect those dots, and he's not resisting. So it's like, okay, while he's still listening to me, I'm going to have him do things that I think will be useful.swyx [00:26:59]: You know, part of one of the pitches that I evaluated for AI engineer is a term. And the term is that maybe the traditional interview path or career path of software engineer goes away, which is because what's the point of lead code? Yeah. And, you know, it actually matters more that you know how to work with AI and to implement the things that you want. Yep.Dharmesh [00:27:16]: That's one of the like interesting things that's happened with generative AI. You know, you go from machine learning and the models and just that underlying form, which is like true engineering, right? Like the actual, what I call real engineering. I don't think of myself as a real engineer, actually. I'm a developer. But now with generative AI. We call it AI and it's obviously got its roots in machine learning, but it just feels like fundamentally different to me. Like you have the vibe. It's like, okay, well, this is just a whole different approach to software development to so many different things. And so I'm wondering now, it's like an AI engineer is like, if you were like to draw the Venn diagram, it's interesting because the cross between like AI things, generative AI and what the tools are capable of, what the models do, and this whole new kind of body of knowledge that we're still building out, it's still very young, intersected with kind of classic engineering, software engineering. Yeah.swyx [00:28:04]: I just described the overlap as it separates out eventually until it's its own thing, but it's starting out as a software. Yeah.Alessio [00:28:11]: That makes sense. So to close the vibe coding loop, the other big hype now is MCPs. Obviously, I would say Cloud Desktop and Cursor are like the two main drivers of MCP usage. I would say my favorite is the Sentry MCP. I can pull in errors and then you can just put the context in Cursor. How do you think about that abstraction layer? Does it feel... Does it feel almost too magical in a way? Do you think it's like you get enough? Because you don't really see how the server itself is then kind of like repackaging theDharmesh [00:28:41]: information for you? I think MCP as a standard is one of the better things that's happened in the world of AI because a standard needed to exist and absent a standard, there was a set of things that just weren't possible. Now, we can argue whether it's the best possible manifestation of a standard or not. Does it do too much? Does it do too little? I get that, but it's just simple enough to both be useful and unobtrusive. It's understandable and adoptable by mere mortals, right? It's not overly complicated. You know, a reasonable engineer can put a stand up an MCP server relatively easily. The thing that has me excited about it is like, so I'm a big believer in multi-agent systems. And so that's going back to our kind of this idea of an atomic agent. So imagine the MCP server, like obviously it calls tools, but the way I think about it, so I'm working on my current passion project is agent.ai. And we'll talk more about that in a little bit. More about the, I think we should, because I think it's interesting not to promote the project at all, but there's some interesting ideas in there. One of which is around, we're going to need a mechanism for, if agents are going to collaborate and be able to delegate, there's going to need to be some form of discovery and we're going to need some standard way. It's like, okay, well, I just need to know what this thing over here is capable of. We're going to need a registry, which Anthropic's working on. I'm sure others will and have been doing directories of, and there's going to be a standard around that too. How do you build out a directory of MCP servers? I think that's going to unlock so many things just because, and we're already starting to see it. So I think MCP or something like it is going to be the next major unlock because it allows systems that don't know about each other, don't need to, it's that kind of decoupling of like Sentry and whatever tools someone else was building. And it's not just about, you know, Cloud Desktop or things like, even on the client side, I think we're going to see very interesting consumers of MCP, MCP clients versus just the chat body kind of things. Like, you know, Cloud Desktop and Cursor and things like that. But yeah, I'm very excited about MCP in that general direction.swyx [00:30:39]: I think the typical cynical developer take, it's like, we have OpenAPI. Yeah. What's the new thing? I don't know if you have a, do you have a quick MCP versus everything else? Yeah.Dharmesh [00:30:49]: So it's, so I like OpenAPI, right? So just a descriptive thing. It's OpenAPI. OpenAPI. Yes, that's what I meant. So it's basically a self-documenting thing. We can do machine-generated, lots of things from that output. It's a structured definition of an API. I get that, love it. But MCPs sort of are kind of use case specific. They're perfect for exactly what we're trying to use them for around LLMs in terms of discovery. It's like, okay, I don't necessarily need to know kind of all this detail. And so right now we have, we'll talk more about like MCP server implementations, but We will? I think, I don't know. Maybe we won't. At least it's in my head. It's like a back processor. But I do think MCP adds value above OpenAPI. It's, yeah, just because it solves this particular thing. And if we had come to the world, which we have, like, it's like, hey, we already have OpenAPI. It's like, if that were good enough for the universe, the universe would have adopted it already. There's a reason why MCP is taking office because marginally adds something that was missing before and doesn't go too far. And so that's why the kind of rate of adoption, you folks have written about this and talked about it. Yeah, why MCP won. Yeah. And it won because the universe decided that this was useful and maybe it gets supplanted by something else. Yeah. And maybe we discover, oh, maybe OpenAPI was good enough the whole time. I doubt that.swyx [00:32:09]: The meta lesson, this is, I mean, he's an investor in DevTools companies. I work in developer experience at DevRel in DevTools companies. Yep. Everyone wants to own the standard. Yeah. I'm sure you guys have tried to launch your own standards. Actually, it's Houseplant known for a standard, you know, obviously inbound marketing. But is there a standard or protocol that you ever tried to push? No.Dharmesh [00:32:30]: And there's a reason for this. Yeah. Is that? And I don't mean, need to mean, speak for the people of HubSpot, but I personally. You kind of do. I'm not smart enough. That's not the, like, I think I have a. You're smart. Not enough for that. I'm much better off understanding the standards that are out there. And I'm more on the composability side. Let's, like, take the pieces of technology that exist out there, combine them in creative, unique ways. And I like to consume standards. I don't like to, and that's not that I don't like to create them. I just don't think I have the, both the raw wattage or the credibility. It's like, okay, well, who the heck is Dharmesh, and why should we adopt a standard he created?swyx [00:33:07]: Yeah, I mean, there are people who don't monetize standards, like OpenTelemetry is a big standard, and LightStep never capitalized on that.Dharmesh [00:33:15]: So, okay, so if I were to do a standard, there's two things that have been in my head in the past. I was one around, a very, very basic one around, I don't even have the domain, I have a domain for everything, for open marketing. Because the issue we had in HubSpot grew up in the marketing space. There we go. There was no standard around data formats and things like that. It doesn't go anywhere. But the other one, and I did not mean to go here, but I'm going to go here. It's called OpenGraph. I know the term was already taken, but it hasn't been used for like 15 years now for its original purpose. But what I think should exist in the world is right now, our information, all of us, nodes are in the social graph at Meta or the professional graph at LinkedIn. Both of which are actually relatively closed in actually very annoying ways. Like very, very closed, right? Especially LinkedIn. Especially LinkedIn. I personally believe that if it's my data, and if I would get utility out of it being open, I should be able to make my data open or publish it in whatever forms that I choose, as long as I have control over it as opt-in. So the idea is around OpenGraph that says, here's a standard, here's a way to publish it. I should be able to go to OpenGraph.org slash Dharmesh dot JSON and get it back. And it's like, here's your stuff, right? And I can choose along the way and people can write to it and I can prove. And there can be an entire system. And if I were to do that, I would do it as a... Like a public benefit, non-profit-y kind of thing, as this is a contribution to society. I wouldn't try to commercialize that. Have you looked at AdProto? What's that? AdProto.swyx [00:34:43]: It's the protocol behind Blue Sky. Okay. My good friend, Dan Abramov, who was the face of React for many, many years, now works there. And he actually did a talk that I can send you, which basically kind of tries to articulate what you just said. But he does, he loves doing these like really great analogies, which I think you'll like. Like, you know, a lot of our data is behind a handle, behind a domain. Yep. So he's like, all right, what if we flip that? What if it was like our handle and then the domain? Yep. So, and that's really like your data should belong to you. Yep. And I should not have to wait 30 days for my Twitter data to export. Yep.Dharmesh [00:35:19]: you should be able to at least be able to automate it or do like, yes, I should be able to plug it into an agentic thing. Yeah. Yes. I think we're... Because so much of our data is... Locked up. I think the trick here isn't that standard. It is getting the normies to care.swyx [00:35:37]: Yeah. Because normies don't care.Dharmesh [00:35:38]: That's true. But building on that, normies don't care. So, you know, privacy is a really hot topic and an easy word to use, but it's not a binary thing. Like there are use cases where, and we make these choices all the time, that I will trade, not all privacy, but I will trade some privacy for some productivity gain or some benefit to me that says, oh, I don't care about that particular data being online if it gives me this in return, or I don't mind sharing this information with this company.Alessio [00:36:02]: If I'm getting, you know, this in return, but that sort of should be my option. I think now with computer use, you can actually automate some of the exports. Yes. Like something we've been doing internally is like everybody exports their LinkedIn connections. Yep. And then internally, we kind of merge them together to see how we can connect our companies to customers or things like that.Dharmesh [00:36:21]: And not to pick on LinkedIn, but since we're talking about it, but they feel strongly enough on the, you know, do not take LinkedIn data that they will block even browser use kind of things or whatever. They go to great, great lengths, even to see patterns of usage. And it says, oh, there's no way you could have, you know, gotten that particular thing or whatever without, and it's, so it's, there's...swyx [00:36:42]: Wasn't there a Supreme Court case that they lost? Yeah.Dharmesh [00:36:45]: So the one they lost was around someone that was scraping public data that was on the public internet. And that particular company had not signed any terms of service or whatever. It's like, oh, I'm just taking data that's on, there was no, and so that's why they won. But now, you know, the question is around, can LinkedIn... I think they can. Like, when you use, as a user, you use LinkedIn, you are signing up for their terms of service. And if they say, well, this kind of use of your LinkedIn account that violates our terms of service, they can shut your account down, right? They can. And they, yeah, so, you know, we don't need to make this a discussion. By the way, I love the company, don't get me wrong. I'm an avid user of the product. You know, I've got... Yeah, I mean, you've got over a million followers on LinkedIn, I think. Yeah, I do. And I've known people there for a long, long time, right? And I have lots of respect. And I understand even where the mindset originally came from of this kind of members-first approach to, you know, a privacy-first. I sort of get that. But sometimes you sort of have to wonder, it's like, okay, well, that was 15, 20 years ago. There's likely some controlled ways to expose some data on some member's behalf and not just completely be a binary. It's like, no, thou shalt not have the data.swyx [00:37:54]: Well, just pay for sales navigator.Alessio [00:37:57]: Before we move to the next layer of instruction, anything else on MCP you mentioned? Let's move back and then I'll tie it back to MCPs.Dharmesh [00:38:05]: So I think the... Open this with agent. Okay, so I'll start with... Here's my kind of running thesis, is that as AI and agents evolve, which they're doing very, very quickly, we're going to look at them more and more. I don't like to anthropomorphize. We'll talk about why this is not that. Less as just like raw tools and more like teammates. They'll still be software. They should self-disclose as being software. I'm totally cool with that. But I think what's going to happen is that in the same way you might collaborate with a team member on Slack or Teams or whatever you use, you can imagine a series of agents that do specific things just like a team member might do, that you can delegate things to. You can collaborate. You can say, hey, can you take a look at this? Can you proofread that? Can you try this? You