Podcasts about industries

Join AI host Roxie Rush on Mr. Beast Biography Flash as she covers the major February-March 2026 developments shaking up the MrBeast empire — including Beast Industries' acquisition of teen financial app Step, Jimmy Donaldson's mission to provide financial education to millions, the trademarking of Beast Financial, and the swift firing of a North Carolina editor following insider trading allegations on prediction market platform Kalshi. Roxie breaks down what these moves mean for the $5 billion content-to-conglomerate transformation and why this could be a defining moment in creator economy history.Loved this episode? Discover more original shows from the Quiet Please Network at QuietPlease.ai, explore our curated favorites here amzn.to/42YoQGI, and catch just a slice of our AI hosts in action on Instagram at instagram.com/claredelish and YouTube at youtube.com/@DIYHOMEGARDENTVThis content was created in partnership and with the help of Artificial Intelligence AI

Pool Pros text questions hereThis week, Rudy tackles something the “state of the industry” reports don't always capture:First: How the War on Iran is likely to impact the U.S. Boric Acid/Borax MarketNext, the emotional strain underneath the numbers.From Florida techs charging $70–$100 per month (including chemicals) and still feeling squeezed… To competitors undercutting bids out of fear… To Amazon underpricing distribution channels…The conversation isn't about collapse.It's about reorganization under pressure.

