Podcast appearances and mentions of Michael Arrington

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

$1B Into XRP?! Evernorth Just Changed Everything Evernorth — backed by Ripple — is making headlines with a $1 billion XRP treasury move, and it's sending shockwaves through the entire crypto world. In today's show, Jeff & Chip break down: • How Evernorth's massive XRP allocation could redefine institutional adoption. • What Digital Asset Treasuries (DATs) mean for traditional finance. • Insights from Asheesh Birla, Joel Katz (David Schwartz), and Michael Arrington live from Swell 2025. • The bigger picture — is this the start of a full-scale TradFi-to-DeFi shift?

Turning down that med school acceptance might cost more than you think. Listener “my initials are ARM” got into medical school—cue the confetti—but now that reality's set in, she's not feeling great about her only acceptance. The school is small, expensive, and far from home. Should she go anyway or risk reapplying in hopes of a better fit next year? MD/PhD students Michael Arrington, Shruthi Kondaboina, Jessica Smith, and M1 Maria Schapfel weigh the real costs of walking away from an acceptance, from the red flags admissions committees look for to the gamble of getting in again. They get honest about finances, family, and the very unsexy truth about how much the campus “vibe” actually matters. Plus, what to say if you do it anyway. Bonus: the MD/PhD students dish about why they took that road, while Maria counters with why MD is better for her.

Cardiologist David Sabgir was tired of telling patients to exercise, so he did something ridiculous…and it spawned a movement. Walk With A Doc began with a simple idea: don't just recommend lifestyle changes—live them, with your patients, in the wild. In this episode, we unpack the surprising power of walking with a community instead of talking at patients about exercise, and how a one-mile stroll has turned into an international public health initiative. Co-hosts M3 Jeff Goddard, and M1s Sydney Skuodas, Michael Arrington, and Zach Grissom are also asking: what happens when docs and med students bring their kids, their real lives, and their full humanity into community care? For some, it could be a real antidote to burnout, and the solution might be hiding in the park—with some sneakers and your neighbors. The cardiologist that stared it all shares how failing at patient motivation led to something wildly more effective. This episode is your unofficial permission slip to stop recommending change and start doing it.

Turning down that med school acceptance might cost more than you think. Listener “my initials are ARM” got into medical school—cue the confetti—but now that reality's set in, she's not feeling great about her only acceptance. The school is small, expensive, and far from home. Should she go anyway or risk reapplying in hopes of a better fit next year? MD/PhD students Michael Arrington, Shruthi Kondaboina, Jessica Smith, and M1 Maria Schapfel weigh the real costs of walking away from an acceptance, from the red flags admissions committees look for to the gamble of getting in again. They get honest about finances, family, and the very unsexy truth about how much the campus “vibe” actually matters. Plus, what to say if you do it anyway. Bonus: the MD/PhD students dish about why they took that road, while Maria counters with why MD is better for her.

Guest: David Heinemeier Hansson, CTO & co-owner of 37signals and creator of Ruby on Rails 37signals CTO David Heinemeier Hansson has organized his life around his passions: Writing, racing sports cars, and coding. “ Why aren't we all doing that?” he wonders. “Why aren't we all trying to optimize our life in such a way that much of it is enjoyable?”Part of the problem, David argues, is that it's impossible to find a creative or productive flow inside of mainstream work culture. Open offices, managerial over-hiring, and sloppy scheduling prevents people from reaching a flow state.“40 hours a week is plenty than most people,” he says. “... So many people today are focused on just adding more and more hours. They're not thinking about how those hours are spent.” Chapters:(01:19) - 24 Hours of Le Mans (06:48) - Amateurs in sports car racing (10:54) - Flow and meditation (15:25) - Mundane bulls**t (18:14) - Optimizing for flow (21:09) - Calendars and open offices (24:30) - Full-time managers (29:06) - Small companies (32:20) - Selfishness and work (40:21) - Taking other people's money (45:43) - Temptation (49:49) - Moderately rich (55:19) - “The day I became a millionaire” (58:56) - The hassle (01:03:58) - Achieving the dream (01:08:34) - Shopify and Tobias Lütke (01:14:50) - Trade-offs and downsides (01:18:43) - The impact of Ruby on Rails (01:22:02) - “I love being wrong” (01:25:37) - DEI and illegal drugs (01:29:49) - Not hiring (01:30:35) - What “grit” means to David Mentioned in this episode: TikTok, Minecraft, Mario Kart, Formula One, NASCAR, Lewis Hamilton, the NBA, Tesla Model S, Flow: The Psychology of Optimal Experience by Mihaly Csikszentmihalyi, Steve McQueen, Jason Fried, Tetris, Bullshit Jobs: A Theory by David Graeber, Elon Musk and Twitter, the Dunbar number, Zappos, Google, Adam Smith, Stripe, Meta, Jeff Bezos, Basecamp, Zapier, 1Password, GitHub, SpaceX, private jets, Aesop, the Pagani Zonda, the Porsche Boxster, Lamborghini, Coco Chanel, LeBron James, Hey, Steve Jobs, Michael Arrington and TechCrunch, Y Combinator, Dr. Thomas Sowell,Punished by Rewards by Alfie Kohn, Grit by Angela Duckworth, and LEGO. Links:Connect with DavidTwitterLinkedInConnect with JoubinTwitterLinkedInEmail: grit@kleinerperkins.com Learn more about Kleiner PerkinsThis episode was edited by Eric Johnson from LightningPod.fm

Med Students discuss their “Why Medicine?” answers. Dave welcomes newly minted medical and PA students at the Carver College of Medicine to share their first-week experiences and the challenges of adapting to medical school. M1s Sydney Skuodas, Michael Arrington, Alex Murra, Luke Geis, and PA1 Harrison Parker discuss what they've learned about time management, personal growth during “gap years,” overcoming imposter syndrome, and balancing personal life with rigorous medical training. The co-hosts also discuss the personal motivations behind their decisions to pursue medicine, revealing stories of past careers, family influences, and the aspiration to impact lives directly. Don't worry about the shock device we're using, I'm sure they're fine, plus it was Luke's idea.