can... Whatever it happens to be. So I think it is... I will go so far as to say it's inevitable that we're going to have hybrid teams someday. And what I mean by hybrid teams... So back in the day, hybrid teams were, oh, well, you have some full-time employees and some contractors. Then it was like hybrid teams are some people that are in the office and some that are remote. That's the kind of form of hybrid. The next form of hybrid is like the carbon-based life forms and agents and AI and some form of software. So let's say we temporarily stipulate that I'm right about that over some time horizon that eventually we're going to have these kind of digitally hybrid teams. So if that's true, then the question you sort of ask yourself is that then what needs to exist in order for us to get the full value of that new model? It's like, okay, well... You sort of need to... It's like, okay, well, how do I... If I'm building a digital team, like, how do I... Just in the same way, if I'm interviewing for an engineer or a designer or a PM, whatever, it's like, well, that's why we have professional networks, right? It's like, oh, they have a presence on likely LinkedIn. I can go through that semi-structured, structured form, and I can see the experience of whatever, you know, self-disclosed. But, okay, well, agents are going to need that someday. And so I'm like, okay, well, this seems like a thread that's worth pulling on. That says, okay. So I... So agent.ai is out there. And it's LinkedIn for agents. It's LinkedIn for agents. It's a professional network for agents. And the more I pull on that thread, it's like, okay, well, if that's true, like, what happens, right? It's like, oh, well, they have a profile just like anyone else, just like a human would. It's going to be a graph underneath, just like a professional network would be. It's just that... And you can have its, you know, connections and follows, and agents should be able to post. That's maybe how they do release notes. Like, oh, I have this new version. Whatever they decide to post, it should just be able to... Behave as a node on the network of a professional network. As it turns out, the more I think about that and pull on that thread, the more and more things, like, start to make sense to me. So it may be more than just a pure professional network. So my original thought was, okay, well, it's a professional network and agents as they exist out there, which I think there's going to be more and more of, will kind of exist on this network and have the profile. But then, and this is always dangerous, I'm like, okay, I want to see a world where thousands of agents are out there in order for the... Because those digital employees, the digital workers don't exist yet in any meaningful way. And so then I'm like, oh, can I make that easier for, like... And so I have, as one does, it's like, oh, I'll build a low-code platform for building agents. How hard could that be, right? Like, very hard, as it turns out. But it's been fun. So now, agent.ai has 1.3 million users. 3,000 people have actually, you know, built some variation of an agent, sometimes just for their own personal productivity. About 1,000 of which have been published. And the reason this comes back to MCP for me, so imagine that and other networks, since I know agent.ai. So right now, we have an MCP server for agent.ai that exposes all the internally built agents that we have that do, like, super useful things. Like, you know, I have access to a Twitter API that I can subsidize the cost. And I can say, you know, if you're looking to build something for social media, these kinds of things, with a single API key, and it's all completely free right now, I'm funding it. That's a useful way for it to work. And then we have a developer to say, oh, I have this idea. I don't have to worry about open AI. I don't have to worry about, now, you know, this particular model is better. It has access to all the models with one key. And we proxy it kind of behind the scenes. And then expose it. So then we get this kind of community effect, right? That says, oh, well, someone else may have built an agent to do X. Like, I have an agent right now that I built for myself to do domain valuation for website domains because I'm obsessed with domains, right? And, like, there's no efficient market for domains. There's no Zillow for domains right now that tells you, oh, here are what houses in your neighborhood sold for. It's like, well, why doesn't that exist? We should be able to solve that problem. And, yes, you're still guessing. Fine. There should be some simple heuristic. So I built that. It's like, okay, well, let me go look for past transactions. You say, okay, I'm going to type in agent.ai, agent.com, whatever domain. What's it actually worth? I'm looking at buying it. It can go and say, oh, which is what it does. It's like, I'm going to go look at are there any published domain transactions recently that are similar, either use the same word, same top-level domain, whatever it is. And it comes back with an approximate value, and it comes back with its kind of rationale for why it picked the value and comparable transactions. Oh, by the way, this domain sold for published. Okay. So that agent now, let's say, existed on the web, on agent.ai. Then imagine someone else says, oh, you know, I want to build a brand-building agent for startups and entrepreneurs to come up with names for their startup. Like a common problem, every startup is like, ah, I don't know what to call it. And so they type in five random words that kind of define whatever their startup is. And you can do all manner of things, one of which is like, oh, well, I need to find the domain for it. What are possible choices? Now it's like, okay, well, it would be nice to know if there's an aftermarket price for it, if it's listed for sale. Awesome. Then imagine calling this valuation agent. It's like, okay, well, I want to find where the arbitrage is, where the agent valuation tool says this thing is worth $25,000. It's listed on GoDaddy for $5,000. It's close enough. Let's go do that. Right? And that's a kind of composition use case that in my future state. Thousands of agents on the network, all discoverable through something like MCP. And then you as a developer of agents have access to all these kind of Lego building blocks based on what you're trying to solve. Then you blend in orchestration, which is getting better and better with the reasoning models now. Just describe the problem that you have. Now, the next layer that we're all contending with is that how many tools can you actually give an LLM before the LLM breaks? That number used to be like 15 or 20 before you kind of started to vary dramatically. And so that's the thing I'm thinking about now. It's like, okay, if I want to... If I want to expose 1,000 of these agents to a given LLM, obviously I can't give it all 1,000. Is there some intermediate layer that says, based on your prompt, I'm going to make a best guess at which agents might be able to be helpful for this particular thing? Yeah.Alessio [00:44:37]: Yeah, like RAG for tools. Yep. I did build the Latent Space Researcher on agent.ai. Okay. Nice. Yeah, that seems like, you know, then there's going to be a Latent Space Scheduler. And then once I schedule a research, you know, and you build all of these things. By the way, my apologies for the user experience. You realize I'm an engineer. It's pretty good.swyx [00:44:56]: I think it's a normie-friendly thing. Yeah. That's your magic. HubSpot does the same thing.Alessio [00:45:01]: Yeah, just to like quickly run through it. You can basically create all these different steps. And these steps are like, you know, static versus like variable-driven things. How did you decide between this kind of like low-code-ish versus doing, you know, low-code with code backend versus like not exposing that at all? Any fun design decisions? Yeah. And this is, I think...Dharmesh [00:45:22]: I think lots of people are likely sitting in exactly my position right now, coming through the choosing between deterministic. Like if you're like in a business or building, you know, some sort of agentic thing, do you decide to do a deterministic thing? Or do you go non-deterministic and just let the alum handle it, right, with the reasoning models? The original idea and the reason I took the low-code stepwise, a very deterministic approach. A, the reasoning models did not exist at that time. That's thing number one. Thing number two is if you can get... If you know in your head... If you know in your head what the actual steps are to accomplish whatever goal, why would you leave that to chance? There's no upside. There's literally no upside. Just tell me, like, what steps do you need executed? So right now what I'm playing with... So one thing we haven't talked about yet, and people don't talk about UI and agents. Right now, the primary interaction model... Or they don't talk enough about it. I know some people have. But it's like, okay, so we're used to the chatbot back and forth. Fine. I get that. But I think we're going to move to a blend of... Some of those things are going to be synchronous as they are now. But some are going to be... Some are going to be async. It's just going to put it in a queue, just like... And this goes back to my... Man, I talk fast. But I have this... I only have one other speed. It's even faster. So imagine it's like if you're working... So back to my, oh, we're going to have these hybrid digital teams. Like, you would not go to a co-worker and say, I'm going to ask you to do this thing, and then sit there and wait for them to go do it. Like, that's not how the world works. So it's nice to be able to just, like, hand something off to someone. It's like, okay, well, maybe I expect a response in an hour or a day or something like that.Dharmesh [00:46:52]: In terms of when things need to happen. So the UI around agents. So if you look at the output of agent.ai agents right now, they are the simplest possible manifestation of a UI, right? That says, oh, we have inputs of, like, four different types. Like, we've got a dropdown, we've got multi-select, all the things. It's like back in HTML, the original HTML 1.0 days, right? Like, you're the smallest possible set of primitives for a UI. And it just says, okay, because we need to collect some information from the user, and then we go do steps and do things. And generate some output in HTML or markup are the two primary examples. So the thing I've been asking myself, if I keep going down that path. So people ask me, I get requests all the time. It's like, oh, can you make the UI sort of boring? I need to be able to do this, right? And if I keep pulling on that, it's like, okay, well, now I've built an entire UI builder thing. Where does this end? And so I think the right answer, and this is what I'm going to be backcoding once I get done here, is around injecting a code generation UI generation into, the agent.ai flow, right? As a builder, you're like, okay, I'm going to describe the thing that I want, much like you would do in a vibe coding world. But instead of generating the entire app, it's going to generate the UI that exists at some point in either that deterministic flow or something like that. It says, oh, here's the thing I'm trying to do. Go generate the UI for me. And I can go through some iterations. And what I think of it as a, so it's like, I'm going to generate the code, generate the code, tweak it, go through this kind of prompt style, like we do with vibe coding now. And at some point, I'm going to be happy with it. And I'm going to hit save. And that's going to become the action in that particular step. It's like a caching of the generated code that I can then, like incur any inference time costs. It's just the actual code at that point.Alessio [00:48:29]: Yeah, I invested in a company called E2B, which does code sandbox. And they powered the LM arena web arena. So it's basically the, just like you do LMS, like text to text, they do the same for like UI generation. So if you're asking a model, how do you do it? But yeah, I think that's kind of where.Dharmesh [00:48:45]: That's the thing I'm really fascinated by. So the early LLM, you know, we're understandably, but laughably bad at simple arithmetic, right? That's the thing like my wife, Normies would ask us, like, you call this AI, like it can't, my son would be like, it's just stupid. It can't even do like simple arithmetic. And then like we've discovered over time that, and there's a reason for this, right? It's like, it's a large, there's, you know, the word language is in there for a reason in terms of what it's been trained on. It's not meant to do math, but now it's like, okay, well, the fact that it has access to a Python interpreter that I can actually call at runtime, that solves an entire body of problems that it wasn't trained to do. And it's basically a form of delegation. And so the thought that's kind of rattling around in my head is that that's great. So it's, it's like took the arithmetic problem and took it first. Now, like anything that's solvable through a relatively concrete Python program, it's able to do a bunch of things that I couldn't do before. Can we get to the same place with UI? I don't know what the future of UI looks like in a agentic AI world, but maybe let the LLM handle it, but not in the classic sense. Maybe it generates it on the fly, or maybe we go through some iterations and hit cache or something like that. So it's a little bit more predictable. Uh, I don't know, but yeah.Alessio [00:49:48]: And especially when is the human supposed to intervene? So, especially if you're composing them, most of them should not have a UI because then they're just web hooking to somewhere else. I just want to touch back. I don't know if you have more comments on this.swyx [00:50:01]: I was just going to ask when you, you said you got, you're going to go back to code. What