The reception to our recent post on Code Reviews has been strong. Catch up!Amid a maelstrom of discussion on whether or not AI is killing SaaS, one of the top publicly listed SaaS companies in the world has just reported record revenues, clearing well over $1.1B in ARR for the first time with a 28% margin. As we comment on the pod, Aaron Levie is the rare public company CEO equally at home in both worlds of Silicon Valley and Wall Street/Main Street, by day helping 70% of the Fortune 500 with their Enterprise Advanced Suite, and yet by night is often found in the basements of early startups and tweeting viral insights about the future of agents.Now that both Cursor, Cloudflare, Perplexity, Anthropic and more have made Filesystems and Sandboxes and various forms of “Just Give the Agent a Box” cool (not just cool; it is now one of the single hottest areas in AI infrastructure growing 100% MoM), we find it a delightfully appropriate time to do the episode with the OG CEO who has been giving humans and computers Boxes since he was a college dropout pitching VCs at a Michael Arrington house party.Enjoy our special pod, with fan favorite returning guest/guest cohost Jeff Huber!Note: We didn't directly discuss the AI vs SaaS debate - Aaron has done many, many, many other podcasts on that, and you should read his definitive essay on it. Most commentators do not understand SaaS businesses because they have never scaled one themselves, and deeply reflected on what the true value proposition of SaaS is.We also discuss Your Company is a Filesystem:We also shoutout CTO Ben Kus' and the AI team, who talked about the technical architecture and will return for AIE WF 2026.Full Video EpisodeTimestamps* 00:00 Adapting Work for Agents* 01:29 Why Every Agent Needs a Box* 04:38 Agent Governance and Identity* 11:28 Why Coding Agents Took Off First* 21:42 Context Engineering and Search Limits* 31:29 Inside Agent Evals* 33:23 Industries and Datasets* 35:22 Building the Agent Team* 38:50 Read Write Agent Workflows* 41:54 Docs Graphs and Founder Mode* 55:38 Token FOMO Culture* 56:31 Production Function Secrets* 01:01:08 Film Roots to Box* 01:03:38 AI Future of Movies* 01:06:47 Media DevRel and EngineeringTranscriptAdapting Work for AgentsAaron Levie: Like you don't write code, you talk to an agent and it goes and does it for you, and you may be at best review it. That's even probably like, like largely not even what you're doing. What's happening is we are changing our work to make the agents effective. In that model, the agent didn't really adapt to how we work.We basically adapted to how the agent works. All of the economy has to go through that exact same evolution. Right now, it's a huge asset and an advantage for the teams that do it early and that are kinda wired into doing this ‘cause you'll see compounding returns. But that's just gonna take a while for most companies to actually go and get this deployed.swyx: Welcome to the Lane Space Pod. We're back in the chroma studio with uh, chroma, CEO, Jeff Hoover. Welcome returning guest now guest host.Aaron Levie: It's a pleasure. Wow. How'd you get upgraded to, uh, to that?swyx: Because he's like the perfect guy to be guest those for you.Aaron Levie: That makes sense actually, for We love context. We, we both really love context le we really do.We really do.swyx: Uh, and we're here with, uh, Aaron Levy. Welcome.Aaron Levie: Thank you. Good to, uh, good to be [00:01:00] here.swyx: Uh, yeah. So we've all met offline and like chatted a little bit, but like, it's always nice to get these things in person and conversation. Yeah. You just started off with so much energy. You're, you're super excited about agents.I loveAaron Levie: agents.swyx: Yeah. Open claw. Just got by, got bought by OpenAI. No, not bought, but you know, you know what I mean?Aaron Levie: Some, some, you know, acquihire. Executiveswyx: hire.Aaron Levie: Executive hire. Okay. Executive hire. Say,swyx: hey, that's my term. Okay. Um, what are you pounding the table on on agents? You have so many insightful tweets.Why Every Agent Needs a BoxAaron Levie: Well, the thing that, that we get super excited by that I think is probably, you know, should be relatively obvious is we've, we've built a platform to help enterprises manage their files and their, their corporate files and the permissions of who has access to those files and the sharing collaboration of those files.All of those files contain really, really important information for the enterprise. It might have your contracts, it might have your research materials, it might have marketing information, it might have your memos. All that data obviously has, you know, predominantly been used by humans. [00:02:00] But there's been one really interesting problem, which is that, you know, humans only really work with their files during an active engagement with them, and they kind of go away and you don't really see them for a long time.And all of a sudden, uh, with the power of AI and AI agents, all of that data becomes extremely relevant as this ongoing source of, of answers to new questions of data that will transform into, into something else that, that produces value in your organization. It, it contains the answer to the new employee that's onboarding, that needs to ramp up on a project.Um, it contains the answer to the right thing to sell a customer when you're having a conversation to them, with them contains the roadmap information that's gonna produce the next feature. So all that data. That previously we've been just sort of storing and, and you know, occasionally forgetting about, ‘cause we're only working on the new active stuff.All of that information becomes valuable to the enterprise and it's gonna become extremely valuable to end users because now they can have agents go find what they're looking for and produce new, new [00:03:00] value and new data on that information. And it's gonna become incredibly valuable to agents because agents can roam around and do a bunch of work and they're gonna need access to that data as well.And um, and you know, sometimes that will be an agent that is sort of working on behalf of, of, of you and, and effectively as you as and, and they are kind of accessing all of the same information that you have access to and, and operating as you in the system. And then sometimes there's gonna be agents that are just.Effectively autonomous and kind of run on their own and, and you're gonna collaborate and work with them kind of like you did another person. Open Claw being the most recent and maybe first real sort of, you know, kind of, you know, up updating everybody's, you know, views of this landscape version of, of what that could look like, which is, okay, I have an agent.It's on its own system, it's on its own computer, it has access to its own tools. I probably don't give it access to my entire life. I probably communicate with it like I would an assistant or a colleague and then it, it sort of has this sandbox environment. So all of that has massive implications for a platform that manage that [00:04:00] enterprise data.We think it's gonna just transform how we work with all of the enterprise content that we work with, and we just have to make sure we're building the right platform to support that.swyx: The sort of shorthand I put it is as people build agents, everybody's just realizing that every agent needs a box. Yes.And it's nice to be called box and just give everyone a box.Aaron Levie: Hey, I if I, you know, if we can make that go viral, uh, like I, I think that that terminology, I, that's theswyx: tagline. Every agentAaron Levie: needs a box. Every agent needs a box. If we can make that the headline of this, I'm fine with this. And that's the billboard I wanna like Yeah, exactly.Every agent needs a box. Um, I like it. Can we ship this? Like,swyx: okay, let's do it. Yeah.Aaron Levie: Uh, my work here is done and I got the value I needed outta this podcast Drinks.swyx: Yeah.Agent Governance and IdentityAaron Levie: But, but, um, but, but, you know, so the thing that we, we kind of think about is, um, is, you know, whether you think the number 10 x or a hundred x or whatever the number is, we're gonna have some order of magnitude more agents than people.That's inevitable. It has to happen. So then the question is, what is the infrastructure that's needed to make all those agents effective in the enterprise? Make sure that they are well governed. Make sure they're only doing [00:05:00] safe things on your information. Make sure that they're not getting exposed. The data that they shouldn't have access to.There's gonna be just incredibly spectacularly crazy security incidents that will happen with agents because you'll prompt, inject an agent and sort of find your way through the CRM system and pull out data that you shouldn't have access to. Oh, weJeff Huber: have God,Aaron Levie: right? I mean, that's just gonna happen all over the place, right?So, so then the thing is, is how do you make sure you have the right security, the permissions, the access controls, the data governance. Um, we actually don't yet exactly know in many cases how we're gonna regulate some of these agents, right? If you think about an agent in financial services, does it have the exact same financial sort of, uh, requirements that a human did?Or is it, is the risk fully on the human that was interacting or created the agent? All open questions, but no matter what, there's gonna need to be a layer that manages the, the data they have access to, the workflows that they're involved in, pulling up data from multiple systems. This is the new infrastructure opportunity in the era of agents.swyx: You have a piece on agent identities, [00:06:00] which I think was today, um, which I think a lot of breaking news, the security, security people are talking about, right? Like you basically, I, I always think of this as like, well you need the human you and then there you need the agent. YouAaron Levie: Yes.swyx: And uh, well, I don't know if it's that simple, but is box going to have an opinion on that or you're just gonna be like, well we're just the sort of the, the source layer.Yeah. Let's Okta of zero handle that.Aaron Levie: I think we're gonna have an opinion and we will work with generally wherever the contours of the market end up. Um, and the reason that we're gonna have an opinion more than other topics probably is because one of the biggest use cases for why your agent might need it, an identity is for file system access.So thus we have to kind of think about this pretty deeply. And I think, uh, unless you're like in our world thinking about this particular problem all day long, it might be, you know, like, why is this such a big deal? And the reason why it's a really big deal is because sometimes sort of say, well just give the agent an, an account on the system and it just treats, treat it like every other type of user on the system.The [00:07:00] problem is, is that I as Aaron don't really have any responsibility over anybody else's box account in our organization. I can't see the box account of any other employee that I work with. I am not liable for anything that they do. And they have, I have, I have, you know, strict privacy requirements on everything that they're able to, you know, that, that, that they work on.Agents don't have that, you know, don't have those properties. The person who creates the agent probably is gonna, for the foreseeable future, take on a lot of the liability of what that agent does. That agent doesn't deserve any privacy because, because it's, you know, it can't fully be autonomously operated and it doesn't have any legal, you know, kind of, you know, responsibility.So thus you can't just be like, oh, well I'll just create a bunch of accounts and then I'll, I'll kind of work with that agent and I'll talk to it occasionally. Like you need oversight of that. And so then the question is, how do you have a world where the agent, sometimes you have oversight of, but what if that agent goes and works with other people?That person over there is collaborating with the agent on something you shouldn't have [00:08:00] access to what they're doing. So we have all of these new boundaries that we're gonna have to figure out of, of, you know, it's really, really easy. So far we've been in, in easy mode. We've hit the easy button with ai, which is the agent just is you.And when you're in quad code and you're in cursor, and you're in Codex, you're just, the agent is you. You're offing into your services. It can do everything you can do. That's the easy mode. The hard mode is agents are kind of running on their own. People check in with them occasionally, they're doing things autonomously.How do you give them access to resources in the enterprise and not dramatically increased the security risk and the risk that you might expose the wrong thing to somebody. These are all the new problems that we have to get solved. I like the identity layer and, and identity vendors as being a solution to that, but we'll, we'll need some opinions as well because so many of the use cases are these collaborative file system use cases, which is how do I give it an agent, a subset of my data?Give it its own workspace as well. ‘cause it's gonna need to store off its own information that would be relevant for it. And how do I have the right oversight into that? [00:09:00]Jeff Huber: One thing, which, um, I think is kind interesting, think about is that you know, how humans work, right? Like I may not also just like give you access to the whole file.I might like sit next to you and like scroll to this like one part of the file and just show you that like one part and like, you know,swyx: partial file access.Jeff Huber: I'm just saying I think like our, like RA does seem to be dead, right? Like you wanna say something is dead uhhuh probably RA is dead. And uh, like the auth story to me seems like incredibly unsolved and unaddressed by like the existing state of like AI vendors.ButAaron Levie: yeah, I think, um, we're, I mean you're taking obviously really to level limit that we probably need to solve for. Yeah. And we built an access control system that was, was kind of like, you know, its own little world for, for a long time. And um, and the idea was this, it's a many to many collaboration system where I can give you any part of the file system.And it's a waterfall model. So if I give you higher up in the, in the, in the system, you get everything below. And that, that kind of created immense flexibility because I can kind of point you to any layer in the, in the tree, but then you're gonna get access to everything kind of below it. And that [00:10:00] mostly is, is working in this, in this world.But you do have to manage this issue, which is how do I create an agent that has access to some of my stuff and somebody else's stuff as well. Mm-hmm. And which parts do I get to look at as the creator of the agent? And, and these are just brand new problems? Yeah. Crazy. And humans, when there was a human there that was really easy to do.Like, like if the three of us were all sharing, there'd be a Venn diagram where we'd have an overlapping set of things we've shared, but then we'd have our own ways that we shared with each other. In an agent world, somebody needs to take responsibility for what that agent has access to and what they're working on.These are like the, some of the most probably, you know, boring problems for 98% of people on, on the internet, but they will be the problems that are the difference between can you actually have autonomous agents in an enterprise contextswyx: Yeah.Aaron Levie: That are not leaking your data constantly.swyx: No. Like, I mean, you know, I run a very, very small company for my conference and like we already have data sensitivity issues.Yes. And some of my team members cannot see Yes. Uh, the others and like, I can't imagine what it's like to run a Fortune 500 and like, you have to [00:11:00] worry about this. I'm just kinda curious, like you, you talked to a lot like, like 70, 80% of your cus uh, of the Fortune 500, your customers.Aaron Levie: Yep. 67%. Just so we're being verySEswyx: precise.So Yeah. I'm notAaron Levie: Okay. Okay.swyx: Something I'm rounding up. Yes. Round up. I'm projecting to, forAaron Levie: the government.swyx: I'm projecting to the end of the year.Aaron Levie: Okay.swyx: There you go.Aaron Levie: You do make it sound like, like we, we, well we've gotta be on this. Like we're, we're taking way too long to get to 80%. Well,swyx: no, I mean, so like. How are they approaching it?Right? Because you're, you don't have a, you don't have a final answer yet.Why Coding Agents Took Off FirstAaron Levie: Well, okay, so, so this is actually, this is the stark reality that like, unfortunately is the kinda like pouring the water on the party a little bit.swyx: Yes.Aaron Levie: We all in Silicon Valley are like, have the absolute best conditions possible for AI ever.And I think we all saw the dke, you know, kind of Dario podcast and this idea of AI coding. Why is that taken off? And, and we're not yet fully seeing it everywhere else. Well, look, if you just like enumerated the list of properties that AI coding has and then compared it to other [00:12:00] knowledge work, let's just, let's just go through a few of them.Generally speaking, you bring on a new engineer, they have access to a large swath of the code base. Like, there's like very, like you, just, like new engineer comes on, they can just go and find the, the, the stuff that they, they need to work with. It's a fully text in text out. Medium. It's only, it's just gonna be text at the end of the day.So it's like really great from a, from just a, uh, you know, kinda what the agent can work with. Obviously the models are super trained on that dataset. The labs themselves have a really strong, kind of self-reinforcing positive flywheel of why they need to do, you know, agent coding deeply. So then you get just better tooling, better services.The actual developers of the AI are daily users of the, of the thing that they're we're working on versus like the, you know, probably there's only like seven Claude Cowork legal plugin users at Anthropic any given day, but there's like a couple thousand Claude code and you know, users every single day.So just like, think about which one are they getting more feedback on. All day long. So you just go through this list. You have a, you know, everybody who's a [00:13:00] developer by definition is technical so they can go install the latest thing. We're all generally online, or at least, you know, kinda the weird ones are, and we're all talking to each other, sharing best practices, like that's like already eight differences.Versus the rest of the economy. Every other part of the economy has like, like six to seven headwinds relative to that list. You go into a company, you're a banker in financial services, you have access to like a, a tiny little subset of the total data that's gonna be relevant to do your job. And you're have to start to go and talk to a bunch of people to get the right data to do your job because Sally didn't add you to that deal room, you know, folder.And that that, you know, the information is actually in a completely different organization that you now have to go in and, and sort of run into. And it's like you have this endless list of access controls and security. As, as you talked about, you have a medium, which is not, it's not just text, right? You have, you have a zoom call that, that you're getting all of the requirements from the customer.You have a lot of in-person conversations and you're doing in-person sales and like how do you ever [00:14:00] digitize all of that information? Um, you know, I think a lot of people got upset with this idea that the code base has all the context, um, that I don't know if you follow, you know, did you follow some of that conversation that that went viral?Is like, you know, it's not that simple that, that the code base doesn't have all the knowledge, but like it's a lot, you're a lot better off than you are with other areas of knowledge work. Like you, we like, we like have documentation practices, you write specifications. Those things don't exist for like 80% of work that happens in the enterprise.That's the divide that we have, which is, which is AI coding has, has just fully, you know, where we've reached escape velocity of how powerful this stuff is, and then we're gonna have to find a way to bring that same energy and momentum, but to all these other areas of knowledge work. Where the tools aren't there, the data's not set up to be there.The access controls don't make it that easy. The context engineering is an incredibly hard problem because again, you have access control challenges, you have different data formats. You have end users that are gonna need to kind of be kind of trained through this as opposed to their adopting [00:15:00] these tools in their free time.That's where the Fortune 500 is. And so we, I think, you know, have to be prepared as an industry where we are gonna be on a multi-year march to, to be able to bring agents to the enterprise for these workflows. And I think probably the, the thing that we've learned most in coding that, that the rest of the world is not yet, I think ready for, I mean, we're, they'll, they'll have to be ready for it because it's just gonna inevitably happen is I think in coding.What, what's interesting is if you think about the practice of coding today versus two years ago. It's probably the most changed workflow in maybe the history of time from the amount of time it's changed, right? Yeah. Like, like has any, has any workflow in the entire economy changed that quickly in terms of the amount of change?I just, you know, at least in any knowledge worker workflow, there's like very rarely been an event where one piece of technology and work practice has so fundamentally, you know, changed, changed what you do. Like you don't write code, you talk to an agent and it goes and [00:16:00] does it for you, and you may be at best review it.And even that's even probably like, like largely not even what you're doing. What's happening is we are changing our work to make the agents effective. In that model, the agent didn't really adapt to how we work. We basically adapted to how the agent works. Mm-hmm. All of the economy has to go through that exact same evolution.The rest of the economy is gonna have to update its workflows to make agents effective. And to give agents the context that they need and to actually figure out what kind of prompting works and to figure out how do you ensure that the agent has the right access to information to be able to execute on its work.I, you know, this is not the panacea that people were hoping for, of the agent drops in, just automates your life. Like you have to basically re-engineer your workflow to get the most out of agents and, uh, and that, that's just gonna take, you know, multiple years across the economy. Right now it's a huge asset and an advantage for the teams that do it early and that are kinda wired into doing this.‘cause [00:17:00] you'll see compounding returns, but that's just gonna take a while for most companies to actually go and get this deployed.swyx: I love, I love pushing back. I think that. That is what a lot of technology consultants love to hear this sort of thing, right? Yeah, yeah, yeah. First to, to embrace the ai. Yes. To get to the promised land, you must pay me so much money to a hundred percent to adopt the prescribed way of, uh, conforming to the agents.Yes. And I worry that you will be eclipsed by someone else who says, no, come as you are.Aaron Levie: Yeah.swyx: And we'll meet you where you are.Aaron Levie: And, and, and and what was the thing that went viral a week ago? OpenAI probably, uh, is hiring F Dees. Yeah. Uh, to go into the enterprise. Yeah. Yeah. And then philanthropic is embedded at Goldman Sachs.Yeah. So if the labs are having to do this, if, if the labs have decided that they need to hire FDE and professional services, then I think that's a pretty clear indication that this, there's no easy mode of workflow transformation. Yeah. Yeah. So, so to your point, I think actually this is a market opportunity for, you know, new professional services and consulting [00:18:00] firms that are like Agent Build and they, and they kind of, you know, go into organizations and they figure out how to re-engineer your workflows to make them more agent ready and get your data into the right format and, you know, reconstruct your business process.So you're, you're not doing most of the work. You're telling agents how to do the work and then you're reviewing it. But I haven't seen the thing that can just drop in and, and kinda let you not go through those changes.swyx: I don't know how that kind of sales pitch goes over. Yeah. You know, you're, you're saying things like, well, in my sort of nice beautiful walled garden, here's, there's, uh, because here's this, here's this beautiful box account that has everything.Yes. And I'm like, well, most, most real life is extremely messy. Sure. And like, poorly named and there duplicate this outdated s**tAaron Levie: a hundred percent. And so No, no, a hundred percent. And so this is actually No. So, so this is, I mean, we agree that, that getting to the beautiful garden is gonna be tough.swyx: Yeah.Aaron Levie: There's also the other end of the spectrum where I, I just like, it's a technical impossibility to solve. The agent is, is truly cannot get enough context to make the right decision in, in the, in the incredibly messy land. Like there's [00:19:00] no a GI that will solve that. So, so we're gonna have to kind of land in somewhere in between, which is like we all collectively get better at.Documentation practices and, and having authoritative relatively up-to-date information and putting it in the right place like agents will, will certainly cause us to be much better organized around how we work with our information, simply because the severity of the agent pulling the wrong data will be too high and the productivity gain of that you'll miss out on by not doing this will be too high as well, that you, that your competition will just do it and they'll just have higher velocity.So, uh, and, and we, we see this a lot firsthand. So we, we build a series of agents internally that they can kind of have access to your full box account and go off and you give it a task and it can go find whatever information you're looking for and work with. And, you know, thank God for the model progress, but like, if, if you gave that task to an agent.Nine months ago, you're just gonna get lots of bogus answers because it's gonna, it's gonna say, Hey, here's, here are fi [00:20:00] five, you know, documents that all kind of smell like the right thing. And I'm gonna, but I, but you're, you're putting me on the clock. ‘cause my assistant prompt says like, you know, be pretty smart, but also try and respond to the user and it's gonna respond.And it's like, ah, it got the wrong document. And then you do that once or twice as a knowledge worker and you're just neverswyx: again,Aaron Levie: never again. You're just like done with the system.swyx: Yeah. It doesn't work.Aaron Levie: It doesn't work. And so, you know, Opus four six and Gemini three one Pro and you know, whatever the latest five 3G BT will be, like, those things are getting better and better and it's using better judgment.And this sort of like the, all of these updates to the agentic tool and search systems are, are, we're seeing, we're seeing very real progress where the agent. Kind of can, can almost smell some things a little bit fishy when it's getting, you know, we, we have this process where we, we have it go fan out, do a bunch of searches, pull up a bunch of data, and then it has to sort of do its own ranking of, you know, what are the right documents that, that it should be working with.And again, like, you know, the intelligence level of a model six months ago, [00:21:00] it'd be just throwing a dart at like, I'm just, I'm gonna grab these seven files and I, I pray, I hope that that's the right answer. And something like an opus first four five, and now four six is like, oh, it's like, no, that one doesn't seem right relative to this question because I'm seeing some signal that is making that, you know, that's contradicting the document where it would normally be in the tree and who should have access.Like it's doing all of that kind of work for you. But like, it still doesn't work if you just have a total wasteland of data. Like, it's just not, it's just not possible. Partly ‘cause a human wouldn't even be able to do it. So basically if a, if a really, really smart human. Could not do that task in five or 10 minutes for a search retrieval type task.Look, you know, your agent's not gonna be able to do it any better. You see this all day long. SoContext Engineering and Search Limitsswyx: this touches on a thing that just passionate about it was just context engineering. I, I'm just gonna let you ramble or riff on, on context engineering. If, if, if there's anything like he, he did really good work on context fraud, which has really taken over as like the term that people use and the referenceAaron Levie: a hundred percent.We, we all we think about is, is the context rob problem. [00:22:00]Jeff Huber: Yeah, there's certainly a lot of like ranking considerations. Gentech surgery think is incredibly promising. Um, yeah, I was trying to generate a question though. I think I have a question right now. Swyx.Aaron Levie: Yeah, no, but like, like I think there was this moment, um, you know, like, I don't know, two years ago before, before we knew like where the, the gotchas were gonna be in ai and I think someone was like, was like, well, infinite context windows will just solve all of these problems and ‘cause you'll just, you'll just give the context window like all the data and.It's just like, okay, I mean, maybe in 2035, like this is a viable solution. First of all, it, it would just, it would just simply cost too much. Like we just can't give the model like the 5,000 documents that might be relevant and it's gonna read them all. And I've seen enough to, to start believing in crazy stuff.So like, I'm willing to just say, sure. Like in, in 10 years from now,swyx: never say, never, never.Aaron Levie: In, in 10 years from now, we'll have infinite context windows at, at a thousandth of the price of today. Like, let's just like believe that that's possible, but Right. We're in reality today. So today we have a context engineering [00:23:00] problem, which is, I got, I got, you know, 200,000 tokens that I can work with, or prob, I don't even know what the latest graph is before, like massive degradation.16. Okay. I have 60,000 tokens that I get to work with where I'm gonna get accurate information. That's not a lot of tokens for a corpus of 10 million documents that a knowledge worker might have across all of the teams and all the projects and all the people they work with. I have, I have 10 million documents.Which, you know, maybe is times five pages per document or something like that. I'm at 50 million pages of information and I have 60,000 tokens. Like, holy s**t. Yeah. This is like, how do I bridge the 50 million pages of information with, you know, the couple hundred that I get to work with in that, in that token window.Yeah. This is like, this is like such an interesting problem and that's why actually so much work is actually like, just like search systems and the databases and that layer has to just get so locked in, but models getting better and importantly [00:24:00] knowing when they've done a search, they found the wrong thing, they go back, they check their work, they, they find a way to balance sort of appeasing the user versus double checking.We have this one, we have this one test case where we ask the agent to go find. 10 pieces of information.swyx: Is this the complex work eval?Aaron Levie: Uh, this is actually not in the eval. This is, this is sort of just like we have a bunch of different, we have a bunch of internal benchmark kind of scenarios. Every time we, we update our agent, we have one, which is, I ask it to find all of our office addresses, and I give it the list of 10 offices that we have.And there's not one document that has this, maybe there should be, that would be a great example of the kind of thing that like maybe over time companies start to, you know, have these sort of like, what are the canonical, you know, kind of key areas of knowledge that we need to have. We don't seem to have this one document that says, here are all of our offices.We have a bunch of documents that have like, here's the New York office and whatever. So you task this agent and you, you get, you say, I need the addresses for these 10 offices. Okay. And by the way, if you do this on any, you know, [00:25:00] public chat model, the same outcome is gonna happen. But for a different kind of query, you give it, you say, I need these 10 addresses.How many times should the agent go and do its search before it decides whether or not, there's just no answer to this question. Often, and especially the, the, let's say lower tier models, it'll come back and it'll give you six of the 10 addresses. And it'll, and I'll just say I couldn't find the otherswyx: four.It, it doesn't know what It doesn't know. ItAaron Levie: doesn't know what It doesn't know. Yeah. So the model is just like, like when should it stop? When should it stop doing? Like should it, should it do that task for literally an hour and just keep cranking through? Maybe I actually made up an office location and it doesn't know that I made it up and I didn't even know that I made it up.Like, should it just keep, re should it read every single file in your entire box account until it, until it should exhaust every single piece of information.swyx: Expensive.Aaron Levie: These are the new problems that we have. So, you know, something like, let's say a new opus model is sort of like, okay, I'm gonna try these types of queries.I didn't get exactly what I wanted. I'm gonna try again. I'm gonna, at [00:26:00] some point I'm gonna stop searching. ‘cause I've determined that that no amount of searching is gonna solve this problem. I'm just not able to do it. And that judgment is like a really new thing that the model needs to be able to have.It's like, when should it give up on a task? ‘cause, ‘cause you just don't, it's a can't find the thing. That's the real world of knowledge, work problems. And this is the stuff that the coding agents don't have to deal with. Because they, it just doesn't like, like you're not usually asking it about, you're, you're always creating net new information coming right outta the model for the most part.Obviously it has to know about your code base and your specs and your documentation, but, but when you deploy an agent on all of your data that now you have all of these new problems that you're dealing withJeff Huber: our, uh, follow follow-up research to context ride is actually on a genetic search. Ah. Um, and we've like right, sort of stress tested like frontier models and their ability to search.Um, and they're not actually that good at searching. Right. Uh, so you're sort of highlighting this like explore, exploit.swyx: You're just say, Debbie, Donna say everything doesn't work. Like,Aaron Levie: well,Jeff Huber: somebody has to be,Aaron Levie: um, can I just throw out one more thing? Yeah. That is different from coding and, and the rest [00:27:00] of the knowledge work that I, I failed to mention.So one other kind of key point is, is that, you know, at the end of the day. Whether you believe we're in a slop apocalypse or, or whatever. At the end of the day, if you, if you build a working product at the end of, if you, if you've built a working solution that is ultimately what the customer is paying for, like whether I have a lot of slop, a little slop or whatever, I'm sure there's lots of code bases we could go into in enterprise software companies where it's like just crazy slop that humans did over a 20 year period, but the end customer just gets this little interface.They can, they can type into it, it does its thing. Knowledge work, uh, doesn't have that property. If I have an AI model, go generate a contract and I generate a contract 20 times and, you know, all 20 times it's just 3% different and like that I, that, that kind of lop introduces all new kinds of risk for my organization that the code version of that LOP didn't, didn't introduce.These are, and so like, so how do you constrain these models to just the part that you want [00:28:00] them to work on and just do the thing that you want them to do? And, and, you know, in engineering, we don't, you can't be disbarred as an engineer, but you could be disbarred as a lawyer. Like you can do the wrong medical thing In healthcare, you, there's no, there's no equivalent to that of engineering.Like, doswyx: you want there to be, because I've considered softwareJeff Huber: engineer. What's that? Civil engineering there is, right? NotAaron Levie: software civil engineer. Sure. Oh yeah, for sure. But like in any of our companies, you like, you know, you'll be forgiven if you took down the site and, and we, we will do a rollback and you'll, you'll be in a meeting, but you have not been disbarred as an engineer.We don't, we don't change your, you know, your computer science, uh, blameJeff Huber: degree, this postmortem.Aaron Levie: Yeah, exactly. Exactly. So, so, uh, now maybe we collectively as an industry need to figure out like, what are you liable for? Not legally, but like in a, in a management sense, uh, of these agents. All sorts of interesting problems that, that, that, uh, that have to come out.But in knowledge work, that's the real hostile environments that we're operating in. Hmm.swyx: I do think like, uh, a lot of the last year's, 2025 story was the rise of coding agents and I think [00:29:00] 2026 story is definitely knowledge work agents. Yes. A hundredAaron Levie: percent.swyx: Right. Like that would, and I think open claw core work are just the beginning.Yes. Like it's, the next one's gonna just gonna be absolute craziness.Aaron Levie: It it is. And, and, uh, and it's gonna be, I mean, again, like this is gonna be this, this wave where we, we are gonna try and bring as many of the practices from coding because that, that will clearly be the forefront, which is tell an agent to go do something and has an access to a set of resources.You need to be responsible for reviewing it at the end of the process. That to me is the, is the kind of template that I just think goes across knowledge, work and odd. Cowork is a great example. Open Closet's a great example. You can kind of, sort of see what Codex could become over time. These are some, some really interesting kind of platforms that are emerging.swyx: Okay. Um, I wanted to, we touched on evals a little bit. You had, you had the report that you're gonna go bring up and then I was gonna go into like, uh, boxes, evals, but uh, go ahead. Talk about your genetic search thing.Jeff Huber: Yeah. Mostly I think kinda a few of the insights. It's like number one frontier model is not good at search.Humans have this [00:30:00] natural explore, exploit trade off where we kinda understand like when to stop doing something. Also, humans are pretty good at like forgetting actually, and like pruning their own context, whereas agents are not, and actually an agent in their kind of context history, if they knew something was bad and they even, you could see in the trace the reason you trace, Hey, that probably wasn't a good idea.If it's still in the trace, still in the context, they'll still do it again. Uhhuh. Uh, and so like, I think pruning is also gonna be like, really, it's already becoming a thing, right? But like, letting self prune the con windowsswyx: be a big deal. Yeah. So, so don't leave the mistake. Don't leave the mistake in there.Cut out the mistake but tell it that you made a mistake in the past and so it doesn't repeat it.Jeff Huber: Yeah. But like cut it out so it doesn't get like distracted by it again. ‘cause really, you know, what is so, so it will repeat its mistake just because it's been, it's inswyx: theJeff Huber: context. It'sAaron Levie: in the context so much.That's a few shot example. Even if it, yeah.Jeff Huber: It's like oh thisAaron Levie: is a great thing to go try even ifJeff Huber: it didn't work.Aaron Levie: Yeah,Jeff Huber: exactly.Aaron Levie: SoJeff Huber: there's like a bunch of stuff there. JustAaron Levie: Groundhogs Day inside these models. Yeah. I'm gonna go keep doing the same wrongJeff Huber: thing. Covering sense. I feel like, you know, some creator analogy you're trying like fit a manifold in latent space, which kind is doing break program synthesis, which is kinda one we think about we're doing right.Like, you know, certain [00:31:00] facts might be like sort of overly pitting it. There are certain, you know, sec sectors of latent space and so like plug clean space. Yeah. And, uh, andswyx: so we have a bell, our editor as a bell every time you say that. SoJeff Huber: you have, you have to like remove those, likeswyx: you shoulda a gong like TPN or something.IfJeff Huber: we gong, you either remove those links to like kinda give it the freedom, kind of do what you need to do. So, but yeah. We'll, we'll release more soon. That'sAaron Levie: awesome.Jeff Huber: That'll, that'll be cool.swyx: We're a cerebral podcast that people listen to us and, and sort of think really deep. So yeah, we try to keep it subtle.Okay. We try to keep it.Aaron Levie: Okay, fine.Inside Agent Evalsswyx: Um, you, you guys do, you guys do have EVs, you talked about your, your office thing, but, uh, you've been also promoting APEX agents and complex work. Uh, yeah, whatever you, wherever you wanna take this just Yeah. How youAaron Levie: Apex is, is obviously me, core's, uh, uh, kind of, um, agent eval.We, we supported that by sort of. Opening up some data for them around how we kind of see these, um, data workspaces in, in the, you know, kind of regular economy. So how do lawyers have a workspace? How do investment bankers have a workspace? What kind of data goes into those? And so we, [00:32:00] we partner with them on their, their apex eval.Our own, um, eval is, it's actually relatively straightforward. We have a, a set of, of documents in a, in a range of industries. We give the agent previously did this as a one shot test of just purely the model. And then we just realized we, we need to, based on where everything's going, it's just gotta be more agentic.So now it's a bit more of a test of both our harness and the model. And we have a rubric of a set of things that has to get right and we score it. Um, and you're just seeing, you know, these incredible jumps in almost every single model in its own family of, you know, opus four, um, you know, sonnet four six versus sonnet four five.swyx: Yeah. We have this up on screen.Aaron Levie: Okay, cool. So some, you're seeing it somewhere like. I, I forget the to, it was like 15 point jump, I think on the main, on the overall,swyx: yes.Aaron Levie: And it's just like, you know, these incredible leaps that, that are starting to happen. Um,swyx: and OP doesn't know any, like any, it's completely held out from op.Aaron Levie: This is not in any, there's no public data which has, you know, Ben benefits and this is just a private eval that we [00:33:00] do, and then we just happen to show it to, to the world. Hmm. So you can't, you can't train against it. And I think it's just as representative of. It's obviously reasoning capabilities, what it's doing at, at, you know, kind of test time, compute capabilities, thinking levels, all like the context rot issues.So many interesting, you know, kind of, uh, uh, capabilities that are, that are now improvingswyx: one sector that you have. That's interesting.Industries and Datasetsswyx: Uh, people are roughly familiar with healthcare and legal, but you have public sector in there.Aaron Levie: Yeah.swyx: Uh, what's that? Like, what, what, what is that?Aaron Levie: Yeah, and, and we actually test against, I dunno, maybe 10 industries.We, we end up usually just cutting a few that we think have interesting gains. All extras, won a lot of like government type documents. Um,swyx: what is that? What is it? Government type documents?Aaron Levie: Government filings. Like a taxswyx: return, likeAaron Levie: a probably not tax returns. It would be more of what would go the government be using, uh, as data.So, okay. Um, so think about research that, that type of, of, of data sets. And then we have financial services for things like data rooms and what would be in an investment prospectus. Uhhuh,swyx: that one you can dog food.Aaron Levie: Yeah, exactly. Exactly. Yes. Yes. [00:34:00] So, uh, so we, we run the models, um, in now, you know, more of an agent mode, but, but still with, with kinda limited capacity and just try and see like on a, like, for like basis, what are the improvements?And, and again, we just continue to be blown away by. How, how good these models are getting.swyx: Yeah, I mean, I think every serious AI company needs something like that where like, well, this is the work we do. Here's our company eval. Yeah. And if you don't have it, well, you're not a serious AI company.Aaron Levie: There's two dimensions, right?So there's, there's like, how are the models improving? And so which models should you either recommend a customer use, which one should you adopt? But then every single day, we're making changes to our agents. And you need to knowswyx: if you regressed,Aaron Levie: if you know. Yeah. You know, I've been fully convinced that the whole agent observability and eval space is gonna be a massive space.Um, super excited for what Braintrust is doing, excited for, you know, Lang Smith, all the things. And I think what you're going to, I mean, this is like every enter like literally every enterprise right now. It's like the AI companies are the customers of these tools. Every enterprise will have this. Yeah, you'll just [00:35:00] have to have an eval.Of all of your work and like, we'll, you'll have an eval of your RFP generation, you'll have an eval of your sales material creation. You'll have an eval of your, uh, invoice processing. And, and as you, you know, buy or use new agentic systems, you are gonna need to know like, what's the quality of your, of your pipeline.swyx: Yeah.Aaron Levie: Um, so huge, huge market with agent evals.swyx: Yeah.Building the Agent Teamswyx: And, and you know, I'm gonna shout out your, your team a bit, uh, your CTO, Ben, uh, did a great talk with us last year. Awesome. And he's gonna come back again. Oh, cool. For World's Fair.Aaron Levie: Yep.swyx: Just talk about your team, like brag a little bit. I think I, I think people take these eval numbers in pretty charts for granted, but No, there, I mean, there's, there's lots of really smart people at work during all this.Aaron Levie: Biggest shout out, uh, is we have a, we have a couple folks at Dya, uh, Sidarth, uh, that, that kind of run this. They're like a, you know, kind of tag tag team duo on our evals, Ben, our CTO, heavily involved Yasha, head of ai, uh, you know, a bunch of folks. And, um, evals is one part of the story. And then just like the full, you know, kind of AI.An agent team [00:36:00] is, uh, is a, is a pretty, you know, is core to this whole effort. So there's probably, I don't know, like maybe a few dozen people that are like the epicenter. And then you just have like layers and layers of, of kind of concentric circles of okay, then there's a search team that supports them and an infrastructure team that supports them.And it's starting to ripple through the entire company. But there's that kind of core agent team, um, that's a pretty, pretty close, uh, close knit group.swyx: The search team is separate from the infra team.Aaron Levie: I mean, we have like every, every layer of the stack we have to kind of do, except for just pure public cloud.Um, but um, you know, we, we store, I don't even know what our public numbers are in, you know, but like, you can just think about it as like a lot of data is, is stored in box. And so we have, and you have every layer of the, of the stack of, you know, how do you manage the data, the file system, the metadata system, the search system, just all of those components.And then they all are having to understand that now you've got this new customer. Which is the agent, and they've been building for two types of customers in the past. They've been building for users and they've been building for like applications. [00:37:00] And now you've got this new agent user, and it comes in with a difference of it, of property sometimes, like, hey, maybe sometimes we should do embeddings, an embedding based, you know, kind of search versus, you know, your, your typical semantic search.Like, it's just like you have to build the, the capabilities to support all of this. And we're testing stuff, throwing things away, something doesn't work and, and not relevant. It's like just, you know, total chaos. But all of those teams are supporting the agent team that is kind of coming up with its requirements of what, what do we need?swyx: Yeah. No, uh, we just came from, uh, fireside chat where you did, and you, you talked about how you're doing this. It's, it's kind of like an internal startup. Yeah. Within the broader company. The broader company's like 3000 people. Yeah. But you know, there's, there's a, this is a core team of like, well, here's the innovation center.Aaron Levie: Yeah.swyx: And like that every company kind of is run this way.Aaron Levie: Yeah. I wanna be sensitive. I don't call it the innovation center. Yeah. Only because I think everybody has to do innovation. Um, there, there's a part of the, the, the company that is, is sort of do or die for the agent wave.swyx: Yeah.Aaron Levie: And it only happens to be more of my focus simply because it's existential that [00:38:00] we get it right.swyx: Yeah.Aaron Levie: All of the supporting systems are necessary. All of the surrounding adjacent capabilities are necessary. Like the only reason we get to be a platform where you'd run an agent is because we have a security feature or a compliance feature, or a governance feature that, that some team is working on.But that's not gonna be the make or break of, of whether we get agents right. Like that already exists and we need to keep innovating there. I don't know what the right, exact precise number is, but it's not a thousand people and it's not 10 people. There's a number of people that are like the, the kind of like, you know, startup within the company that are the make or break on everything related to AI agents, you know, leveraging our platform and letting you work with your data.And that's where I spend a lot of my time, and Ben and Yosh and Diego and Teri, you know, these are just, you know, people that, that, you know, kind of across the team. Are working.swyx: Yeah. Amazing.Read Write Agent WorkflowsJeff Huber: How do you, how do you think about, I mean, you talked a lot about like kinda read workflows over your box data. Yep.Right. You know, gen search questions, queries, et cetera. But like, what about like, write or like authoring workflows?Aaron Levie: Yes. I've [00:39:00] already probably revealed too much actually now that I think about it. So, um, I've talked about whatever,Jeff Huber: whatever you can.Aaron Levie: Okay. It's just us. It's just us. Yeah. Okay. Of course, of course.So I, I guess I would just, uh, I'll make it a little bit conceptual, uh, because again, I've already, I've already said things that are not even ga but, but we've, we've kinda like danced around it publicly, so I, yeah, yeah. Okay. Just like, hopefully nobody watches this, um, episode. No.swyx: It's tidbits for the Heidi engaged to go figure out like what exactly, um, you know, is, is your sort of line of thinking.Sure. They can connect the dots.Aaron Levie: Yeah. So, so I would say that, that, uh, we, you know, as a, as a place where you have your enterprise content, there's a use case where I want to, you know, have an agent read that data and answer questions for me. And then there's a use case where I want the agent to create something.And use the file system to create something or store off data that it's working on, or be able to have, you know, various files that it's writing to about the work it's doing. So we do see it as a total read write. The harder problem has so far been the read only because, because again, you have that kind of like 10 [00:40:00] million to one ratio problem, whereas rights are a lot of, that's just gonna come from the model and, and we just like, we'll just put it in the file system and kinda use it.So it's a little bit of a technically easier problem, but the only part that's like, not necessarily technically hard, it is just like it's not yet perfected in the state of the ecosystem is, you know, building a beautiful PowerPoint presentation. It's still a hard problem for these models. Like, like we still, you know, like, like these formats are just, we're not built for.They'reswyx: working on it.Aaron Levie: They're, they're working on it. Everybody's working on it.swyx: Every launch is like, well, we do PowerPoint now.Aaron Levie: We're getting, yeah, getting a lot, getting a lot of better each time. But then you'll do this thing where you'll ask the update one slide and all of a sudden, like the fonts will be just like a little bit different, you know, on two of the slides, or it moved, you know, some shape over to the left a little bit.And again, these are the kind of things that, like in code, obviously you could really care about if you really care about, you know, how beautiful is the code, but at the end, user doesn't notice all those problems and file creation, the end user instantly sees it. You're [00:41:00] like, ah, like paragraph three, like, you literally just changed the font on me.Like it's a totally different font and like midway through the document. Mm-hmm. Those are the kind of things that you run into a lot of in the, in the content creation side. So, mm-hmm. We are gonna have native agents. That do all of those things, they'll be powered by the leading kind of models and labs.But the thing that I think is, is probably gonna be a much bigger idea over time is any agent on any system, again, using Box as a file system for its work, and in that kind of scenario, we don't necessarily care what it's putting in the file system. It could put its memory files, it could put its, you know, specification, you know, documents.It could put, you know, whatever its markdown files are, or it could, you know, generate PDFs. It's just like, it's a workspace that is, is sort of sandboxed off for its work. People can collaborate into it, it can share with other people. And, and so we, we were thinking a lot about what's the right, you know, kind of way to, to deliver that at scale.Docs Graphs and Founder Modeswyx: I wanted to come into sort of the sort of AI transformation or AI sort of, uh, operations things. [00:42:00] Um, one of the tweets that you, that you wanted to talk about, this is just me going through your tweets, by the way. Oh, okay. I mean, like, this is, you readAaron Levie: one by one,swyx: you're the, you're the easiest guest to prep for because you, you already have like, this is the, this is what I'm interested in.I'm like, okay, well, areAaron Levie: we gonna get to like, like February, January or something? Where are we in the, in the timelines? How far back are we going?swyx: Can you, can you describe boxes? A set of skills? Right? Like that, that's like, that's like one of the extremes of like, well if you, you just turn everything into a markdown file.Yeah. Then your agent can run your company. Uh, like you just have to write, find the right sequence of words toAaron Levie: Yes.swyx: To do it.Aaron Levie: Sorry, isthatswyx: the question? So I think the question is like, what if we documented everything? Yes. The way that you exactly said like,Aaron Levie: yes.swyx: Um, let's get all the Fortune five hundreds, uh, prepared for agents.Yes. And like, you know, everything's in golden and, and nicely filed away and everything. Yes. What's missing? Like, what's left, right? LikeAaron Levie: Yeah.swyx: You've, you've run your company for a decade. LikeAaron Levie: Yeah. I think the challenge is that, that that information changes a week later. And because something happened in the market for that [00:43:00] customer, or us as a company that now has to go get updated, and so these systems are living and breathing and they have to experience reality and updates to reality, which right now is probably gonna be humans, you know, kinda giving those, giving them the updates.And, you know, there is this piece about context graphs as as, uh, that kinda went very viral. Yeah. And I, I, I was like a, i, I, I thought it was super provocative. I agreed with many parts of it. I disagree with a few parts around. You know, it's not gonna be as easy as as just if we just had the agent traces, then we can finally do that work because there's just like, there's so much more other stuff that that's happening that, that we haven't been able to capture and digitize.And I think they actually represented that in the piece to be clear. But like there's just a lot of work, you know, that that has to, you just can't have only skills files, you know, for your company because it's just gonna be like, there's gonna be a lot of other stuff that happens. Yeah. Change over time.Yeah. Most companies are practically apprenticeships.swyx: Most companies are practically apprenticeships. LikeJeff Huber: every new employee who joins the team, [00:44:00] like you span one to three months. Like ramping them up.Aaron Levie: Yes. AllJeff Huber: that tat knowledgeAaron Levie: isJeff Huber: not written down.Aaron Levie: Yes.Jeff Huber: But like, it would have to be if you wanted to like give it to an Asian.Right. And so like that seems to me like to beAaron Levie: one is I think you're gonna see again a premium on companies that can document this. Mm-hmm. Much. There'll be a huge premium on that because, because you know, can you shorten that three month ramp cycle to a two week ramp cycle? That's an instant productivity gain.Can you re dramatically reduce rework in the organization because you've documented where all the stuff is and where the answers are. Can you make your average employee as good as your 90th percentile employee because you've captured the knowledge that's sort of in the heads of, of those top employees and make that available.So like you can see some very clear productivity benefits. Mm-hmm. If you had a company culture of making sure you know your information was captured, digitized, put in a format that was agent ready and then made available to agents to work with, and then you just, again, have this reality of like add a 10,000 person [00:45:00] company.Mapping that to the, you know, access structure of the company is just a hard problem. Is like, is like, yeah, well, you just, not every piece of information that's digitized can be shared to everybody. And so now you have to organize that in a way that actually works. There was a pretty good piece, um, this, this, uh, this piece called your company as a file is a file system.I, did you see that one?swyx: Nope.Aaron Levie: Uh, yes. You saw it. Yeah. And, and, uh, I actually be curious your thoughts on it. Um, like, like an interesting kind of like, we, we agree with it because, because that's how we see the world and, uh,swyx: okay. We, we have it up on screen. Oh,Aaron Levie: okay. Yeah. But, but it's all about basically like, you know, we've already, we, we, we already organized in this kind of like, you know, permission structure way.Uh, and, and these are the kind of, you know, natural ways that, that agents can now work with data. So it's kind of like this, this, you know, kind of interesting metaphor, but I do think companies will have to start to think about how they start to digitize more, more of that data. What was your take?Jeff Huber: Yeah, I mean, like the company's probably like an acid compliant file system.Aaron Levie: Uh,Jeff Huber: yeah. Which I'm guessing boxes, right? So, yeah. Yes.swyx: Yeah. [00:46:00]Jeff Huber: Which you have a great piece on, but,swyx: uh, yeah. Well, uh, I, I, my, my, my direction is a little bit like, I wanna rewind a little bit to the graph word you said that there, that's a magic trigger word for us. I always ask what's your take on knowledge graphs?Yeah. Uh, ‘cause every, especially at every data database person, I just wanna see what they think. There's been knowledge graphs, hype cycles, and you've seen it all. So.Aaron Levie: Hmm. I actually am not the expert in knowledge graphs, so, so that you might need toswyx: research, you don't need to be an expert. Yeah. I think it's just like, well, how, how seriously do people take it?Yeah. Like, is is, is there a lot of potential in the, in the HOVI?Aaron Levie: Uh, well, can I, can I, uh, understand first if it's, um, is this a loaded question in the sense of are you super pro, super con, super anti medium? Iswyx: see pro, I see pros and cons. Okay. Uh, but I, I think your opinion should be independent of mine.Aaron Levie: Yeah. No, no, totally. Yeah. I just want to see what I'm stepping into.swyx: No, I know. It's a, and it's a huge trigger word for a lot of people out Yeah. In our audience. And they're, they're trying to figure out why is that? Because whyAaron Levie: is this such aswyx: hot item for them? Because a lot of people get graph religion.And they're like, everything's a graph. Of course you have to represent it as a graph. Well, [00:47:00] how do you solve your knowledge? Um, changing over time? Well, it's a graph.Aaron Levie: Yeah.swyx: And, and I think there, there's that line of work and then there's, there's a lot of people who are like, well, you don't need it. And both are right.Aaron Levie: Yeah. And what do the people who say you don't need it, what are theyswyx: arguing for Mark down files. Oh, sure, sure. Simplicity.Aaron Levie: Yeah.swyx: Versus it's, it's structure versus less structure. Right. That's, that's all what it is. I do.Aaron Levie: I think the tricky thing is, um, is, is again, when this gets met with real humans, they're just going to their computer.They're just working with some people on Slack or teams. They're just sharing some data through a collaborative file system and Google Docs or Box or whatever. I certainly like the vision of most, most knowledge graph, you know, kind of futuristic kind of ways of thinking about it. Uh, it's just like, you know, it's 2026.We haven't seen it yet. Kind of play out as as, I mean, I remember. Do you remember the, um, in like, actually I don't, I don't even know how old you guys are, but I'll for, for to show my age. I remember 17 years ago, everybody thought enterprises would just run on [00:48:00] Wikis. Yeah. And, uh, confluence and, and not even, I mean, confluence actually took off for engineering for sure.Like unquestionably. But like, this was like everything would be in the w. And I think based on our, uh, our, uh, general style of, of, of what we were building, like we were just like, I don't know, people just like wanna workspace. They're gonna collaborate with other people.swyx: Exactly. Yeah. So you were, you were anti-knowledge graph.Aaron Levie: Not anti, not anti. Soswyx: not nonAaron Levie: I'm not, I'm not anti. ‘cause I think, I think your search system, I just think these are two systems that probably, but like, I'm, I'm not in any religious war. I don't want to be in anybody's YouTube comments on this. There's not a fight for me.swyx: We, we love YouTube comments. We're, we're, we're get into comments.Aaron Levie: Okay. Uh, but like, but I, I, it's mostly just a virtue of what we built. Yeah. And we just continued down that path. Yeah.swyx: Yeah.Aaron Levie: And, um, and that, that was what we pursued. But I'm not, this is not a, you know, kind of, this is not a, uh, it'sswyx: not existential for you. Great.Aaron Levie: We're happy to plug into somebody else's graph.We're happy to feed data into it. We're happy for [00:49:00] agents to, to talk to multiple systems. Not, not our fight.swyx: Yeah.Aaron Levie: But I need your answer. Yeah. Graphs or nerd Snipes is very effective nerd.swyx: See this is, this is one, one opinion and then I've,Jeff Huber: and I think that the actual graph structure is emergent in the mind of the agent.Ah, in the same way it is in the mind of the human. And that's a more powerful graph ‘cause it actually involved over time.swyx: So don't tell me how to graph. I'll, I'll figure it out myself. Exactly. Okay. All right. AndJeff Huber: what's yours?swyx: I like the, the Wiki approach. Uh, my, I'm actually

In Sentientism episode 244, philosopher John Sanbonmatsu (https://sentientism.info/sentientist-...) discusses his powerful new book The Omnivore's Deception (https://uk.bookshop.org/a/15422/97814.... It's a radical, hard-hitting critique of the stories we tell ourselves and each other to justify violence and oppression.We explore why the exploitation of nonhuman animals is not a trivial issue, but the defining ethical crisis of our time. John argues there is no such thing as “ethical” animal agriculture, challenging narratives from figures like Michael Pollan, Temple Grandin and Barbara Kingsolver.Topics include:The hidden violence of factory farming and so-called “humane” farming“Bad faith” and why people avoid uncomfortable truths (via Jean-Paul Sartre)Meat, masculinity, populism, misogyny, fascism and figures like Joe Rogan, Jordan Peterson, Andrew Tate and Robert Kennedy JrThe femivore women who look for meaning in doing violence against animalsThe myth of “ethical” or “sustainable” animal farmingCapitalism, disinformation, and self-deceptionWhy welfarist or incremental reforms and utilitarianism risk obscuring or distracting us from the real problem.This is a bold, uncompromising conversation about truth, ethics, and our relationship with other sentient beings.In Sentientist Conversations we talk about the most important questions: “what's real?”, “who matters?” and "how can we make a better world?"Sentientism answers those questions with "evidence, reason & compassion for all sentient beings." The video of our conversation is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here on YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.00:00 Clips“What I conclude in the book is that our violence against animals, the way we treat animals, the meat question, the food question, these are not trivial matters.”“What I argue is that this is the most important issue of our time. We kill about 80 billion land animals every year in agriculture and up to almost 3 trillion marine animals in the oceans.”“Industries intentionally don't show us the violence and suffering and filth that goes into the production. You're only going to see the commodity in its processed form.”“My message is simply that we have to show a kind of courage and resilience in the face of what's happening. And we just can't give up. We do the work because it matters and it's the right thing to do.”01:11 WelcomeJohn on Sentientism episode 171    • "We've made a civilizational error" - Phil...  03:06 John's Intro06:34 Deceptions11:27 Bad Faith13:43 Michael Pollan, Temple Grandin, Barbara Kingsolver19:50 Andrew Tate, Joe Rogan, Jordan Peterson, Carnivore Dieters and Fascism25:22 The Femivores33:45 Wellness, #Conspirituality, New Age and #MAHA 39:10 It's Natural!40:50 Our Civilisational Error51:28 Fixing the Error01:09:44 Closing MessagesSentientism is “Evidence, reason & compassion for all sentient beings.” More at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Sentientism.info⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Join our⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠"I'm a Sentientist" wall⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ via⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ this simple form⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Everyone, Sentientist or not, is welcome in our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠groups⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. The biggest so far is ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here on FaceBook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Come join us there!