Jim Walter, Senior Threat Researcher on SentinelLabs research team, to discuss their work on "HellCat and Morpheus | Two Brands, One Payload as Ransomware Affiliates Drop Identical Code." Over the past six months, new ransomware groups like FunkSec, Nitrogen, and Termite have emerged, while established threats such as Cl0p and LockBit 4.0 have resurfaced. Two prominent Ransomware-as-a-Service (RaaS) operations, HellCat and Morpheus, have gained traction, with research indicating that affiliates of both are using nearly identical ransomware payloads. Despite similarities in their encryption techniques and ransom notes, there is no conclusive evidence linking HellCat and Morpheus to the Underground Team, though shared tools or affiliates may be involved. The research can be found here: HellCat and Morpheus | Two Brands, One Payload as Ransomware Affiliates Drop Identical Code Learn more about your ad choices. Visit megaphone.fm/adchoices

Jim Walter, Senior Threat Researcher on SentinelLabs research team, to discuss their work on "HellCat and Morpheus | Two Brands, One Payload as Ransomware Affiliates Drop Identical Code." Over the past six months, new ransomware groups like FunkSec, Nitrogen, and Termite have emerged, while established threats such as Cl0p and LockBit 4.0 have resurfaced. Two prominent Ransomware-as-a-Service (RaaS) operations, HellCat and Morpheus, have gained traction, with research indicating that affiliates of both are using nearly identical ransomware payloads. Despite similarities in their encryption techniques and ransom notes, there is no conclusive evidence linking HellCat and Morpheus to the Underground Team, though shared tools or affiliates may be involved. The research can be found here: HellCat and Morpheus | Two Brands, One Payload as Ransomware Affiliates Drop Identical Code Learn more about your ad choices. Visit megaphone.fm/adchoices

Jake Hall, a trailblazer in manufacturing automation and robotics, joins Manufacturing Tech Australia to explore the cutting edge of technological advancements shaping the industry.  In this episode, we delve into the transformative impact of robotics, AI, and digital tools, including:  How AI-driven, no-code solutions are simplifying robotics programming.  The rise of Robotics-as-a-Service (RaaS) and its implications for manufacturers.  Strategies for bridging the talent gap using digital work instructions and capturing tribal knowledge.  Jake shares insights from his global experience, discussing how these innovations can empower small and medium-sized manufacturers to thrive in a competitive landscape.  Tune in for an engaging conversation that offers actionable advice for businesses ready to embrace the future of manufacturing. 

The rise of Retail as a Service (RaaS) has opened up transformative opportunities for retailers, but it also poses serious challenges. In this episode, join Oliver Banks to dive deep into the evolving RaaS landscape and explore the key factors that are shaping its future. From data privacy concerns to expansion into new categories, we'll dissect the pros, cons, and potential pitfalls of this new business model. Whether you're considering RaaS for your business or are curious about the changing dynamics of retail, this episode offers fresh insights and perspectives on what's to come. Listen to this episode now to:Understand how RaaS is both levelling the playing field and empowering major retailers.Explore the 5 emerging factors which are shaping the future of RaaS.Discover how non-retail companies are entering the RaaS space and what that means for the future.Show notes are at www.obandco.uk/317.

Retail-as-a-Service (RaaS) is a fast evolving segment of retail which offers new profit streams or the ability to quickly scale a new business or channel. Today, we're exploring how this model is reshaping the retail landscape. From the growth of global giants like Amazon, Ocado and THG to the rise of supply chain innovators like Shein, we unpack the key drivers behind this trend and what it means for retailers of all sizes. Whether you're considering adopting RaaS, already a provider, or wondering about the challenges and opportunities that this shift means for your business, this episode will offer valuable insights into the RaaS opportunity. Show notes are at www.obandco.uk/316.

Welcome to another episode of Category Visionaries — the show that explores GTM stories from tech's most innovative B2B founders. In today's episode, we're speaking with Saman Farid, CEO & Founder of Formic, a robotics platform that has raised over $60 Million in funding. Here are the most interesting points from our conversation: On-demand robot workforce: Formic provides factories with robots that can work on an hourly basis, aiming to solve labor shortages by making robotic solutions more accessible. COVID and labor shortages: Saman founded Formic during the pandemic, driven by supply chain disruptions and the unfilled jobs crisis in manufacturing, which showed a need for better automation solutions. From VC to founder: Saman transitioned back to being a founder because he believed in the massive potential of robotics. He saw a $10 billion opportunity in automating manufacturing tasks and felt compelled to take the leap. Robustness over cutting-edge tech: Formic focuses on reliability, prioritizing proven, dependable robotics technology that can run two shifts daily without downtime, over pursuing the latest but less mature advancements. Unique business model - "Pay for Productivity": Formic guarantees performance and productivity, only charging clients for the output they get, which has been a game-changer in driving faster adoption of robotics. Scaling with $250M in financing: Formic uses a sophisticated capital stack to finance deployments, which allows them to offer a "try before you buy" model, making robotics more affordable and less risky for manufacturers. //   Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe.  www.GlobalTalent.co

The FBI is the repossessor of Dispossessor. The NCA collars and extradites a notorious cybercriminal. A German company loses sixty million dollars to business email compromise. DeathGrip is a new Ransomware-as-a-Service (RaaS) platform. Russia blocks access to Signal. NIST publishes post-quantum cryptography standards. DARPA awards $14 million to teams competing in the AI Cyber Challenge. On our Solution Spotlight, N2K President Simone Petrella talks with Lee Parrish, CISO of Newell Brands, about his book "The Shortest Hour: An Applied Approach to Boardroom Governance of Cyber Security". AI generates impossible code - for knitters and crocheters. Miss an episode? Sign-up for our daily intelligence roundup, Daily Briefing, and you'll never miss a beat. And be sure to follow CyberWire Daily on LinkedIn. CyberWire Guest On our Solution Spotlight, N2K President Simone Petrella talks with Lee Parrish, CISO of Newell Brands, about his book "The Shortest Hour: An Applied Approach to Boardroom Governance of Cyber Security" and security relationship management. Coming tomorrow, stay tuned for a special edition with Simone and Lee's full conversation.  Selected Reading FBI strikes down rumored LockBit reboot (CSO Online) Suspected head of prolific cybercrime groups arrested and extradited (National Crime Agency) Orion SA says scammers conned company out of $60 million (The Register) DeathGrip Ransomware Expanding Services Using RaaS Service (GB Hackers) Swiss manufacturer investigating ransomware attack that shut down IT network (The Record) Russia Blocks Signal Messaging App as Authorities Tighten Control Over Information (SecurityWeek) Post-Quantum Cryptography Standards Officially Announced by NIST – a History and Explanation (SecurityWeek) Need to know: NIST finalizes post-quantum encryption standards essential for cybersecurity (N2K CyberWire) NIST Releases First 3 Finalized Post-Quantum Encryption Standards (NIST)   DARPA Awards $14m to Seven Teams in AI Cyber Challenge (Infosecurity Magazine) The AI scams infiltrating the knitting and crochet world - and why it matters for everyone (ZDNET) Share your feedback. We want to ensure that you are getting the most out of the podcast. Please take a few minutes to share your thoughts with us by completing our brief listener survey as we continually work to improve the show.  Want to hear your company in the show? You too can reach the most influential leaders and operators in the industry. Here's our media kit. Contact us at cyberwire@n2k.com to request more info. The CyberWire is a production of N2K Networks, your source for strategic workforce intelligence. © N2K Networks, Inc. Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode, CJ interviews Dustin Pederson of Locus Robotics, as part of his series of interviews with CFOs from pre-IPO companies recorded live on the floor of the New York Stock Exchange. Dustin explains the Robot-as-a-Service (RaaS) model, a subscription-based service, how it works, and how it makes money. He and CJ do a deep dive into business models that rely on supply chains, the unique challenges of managing inventory, and tactical tips for CFOs looking to optimize their cash conversion cycles. They also examine the unique metrics tracked by Locus Robotics as both a hardware and software company compared to that of pure SaaS models. Dustin provides helpful information and tactical advice on how to build an ROI model and present it to buyers. He also shares insights on Locus Robotics' market positioning, specialized ERPs for warehouses, and how the interactions between humans and robots play out in the companies Locus Robotics serves. If you're looking for an ERP head to NetSuite: https://netsuite.com/metrics and get a customized KPI checklist.—SPONSORS:Leapfin is accounting automation software that automatically prepares and posts reliable journal entries. High-growth businesses like Reddit, Canva, and Seat Geek choose Leapfin to eliminate manual tasks, accelerate month-end close, and enable accounting leaders to provide faster insights to help their companies grow. To automatically standardize your revenue data with measurable business impact, check out leapfin.com today. Mercury is the fintech ambitious companies use for banking and all their financial workflows. With a powerful bank account at the center of their operations, companies can make better financial decisions and ensure that every dollar spent aligns with company priorities. That's why over 100K startups choose Mercury to confidently run all their financial operations with the precision, control, and focus they need to operate at their best. Learn more at mercury.com.Mercury is a financial technology company, not a bank. Banking services provided by Choice Financial Group and Evolve Bank & Trust®; Members FDIC.NetSuite provides financial software for all your business needs. More than 37,000 thousand companies have already upgraded to NetSuite, gaining visibility and control over their financials, inventory, HR, eCommerce, and more. If you're looking for an ERP platform ✅ NetSuite: https://netsuite.com/metrics and get a customized KPI checklist. Maxio is the only billing and financial operations platform that was purpose built for B2B SaaS. They're helping SaaS finance teams automate billing and revenue recognition, manage collections and payments, and put together investor grade reporting packages.

Water From Thin Air Hit me up: mylesdhillon@gmail.com And please share this pod with friend. ## Humanoid Robots Enter the Warehouse- GXO Logistics signs multi-year deal with Agility Robotics to deploy Digit humanoid robots- Digit robots are 5'9" tall, can lift 35 lbs, and assist with repetitive tasks like moving totes- First commercial Robots-as-a-Service (RaaS) deployment of humanoid robots- Managed through Agility Arc cloud platform for easy integration- RaaS model lowers barriers for companies to adopt advanced robotics- Marks significant milestone for warehouse automation and human-robot collaboration## Harvesting Water from Air- New technology uses adsorbent fins to extract water from air more efficiently - Can harvest water even in low humidity (10% relative humidity)- Compact design with fins 2mm apart collects up to 1.3L water/day at 30% humidity- 2-5x more efficient than similar devices- Uses heat to release collected water- Addresses water scarcity concerns, tapping into atmospheric water vapor- Prototype tested successfully, research published in ACS Energy Letters## 3D Printing Corneas - Researchers developing 3D printed personalized corneas to treat blindness/disorders- Key benefits: customization, reduced donor dependence, lower rejection risk- Uses bioink from patient's stem cells or modified collagen fibers- Showing promise in lab/animal testing, moving towards human trials - Could help millions with corneal blindness- Challenges remain in scaling production and further testing- Multiple research groups working on the technology- Seen as promising solution to cornea shortages for aging populationCitations:[1] https://retailtechinnovationhub.com/home/2024/6/28/gxo-logistics-lays-claim-to-an-industry-first-as-it-inks-multi-year-agreement-with-agility-robotics[2] https://science4data.com/gxo-logistics-and-agility-robotics-deploy-digit-humanoid-robots/[3] https://www.logisticsmatters.co.uk/Humanoid-robot-to-deploy[4] https://gxo.com/news_article/gxo-signs-industry-first-multi-year-agreement-with-agility-robotics/[5] https://www.therobotreport.com/agility-robotics-digit-humanoid-lands-first-official-job/Get intouch with Myles at mylesdhillon@gmail.com

Video - https://youtu.be/uTQLducNdkk Explore the dark side of the web with Ransomware-as-a-Service (RaaS), where cybercriminals lease ransomware to affiliates, amplifying their reach. This guide reveals how RaaS works, its impact, and essential tips for protection and recovery. Stay ahead of cyber threats with practical advice on safeguarding your digital life. I used GPT-4o and Pictory.ai to put this information together. If you're interested in trying Pictory.ai please use the following link. https://pictory.ai?ref=t015o --- Support this podcast: https://podcasters.spotify.com/pod/show/norbert-gostischa/support

Join me as I speak with internationally recognized operational security and technology executive, Steve Hindle, as we talk about data...lots and lots of data. We talk about how organizations need to protect their data because many aren't quite doing it correctly. During our chat Steve touches on: 1. Defining data, 2. Classifying data, 3. Confidentiality, Integrity, and Availability (CIA), 4. Where does your data really reside? 5. What type of data do you have and is it accurate? 6. The biggest threat to data? 7. Internal and external threats, 8. Espionage, 9. Cyber threats, 10. Who is more innovate - the attacker or the defender? 11. Security / cyber budgets, 12. Ransomware as a Service (RaaS), 13. Focus on fundamentals...and more! Steve shares some very insightful - if not downright scary - insights when it comes to our data and what organizations might be forgetting. Don't miss what Steve has to share. Enjoy!

In this episode, we dive into the latest ransomware incidents impacting organizations in Ascension, Montclair, NJ, and Wichita, KS. We'll explore the rise of Ransomware-as-a-Service (RaaS) and analyze CISA's recent advisory on this growing menace. Discover how implementing Zero Trust Architecture and investing in cyber insurance can bolster your defenses against cyber-attacks. Stay ahead of the curve with insights into the emerging cyber threats of 2024 and learn proactive measures to safeguard your systems. Don't miss this essential discussion on protecting your business from cyber-attacks. Stay informed, stay protected! #SecuritySquawk #CyberSecurity #Ransomware #ZeroTrust #CybersecurityPodcast #CybersecurityExperts

On this edition of the Precision Farming Dealer podcast, brought to you by Ag Express Electronics, technology editor Noah Newman catches up with Bluewhite CEO and founder Ben Alfi for a discussion about the future of autonomy in agriculture and the company's Robots-as-a-Service (RaaS) model. The Bluewhite autonomy kit retrofits to existing tractor fleets and implements. Alfi explains how the technology works and why the retrofit approach is widening the path to autonomy. He also talks about dealer opportunities, how Bluewhite is helping growers reduce chemical, fuel, and labor inputs, and shares his overall vision for the future of the company.

In their conversation, Edgar Roth, Protocol Specialist at Kiln interviews Amrit Kuma, COO at AltLayer. Amrit shares his journey into the field, starting first with computer science. They explore AltLayer's Rollup as a Service (RaaS) platform and its AVS offerings, focusing on decentralized sequencing, verification, and faster finality. Tune in to learn more about AltLayer value proposition and future of AVSs!

⭐ My guest today is ⁠Kameale Terry, Cofounder and CEO of ChargerHelp!. ChargerHelp! is the only national EV charger-dedicated operations and maintenance service provider, with over 1,000 EV technicians trained so far. Their key offering is Reliability as a Service (RaaS) – “a labor subscription service that provides peace of mind to charging station owners and operators who require fast and reliable O&M services at consistent, hassle-free prices, with 97% EV charger up time.” Kameale Terry is a former banker, policy fellow, and EV charging software executive. She's also the daughter of Belizean immigrants born and raised in South Central Los Angeles. She believes that an “equitable green economy can be achieved through realignment of existing workforces in conjunction with clean technology.” ---

This week the team take stock of Binance; what may be going on and the potential ramifications. We review the regulation win for Coinbase, as approval is granted for retail perpetual futures trading. We dive deep on Rollups-as-a-Service (RaaS). Mike explains why he's been ‘Pudgy Pilled'. We review the current state of the SEC/Crypto relationship saga, where we are with ETH Futures ETFs, the upcoming Celestia (TIA) Airdrop, and more! Hit play now and find relevant links below, enjoy! - - Maverick Protocol is a DeFi infrastructure provider focused on increasing industry efficiency, powered by Maverick AMM. Maverick helps token projects, DAO treasuries, liquidity providers or anyone in DeFi shape their liquidity with efficiency and flexibility. In other words, Maverick makes your liquidity smarter.  Shape liquidity for your token today on Maverick at https://app.mav.xyz/bellcurve   - - Timestamps: (00:00) Introduction (01:12) Coinbase: regulatory approval for retail perpetual futures trading (07:42) Dumb Money (08:14) “Maverick Ad” (09:29) Binance Meltdown Review  (20:035 RaaS: The Key Ingredient to a Rollup-Centric Roadmap (39:26) Pudgy Penguins: Pudgy Pilled (45:06) SEC: Gary Gensler Crypto Overreach  (48:51) ETH Futures ETF Update (53:51) Celestia (TIA) Airdrop (1:00:38) Platform Risk Shift - - Follow Mike: https://twitter.com/MikeIppolito_ Follow Myles: https://twitter.com/MylesOneil Follow Michael: https://twitter.com/im_manderson Subscribe on YouTube: https://bit.ly/3R1D1D9 Subscribe on Apple: https://apple.co/3pQTfmD Subscribe on Spotify: https://spoti.fi/3cpKZXH -- Research, news, data, governance and models – now, all in one place. As a listener of Bell Curve, you can use code "BELLCURVE10" for a 10% discount when signing up to Blockworks Research https://www.blockworksresearch.com/ - - Resources: RaaS: The Key Ingredient to a Rollup-Centric Roadmap https://www.reverie.ooo/post/raas-the-key-ingredient-to-a-rollup-centric-roadmap - - Disclaimer: Nothing said on Bell Curve is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only, and any views expressed by anyone on the show are solely our opinions, not financial advice. Mike, Jason, Michael, Vance and our guests may hold positions in the companies, funds, or projects discussed.

Blake Coram is a seasoned supply chain professional with expertise in requirements gathering, solution design, and fostering cross-functional collaboration. In his current role as Director of Product Management at Manhattan Associates since November 2020, he has played a pivotal role in designing and implementing Manhattan's Warehouse Management software, integrating with third-party systems, and enhancing various software modules. Blake's career highlights include leading design efforts for multiple clients, mentoring consultants, and contributing to internal initiatives.SHOW SUMMARYIn this episode of eCom Logistics Podcast, Dan Coll and Ninaad Acharya welcomes Blake Coram to share his journey from a consultant to product management at Manhattan, emphasizing the evolution of warehouse management solutions and the move towards unified supply chain solutions. They discuss topics like automation, robotics as a service, large language models, and digital twins, highlighting the exciting innovations shaping the future of supply chain and warehousing operationsHIGHLIGHTS[00:01:20] Blake Coram's journey to product management at Manhattan Associates[00:03:45] Evolution of warehouse management solutions[00:05:30] The shift towards unified supply chain solutions[00:09:15] The role of automation in modern warehousing[00:11:40] Robotics as a Service (RaaS) and its benefits[00:15:20] The potential of large language models in supply chain operations[00:17:45] Digital twins for optimizing warehouse operations[00:20:10] Balancing automation with human involvement[00:22:30] Addressing concerns about automation and job displacement[00:25:15] The importance of adaptability in supply chain technology[00:28:00] The future of supply chain and warehousingQUOTES[00:06:53] Blake Coram: "It's no longer about siloed solutions; it's about integrated, unified supply chain solutions that adapt and execute efficiently."[00:09:47] Blake Coram: "Data is the lifeblood of modern supply chains. Real-time analytics enable smarter, more agile decisions in an ever-changing market."[00:15:28] Blake Coram: "Sustainability isn't just a buzzword anymore; it's a core driver in supply chain strategy. Companies that embrace eco-friendly practices will thrive."[00:22:02] Ninaad Acharya: "I think there's a world in the not too distant future where it's robots as a service. The man-machine execution within warehouses is becoming more prevalent."Find out more about Blake in the link below:LinkedIn: https://www.linkedin.com/in/blake-coram-1633b231/

In this episode, we chat with Andrew Huang, founder of Conduit and Brandon Curtis, a long-time infrastructure builder and investor. We begin with a brief overview of Andrew's background and what led him to build a Rollup-as-a-Service (RaaS) business. We then speak to the value proposition of RaaS businesses, compare them to previous iterations of blockchain-as-a-service, and hear why Andrew believes that this is the “cloud moment” for crypto. We also explore Conduit's strategic positioning and future roadmap – as well as value accrual across stakeholders in the rollup stack. Stick around until the end to hear Andrew's thoughts on who his dream customer would be!