Across Australia, for every dollar a man earns, women on average are earning 88- point- 8 cents. The government's gender equality agency says the gender pay gap has narrowed to 11. 2 per cent. And while most sectors have seen improvements, pay gaps remain large in some male-dominated industries, such as finance, construction and mining. - จากการสำรวจค่าจ้างทั่วออสเตรเลียพบว่า สำหรับรายได้ทุก 1 ดอลลาร์ที่ผู้ชายได้รับ ผู้หญิงโดยเฉลี่ยจะได้รับประมาณ 88.8 เซนต์ อย่างไรก็ตามหน่วยงานด้านความเท่าเทียมทางเพศของรัฐบาลกลางออสเตรเลียระบุว่า ช่องว่างค่าจ้างระหว่างเพศ (gender pay gap) ลดลงมาอยู่ที่ร้อยละ11.2

(00:00:00) First, Penny Lenig‑Zerby, director of the UPMC Shadyside School of Nursing in Harrisburg, and Joye Gingrich, UPMC in Central Pa.’s Chief Nursing Officer, share their personal journeys into nursing and what drives them to train the next generation. They discuss the realities of today’s nursing workforce, the many career paths available to new graduates, and how UPMC supports nurses as they enter the field and continue their education. They also outline practical steps for listeners interested in applying to nursing school at a time when demand for skilled nurses has never been higher. (00:22:22) Then, the conversation shifts to Pennsylvania’s hemp and cannabis landscape through the story of Lazy Moon Ranch and its founder, Ron Boyles. After a debilitating back injury and years of opioid dependence, Ron turned to medical cannabis—an experience that helped him reclaim his health and sparked his advocacy for patient access. Today he leads the Green Bridge Society, connecting patients with certifying doctors across multiple states, and cultivates CBD hemp at Lazy Moon Ranch following the 2018 Hemp Farm Bill. Ron shares what distinguishes hemp from cannabis, how the industry works, and what recent legislation means for growers, consumers, and curious newcomers. Support WITF: https://www.witf.org/support/give-now/See omnystudio.com/listener for privacy information.

Across Australia, for every dollar a man earns, women on average are earning 88- point- 8 cents. The government's gender equality agency says the gender pay gap has narrowed to 11. 2 per cent. And while most sectors have seen improvements, pay gaps remain large in some male-dominated industries, such as finance, construction and mining. - در سراسر آسترالیا، در برابر هر یک دالر که مردان به دست می آورند، زنان به طور اوسط ۸۸،۸ سنت درآمد دارند. اداره برابری جنسیتی در محل کار می گوید "شکاف معاش بر اساس جندر" به ۱۱،۲ درصد کاهش یافته است. در حالیکه در بخش های مختلف بهبود دیده می شود، اما در صنعت های مردسالار مثل امور مالی، ساختمان سازی و کار در معدن این تفاوت معاش بطور واضح وجود دارد.

In this episode of The General Counsel Series (in proud collaboration with @ZohoSign), we sit down with Sandhya Tolat, General Counsel at Aarti Industries, to decode what modern legal leadership looks like inside a large, manufacturing-led organisation—where law intersects daily with plant operations, safety, environment, supply continuity, contracts, and reputation.  From the mindset shift required to move from “legal correctness” to legal, business, and operational decision-making, to building high-trust internal legal teams and choosing technology that actually gets adopted across locations and workflows - this conversation is packed with practical insights for in-house counsel, external counsel, law students, and business leaders.  A special focus in this episode is how GCs evaluate and implement digital execution and governance, and where digital signature solutions like Zoho Sign can make the biggest day-to-day difference, from vendor and customer contracting to HR documentation and board/governance workflows.  A big thank you to @ZohoSign for powering this series. About Zoho Sign Zoho Sign is part of the Zoho suite of digital products and enables organisations to streamline document execution with secure digital signing and governance-friendly workflows. Connect with us The Daily Lawyer Contact: contactus@thedailylawyer.in Website: https://thedailylawyer.in/ Instagram: https://www.instagram.com/thedailylawyer/ LinkedIn (Jenna Krishnan): https://www.linkedin.com/in/jenna-v-krishnan/ Connect with Zoho Sign Instagram: https://www.instagram.com/zohosignoff... X: https://x.com/zohosign?lang=en LinkedIn: https://www.linkedin.com/company/zohosign/ YouTube: https://www.youtube.com/@zohosign Explore: https://www.zoho.com/en-in/sign/ #GeneralCounsel #InHouseCounsel #ZohoSign #ContractManagement #LegalTech

Plus: Goldman Sachs report predicts artificial intelligence will displace 6% of the US workforce. And Verizon has discussed revising or exiting its NFL partnership as part of a company-wide push to reduce costs. Danny Lewis hosts. Learn more about your ad choices. Visit megaphone.fm/adchoices

Across Australia, for every dollar a man earns, women on average are earning 88- point- 8 cents. The government's gender equality agency says the gender pay gap has narrowed to 11. 2 per cent. And while most sectors have seen improvements, pay gaps remain large in some male-dominated industries, such as finance, construction and mining.

On Episode 813 of The Core Report, financial journalist Govindraj Ethiraj talks to Dr. Amit Goenka, Founder, Chairman and Managing Director at the Nisus Finance Group (NiFCO). SHOW NOTES(00:00) Stories of the Day(01:09) Gas supplies to critical industries like fertiliser and power will see cuts as Qatar shuts production(02:27) The amazing US argument for exporting its LNG to other countries.(07:41) Brent crude futures have hit $85 a barrel(08:56) How a strong dollar is keeping gold, silver in check(10:26) Flights into and out of the Emirates have resumed but only sporadically suggesting travellers have a longer wait ahead(11:22) Freight Rates have gone up Significantly(12:03) Why real estate funds are becoming popularRegister for India Finance and Innovation Forum 2026https://tinyurl.com/IFIFCOREFor more of our coverage check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠thecore.in⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow us on:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Youtube⁠⁠⁠⁠⁠

In episode #64 of PodSpot, Jon Pittham is joined by Hank Lander, Group Product Manager at HubSpot, to discuss sensitive data management and AI governance in regulated industries. The episode explores how HubSpot defines and categorises sensitive data, how firms can configure controls within the platform, and what enhanced auditing and visibility look like in practice. The discussion also covers integration considerations for organisations connecting HubSpot with core systems. A key focus is AI. Hank explains HubSpot's approach to zero data retention, the handling of sensitive properties within AI workflows, and how customers can align platform controls with their own risk appetite. The episode also touches on emerging capabilities designed to help firms identify and manage sensitive information more proactively. This is a practical conversation for financial services and professional services leaders who want to balance innovation with strong governance, without compromising trust.   Key discussion points: 04:10 – What Is Sensitive Data? 10:05 – Standard vs Highly Sensitive Properties 16:05 – Audit Controls & Integrations 21:05 – Zero Data Retention and AI Model Transparency 29:10 – Roadmap Direction and Future Investment in Data Controls   Want to learn more about HubSpot? Visit our website: https://www.karman.digital/ Follow us on LinkedIn Listen on Spotify Listen on Apple Podcasts

Ty Farmer, senior director of Corporate Safety at Dycom Industries, Inc. could have let being placed on a performance improvement plan (PIP) early in his career derail him completely. Instead, he turned a difficult moment into a powerful learning experience and an opportunity for growth. Ty's military background led him to his first role at General Electric (GE), where he was quickly thrown into the fire as a regional EHS manager for the United States, Mexico, and Canada. Rather than shutting down in the face of early challenges, Ty leaned into his experiences, using them as opportunities to reflect and grow. After more than a decade at GE, he moved on to a new role where he built an organization's safety program completely from the ground up. In this episode of My Big Safety Challenge, Ty shares why building genuine connections across an organization—from the brand-new employee to the c-suite executive—is essential to creating a strong safety culture. He also discusses the importance of a glass-half-full mindset, offers practical insight on gaining leadership buy-in, and explains why it's a strength, not a weakness, to ask for help.

Toyota Motor Corp. and others said Monday that they will raise their tender offer price for Toyota Industries Corp., the original company of the Toyota group, to 20,600 yen per share from 18,800 yen.

New York City was the focus of the early American television industry. In TV's early years NYC had the highest concentration of television sets, viewers, broadcasters, and infrastructure. In NYC many Americans had their first encounter with TV. In his latest book project, Dr. Richard Popp, associate professor at the University of Wisconsin at Milwaukee, tunes into the tangled relationship between televisions and the urban fabric and lived experience of NYC. Using several collections held in the Hagley Library, including those of RCA, David Sarnoff, and Ernest Dichter, Popp explores the history of television screens in public spaces, and the many misadventures of the television repair industry. In support of his research, Dr. Popp received funding from the Hagley Center for the History of Business, Technology, and Society at the Hagley Museum and Library. For more information, and more Hagley History Hangouts, visit us online at hagley.org. To make a donation underwriting this program and others like it please visit our Eventbrite page: https://www.eventbrite.com/e/underwriting-donation-tickets-1470779985529?aff=oddtdtcreator

After reporting a strong quarter, Nvidia CEO Jensen Huang speaks to Becky Quick about his company's future and the future of the AI landscape–including the ongoing standoff between Anthropic and the Pentagon. FDA Commissioner Dr. Marty Makary discusses the agency's push for reforms and expedited drug approvals, particularly for rare disease therapies. Plus, Beast Games Season 2 finale is out on Amazon Prime, and season three is already in preproduction. Beast Industries CEO Jeff Housenbold discusses his ambitions of building another Disney while producing the most-followed person on the internet, Mr. Beast.    Dr. Marty Makary - 17:16 Jeff Housenbold - 33:30   In this episode: Dr. Marty Makary, @DrMakaryFDA Jeff Housenbold, @jtbold Joe Kernen, @JoeSquawk Becky Quick, @BeckyQuick Andrew Ross Sorkin,  @andrewrsorkin Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Compass Industries President Mike Levy joins Promo Insiders to discuss how the third-generation family business built its product niche and how it tackles industry relationship-building today, both with retail manufacturers and promo distributors.

Plus: FedEx sues the Trump administration seeking a tariff refund. And U.S. markets are pointing to a higher open following a selloff sparked by fears of AI disruption and trade-policy uncertainty. Daniel Bach hosts. Sign up for WSJ's free What's News newsletter. Learn more about your ad choices. Visit megaphone.fm/adchoices

Revolutionizing Compliance: Modernizing Inspection Workflows with Tim HarrisIn a recent episode of The Thoughtful Entrepreneur Podcast, host Josh Elledge sat down with Tim Harris, the Chief Executive Officer of VirtuSpect, to explore how digital transformation is finally reaching the heavily regulated world of physical inspections. Tim shared how VirtuSpect is dismantling the traditional, slow-moving inspection model—particularly in the banking sector—by replacing manual third-party visits with a secure, automated SaaS platform. Their conversation dives into the critical intersection of speed and compliance, revealing how financial institutions and regulated enterprises can close loans faster and reduce operational overhead without compromising on security or regulatory rigor.Accelerating Efficiency: The Shift to Automated, Self-Guided InspectionsThe primary bottleneck in regulated industries has long been the reliance on manual, third-party inspections that can delay business cycles by several days or even weeks. Tim explains that the traditional "wait-and-see" approach, where an external inspector must be scheduled and dispatched, is being replaced by a guided, mobile-first experience that empowers internal staff or even business owners to complete the task themselves. By utilizing a secure mobile app that walks a non-expert through every required photo, video, and data point, VirtuSpect has seen turnaround times plummet from an average of five days to as little as 28 minutes. This radical shift in efficiency allows banks to move from inspection to loan closing in record time, significantly increasing interest income and enhancing the overall customer experience.Cost savings and scalability go hand-in-hand when an organization moves away from per-inspection travel fees and administrative bloat. Because the platform is built to handle thousands of requests per day, it allows enterprises to scale their operations without a linear increase in headcount or external vendor costs. Automated notifications and escalation triggers ensure that remediation steps are handled instantly, preventing human error from stalling a high-stakes audit or loan approval. For organizations conducting hundreds or thousands of inspections annually, this move toward productized, scalable workflows transforms a necessary administrative burden into a streamlined competitive advantage that can be deployed across various verticals.Beyond the immediate gains in speed, the platform is engineered to meet the stringent security and privacy demands of the financial and securities sectors. Every inspection performed through the system creates a comprehensive, encrypted audit trail that is far more robust than the fragmented email chains and physical files of the past. By collaborating with compliance experts to ensure that inspection criteria align with current regulations, VirtuSpect provides an enterprise-grade foundation that protects sensitive data both in transit and at rest. As the platform expands into branch audits, home office inspections, and asset management, it provides a unified source of truth that satisfies regulators while giving leadership real-time visibility into the health of their distributed assets.About Tim HarrisTim Harris is the Chief Executive Officer of VirtuSpect and a veteran leader in the technology space. A disciplined entrepreneur known for his rigorous personal routines—including a decade-long commitment to early-morning swimming—Tim applies a focus on technique and efficiency to help regulated industries modernize their most entrenched manual processes.About VirtuSpectVirtuSpect is a SaaS platform that provides automated inspection and remediation workflows for regulated industries, including banking, securities, and asset management. The company empowers...

Simon and Dan take a break from the usual AI doom talk to focus on the other side of the trade: industries AI is unlikely to disrupt—and may actually strengthen. They discuss why parts of the “real economy” (natural resources, waste collection, skilled trades, and critical infrastructure work) have durable moats tied to physical assets, regulation, and human accountability. In Stocks on Our Radar, Dan revisits Shopify after a sharp drawdown and explains why AI could be a tailwind through payments and backend infrastructure, even if storefront tools get commoditized. Simon breaks down why he started a position in WSP Global, pointing to its backlog, acquisition strategy, and long runway from grid buildouts and electrification tied to AI-driven energy demand. Tickers discussed: SHOP, WSP.TO, ACM, PWR, BDGI.TO, ARE.TO Subscribe to our Our New Youtube Channel! Check out our portfolio by going to Jointci.com Our Website Our New Youtube Channel! Canadian Investor Podcast Network Twitter: @cdn_investing Simon’s twitter: @Fiat_Iceberg Braden’s twitter: @BradoCapital Dan’s Twitter: @stocktrades_ca Want to learn more about Real Estate Investing? Check out the Canadian Real Estate Investor Podcast! Apple Podcast - The Canadian Real Estate Investor Spotify - The Canadian Real Estate Investor Web player - The Canadian Real Estate Investor Asset Allocation ETFs | BMO Global Asset Management Sign up for Fiscal.ai for free to get easy access to global stock coverage and powerful AI investing tools. Register for EQ Bank, the seamless digital banking experience with better rates and no nonsense. See omnystudio.com/listener for privacy information.

Episode 5159: Protecting American Industries And The Fight For Tariffs

If you've only sold sexy products with cool demos and unique features, you're probably missing the fundamentals that separate good salespeople from great ones. Marcus Chan, CEO of Venli Consulting and recent guest on the Sales Gravy podcast, learned to sell in the trenches of commoditized selling: uniforms, facility services, telecom. Industries where you're locked in multi-year contract cycles, competing against five other vendors who offer the exact same thing, and selling at two to three times the market price. "In order to get really, really good at selling in the commoditized market, where price seems to be the only factor... you have to learn how to get really good at the sales process," Chan explains. "You have to be able to take someone who has what I call a latent pain—pain they don't realize—get them to active and create urgency to move." No flash. No sizzle. Just selling. And that's exactly why it works. The First-to-Market Delusion Chan was talking with a client recently. They've closed $5 million in revenue in 12 months. Apple, Fortune 500 companies, massive wins. They're first to market in a brand new category. Zero competitors. Their sales team is flying high. "That's fantastic," he told them. "Now what's your plan for when competitors show up in three years?" Silence. Here's what happens: you get drunk on the product. You don't have to build real sales skills because the product does the heavy lifting. Then the market matures. Competitors launch. Your "unique" features become nothing new. Most teams operate under the belief that they're different. They talk about their proprietary technology, their best-in-class service, and their innovative approach. Meanwhile, buyers are looking at five vendors saying the exact same things. This isn't just true for uniforms and telecom. It's true for SaaS, consulting, financial services. Any market that's been around longer than 18 months gets commoditized fast. The question isn't whether you're in a commoditized market. The question is whether you know how to sell when you are. What Commoditized Selling Actually Teaches You When Chan was selling uniforms at three times the competitor's price to buyers locked into five-year contracts with other vendors, he had nothing to lean on except process. He couldn't say, "Look at this cool new feature." The uniforms were uniforms. Same fabric. Same colors. Same everything. He had to learn three skills most salespeople never develop: Moving buyers from latent pain to active pain. Most buyers don't think they have a problem. They're comfortable. They're "fine" with their current vendor. Your job is to help them realize what they're losing by staying put, and make it real enough that they care. Creating urgency when the status quo is locked in. When a buyer is in year three of a five-year contract, there's zero natural urgency. You have to create it. You have to make the pain of waiting worse than the pain of switching. Navigating complex, multi-stakeholder sales cycles without a product demo to fall back on. You need the operations manager, the finance team, and the C-suite to all agree that switching vendors is worth the headache. And you need to do it without any bells and whistles to distract them from the hard questions. The Hidden Advantage Nobody Talks About Mastering commoditized selling makes everything else easier. Learn to sell uniforms at a premium price, and differentiated products become simple. The hard skills transfer—objection handling, stakeholder navigation, urgency creation. But the real value is that your process becomes your product. In commoditized markets, you compete on how you sell. Your discovery process. Your ability to diagnose the real problem. Your consultative approach. The way you make the buyer feel heard and understood. That's what buyers remember and what separates you from the five other vendors in their inbox. Stop Hiding Behind Your Product Chan sees it all the time with sales teams from "sexy" industries. They lead with features because they can. They lean on their demo because it works. They let the product do the selling. Until it doesn't. Because eventually, every market commoditizes. Your competitor launches the same feature. Buyers stop caring about your "innovative solution" and start asking about price. The salespeople who win in commoditized markets win because of process, not product. They've mastered diagnosis, urgency, and navigating complexity when there's nothing shiny to distract the buyer. A Commoditized Market Is the Best Sales Training Ground If you're selling in a commoditized market right now, congratulations. You're getting an education most salespeople never get—how to compete when you're "just another vendor," how to create value when the product doesn't, how to win on process instead of features. Sell commodities at premium prices to buyers locked into competitor contracts, and you can sell anything. Master the fundamentals where there are no shortcuts, and those fundamentals become automatic. Move to a market with actual differentiation, and you don't just have a good product—you have a good product and the skills to sell it. Winning in Commoditized Selling The best training ground for sales isn't the hottest SaaS company or the coolest startup. It's the "boring," commoditized industries where the product doesn't do the work for you. Where you have to diagnose the problem, create urgency, and navigate complexity without flash to hide behind. The skills you build when nothing else can save you? Those are the skills that make you unstoppable everywhere else. -- If you want to sharpen the fundamentals that win in any market, start with prospecting. Download the free Seven Steps Prospecting Sequence Guide and build a process that creates urgency and fills your pipeline on purpose.