Timestamps: 01:23 - Choosing robotics as his career 08:06 - Building a customer base 17:28 - How AI is used in robotics 19:47 - What does RaaS entail? (Robotics as a Service) 32:17 - How to raise money in a tricky economy About Péter Fankhauser: Péter Fankhauser is the CEO and co-founder at ANYbotics, a robotics company that develops autonomous robots for industrial inspections. He started his robotics journey at ETH Zurich, receiving a Master's and Ph.D. in Robotics. The idea for the company was ignited by a project he worked on during his time at ETH. ANYbotics has crafted two types of business models: the first is Robots as a Service (RaaS), which allows customers to hire a robot with comprehensive hardware, software, and service support within the inspection space, and the second is for customers who opt to purchase the robot and software as a lifetime license. This approach varies based on geographical factors and budget allocation strategies. Regardless of the chosen model, ANYbotics focuses on enabling customers to optimize their workforce and allocate human resources to value-adding, creative, and decision-making activities. Notably, the concern that robots will replace the human workforce is not really relevant in this specific industry, since the jobs performed are so hazardous that not many human workers are currently willing to perform them at all. An added benefit to switching to robots, besides human safety and well-being, is the improved accuracy in gathering data. ANYbotics' customers have discovered another unexpected benefit of incorporating robots into their operations – recruitment. By showcasing their use of cutting-edge robotics, companies attract young talent by offering the opportunity to become plant operators and robotics operators. This unique selling point highlights the innovative nature of the work environment and adds an attractive dimension to the job. It's a testament to the fact that robotics is not about replacing people but empowering and collaborating with them. Péter and his team at ANYbotics recognize that their vision has a global reach. With the high entry barriers and immense potential of the robotics industry, their ambitions lie in becoming international leaders in the field. By striving to be the best globally, ANYbotics aims to drive down costs, expand its reach, and support customers globally. The goal is to establish a sizable company capable of meeting the demands of thousands of robots, ultimately positioning ANYbotics as a world leader in the industry. From robotics as a service to attracting talent through its cutting-edge technology, ANYbotics continues to disrupt the industry while maintaining a robust partnership approach, hoping to witness international success and perhaps even do an IPO. Memorable quotes: “I was always building things when I was a kid, and all I would think was, ‘how can I help people with this, market this and get it out into the world?' '' “We decided we wanted to be a product and robotics solution company versus a research company, and part of that is really understanding the customer problem.” Don't forget to give us a follow on our Twitter, Instagram, Facebook and Linkedin accounts, so you can always stay up to date with our latest initiatives. That way, there's no excuse for missing out on live shows, weekly give-aways or founders dinners!

We're in a clothing waste crisis, buying more clothes than ever but tossing them out twice as fast. Americans trash 11.3 million tons of textiles annually – a whopping 2,150 garments every second! The fashion industry, especially fast fashion, is also one of the world's biggest polluters, responsible for 10% of global carbon emissions. But there's a growing movement among consumers and retailers to give the unwanted threads clogging our closets a new lease on life. Enter thredUP, one of the largest secondhand apparel marketplaces for women's and kids' clothes, shoes, and accessories. Founded by a cash-strapped Harvard grad student named James Reinhart and his co-founders in 2009, thredUP is today one of the largest online resale sites But it's also a massive technology and logistics company. With sprawling automated distribution centers and a custom-built, proprietary operating platform, thredUP processes an impressive 100,000 unique items daily. In addition to its consumer-facing marketplace, the company also runs a Resale-as-a-Service (RaaS) program to help brands and retailers participate in the growing secondhand economy. James joins us to share his unconventional founder story and how his lifelong obsession with market failures and solving really hard problems has been a driving force behind thredUP's growth. He talks about how Gen Z is leading the sustainable resale revolution and why the circular economy will change the way the world shops.

Matt Pines rejoins the podcast to talk cybersecurity basics, including the overlooked importance of non-state actors and how that can affect near-shoring. From there, Matt and Jacob explore what changing technology can mean in a more geopolitical world, especially as it relates to Artificial Intelligence, before talking about aliens. Yup, aliens. Matt is a management consultant at Krebs Stamos and is appearing on the podcast in a strictly personal capacity.Survey: https://forms.gle/NZs3sAZFoahxzycH6--Timestamps:(0:00) - Intro(2:00) - TikTok and Cybersecurity Basics(9:00) - Near-shoring Pitfalls(16:13) - Chinese Hardware Vulnerabilities(22:40) - Which Countries are Safest from Chinese Ransomware?(25:13) - New Frontiers for Threat Actors(31:16) - Everyone is Networked, Everyone is at Risk(42:06) - Is Privacy a Dead?(49:08) - Aliens :)--CI LinkedIn: https://www.linkedin.com/company/cognitive-investments/CI Website: https://cognitive.investmentsCI Twitter: https://twitter.com/CognitiveInvestJacob LinkedIn: https://www.linkedin.com/in/jacob-l-s-a9337416/Jacob Twitter: https://twitter.com/JacobShapSubscribe to the Newsletter: https://investments.us17.list-manage.com/subscribe?u=156086d89c91a42d264546df7&id=4e31ca1340--Cognitive Investments is an investment advisory firm, founded in 2019 that provides clients with a nuanced array of financial planning, investment advisory and wealth management services. We aim to grow both our clients' material wealth (i.e. their existing financial assets) and their human wealth (i.e. their ability to make good strategic decisions for their business, family, and career).--Disclaimer: Nothing discussed on Cognitive Dissidents should be considered as investment advice. Please always do your own research & speak to a financial advisor before putting your money into the markets.This podcast uses the following third-party services for analysis: Chartable - https://chartable.com/privacyPodtrac - https://analytics.podtrac.com/privacy-policy-gdrp

GGZ Oost Brabant heeft als eerste zorginstelling robots in dienst genomen. Met de inzet van robotica probeert de instelling toekomstbestendige oplossingen te vinden voor het nijpende personeelstekort in de zorg. Daarnaast vragen ze aandacht voor de huidige uitdagingen van de sector.Die aandacht krijgen zij van ons. Want als je robot Tonnie ‘in dienst neemt' dan hebben wij vragen. Vragen over het hoe, wat en waarom, maar ook over de technische uitdagingen, beveiliging, privacy en alle andere uitdagingen waar nerds direct aan denken.We praten met Nicole Verhoeven, Manager Kwaliteit en Innovatie bij GGZ Oost Brabant en met Mike van Rijswijk, Directeur van The Innovation Playground. De persoon die de robots aan het werk zet en degene die ze helpt te ontwikkelen dus.Tijdschema00:00:00 Reclame: ICT Group00:00:56 Voorstellen: Nicole Verhoeven00:01:24 Voorstellen: Mike van Rijswijk00:02:21 Hoe bouw je een sociale robot voor de zorg?00:03:55 Robots met een vleugje menselijkheid00:20:10 Robots as a Service (RaaS)00:31:43 Interactie met je robot00:42:27 Hoe hou je robots op lange termijn in gebruik?00:49:43 Hoe reageren medewerkers?00:54:02 Onderlinge beveiligde communicatie00:56:52 Wanneer is Tonnie een succes?01:02:45 Vragen van de luisteraars01:03:08 Waar komt de naam Tonnie vandaan?01:05:41 Zitten er easter eggs in Tonnie?01:07:46 Gaat Tonnie samenwerken met ChatGPT01:12:10 Worden straks alle leuke taakjes van zorgmedewerkers afgepakt?01:16:51 Moeten we niet eerst de oorzaak oplossen?01:18:19 Tips01:31:30 Afkondiging01:32:11 Cadeautjes!!01:33:05 De vraag van Anne BrasTipsRuurd SandersMizuno Wave Sky 6Steun Nabu CasaKijk uit met je iPhone pincodeRandal PeelenEverything Wrong with Jurassic World DominionMeetup zaterdag 18 maart 2023Mike van RijswijkHou het nou gewoon lekker simpelNicole VerhoevenTechnologische innovatie is vooral sociale innovatie: ga uit van inspiratie van medewerkersZie het privacybeleid op https://art19.com/privacy en de privacyverklaring van Californië op https://art19.com/privacy#do-not-sell-my-info.

What's up, everyone?! In this episode, Ryan and Shannon discuss how lower Ransomware as a Service (RAAS) payoffs may be causing hackers to be laid off. Please LISTEN

Live from Manifest 2023 in the Pitney Bowes booth, The New warehouse was pleased to interview Stephanie Cannon, Senior Vice President of Operations Excellence and Collaborative Innovation. Pitney Bowes is a global technology company that provides innovative solutions to businesses worldwide. Their services include shipping, mailing, data management, e-commerce, and financial services. Stephanie discusses Robots as a Service (RaaS), autonomous transportation, and the collaborative innovation program with robotics companies like Plus One Robotics and Ambi Robotics. Want to get a shoutout for you and your company on the podcast? Become a VIP listener here. Save on internet for your facility by using our special discount with Meter. Learn more here.Get labor with no fees for one month! Utilize Veryable for on-demand labor by signing your business up here. Follow us on LinkedIn here for more content.

J. Crew launched its resale program, J Crew Always, with Thredup's Resale as a Service (RaaS) last week, well-timed to be announced at NRF's Big Show. Given the existing Madewell program with ThredUP, it wasn't surprising to see J Crew enter resale in this way.According to WWD, “The J. Crew items already listed on ThredUp are not part of the J. Crew Always initiative.” Historically it has been a marketplace limitation to pull in thousands of items already listed on the branded resale site, often degrading the brand given the wide range of item conditions. This program seems to be a significant step forward to designate only some of the items as fitting branded resale.Second, segmented inventory allows J Crew to sell in select stores. According to a Retail Dive article, “the 40-year-old brand is leveraging its longevity with ‘J. Crew Vintage,' a curated collection for men and women to be sold at select stores, including two in New York City.” It is a smart move for J Crew as it provides a reason to visit a physical store and leverages store traffic to create awareness of the online program.Similarly, Depop launched a collection in combination with Tommy Hilfiger. No bells and whistles to call out but worth noting as more brands are looking to capitalize on the shift to secondhand. RaaS programs have come a long way in recent years with more customizable storefronts and now more segmented inventory. However, brands need to remember even with these steps, and it is far from a branded experience. In the end, J Crew Always will operate on the same technology as ThredUP, constrained on brand choices such as product title, description, search, and markdowns which optimizes ThredUP, not the J Crew brand. Additionally, at some point, all brands will need to own their customers and keep a competitor from sharing sales data for a significant and growing channel.The New York Times started their piece, Rolex Now Has a Resale Program. The Watch World Quakes, “There is a saying in the high-end watch trade that there are only two kinds of watchmakers: Rolex and everyone else.” It's an excellent article for anyone in the resale space. Rolex is not only instructive for the watch category, but the high-end watch category is instructive for fashion, luxury handbags, ready-to-wear, outdoor gear, and footwear companies. There are learnings here for how to view items, even if many are aspirational.Rolex Certified Pre-Owned (CPO) validates the secondhand market for many customers and undoubtedly increases the value of every new Rolex sold–as a product becomes an asset. By enforcing CPO standards, Rolex will also drive up the secondary price of these timepieces, furthering the quality of the brand–i.e., CPO Rolex will sell at a premium, which is a good thing for Rolex. Finally, HBR published an article, How Sustainability Efforts Fall Apart; an excellent read for anyone in a larger brand organization working on resale. I listened this morning as Max Bittner, CEO of Vestiaire Collective, answered a question about the metrics his investors watch as a B Corp. Max's straight-faced answer was GMV, Revenue, and Net Profit. The audience gasped as he didn't mention CO2, Water, etc. I agree with Max's answer and would have likely added that resale models achieving business value is the way we will achieve more sustainable, circular models. Brands must make similar or even more money on circular models if we want them to take hold and ultimately provide more sustainable solutions to the fashion industry.The So WhatEven as marketplace platforms provide more options for brands, they ultimately are incentivized to build their customer base rather than the brand.Rolex's move into CPO can be instructive for others in the high-end watch industry as other industries, including fashion, luxury, outdoor, and footwear.

Guardforce AI Chief Financial Officer Brian Ma joins Natalie Stoberman from the Proactive studio to share more details behind the acquisition of Shenzhen Kewei's robot business-related assets in China. Ma says the agreement includes Kewei transferring select equipment assets, client base in the sales pipeline and related sales channels and staff. Also included are rights to the permanent use of Kewei's patents which would provide an opportunity to enhance Guardforce AI's new Robot-as-a-Service (RaaS) sales and capabilities. #proactiveinvestors #guardforceai #NASDAQ #GFAI #GFAIW #kewei #acquisition #robotics #robotsasaservice #assets #business #patents

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"The thing that we've heard over and over and over again from our customers is 'Yeah, we've been planning to automate. We're right about to do it. We've been planning this project for the last five or ten years.' Well, why don't I see a robot over here?" asks Saman Farid, CEO of Formic. Host Cathy Ma chats with Farid about why automation is no longer a luxury for manufacturers and how Formic's Robots-as-a-Service (RaaS) business model is making automation more accessible.

Recent reports indicate a decrease in ransomware attacks. Should organizations breathe a sigh of relief—or batten down the hatches? In this episode, Sean talks with Alix Weaver, Solutions Architect at Semperis, about the ways that ransomware gangs are reinventing themselves and changing tactics and why ransomware as a service is gaining traction.

Recent reports indicate a decrease in ransomware attacks. Should organizations breathe a sigh of relief—or batten down the hatches? In this episode, Sean talks with Alix Weaver, Solutions Architect at Semperis, about the ways that ransomware gangs are reinventing themselves and changing tactics and why ransomware as a service is gaining traction.

Microsoft's recent release of their Security Insider talks about Ransomware as a Service (RaaS) called Extortion Economics. This episode talks about the main data points from their study and gives a shocking insight to how ransomware gets into an organization and how long you have to stop the spread. Source - https://www.microsoft.com/en-us/security/business/security-insider/anatomy-of-an-external-attack-surface/extortion-economics/ Be aware, be safe. Support the show and get access to behind the scenes content as a patron - https://www.patreon.com/SecurityInFive *** Support the podcast with a cup of coffee *** - Ko-Fi Security In Five Mighty Mackenzie - https://www.facebook.com/mightymackie Where you can find Security In Five - https://linktr.ee/binaryblogger Email - bblogger@protonmail.com

A eficiência está no centro do negócio da DHL Supply Chain, empresa global do setor de armazenagem e distribuição. E para tornar sua operação logística ainda mais eficiente, a companhia tem apostado na robótica e na automação como parte de uma estratégia de "Logística 4.0". O projeto piloto, que usa uma paleteira inteligente para separação de pedidos, já está em testes no Centro de Distribuição (CD) da DHL em Cabreúva, no interior de São Paulo. Os resultados dos testes já são promissores, com uma redução de até 50% no tempo de separação. Neste episódio de ‘E agora, TI?', Lilio Neto, evangelizador em Inovação da DHL Supply Chain, fala sobre como surgiu o projeto de automação da empresa, sobre o conceito de Robotics-as-a-Service (RaaS) e sobre um dos pilares essenciais de uma iniciativa envolvendo robôs: a segurança.

How are consumers changing consumption patterns as inflation pushes CPG prices higher? On this episode of The Food Institute Podcast, Ibotta SVP Chris Jensen discusses how consumers are gravitating towards at-home eating, tactics retailers are employing to maintain and grow their customer bases, and how loyalty programs can benefit consumers and retailers alike. More About Chris Jensen: Chris leads revenue and operations for Ibotta, including a team of 250+ individuals in sales, account management and operations. His team is responsible for bringing to market Ibotta's Rewards as a Service (RaaS) solution to strengthen the ties between advertisers, retailers, publishers and consumers, leveraging best-in-class technology and real-time performance analytics. Prior to joining Ibotta, Chris served as global marketing director for Whole Foods Market, building WFM's performance marketing function and driving more than $300 million in incremental revenue through the launch of new marketing vehicles. The gaps he identified in the card linked offer space while at Whole Foods inspired him to launch Givella, a fintech-based marketing platform dedicated to deepening the connection between brands and consumers through a nonprofit giving incentive. More About Ibotta: Built in Denver, CO, Ibotta (“I bought a…”) is a cash back rewards platform that has delivered more than $1.1 billion in cumulative rewards to its users. Launched in 2012, Ibotta has more than 40 million downloads, is one of the most frequently used shopping platforms in the United States, and offers cash back on purchases on more than 2,700 leading brands and retail partners. In addition to its owned properties, Ibotta also powers rewards programs for top retailers and makes its offer content available on a number of leading websites and apps through the Ibotta Performance Network. The Ibotta Performance Network is the CPG industry's leading performance marketing network. With a reach of more than 120M consumers across the country's top retailers, Ibotta delivers promotions at unprecedented scale with performance marketing efficiency. The IPN is a one-stop shop where advertisers can reach consumers during their shopping journey and improve performance across all marketing channels, with unparalleled precision and measurability. Learn more at: https://home.ibotta.com/ Sign Up for the Food Institute's Retail 360 Newsletter: https://lp.constantcontactpages.com/su/cIOL5ME/FIRetail360

Guardforce AI chairman Terence Yap joined Proactive's Stephen Gunnion with details of the company's decision to open new offices in Tokyo and San Francisco as it expands its Robotics-as-a-Service (RaaS) business in those two markets. Yap telling Proactive that the two markets represent significant opportunities for Guardforce's RaaS business line. He also updated investors on recent acquisitions in China and the extension of its contract as the automated teller machine (ATM) service provider for Government Savings Bank (GSB) in Thailand.

In our third Expert Insights update for 2022, Cybersecurity Consultant, David Gittens shares his thoughts on, among other things: key trends in the current threat landscape; the Conti ransomware and what Caribbean countries can learn from the Costa Rican experience; what does Ransomware-as-a-Service (RaaS) mean; and the top three things businesses should be doing in 2022 to improve their network/IT security.    The episode, show notes and links to some of the things mentioned during the episode can be found at ICT Pulse Podcast Page (www.ict-pulse.com/category/podcast/)  Do subscribe and leave us a review!     Music credit: The Last Word (Oui Ma Chérie), by Andy Narrell Podcast editing support: Mayra Bonilla Lopez

Sign up for my Daily Fintech or Daily Digital Banking Newsletters here. Check out my latest podcast episode below: Welcome to another episode of our Daily Fintech Podcast. This podcast episode is sponsored by Payhawk. Payhawk is the most efficient credit card backed by powerful financial software to help companies stay in control of their spend. Try efficient, paperless, compliant spending today. THE NEWS HIGHLIGHT OF THE DAY IS Alphabet's Google (GOOG) has committed to invest $1.2 billion in Latin America over the next five years to support economic development and digital transformation in the region, where the company has had an active presence since 2005. The investment was announced by Google and Alphabet Inc. CEO Sundar Pichai during the IX Summit of the Americas, held this week in Los Angeles, California. JUST IN: The PayRetailers- Pago Digital- Paygol announces the launch of its first Social Responsibility campaign to support charitable causes in Latin America. ALSO: Railsr launched a new Rewards-as-a-Service (RaaS) product that enables brands to build their own branded rewards programmes.

Guardforce AI Co. Limited Chairman Terence Yap tells Proactive it has signed a supplemental letter of intent (LOI) with Shenzhen Kewei Robot Technology Co. Limited to acquire an additional twelve robotics companies in China as it advances its goal of becoming the world's leading provider of Robotics-as-a-Service (RaaS) solutions. The deal, valued at US$12 million based on one-time projected average revenues for the twelve companies over the next five years, follows its previously announced definitive agreement to acquire seven robotics companies in China, the company said.

Saman Farid believes that robots are a means to an end and while their importance is derived from the output they create, many companies are focused solely on the hardware itself. In this episode, we are joined by Saman Farid, the CEO of Formic which is a privately held Robotics as a Service (RaaS) company that focuses on the output rather than the hardware. He sheds light on the concept of Robotics as a Service and what this really means. On today's episode, you'll hear about the barriers to robot adoption in manufacturing, the development of technologies that make it possible to use industrial robots in a collaborative way, the challenges of implementation in this field, and how the declining costs of hardware are opening up more opportunities in this sector. You'll also learn more about why Saman believes that in the future, companies will either be building new robots, or operating them and generating value from them, but not both. To hear what excites Saman the most about the advancement of robotics in the next five years and why he believes that robots are not stealing jobs but creating more, listen now! I think eventually we'll get to the point where every robot by default is collaborative, and not just collaborative between robots and humans, but more importantly, collaborative between robots and other robots.” — @samanfarid Key Points from this Episode Saman Farid's thoughts on the concept of Robotics as a Service and what this really means. Thoughts on how innovative technologies tend to take hold during tumultuous times and how the pandemic is driving adoption. The labor shortage and supply chain challenges and how Formic is trying to formulate ideas to address these issues. The barriers to robot adoption in manufacturing. The types of tasks that Formic has had the most success in automating and those that still need work. The dynamic Saman sees in the use of collaborative robots versus more traditional caged-off industrial robots. The development of technologies that make it possible to use industrial robots in a collaborative way. The challenges of implementation and training in the development of this field. Business alignment challenges between companies that build robots and those that do Robotics as a Service. Saman's prediction that the differentiation between the hardware vendors of robots is decreasing and specialization is increasing. Thoughts on the declining costs for the hardware of robotics and the opportunities that this opens up in manufacturing. Saman's answer to the common question “Are robots stealing and destroying jobs?” What excites him the most about the advancement of robotics in the next five years.