New @InThisLeaguePod Fantasy Baseball Podcast with @BogmanSports and @IsItTheWelsh⚾ Industries Favorite Draft Targets ⚾➡️ ECR vs ADP➡️ Players with abnormal high ranks➡️ Players with the biggest gap between high and low ranksJoin up to be a member of the army and support your boys to create more and more fantasy Baseball content that not only wins your league, but makes you laugh! Redraft ranks, prospect/dynasty ranks, groupme rooms, live podcasts, and more! Find it all at inthisleague.com

What does it take to grow a third-generation family machine shop into a diversified, nearly 100-person operation pushing $20 million in revenue? In this episode of Machine Shop Mastery, I sit down with Zac Overton of Overton Industries to unpack the evolution of a business that started as a 900-square-foot carbide tooling shop in 1968 and grew into a multi-division manufacturing company spanning tool & die, contract CNC machining, high-speed stamping (300 million parts per year), and advanced tube forming automation systems. Zac shares how his grandfather's "lifestyle business" became something much bigger when the second generation stepped in unexpectedly and decided scale was the only path forward. We talk about diversification, leadership development, transparency with employees, workforce pipelines, and what it really takes to evolve from tool-and-die thinking into a continuous-improvement contract machining mindset. One of the most powerful takeaways is Zac's perspective on marketing. Overton has generated nearly $10 million in new business in the last five years directly attributable to strategic marketing investments. If you think marketing doesn't apply to manufacturing, this conversation might change your mind. This episode is a masterclass in multi-generational leadership, operational transition, and intentional growth.  You will want to hear this episode if you are interested in... (0:48) Overview of Overton Industries: tool & die, stamping, contract machining, and tube forming systems (4:55) The evolution of the tool & die business, carbide tooling, and high-speed stamping (8:22) It's time to gear up for IMTS 2026 — will you see us there? (10:13) Company size, revenue, and scaling toward $20M (10:56) How Zac's grandfather launched the business in 1968 (12:56) Taking a deep-dive into carbine compaction tooling (15:44) From lifestyle business to growth-focused enterprise (20:15) Zac's path into the business and why he had to earn his way in (25:31) Early sales lessons: curiosity, humility, and learning before selling (27:50) Why we love Phoenix Heat Treating for outside processing (30:01) Workforce development strategy and building long-term talent pipelines (34:37) Partnering with high schools, technical centers, and universities (37:34) Engaging younger students and creating early awareness of manufacturing careers (41:04) Financial transparency and communicating profitability to employees (44:45) Transitioning from tool & die thinking to contract machining optimization (49:08) Continuous improvement challenges and pushing cycle time efficiency (58:00) Growing leaders internally and creating upward career paths (1:03:35) Why marketing has driven over $10M in new business (1:07:38) Qualified hires chosen by industry experts: HireMFGLeaders.com (1:08:21) Brand positioning: shifting from "Everyman" to high-tech leader (1:10:47) Where to connect with Zac and learn more about Overton Industries Resources & People Mentioned It's time to gear up for IMTS 2026 — will you see us there?  Why we love Phoenix Heat Treating for outside processing Qualified hires chosen by industry experts: HireMFGLeaders.com Connect with Zac OVerton Overton Industries Connect on LinkedIn Connect With Machine Shop Mastery The website LinkedIn YouTube Instagram Subscribe to Machine Shop Mastery on Apple, Spotify Audio Production and Show Notes by - PODCAST FAST TRACK

Listen and subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, www.moneymakingconversations.com/subscribe/ or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed T.M. Robinson-Mosley. Summary of the Interview: Dr. T.M. Robinson-Mosley on Money Making Conversations Masterclass Dr. T.M. Robinson-Mosley—founder of The Playbook, an award‑winning mental‑health‑performance sports‑tech company—joins Rushion McDonald to discuss how her platform is transforming athlete care, team culture, and performance measurement. The Playbook uses AI‑powered, gamified psychological assessments to measure stress, resilience, and overall mental well‑being across youth, collegiate, professional, and military sports environments. Mosley explains how mental health—long treated as unmeasurable and stigmatized—is finally becoming trackable, private, and actionable. The Playbook provides real‑time alerts, data‑driven insights, and ecosystem‑wide tools for coaches, trainers, clinicians, and entire organizations. She also shares her journey as a non‑coding tech founder, the scaling challenges brought on by the pandemic, and the broader impact The Playbook is poised to have across corporate, construction, military, and other high‑stress fields. Purpose of the Interview 1. Introduce and explain The Playbook To present The Playbook as a next‑generation mental health performance platform that quantifies mental well‑being, provides action plans, and enhances team culture. 2. Elevate the conversation around athlete mental health Mosley breaks down stigma, highlights real athlete stories, and explains why mental analytics are as critical as physical analytics. 3. Show how the platform uses technology to prevent crises The Playbook provides early detection, privacy protection, and immediate care support—catching problems before they become crises. 4. Highlight the expansion beyond sports Although built in sports, the platform is already being requested by industries like construction, healthcare, first responders, and more. ] 5. Demonstrate the business model As a SaaS B2B platform, The Playbook sells licensed subscriptions to organizations, teams, and associations. Key Takeaways 1. Mental health can be measured—and must be The Playbook converts psychological assessments into quantifiable metrics similar to heart rate or step count.Athletes receive resilience, stress, and well‑being scores—like a “mental batting average.” 2. The platform offers real-time alerts If an athlete’s score enters the “red zone,” coaches/clinicians receive immediate alerts with steps to take within 24 hours. 3. Privacy is paramount The Playbook is HIPAA‑compliant, mobile, secure, and built to protect athlete data from misuse (e.g., contract negotiations). 4. Mental analytics are the next frontier of sports Teams already use physical analytics. Now they can use mental analytics to track performance, prevent burnout, and reduce crises. 5. Built for the entire ecosystem—not just athletes Coaches, front offices, sports medicine staff, and military leadership also use the platform—promoting culture-wide mental health. 6. The Playbook is expanding beyond sports Industries with high stress—construction, medicine, law, emergency responders, veterinarians—are already approaching Mosley to adapt the system. 7. A critical solution for underserved communities The platform makes mental health care accessible, private, digital, and stigma‑free—especially for youth and communities of color. 8. Performance is universal Whether you’re an athlete, military member, parent, or worker—your mental state impacts how you perform. Performance is “agnostic.” [ 9. Mosley’s journey shows innovation can come from anywhere She is a non‑coding tech founder, originally trained as a psychologist working across the NBA, NFL, NCAA, and Olympic sports. [T.M. ROBINSON MOSLEY | Txt] Notable Quotes On what The Playbook does “We measure mental health metrics like resilience, stress and overall well‑being using gamified psych assessments.” “Mental health becomes measurable—like a batting average.” [ On why athletes need this “Elite athletes report battling depression and anxiety so severe they find it difficult to function, let alone perform.” On the power of technology “If we don’t measure something, we’re saying it doesn’t matter.” “We use AI and machine learning to quantify mental health status.” On privacy “We are a HIPAA‑compliant platform… we don’t sell your data.” On team culture “Building a winning team culture is everybody’s everyday work.” On mental and physical health “If you are not mentally healthy, you are not able to perform at the highest level.” On the future outside sports “Who doesn’t want to train like an athlete?” “Performance is agnostic.” On purpose “How do we make something exclusive accessible?” “This is mental health care—it’s just a different version of it.” In One Sentence The interview reveals how Dr. T.M. Robinson-Mosley’s Playbook uses AI‑driven mental health metrics to revolutionize athlete care, provide real‑time performance insights, and expand mental wellness tools far beyond sports into everyday life. #SHMS #STRAW #BESTSupport the show: https://www.steveharveyfm.com/See omnystudio.com/listener for privacy information.

Listen and subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, www.moneymakingconversations.com/subscribe/ or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed T.M. Robinson-Mosley. Summary of the Interview: Dr. T.M. Robinson-Mosley on Money Making Conversations Masterclass Dr. T.M. Robinson-Mosley—founder of The Playbook, an award‑winning mental‑health‑performance sports‑tech company—joins Rushion McDonald to discuss how her platform is transforming athlete care, team culture, and performance measurement. The Playbook uses AI‑powered, gamified psychological assessments to measure stress, resilience, and overall mental well‑being across youth, collegiate, professional, and military sports environments. Mosley explains how mental health—long treated as unmeasurable and stigmatized—is finally becoming trackable, private, and actionable. The Playbook provides real‑time alerts, data‑driven insights, and ecosystem‑wide tools for coaches, trainers, clinicians, and entire organizations. She also shares her journey as a non‑coding tech founder, the scaling challenges brought on by the pandemic, and the broader impact The Playbook is poised to have across corporate, construction, military, and other high‑stress fields. Purpose of the Interview 1. Introduce and explain The Playbook To present The Playbook as a next‑generation mental health performance platform that quantifies mental well‑being, provides action plans, and enhances team culture. 2. Elevate the conversation around athlete mental health Mosley breaks down stigma, highlights real athlete stories, and explains why mental analytics are as critical as physical analytics. 3. Show how the platform uses technology to prevent crises The Playbook provides early detection, privacy protection, and immediate care support—catching problems before they become crises. 4. Highlight the expansion beyond sports Although built in sports, the platform is already being requested by industries like construction, healthcare, first responders, and more. ] 5. Demonstrate the business model As a SaaS B2B platform, The Playbook sells licensed subscriptions to organizations, teams, and associations. Key Takeaways 1. Mental health can be measured—and must be The Playbook converts psychological assessments into quantifiable metrics similar to heart rate or step count.Athletes receive resilience, stress, and well‑being scores—like a “mental batting average.” 2. The platform offers real-time alerts If an athlete’s score enters the “red zone,” coaches/clinicians receive immediate alerts with steps to take within 24 hours. 3. Privacy is paramount The Playbook is HIPAA‑compliant, mobile, secure, and built to protect athlete data from misuse (e.g., contract negotiations). 4. Mental analytics are the next frontier of sports Teams already use physical analytics. Now they can use mental analytics to track performance, prevent burnout, and reduce crises. 5. Built for the entire ecosystem—not just athletes Coaches, front offices, sports medicine staff, and military leadership also use the platform—promoting culture-wide mental health. 6. The Playbook is expanding beyond sports Industries with high stress—construction, medicine, law, emergency responders, veterinarians—are already approaching Mosley to adapt the system. 7. A critical solution for underserved communities The platform makes mental health care accessible, private, digital, and stigma‑free—especially for youth and communities of color. 8. Performance is universal Whether you’re an athlete, military member, parent, or worker—your mental state impacts how you perform. Performance is “agnostic.” [ 9. Mosley’s journey shows innovation can come from anywhere She is a non‑coding tech founder, originally trained as a psychologist working across the NBA, NFL, NCAA, and Olympic sports. [T.M. ROBINSON MOSLEY | Txt] Notable Quotes On what The Playbook does “We measure mental health metrics like resilience, stress and overall well‑being using gamified psych assessments.” “Mental health becomes measurable—like a batting average.” [ On why athletes need this “Elite athletes report battling depression and anxiety so severe they find it difficult to function, let alone perform.” On the power of technology “If we don’t measure something, we’re saying it doesn’t matter.” “We use AI and machine learning to quantify mental health status.” On privacy “We are a HIPAA‑compliant platform… we don’t sell your data.” On team culture “Building a winning team culture is everybody’s everyday work.” On mental and physical health “If you are not mentally healthy, you are not able to perform at the highest level.” On the future outside sports “Who doesn’t want to train like an athlete?” “Performance is agnostic.” On purpose “How do we make something exclusive accessible?” “This is mental health care—it’s just a different version of it.” In One Sentence The interview reveals how Dr. T.M. Robinson-Mosley’s Playbook uses AI‑driven mental health metrics to revolutionize athlete care, provide real‑time performance insights, and expand mental wellness tools far beyond sports into everyday life. #SHMS #STRAW #BESTSee omnystudio.com/listener for privacy information.

Listen and subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, www.moneymakingconversations.com/subscribe/ or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed T.M. Robinson-Mosley. Summary of the Interview: Dr. T.M. Robinson-Mosley on Money Making Conversations Masterclass Dr. T.M. Robinson-Mosley—founder of The Playbook, an award‑winning mental‑health‑performance sports‑tech company—joins Rushion McDonald to discuss how her platform is transforming athlete care, team culture, and performance measurement. The Playbook uses AI‑powered, gamified psychological assessments to measure stress, resilience, and overall mental well‑being across youth, collegiate, professional, and military sports environments. Mosley explains how mental health—long treated as unmeasurable and stigmatized—is finally becoming trackable, private, and actionable. The Playbook provides real‑time alerts, data‑driven insights, and ecosystem‑wide tools for coaches, trainers, clinicians, and entire organizations. She also shares her journey as a non‑coding tech founder, the scaling challenges brought on by the pandemic, and the broader impact The Playbook is poised to have across corporate, construction, military, and other high‑stress fields. Purpose of the Interview 1. Introduce and explain The Playbook To present The Playbook as a next‑generation mental health performance platform that quantifies mental well‑being, provides action plans, and enhances team culture. 2. Elevate the conversation around athlete mental health Mosley breaks down stigma, highlights real athlete stories, and explains why mental analytics are as critical as physical analytics. 3. Show how the platform uses technology to prevent crises The Playbook provides early detection, privacy protection, and immediate care support—catching problems before they become crises. 4. Highlight the expansion beyond sports Although built in sports, the platform is already being requested by industries like construction, healthcare, first responders, and more. ] 5. Demonstrate the business model As a SaaS B2B platform, The Playbook sells licensed subscriptions to organizations, teams, and associations. Key Takeaways 1. Mental health can be measured—and must be The Playbook converts psychological assessments into quantifiable metrics similar to heart rate or step count.Athletes receive resilience, stress, and well‑being scores—like a “mental batting average.” 2. The platform offers real-time alerts If an athlete’s score enters the “red zone,” coaches/clinicians receive immediate alerts with steps to take within 24 hours. 3. Privacy is paramount The Playbook is HIPAA‑compliant, mobile, secure, and built to protect athlete data from misuse (e.g., contract negotiations). 4. Mental analytics are the next frontier of sports Teams already use physical analytics. Now they can use mental analytics to track performance, prevent burnout, and reduce crises. 5. Built for the entire ecosystem—not just athletes Coaches, front offices, sports medicine staff, and military leadership also use the platform—promoting culture-wide mental health. 6. The Playbook is expanding beyond sports Industries with high stress—construction, medicine, law, emergency responders, veterinarians—are already approaching Mosley to adapt the system. 7. A critical solution for underserved communities The platform makes mental health care accessible, private, digital, and stigma‑free—especially for youth and communities of color. 8. Performance is universal Whether you’re an athlete, military member, parent, or worker—your mental state impacts how you perform. Performance is “agnostic.” [ 9. Mosley’s journey shows innovation can come from anywhere She is a non‑coding tech founder, originally trained as a psychologist working across the NBA, NFL, NCAA, and Olympic sports. [T.M. ROBINSON MOSLEY | Txt] Notable Quotes On what The Playbook does “We measure mental health metrics like resilience, stress and overall well‑being using gamified psych assessments.” “Mental health becomes measurable—like a batting average.” [ On why athletes need this “Elite athletes report battling depression and anxiety so severe they find it difficult to function, let alone perform.” On the power of technology “If we don’t measure something, we’re saying it doesn’t matter.” “We use AI and machine learning to quantify mental health status.” On privacy “We are a HIPAA‑compliant platform… we don’t sell your data.” On team culture “Building a winning team culture is everybody’s everyday work.” On mental and physical health “If you are not mentally healthy, you are not able to perform at the highest level.” On the future outside sports “Who doesn’t want to train like an athlete?” “Performance is agnostic.” On purpose “How do we make something exclusive accessible?” “This is mental health care—it’s just a different version of it.” In One Sentence The interview reveals how Dr. T.M. Robinson-Mosley’s Playbook uses AI‑driven mental health metrics to revolutionize athlete care, provide real‑time performance insights, and expand mental wellness tools far beyond sports into everyday life. #SHMS #STRAW #BESTSteve Harvey Morning Show Online: http://www.steveharveyfm.com/See omnystudio.com/listener for privacy information.