Bonjour à tous et bienvenue dans le ZD Tech, le podcast quotidien de la rédaction de ZDNet. Je m'appelle Louis Adam et aujourd'hui, je vais vous parler du Ransomware-as-a-Service et de la façon dont ces groupes ont changé le visage du cybercrime.  Aujourd'hui, on parle beaucoup d'informatique « as-a-service », que ce soit pour du logiciel, de l'infrastructure ou des données. Le monde cybercriminel n'échappe pas à la tendance. Ces dernières années, le concept de Ransomware-as-a-Service (RaaS) a émergé afin de décrire les nouvelles organisations cybercriminelles spécialisées dans le ransomware. Un ransomware (ou rançongiciel en bon français) est un logiciel malveillant qui va chiffrer les données de la victime et rendre l'appareil inutilisable. Seul le paiement d'une rançon permet d'obtenir la clé de déchiffrement et de récupérer l'accès aux données. Depuis le début des années 2010, ce type de logiciel est devenu une manne financière considérable pour les cybercriminels. Mais développer et maintenir un rançongiciel n'est pas à la portée de n'importe qui. Alors, assez naturellement, les cybercriminels se sont réparti les tâches. Ceux qui étaient en capacité de développer des logiciels de ransomware ont proposé à d'autres groupes de les utiliser. C'est ce modèle qui a fait le succès de groupes connus, comme Conti, REvil ou encore Lockbit. Le groupe initial se concentre sur la conception, le développement et la maintenance du rançongiciel. Celui-ci doit être mis à jour régulièrement afin de contourner les protections des antivirus, et il faut aussi s'assurer que les outils de chiffrement et de déchiffrement fonctionnent comme prévu. Dans certains cas, le groupe s'occupe également de négocier les rançons avec les victimes et de diffuser d'éventuelles données volées pour accentuer la pression. Autour de ces groupes gravitent d'autres cybercriminels qui viennent louer l'utilisation du rançongiciel : on les appelle généralement les « affiliés ». Ils se chargent d'infiltrer les cibles, de se déplacer dans le réseau pour prendre le contrôle des appareils les plus intéressants et ensuite d'activer le rançongiciel. Et si au passage, ils peuvent mettre la main sur des données confidentielles, c'est toujours ça de pris. Ce mode de fonctionnement a commencé à voir le jour aux alentours de 2016, avant de se populariser largement au cours des deux dernières années. Et c'est un business florissant pour les développeurs de ransomwares. Différents modèles économiques sont proposés par les acteurs de ce type : certains proposent une simple location du ransomware à l'usage, tandis que d'autres passent des accords plus poussés avec leurs affiliés, prévoyant un partage des rançons récupérées. Et ce modèle rend les choses plus compliquées pour les forces de l'ordre : ce sont les affiliés qui prennent l'essentiel des risques et qui sont le plus souvent arrêtés par les policiers. Les concepteurs du rançongiciel, eux, restent généralement à l'abri et se contentent de trouver de nouveaux volontaires pour faire tourner leur business.

Guest Jon DiMaggio, Chief Security Strategist at Analyst1, joins Dave Bittner to discuss his team's research "A History of REvil" that chronicles the rise and fall of REvil. The REvil gang is an organized criminal enterprise based primarily out of Russia that runs a Ransomware as a Service (RaaS) operation. The core members of the gang reside and operate out of Russia. REvil leverages hackers for hire, known as affiliates, to conduct the breach, steal victim data, delete backups, and infect victim systems with ransomware for a share of the profits. Affiliates primarily stem across eastern Europe, though a small percentage operate outside that region. In return, the core gang maintains and provides the ransomware payload, hosts the victim data leak/auction site, facilitates victim communication and payment services, and distributes the decryption key. In simpler terms, the core gang are the service provider and persona behind the operation, while the affiliates are the hired muscle facilitating attacks. Jon walks us through the team's findings and details REvil's story. The research can be found here: A History of REvil

Guest Jon DiMaggio, Chief Security Strategist at Analyst1, joins Dave Bittner to discuss his team's research "A History of REvil" that chronicles the rise and fall of REvil. The REvil gang is an organized criminal enterprise based primarily out of Russia that runs a Ransomware as a Service (RaaS) operation. The core members of the gang reside and operate out of Russia. REvil leverages hackers for hire, known as affiliates, to conduct the breach, steal victim data, delete backups, and infect victim systems with ransomware for a share of the profits. Affiliates primarily stem across eastern Europe, though a small percentage operate outside that region. In return, the core gang maintains and provides the ransomware payload, hosts the victim data leak/auction site, facilitates victim communication and payment services, and distributes the decryption key. In simpler terms, the core gang are the service provider and persona behind the operation, while the affiliates are the hired muscle facilitating attacks. Jon walks us through the team's findings and details REvil's story. The research can be found here: A History of REvil

En este programa nos visita con Eutimio Fernandez, Regional Sales Manager de ThreatQuotient. Con Eutimio hablamos sobre la necesidad que existe en las organizaciones de poner a trabajar la CiberInteligencia que obtienen de distintas fuentes. La forma de ponerla a trabajar muchas veces no es sencilla, pero para ello contamos con plataformas como ThreatQuotient. En nuestro apartado de noticias hablamos de una advertencia que hace el FBI sobre un grupo de Ransomware as a Service (RaaS), denominado BlackByte. La alerta es especialmente interesante ya que este grupo tiene como objetivo las infraestructuras críticas y han tenido bastante éxito en los últimos meses. Además, como en anteriores programas, los especialistas de Netskope nos acercaron la Píldora SASE. Ese nuevo paradigma que proveyendo de seguridad desde la nube, esta revolucionando la forma de entender la seguridad para los usuarios y empresas. En esta ocasión nos acompañó Federico Teti Sales Engineer de Netskope, Fede nos habló de cómo la solución de Netskope permite integrarse con muchos partners gracias a la tecnología CTE y entre las muchas integraciones que han desarrollado, existe una integración con ThreatQuotient. Además hablamos con Igor Lukic, uno de los organizadores de HackRon congreso de referencia en las Islas Canarias, concretamente en Tenerife. HackRon es noticia porque retoma su actividad este 25 de Febrero. También, contamos con la presencia de Alberto Rodríguez, miembro de RootedCON quién dio los nombres de los tres ganadores del sorteo de entradas de la RootedCON y planteó una nueva pregunta para el sorteo de 3 entradas para RootedCON. Los oyentes del programa que respondan correctamente en afterwork@capitalradio.es a la pregunta que plantea Alberto entran en el sorteo de 3 nuevas entradas para RootedCON. ¿Que animal había en el logo de la cuarta edición de RootedCON? Con Eutimio continuamos gran parte del programa conversando sobre los distintos aceptos que tiene la ciberinteligencia y como es necesario que plataformas como la de ThreatQuotient esté en las organizaciones para ayudar al SOAR y a la defensa de las organizaciones. Twitter: @ciberafterwork Instagram @ciberafterwork +info: https://psaneme.com/ https://bitlifemedia.com/ Píldora SASE: https://www.netskope.com/ https://resources.netskope.com/netskope-data-sheets/netskope-cloud-threat-exchange Noticias: https://unaaldia.hispasec.com/2022/02/el-fbi-avisa-de-que-el-ransomware-blackbyte-tiene-infraestructuras-criticas-como-objetivo.html ThreatQuotient: https://www.threatq.com/ RootedCON: https://www.rootedcon.com/ HackRon: https://hackron.com/

PLEASE JOIN US for podcast #6 of This Is Robotics: Radio News, a fresh, new and lively look at our wonderful world of global robotics...technology, business and people. #1 Global Robotics News Podcast. You're Going to Love What You Hear! The lineup for podcast #6 Robotics for the New Year: 2022! THREE HALLMARKS DEFINING COBOT SUCCESS  Three tech attributes showing themselves to be necessary for cobot success. Universal Robots, Techman, and Doosan share the knack, but better keep an eye on newcomer ELITE ROBOT.ROBOTS TO KEEP WINTER OLYMPICS SAFE The Winter Games are right around the corner. The massive Wukesong Arena is getting ready to host the ice hockey events for February's Beijing Winter Olympics 2022 (February 4 to 20). For 16 days, over 30 robots will be deployed to help keep the players, staff, and thousands of fans safe from COVID.ASK ANY COBOT: HUMAN WORKERS COST MORE THAN WAGES  Renting cobots: From Capex to Opex. Rent, lease, contract for, or Robots as a Service (RaaS)…whatever!  Not owning a cobot has a big upside that's getting bigger. HOORAY FOR CONSTRUCTION ROBOTICS: ON THE RISE FOR 2022 Construction site cacophony. We've all suffered through the annoying din. Construction is not only noisy and a traffic nightmare, but it's also inefficient, woefully expensive and dangerous. Thankfully, construction is now getting serious attention from automation and robotics, and 2022 might be a breakout year.CHINA'S NEW TREND: PRECISION ROBOTICS  Precision robotics is a key competitive advantage. China turns hard-to-do robotics, like welding, grinding and polishing, into a powerful new industry.AND MORE...   Join us at Asian Robotics Review or Apple Podcasts, Spotify, Google Podcasts, Stitcher, Pandora, TuneIn or where ever your podcast resource.Thanks. You're going to love what you hear!   Contact: News@ThisIsRobotics.com Website: Asian Robotics Review

In this episode, Marcus Edwardes speaks with Jesse Tinsley, a serial entrepreneur who got his start in tech at the age of 15. In 2012, he dropped out of college to found Job Mobz to provide on-demand recruiting for technology companies.He is a regular contributor to Forbes and SourceCon, and he hosts The People Podcast, where he interviews HR, recruiting leaders, and tech founders on the latest trends.Listen in as Jesse discusses Job Mobz' Recruitment as a Service (RaaS) business model, the approach his team takes towards recruitment as opposed to that of traditional agency or internal teams, and why the company ultimately abides by the ethos: The outcome is what matters, not the path we took to get there.Jesse talks about the fundamental importance of building a brand that naturally attracts ideal clients, which he believes trumps any sort of outreach campaign. He says that the key to cultivating a powerful brand is to consistently create authentic, engaging, informative content.Finally, Jesse reacts to a few of his most provocative social media posts.What You'll Learn in This Episode:●      [02:52] About Job Mobz' Recruitment as a Service (RaaS) business model●      [06:45] Training from the ground-up●      [10:53] Common areas noticed by Jesse in which clients can improve upon●      [13:38] The power of building a brand●      [16:46] Jesse's content strategy and how to “make time” for it●      [20:26] Engaging with niche communities●      [24:26] Forging long-term relationships with clients●      [25:49] Jesse reacts to his best social media postsKey quotes:●      “The first thing that we screen for when we hire recruiters is communications, both written and verbal. And the reason is because I think a lot of recruiting comes down to communication for internal hiring.”●      “We'll take somebody who is ambitious and has strong communications versus has worse comms and a lot of experience, because a lot of it comes down not only to stakeholder management, but also candidate experience.”●      “We care about outcomes, not how we get there.”●      “The number one candidate channel in 2022 and beyond is none of the above. It's creating a brand, and having that brand funnel you candidates.”

On the Sixth Day of JOURNOS, we first look back on a ninja attack on American soil. Well, not really — but a guy in Kern County did dress up as one in September to ambush a special forces unit under a cloak of darkness. But speaking of vulnerabilities, how about that Colonial pipeline shitshow back in May? Among other things, it brought to light the burgeoning industry of Ransomware as a Service (RaaS), where organized crime starts to look a lot more like Salesforce than the Gambino Family.  While the threat of ninja attack is nothing to be worried about in the grand scheme of things, the notion of a forever cyberwar certainly is. Problem is, we're just too used to fearing The Bomb.  

Ransomware as a service (RaaS) is a subscription-based model that enables affiliates to use already-developed ransomware tools to execute ransomware attacks. Affiliates earn a percentage of each successful ransom payment. Ransomware as a Service (RaaS) is an adoption of the Software as a Service (SaaS) business model. Ransomware Group Quits International Feds Going After Renting Ransomware Attacks Every day Big Tech and Mass Media make it hard to find out what is going on with the internet. The suppression of information is a danger to all of us. Social media attempts to shape news and information by over-amplification of disinformation. This podcast hope to give information and provide insights from Join our community!! Subscribe to the Insecurity Brief podcast now on every platform we can find Follow me on Twitter @trip_elix Links Our Website: https://www.tripelix.com/insecurity/ransomware-group-quits-international-feds-going-after-renting-ransomware-attacks/ Youtube: https://youtu.be/Wr_4zFKFxI8 Rumble: https://rumble.com/vooxnh-ransomware-group-quits-international-feds-going-after-renting-ransomware-at.html iTunes: https://podcasts.apple.com/us/podcast/ransomware-group-quits-international-feds-going-after/id1583788677?i=1000540718566 Spotify: https://open.spotify.com/episode/5J56Z3RQyTyQlTKDkEndDC Trip’s books https://www.tripelix.com/merch #Ransomware BlackMatter Ransomware Reportedly Shutting Down; Latest Analysis Released An analysis of new samples of BlackMatter ransomware for Windows and Linux has revealed the extent to which the operators have continually added new features and encryption capabilities in successive iterations over a three-month period. No fewer than 10 Windows and two Linux versions of the ransomware have been observed in the wild to date, Group-IB threat researcher Andrei Zhdanov said in a report shared with The Hacker News, pointing out the changes in the implementation of the ChaCha20 encryption algorithm used to encrypt the contents of the files. https://thehackernews.com/2021/11/blackmatter-ransomware-reportedly.html RANSOMWARE AS A SERVICE (RAAS) EXPLAINED Ransomware as a Service (RaaS) is a business model used by ransomware developers, in which they lease ransomware variants in the same way that legitimate software developers lease SaaS products. RaaS gives everyone, even people without much technical knowledge, the ability to launch ransomware attacks just by signing up for a se

If the single most important component of a camera is the twelve inches behind it and the “camera is a license to explore” then let's hit the motor drive because we've got a lot of scenery to cover! We start with an appetite so large for taking pictures that consumer interest groups are now asking for receipts. We move on to dadada and password reuse, the inflationary pressure on phishing, and a suggestion that T-mobile might want to be a bit more polished in their breach news releases. We end up with a demonstration of a solid backup and recovery process and a kid who is going back to church with his camera. You're going to love this week's IT Privacy and Security update … frame, by frame! "We start with a story about reinvention: There's been a lot of press lately about Ransomware as a Service (RaaS) groups disappearing. The truth is, when you make as much money as they do, it's hard to just walk away. So here are this weeks RaaS Renames: Darkside has become BlackMatter DoppelPaymer is now known as Grief and Avaddon shall henceforth be known as Haron How do we know? Much of the signature software in use by the new gangs is bit-for-bit the same as was used by their earlier alias."... Find this week's full transcript at Discuss.daml.com --- Send in a voice message: https://anchor.fm/rps5/message

Kaseya VSA, a remote management software, experienced a breach over the holiday weekend that is already impacting a number of clients. It appears that this attack is connected to the Russian hacker gang known as REvil—but it has not been determined whether or not it is the work of REvil itself or an affiliate in their Ransomware as a Service (RaaS) program (and yes, that's a thing).Evan and Brad break down the attack on this week's UNSECURITY episode.Additionally, and flying under the radar because of Kaseya, news broke on June 30th about an impressive and potentially very damaging vulnerability in the Microsoft Print Spooler service. This has actually impacted a larger number of customers than Kaseya (millions of servers) and likely would have been bigger news had it not been for Kaseya.If you feel you've been impacted by the Kaseya attack directly, or would like more information, visit: https://helpdesk.kaseya.com/hc/en-gb/articles/4403440684689Here is more information on the Microsoft bug: https://www.yahoo.com/entertainment/microsoft-sounds-urgent-warning-windows-022541397.html?Additionally, Evan was on KARE 11 discussing Kaseya yesterday (July 5): https://www.kare11.com/video/news/local/breaking-the-news/ransomware-crime-wave-keeps-us-on-edge/89-44bed2c8-bbb1-4572-abc9-53551c6c74fa?jwsource=clGive episode 138 a watch/listen and send questions, comments, and feedback to unsecurity@protonmail.com.

Welcome to this week's episode of the PEBCAK Podcast! We’ve got three amazing stories this week so sit back, relax, and keep being awesome! Be sure to stick around for our Dad Joke of the Week. (DJOW)PEBCAK - Acronym of “problem exists between chair and keyboard.” Darkside ransomware devastates US East Coast gas supply. A deeper dive into Ransomware as a Service (RaaS)https://www.cnbc.com/2021/05/13/colonial-pipeline-paid-ransom-to-hackers-source-says.htmlhttps://www.chrislouie.net/blog/2019/10/20/ransomware-as-a-service-a-race-to-the-bottomhttps://krebsonsecurity.com/2021/05/darkside-ransomware-gang-quits-after-servers-bitcoin-stash-seized/Peloton's troubles extend into the cyber worldhttps://news.yahoo.com/peloton-fixes-bug-reportedly-exposed-170541480.htmlhttps://www.pentestpartners.com/security-blog/tour-de-peloton-exposed-user-data/Fun Western Union Storieshttps://www.westernunion.com/us/en/fraudawareness/fraud-report-fraud.htmlhttps://www.bustathief.com/western-union-moneygram-popular-scammer-payment-options/Proud dad moment for Glenn!Dad Joke of the Week (DJOW)Remember, your chances of getting a raise at work just improved by 20% now that you've listened to the podcast. If you know anyone else who would like a 20% better chance of a raise, please share this podcast with them!Find the hosts on LinkedIn:Chris - https://www.linkedin.com/in/chlouie/Brian - https://www.linkedin.com/in/briandeitch-sase/Glenn - https://www.linkedin.com/in/glennmedina/

Welcome to this week's episode of the PEBCAK Podcast!  We've got three amazing stories this week so sit back, relax, and keep being awesome!  Be sure to stick around for our Dad Joke of the Week. (DJOW) PEBCAK - Acronym of “problem exists between chair and keyboard.”   Darkside ransomware devastates US East Coast gas supply.  A deeper dive into Ransomware as a Service (RaaS) https://www.cnbc.com/2021/05/13/colonial-pipeline-paid-ransom-to-hackers-source-says.html https://www.chrislouie.net/blog/2019/10/20/ransomware-as-a-service-a-race-to-the-bottom https://krebsonsecurity.com/2021/05/darkside-ransomware-gang-quits-after-servers-bitcoin-stash-seized/   Peloton's troubles extend into the cyber world https://news.yahoo.com/peloton-fixes-bug-reportedly-exposed-170541480.html https://www.pentestpartners.com/security-blog/tour-de-peloton-exposed-user-data/   Fun Western Union Stories https://www.westernunion.com/us/en/fraudawareness/fraud-report-fraud.html https://www.bustathief.com/western-union-moneygram-popular-scammer-payment-options/   Proud dad moment for Glenn!   Dad Joke of the Week (DJOW)   Remember, your chances of getting a raise at work just improved by 20% now that you've listened to the podcast.  If you know anyone else who would like a 20% better chance of a raise, please share this podcast with them!   Find the hosts on LinkedIn: Chris - https://www.linkedin.com/in/chlouie/ Brian - https://www.linkedin.com/in/briandeitch-sase/ Glenn - https://www.linkedin.com/in/glennmedina/

We've all heard of Software-as-a-Service (SaaS) and, of course, the hardware needed for that software to work. But what happens when SaaS and complex hardware are combined? Paul Willard, a founding partner at grep -vc, refers to this as RaaS or Robotics-as-a-Service. In this episode of Over the Air, Paul tells Ryan about… - What RaaS is and why it's valuable - How his rare background makes him the perfect RaaS investor - What he looks for in founders - The robot he can't wait for someone to build Over The Air

Nicolaus Radford joins Crownsmen Energy to discuss Houston Mechatronics. They are developing an ecosystem of cloud-based subsea robots, software, and subsea services delivered in a modern business model to the offshore industry. These include our flagship product, Aquanaut, its Dept. of Defense counterpart, and a suite of hardware and software to update existing ROVs(Remotely operated underwater vehicle). HMI's robotic systems will be delivered to commercial and Department of Defense (DoD) customers primarily through a Robotics as a Service (RaaS) subscription business model but also direct product sales where required. RaaS products are controlled through HMI's Wavelink, our over the horizon remote connectivity. This modernized approach to subsea robotics as a service has also resulted in the development of a range of products for retrofit/upgrading legacy ROV/AUV platforms. Nicolaus believes that there are many changes to make to conventional ROVs and AUVs(Autonomous underwater vehicles), that will ensure near term revenue opportunities and help push the entire industry forward thereby also increasing our overall value. Our services provide customers the necessary data and manipulation capability to support maximizing production and improving asset value while minimizing their operating footprint, operating cost, carbon footprint, and offshore HS&E exposure. Watch Episode Here: https://youtu.be/mRNFL1C-2Gw

Chameleon Technologies is a 20-year-old company servicing both traditional and  technology businesses and they have three divisions. They work with small, mid-sized, and large companies. Their divisions are:Chameleon Staffing is a seasoned executive search and IT recruiting agency. Chameleon BI is focused on delivering solutions in the data services space.Reporting as a Service (RaaS) is their newest division.Melissa discusses her three divisions and how she keeps two teams motivated, while working remotely.  You can see more about the firm at www.chameleontechnologiesinc.com.