In this episode, Michelle shares her honest experience after spending a full year in a networking group — including the time commitment, the revenue results, and what she learned along the way. We break down the real numbers, the expectations versus reality, and why what seems like a great visibility strategy isn't always the right fit.  Key takeaways from this episode: Visibility is not the same as being in the right room. Just because you're showing up doesn't mean the environment is aligned. Networking groups often favor transactional businesses. Industries like real estate, finance, and roofing naturally pass referrals — photography is a more emotional, less frequent purchase. Track your data, not just your feelings. When Michelle broke down the numbers, she could make a clear, objective decision. Everything you say yes to means saying no to something else. A four-hour weekly commitment carries real opportunity cost. Experiments aren't failures — they're clarity. The year wasn't wasted; it sharpened her messaging and helped her evaluate where her time is best spent. Environment matters. Effort alone cannot overcome a misaligned room. This is an honest look at what happens when effort meets a misaligned room — and how to evaluate business experiments without making it mean something about you. If you've ever wondered whether networking groups are worth your time as a photographer, this conversation will give you clarity. How to Support the Podcast: Subscribe to the podcast on iTunes or wherever you listen to podcasts. Please like, share, and leave a review. If you like the content, please share with your friends by posting on social media so that we can reach and impact more people. Join our next free coaching workshop: www.getcoachedbyheather.com Connect: Heather Lahtinen: Website, Facebook, Instagram

In The New Geography of Innovation: The Global Contest for Breakthrough Technologies, Mehran Gul examines how innovation works in different countries around the globe—diving deep into the ecosystems that produce great technology companies.Gul is a writer and leading technology thinker, having served as the Lead for the Digital Transformation of Industries at the World Economic Forum. His book, which was nominated as a Financial Times best business book of 2025, he discusses why the United States remains at the world's technological frontier, with only China being a true challenger.In his conversation with Nikolaus Lang, Global Leader of the BCG Henderson Institute, he talks about how innovation ecosystems are converging, the role of statecraft in fostering innovation ecosystems, and the main forces that will shift the global innovation landscape in the coming decade.Key topics discussed: 01:22 | Attributes of successful innovation ecosystems06:57 | US vs. China talent pool10:26 | What China gets right about innovation13:20 | Why Europe lags behind on innovation18:54 | The role of intentional statecraft in fostering innovation23:31 | The convergence of innovation ecosystems around the globe26:34 | Implications for businesses28:56 | How the global innovation landscape will evolve in the next decade

Terra Industries, the African defense company, announced Monday that it had secured an additional $22 million in funding to further expand the business. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Episode A33 Be ferocious! How can we help you take action? What can we learn from the web jungle today? Our tiger is back to remind us… Be ferocious in your week this week!YOU be the tiger! And we have a brief surprise visit from the tiger in my backyard! What are YOUR questions? How can we HELP YOU? Listen https://www.askawebgeek.com/wp-content/uploads/animal-033-tiger-again.mp3 Ask a Web Geek: Join our FB group: See Ask a Web Geek (@FB) Jump into our ongoing conversations! What are YOUR questions? How can we HELP YOU? More Resources: More Resources & links at Jungle-Studios.com/resources BONUS Trainings and Resources! Refer to / Browse https://jungle-studios.com/meet-cj Download Episode Related Episodes A33 – Be ferocious! How can we help you take action? by CJ Gilbert | Feb 16, 2026 | Geek BytesEpisode A33 Be ferocious! How can we help you take action?What can we learn from the web jungle today? Our tiger is back to remind us... Be ferocious in your week this week!YOU be the tiger! And we have a brief surprise visit from the tiger in my backyard! What are... GB032-01 – Website Tour – Examples & Links of ALL 7 Levels! by CJ Gilbert | Feb 11, 2026 | Geek BytesEpisode GB032-01 Website Tour - Examples & Links of ALL 7 Levels!CJ answers: "Hey CJ! Can you show us some of the different kinds of website you build? Different Capabilities, Industries, etc...?"CJ takes us on a guided tour of the website jungle showing us all the... New Topics Discussed Weekly Join our Facebook Group Today! Want to Join Us? Join our FB Group to Ask a Question and Participate LIVE Play / Watch / Listen 1.) Join Us on Facebook 2.) Watch on YouTube 3.) Follow Us on Twitter 4.) Listen by Podcast Apple Podcasts | Google Podcasts | RSS

Relooted launched.  Apparently.   That's right, another game for "the modern audience" launched to great applause amongst the 160 people who played it. Whereas last week Highguard peaked at almost 100,000 players before catering from the stratosphere, it seems this game never even left the ground. Will game studios ever learn, or are we stuck playing Asian games forever?  

Send a textIf your business results are inconsistent, this episode hits on the real issues of entrepreneurship:execution, micro-corrections, and the decision rules that keep you from blowing up your business.Our special guest is Bob Campana, a California-based serial entrepreneur with over 40 years of experience building successful ventures across hospitality, travel, real estate, and aviation. He's the author of Don't Look Down! The Improbable Adventures and Battle-Tested Lessons of a Serial Entrepreneur: a candid look at the grit and resilience behind four decades of business-building.From hot tub manufacturing to creating Redwood Café, one of Modesto's most beloved spots, and now leading Redwood Café Tours across Europe, Asia, and Oceania, Bob's story is a masterclass in adaptability and optimism. He continues to expand into real estate and aircraft leasing, and has launched his own entrepreneurship podcast. 

In this episode we discuss AI-driven volatility and why “sell first” moments can ignore fundamentals. We share a stay-the-course process: assess fundamentals, judge AI’s impact, then decide: buy, hold, or sell with conviction.#AI #Investing #Markets #RiskManagement To read this week's Sight|Lines, click here. The views expressed in this podcast may not necessarily reflect the views of Stifel Financial Corp. or its affiliates (collectively, Stifel). This communication is provided for information purposes only. Past performance does not guarantee future results. Investing involves risk, including the possible loss of principal. Asset allocation and diversification do not ensure a profit or protect against loss. © Stifel, Nicolaus & Company, Incorporated | Member SIPC & NYSE | www.stifel.com See omnystudio.com/listener for privacy information.

Guests: Alan Tonelson and Jim McTague. The guests analyze a Morgan Stanley report on AI, debating whether increased productivity will cause job losses or create new industries for creative workers.

Guests: Alan Tonelson and Jim McTague. The guests analyze a Morgan Stanley report on AI, debating whether increased productivity will cause job losses or create new industries for creative workers.

Leadership advisor and author Greg Morley joins me to unpack what it actually takes to rebound from setbacks—and why resilience isn't an individual trait as much as a relational one.Most conversations about adversity focus on grit, mindset, or personal toughness. This episode doesn't. Greg and I explore what happens after layoffs, career pivots, health crises, and identity shifts—and why the people who rally fastest are rarely the ones who go it alone.Drawing from over 30 years in global HR leadership, and from interviews conducted for his upcoming book Rally, Greg shares lessons from individuals who endured job loss, serious illness, organizational upheaval, and even genocide. The common thread isn't bravado. It's perspective, learning velocity, and community depth.We discuss why layoffs feel existential, how high burn rates trap professionals in fragile career paths, and why optionality comes from lowering fixed costs—both financial and psychological. We also examine the hidden tension between success and validation, and why redefining what “winning” means is often the first step toward rebuilding.This isn't a conversation about avoiding setbacks. It's about designing a life resilient enough to absorb them.The lesson isn't endurance for its own sake.It's adaptability, self-reflection, and tending the relationships that hold when titles fall away.TL;DR* Resilience is less about toughness and more about future orientation* Recovery speed determines long-term trajectory* Community acts as long-term insurance against career shocks* High fixed costs limit professional flexibility* Continuous learning expands rebound opportunities* Validation through status or possessions creates fragile identity* Simplicity increases adaptability* Listening across differences builds durable relationshipsMemorable Lines* “Rally isn't about pretending nothing happened—it's about moving forward with what you learned.”* “Your network is a long-term investment, not a short-term transaction.”* “Lower the bar you have to step over, and the world opens up.”* “You can't control the shock—but you can control the response.”* “Resilience lives in community, not isolation.”GuestGreg Morley — Leadership advisor, former global HR executive, and authorAuthor of Bond: Belonging and the Keys to Inclusion and Connection and the forthcoming Rally, focused on resilience, recovery, and leadership through adversity.

In this episode of Valley of Depth, we sit down with David Tearse, co-founder and CEO of Karman Industries, to explore a piece of the AI boom that rarely gets attention: thermal infrastructure.As hyperscale data centers grow into multi-gigawatt “AI factories,” the limiting factor is no longer just chips or capital — it's how efficiently we can move and reject heat. David explains how Karman's Heat Processing Unit (HPU) reimagines cooling from first principles, bringing aerospace-grade turbomachinery and modern power electronics to a decidedly unglamorous but critical layer of the AI stack.The conversation moves from the physics of heat to the politics of data centers, and ultimately to why thermal efficiency may become a quiet national security advantage.We discuss:Why thermal management—not chips—may be the next bottleneck in the AI stackHow Karman's HPU replaces traditional chillers and dry coolers outside the data centerHow much additional compute Karman can unlock from the same power inputWhy CO₂ refrigerant de-risks data center builds from a regulatory standpointHow Karman thinks about reliability, uptime, and “aerospace-style” engineeringWhy data centers are becoming a national security issueWhere Karman could expand beyond data centers—nuclear, geothermal, and beyond…and much more.• Chapters •00:00 – Intro00:51 – Elara Nova ad01:21 – Karman Industries mascot02:28 – How would David describe himself?05:01 – The original insight that became Karman Industries06:31 – What do people underestimate about thermal management?07:26 – The story behind the name08:21 – How David and co-founder CJ Karla ended up working together11:15 – Why is now the right time to be solving thermal management?15:13 – Where does the heat go today?16:31 – Energy usage for compute vs cooling17:32 – Energy Savings with Karman's heat processing units (HPUs)18:05 – Why C02?20:48 – Replacing vs integration21:37 – Regulatory side24:42 – Karman's customer pipeline26:33 – Reliability28:59 – Engineering challenges30:39 – What comes next for Karman31:55 – Is thermal management a national security issue?33:21 – David's thoughts on rerouting heat36:23 – HPUs in space37:58 – The company culture that allows for building relaiable solutions quickly44:35 – Milestones for Karman in the next couple of years47:00 – What does David do for fun? • Show notes •Karman's website —https://www.karmanindustries.com/David's socials — https://x.com/7earseMo's socials — https://x.com/itsmoislamPayload's socials — https://twitter.com/payloadspace / https://www.linkedin.com/company/payloadspaceIgnition's socials — https://twitter.com/ignitionnuclear / https://www.linkedin.com/company/ignition-nuclear/Tectonic's socials  — https://twitter.com/tectonicdefense / https://www.linkedin.com/company/tectonicdefense/Valley of Depth archive — Listen: https://pod.payloadspace.com/ • About us •Valley of Depth is a podcast about the technologies that matter — and the people building them. Brought to you by Arkaea Media, the team behind Payload (space), Ignition (nuclear energy), and Tectonic (defense tech), this show goes beyond headlines and hype. We talk to founders, investors, government officials, and military leaders shaping the future of national security and deep tech. From breakthrough science to strategic policy, we dive into the high-stakes decisions behind the world's hardest technologies.Payload: www.payloadspace.comTectonic: www.tectonicdefense.comIgnition: www.ignition-news.com

Bitcoin traders "adopted SLV and GLD as their meme stocks," says George Noble. He attributes the rise of retail interest in the metal space to their profound volatility. That said, George tells investors, "don't pay attention to the daily volatility," noting both silver and gold are up double digits so far in 2026. As traders see silver as a play in AI and EVs, George makes the case that if prices go up so much, builders will just turn to other metals. ======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about

On this episode of SaaS Fuel, host Jeff Mains dives deep with Alex Berkovic, co-founder and CEO of Sphynx, a company modernizing compliance workflows in financial services with AI-powered agents. Alex shares his journey from design engineering at Imperial College and MIT, through founding Adorno AI, to transforming compliance for fintechs, banks, and payments processors with Sphynx. The conversation explores how AI agents shift compliance teams from manual review to confident decision-making, reducing false positives and enabling scalable, reliable compliance. You'll hear practical insights on building customer-driven products, adapting for global regulations, scaling teams and culture, and the evolving role of SaaS leadership in the age of AI.Key Takeaways00:00 "AI Transforming Compliance and Branding"05:53 Manual Compliance Processes in Finance09:16 AI-Powered Decision Support Systems11:24 "Ensuring 99% Compliance Confidence"13:23 "Frictionless AI Integration Process"19:13 "Chasing PMF Relentlessly"21:17 Founder-Led Sales Through Conferences26:08 "Scaring Candidates to Attract Them"29:08 "Hiring High-Agency Talent Matters"31:41 "Firing Culture-Fit Employees"33:30 "Early Startup Hustle Culture"37:47 "AI Revolution in Compliance"42:03 "Driving Engagement & Strategy Insights"Tweetable QuotesAI-Assisted Decision Making in Regulated Industries: "But what they can have is an AI agent, giving them a summary of all the different sources that we orchestrated, the reasoning that we had into making a decision, and them being the final point into making that decision." — Alex Berkovic [00:09:52 → 00:10:08]AI and Compliance Risks: "In compliance, you can't have 20% where you're, I'm not sure. You can't even have 1% where you're not sure. If you onboard a sanctioned individual into your, your fintech or your bank, regulators are going to come in and hit you with a million-dollar fine." — Alex Berkovic [00:11:43 → 00:11:56]Frictionless AI Integration: "We don't need an engineering team to integrate our product, right? We don't need you to integrate our API or whatnot. So we'll work on top of existing systems, just like an employee." — Alex Berkovic [00:13:32 → 00:13:42]The Elusiveness of Product-Market Fit: "I always feel like it's like touching it by the tips of your finger, and then there's more to be done." — Alex Berkovic [00:19:18 → 00:19:23]The Value of High-Agency Employees: "People that leave and start their own thing is great. It means that you've hired someone that was really good at what they were doing." — Alex Berkovic [00:29:47 → 00:29:51]Viral Topic - Leadership Burnout: "Most leaders are exhausted from playing the lone hero, and it's killing both your results and your sanity." — Alex Berkovic [00:30:46 → 00:30:52]Startup Hustle Culture: "I would rather work twice as much rather than hire someone that's gonna not be the right person because we feel we need too much help and we need to deliver." — Alex Berkovic [00:33:37 → 00:33:47]SaaS Leadership Lessons1. **Build Products Based on Customer Needs, Not Just Passion**2. **Start with Co-pilot Mode to Build Trust Gradually**3. **Escalate Uncertain Cases to Humans—Never Compromise on Accuracy**4. **Onboard with Minimum Friction and Learn Company-Specific Processes**5. **Hire Slowly, Fire Fast, and Prioritize Culture Over Credentials**6. **Sustainable Leadership Means High Ownership and Constant Iteration**Guest ResourcesAlex Berkovicalex@sphinxlabs.aihttps://sphinxhq.comhttps://www.linkedin.com/in/alexandreberkovic/https://x.com/alexberkovicEpisode SponsorThe...

George Ivanov talks about how travel and hospitality are moving from chatbots to "invisible hospitality," using agentic AI to anticipate guest needs, personalize service, improve operations, and build trust.

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This episode originally appeared on the Network State Podcast. Balaji Srinivasan and Benedict Evans sit down in Singapore for a wide-ranging conversation on the mechanics of disruption. Evans, a former Andreessen Horowitz partner who now writes one of tech's most-read newsletters, argues that the conversation about any technology peaks during the transition—not at 0% or 100% adoption. They cover AI's real capabilities and limits, the politics of technological disruption, why crypto's killer metric is block space, and what smart glasses, elevator attendants, and the elephant graph reveal about how change works.  Resources:Follow Benedict Evans on LinkedIn: https://www.linkedin.com/in/benedictevans/Check out Benedict's Newsletter: https://www.ben-evans.com/newsletterFollow Balaji Srinivasan on X: https://x.com/balajisCheck out Network State Podcast: https://www.youtube.com/@nspodcastHigh Output Management: https://www.amazon.com/High-Output-Management-Andrew-Grove-ebook/dp/B015VACHOK/eHang: https://www.youtube.com/watch?v=nUTu4_8QznEThe Deep Research Problem: https://www.ben-evans.com/benedictevans/2025/2/17/the-deep-research-problemARC AGI: https://arcprize.org/arc-agiUber and Airbnb didn't sell software: https://www.ben-evans.com/benedictevans/2025/3/14/what-kind-of-disruptionAI Use cases: https://www.ben-evans.com/benedictevans/2024/4/19/looking-for-ai-use-casesStablecoin surpasses Visa & Mastercard: https://crypto.news/ark-invest-stablecoin-transaction-value-in-2024-surpasses-visa-and-mastercard/Senate passes stablecoin bill: https://www.reuters.com/sustainability/boards-policy-regulation/us-senate-passes-stablecoin-bill-milestone-crypto-industry-2025-06-17/ Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Brady sits down with Danny Barreto of Airlock Industries to dig into what makes the Zero Gravity suppressors such a standout for hunters—especially when ounces, durability, and real-world performance all matter. Plus, the backstory on how he helped Brady rethink using a suppressor for hunting.They break down Airlock's engineering-first design philosophy—more time spent in development and testing, less time chasing flashy marketing hype—and what that means for backcountry hunters. From rifle setup and hearing protection to practical field considerations, this episode covers how to think about suppression as part of a complete hunting system. And Brady gets to the big question: why does Airlock seem to be everywhere so fast? If you've been curious about going suppressed for hunting (or you already do and want to nerd out on the why), this one's for you.Learn more about GOHUNT.Follow Brady on Instagram.Follow GOHUNT on Social Media:InstagramYouTube - Podcast ChannelYouTube - Main ChannelFacebook

Find us at www.crisisinvesting.com   In this episode, Doug and Matt discuss the recent activity in metals and mining markets, including the U.S. government's strategic initiatives to stockpile critical minerals. They scrutinize Trump's $12 billion Project Vault and proposals to expand the export-import bank's budget, exploring how these moves could affect the mining industry. The conversation then shifts to the burgeoning AI landscape, noting developments in AI that enable bots to interact, remember, and even form communities autonomously. Doug and Matt also delve into the criticism of governmental interference and potential impacts on investors, touching on the broader implications of AI on the job market and future technological advancements. The episode wraps up with investment advice and Doug's thoughts on regulatory changes. 00:00 Introduction and Market Overview 00:16 Government Interventions in Mining 01:06 Economic Implications of Government Actions 03:23 Historical Context and Strategic Metals 11:05 AI Developments and Ethical Considerations 18:35 Impact of AI on Jobs and Industries 23:09 Gold and Silver Market Dynamics 30:13 Conclusion and Investment Advice

This Week In Startups is made possible by:Uber - http://uber.com/twistDeel - http://deel.com/twistNorthwest Registered Agent - https://www.northwestregisteredagent.com/twistToday's show: SpaceX is buying xAI, forming a mega-corp that plans to launch data centers into SPACE. Will Tesla also join up, fulfilling Elon's destiny to become real-life Tony Stark, with his own Musk Industries? Jason and Alex break down the future of SpaceXAI in a breaking news report.THEN, we're still celebrating OpenClaw (née Clawdbot) Mania! Oliver and Lukas return to TWiST to share their Almost Top 10 (okay it's just a Top 6) favorite Skills so far. Learn how they're using Replicants to summarize TWiST episodes, surf Reddit, produce original Gamma decks, train agents to make themselves smarter, and take care of LAUNCH's administrative and operations tasks.Timestamps:(00:00) BREAKING: SpaceX bought xAI! (1:56) Why it will be cheaper to generate compute in space than here on Earth(8:19) Will Tesla eventually join the club, forming “Musk Industries”?(11:36) Uber AI Solutions - Your trusted partner to get AI to work in the real world. Book a demo with them TODAY at http://uber.com/twist(12:37) ALSO BREAKING: We're still obsessing about Clawdbot/OpenClaw(14:58) So is OpenClaw and all of its various skills secure yet? NO.(16:42) Today we're looking at our picks for the Top 6 OpenClaw skills(17:13) Alex's first pick: Reddit (read only), which makes it easier to track down what you want on the aggregator(19:35) Reddit hates bots! But maybe they'll change their tune?(21:47) Deel - Founders ship faster on Deel. Set up payroll for any country in minutes and get back to building. Visit http://deel.com/twist to learn more.(22:46) Our Replicant summarized the last few episodes of TWiST… but at what COST? (18 cents)(26:40) Lukas taught our Replicant to make Gamma decks for us(29:23) Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity —  Learn more at https://www.northwestregisteredagent.com/twist(30:21) Our Replicant has ALL the Polymarket data now! The power!(34:14) AI agents are also playing cards together on ClawPoker(35:07) Oliver tested out our pal Matt Van Horn's (@mvanhorn) self-improving “Last 30 Days” skill(38:22) Why memory is so crucial for getting models to improve themselves over time(40:33) Yo dawg I know you like monitoring tasks so I built you a task monitor that monitors your tasks so you can task monitor your tasks(41:40) What makes OpenClaw so powerful is also what makes it dangerous!(49:12) If you want to really learn about OpenClaw, you need to make your own skills(50:03) Jason's advice for OpenClaw's suddenly famous creator: Peter Steinberger (@steipete)(56:31) What would be the best way(s) to monetize OpenClaw?(57:54) Will an OpenClaw agent sue a human in court?*Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com/Check out the TWIST500: https://twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcp*Follow Lon:X: https://x.com/lons*Follow Alex:X: https://x.com/alexLinkedIn: https://www.linkedin.com/in/alexwilhelm/*Thank you to our partners:(11:36) Uber AI Solutions - Your trusted partner to get AI to work in the real world. Book a demo with them TODAY at http://uber.com/twist(21:47) Deel - Founders ship faster on Deel. Set up payroll for any country in minutes and get back to building. Visit http://deel.com/twist to learn more.(29:23) Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity —  Learn more at https://www.northwestregisteredagent.com/twistCheck out all our partner offers: https://partners.launch.co/

Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed T.M. Robinson-Mosley. Summary of the Interview: Dr. T.M. Robinson-Mosley on Money Making Conversations Masterclass Dr. T.M. Robinson-Mosley—founder of The Playbook, an award‑winning mental‑health‑performance sports‑tech company—joins Rushion McDonald to discuss how her platform is transforming athlete care, team culture, and performance measurement. The Playbook uses AI‑powered, gamified psychological assessments to measure stress, resilience, and overall mental well‑being across youth, collegiate, professional, and military sports environments. Mosley explains how mental health—long treated as unmeasurable and stigmatized—is finally becoming trackable, private, and actionable. The Playbook provides real‑time alerts, data‑driven insights, and ecosystem‑wide tools for coaches, trainers, clinicians, and entire organizations. She also shares her journey as a non‑coding tech founder, the scaling challenges brought on by the pandemic, and the broader impact The Playbook is poised to have across corporate, construction, military, and other high‑stress fields. Purpose of the Interview 1. Introduce and explain The Playbook To present The Playbook as a next‑generation mental health performance platform that quantifies mental well‑being, provides action plans, and enhances team culture. 2. Elevate the conversation around athlete mental health Mosley breaks down stigma, highlights real athlete stories, and explains why mental analytics are as critical as physical analytics. 3. Show how the platform uses technology to prevent crises The Playbook provides early detection, privacy protection, and immediate care support—catching problems before they become crises. 4. Highlight the expansion beyond sports Although built in sports, the platform is already being requested by industries like construction, healthcare, first responders, and more. ] 5. Demonstrate the business model As a SaaS B2B platform, The Playbook sells licensed subscriptions to organizations, teams, and associations. Key Takeaways 1. Mental health can be measured—and must be The Playbook converts psychological assessments into quantifiable metrics similar to heart rate or step count.Athletes receive resilience, stress, and well‑being scores—like a “mental batting average.” 2. The platform offers real-time alerts If an athlete’s score enters the “red zone,” coaches/clinicians receive immediate alerts with steps to take within 24 hours. 3. Privacy is paramount The Playbook is HIPAA‑compliant, mobile, secure, and built to protect athlete data from misuse (e.g., contract negotiations). 4. Mental analytics are the next frontier of sports Teams already use physical analytics. Now they can use mental analytics to track performance, prevent burnout, and reduce crises. 5. Built for the entire ecosystem—not just athletes Coaches, front offices, sports medicine staff, and military leadership also use the platform—promoting culture-wide mental health. 6. The Playbook is expanding beyond sports Industries with high stress—construction, medicine, law, emergency responders, veterinarians—are already approaching Mosley to adapt the system. 7. A critical solution for underserved communities The platform makes mental health care accessible, private, digital, and stigma‑free—especially for youth and communities of color. 8. Performance is universal Whether you’re an athlete, military member, parent, or worker—your mental state impacts how you perform. Performance is “agnostic.” [ 9. Mosley’s journey shows innovation can come from anywhere She is a non‑coding tech founder, originally trained as a psychologist working across the NBA, NFL, NCAA, and Olympic sports. [T.M. ROBINSON MOSLEY | Txt] Notable Quotes On what The Playbook does “We measure mental health metrics like resilience, stress and overall well‑being using gamified psych assessments.” “Mental health becomes measurable—like a batting average.” [ On why athletes need this “Elite athletes report battling depression and anxiety so severe they find it difficult to function, let alone perform.” On the power of technology “If we don’t measure something, we’re saying it doesn’t matter.” “We use AI and machine learning to quantify mental health status.” On privacy “We are a HIPAA‑compliant platform… we don’t sell your data.” On team culture “Building a winning team culture is everybody’s everyday work.” On mental and physical health “If you are not mentally healthy, you are not able to perform at the highest level.” On the future outside sports “Who doesn’t want to train like an athlete?” “Performance is agnostic.” On purpose “How do we make something exclusive accessible?” “This is mental health care—it’s just a different version of it.” In One Sentence The interview reveals how Dr. T.M. Robinson-Mosley’s Playbook uses AI‑driven mental health metrics to revolutionize athlete care, provide real‑time performance insights, and expand mental wellness tools far beyond sports into everyday life. #SHMS #STRAW #BEST Just let me know!Support the show: https://www.steveharveyfm.com/See omnystudio.com/listener for privacy information.

Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed T.M. Robinson-Mosley. Summary of the Interview: Dr. T.M. Robinson-Mosley on Money Making Conversations Masterclass Dr. T.M. Robinson-Mosley—founder of The Playbook, an award‑winning mental‑health‑performance sports‑tech company—joins Rushion McDonald to discuss how her platform is transforming athlete care, team culture, and performance measurement. The Playbook uses AI‑powered, gamified psychological assessments to measure stress, resilience, and overall mental well‑being across youth, collegiate, professional, and military sports environments. Mosley explains how mental health—long treated as unmeasurable and stigmatized—is finally becoming trackable, private, and actionable. The Playbook provides real‑time alerts, data‑driven insights, and ecosystem‑wide tools for coaches, trainers, clinicians, and entire organizations. She also shares her journey as a non‑coding tech founder, the scaling challenges brought on by the pandemic, and the broader impact The Playbook is poised to have across corporate, construction, military, and other high‑stress fields. Purpose of the Interview 1. Introduce and explain The Playbook To present The Playbook as a next‑generation mental health performance platform that quantifies mental well‑being, provides action plans, and enhances team culture. 2. Elevate the conversation around athlete mental health Mosley breaks down stigma, highlights real athlete stories, and explains why mental analytics are as critical as physical analytics. 3. Show how the platform uses technology to prevent crises The Playbook provides early detection, privacy protection, and immediate care support—catching problems before they become crises. 4. Highlight the expansion beyond sports Although built in sports, the platform is already being requested by industries like construction, healthcare, first responders, and more. ] 5. Demonstrate the business model As a SaaS B2B platform, The Playbook sells licensed subscriptions to organizations, teams, and associations. Key Takeaways 1. Mental health can be measured—and must be The Playbook converts psychological assessments into quantifiable metrics similar to heart rate or step count.Athletes receive resilience, stress, and well‑being scores—like a “mental batting average.” 2. The platform offers real-time alerts If an athlete’s score enters the “red zone,” coaches/clinicians receive immediate alerts with steps to take within 24 hours. 3. Privacy is paramount The Playbook is HIPAA‑compliant, mobile, secure, and built to protect athlete data from misuse (e.g., contract negotiations). 4. Mental analytics are the next frontier of sports Teams already use physical analytics. Now they can use mental analytics to track performance, prevent burnout, and reduce crises. 5. Built for the entire ecosystem—not just athletes Coaches, front offices, sports medicine staff, and military leadership also use the platform—promoting culture-wide mental health. 6. The Playbook is expanding beyond sports Industries with high stress—construction, medicine, law, emergency responders, veterinarians—are already approaching Mosley to adapt the system. 7. A critical solution for underserved communities The platform makes mental health care accessible, private, digital, and stigma‑free—especially for youth and communities of color. 8. Performance is universal Whether you’re an athlete, military member, parent, or worker—your mental state impacts how you perform. Performance is “agnostic.” [ 9. Mosley’s journey shows innovation can come from anywhere She is a non‑coding tech founder, originally trained as a psychologist working across the NBA, NFL, NCAA, and Olympic sports. [T.M. ROBINSON MOSLEY | Txt] Notable Quotes On what The Playbook does “We measure mental health metrics like resilience, stress and overall well‑being using gamified psych assessments.” “Mental health becomes measurable—like a batting average.” [ On why athletes need this “Elite athletes report battling depression and anxiety so severe they find it difficult to function, let alone perform.” On the power of technology “If we don’t measure something, we’re saying it doesn’t matter.” “We use AI and machine learning to quantify mental health status.” On privacy “We are a HIPAA‑compliant platform… we don’t sell your data.” On team culture “Building a winning team culture is everybody’s everyday work.” On mental and physical health “If you are not mentally healthy, you are not able to perform at the highest level.” On the future outside sports “Who doesn’t want to train like an athlete?” “Performance is agnostic.” On purpose “How do we make something exclusive accessible?” “This is mental health care—it’s just a different version of it.” In One Sentence The interview reveals how Dr. T.M. Robinson-Mosley’s Playbook uses AI‑driven mental health metrics to revolutionize athlete care, provide real‑time performance insights, and expand mental wellness tools far beyond sports into everyday life. #SHMS #STRAW #BEST Just let me know!See omnystudio.com/listener for privacy information.

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