Whist I was manically refreshing my Crypto Fidelity page while smoking a joint praying for better spreads and a painless brazilian wax, it occurred to me that this new cycle will hit different. Alas I wager we will see less of the pitiful tech bros peddling nonsensical seasons of DeFi summers and meaningless phrases like interoperable metaverse masking their low confidence in newfound stoicism and Marcus Aurelius Bullshit- but of what is to come remains remarkably unknown. Deep in the confines of my own imagination, I still wonder, is it cool to Love Trump if my Bitcoin earnings finance my donation to a do nothing liberal organization. Alas, with prices higher than losers at Burning man I still remain on my somewhat asbergers yet violent quest armed with my baccarat bedazzled magnifying glass to discover if people are actually using this shit. I see everyone with a networth that can finance a qui qong instructor and a ski chalet in Verbier purchase crypto at Fidelity. Why? Because ultimately, my banker is my best friend. Show me a rich person lending on Aave save for Stani and I will show you an Alvin Ailey Dancer who voted for Trump. Ce n'est pas possible. I digress; My guest is the ever so fabulous hot crypto power mom fellow podcast host Fund Partner Keli Callaghan. I met Keli deep in the trenches of Covid in a Cafeteria somewhere in Gstaad. She educated me on the deep misrepresentations of both masks and Algorand, wildly misunderstood concepts that played a crucial role in the health of our society and their impacts will be studied for years to come. Despite her no longer being at Algorand, Keli drove its marketcap to astronomical proportions resulting in Keli's undeniable fame. She has over 20K X followers leading her to require a security team at Glitter Ledger Headquarters.Keli currently serves as the Partner and Chic Growth Officer of Arrington Capital alongside Michael Arrington. She is so much more than your typical soulless one dimensional crypto VC with no meaningful thoughts or insights. Keli has a long history of marketing and storytelling for brands in the traditional world of actually working. She also studies how to manipulate people and how to find psychopaths amongst us in a course that one must be specially recommended for. Her insights on leadership, luck, and career development are insightful without being trite or pathetic. She is smart, hilarious and could have hosted this show herself. 

In this episode of the Pirate Pod, Michael Arrington (x.com/arrington) and Ron Palmeri (x.com/RonP) discuss TrainSpot, a new AI data marketplace focused on the intersection of content and ownership. They explore the implications of data ownership, the legal landscape surrounding content usage, and the challenges faced by content creators in monetizing their work. The discussion also touches on the future of copyright law and the need for a cultural movement to support content creators in the evolving digital landscape.Topics covered include:TrainSpot's approach with a two-sided marketplace for AI-related content and dataContent creators' control over how their data is used - and how they could be empoweredLegal issues surrounding data scraping and copyrightMonetization opportunities for content creators in the AI spaceTransparency in data value and the facilitation of fair compensationThe uncertain future of content rights and AI integration For more information, visit trainspot.ai.Disclaimer: The views discussed in this conversation are the views of the individuals, and not of Arrington Capital. This podcast is provided solely for informational purposes and is not financial, legal, tax or investment advice.The participants of this podcast are not recommending any particular security, protocol, token, financial instrument, or other tradable asset or any investment strategy and is not offering to sell or soliciting to buy any security or asset. Arrington Capital may have an economic interest in any companies or protocols discussed in this podcast.

Med Students discuss their “Why Medicine?” answers. Dave welcomes newly minted medical and PA students at the Carver College of Medicine to share their first-week experiences and the challenges of adapting to medical school. M1s Sydney Skuodas, Michael Arrington, Alex Murra, Luke Geis, and PA1 Harrison Parker discuss what they've learned about time management, personal growth during “gap years,” overcoming imposter syndrome, and balancing personal life with rigorous medical training. The co-hosts also discuss the personal motivations behind their decisions to pursue medicine, revealing stories of past careers, family influences, and the aspiration to impact lives directly. Don't worry about the shock device we're using, I'm sure they're fine, plus it was Luke's idea.

Arthur Hayes joins Michael Arrington for a discussion on the current geopolitical arrangement and his prediction on the coming shift to a new system. The episode covers the interconnectedness of volatility and Bitcoin, how the macro world revolves around this, fiscal dominance and central bank's current decision making, the importance of energy costs, what these two leaders are doing about holding gold and the potential for massive inflation. Arthur teases an upcoming essay he is working on regarding dollar swap lines and what is going with Japanese Yen valuation and what that means for China, Japan and the rest of the world. With Arthur's involvement in Ethena and Pendle, there is also a focus on investment trends, advice for entrepreneurs, hiring, and running organizations of different sizes. Disclaimer: The views discussed in this conversation are the views of the individuals, and not of Arrington Capital. This podcast is provided solely for informational purposes and is not financial, legal, tax or investment advice.The participants of this podcast are not recommending any particular security, protocol, token, financial instrument, or other tradable asset or any investment strategy and is not offering to sell or soliciting to buy any security or asset.

Sam Schillace is deputy CTO and corporate vice president at Microsoft. Prior to working at Microsoft, Sam started a company called Writely, which was acquired by Google and became the foundation of what today is Google Docs. While at Google, Sam helped lead many of Google's consumer products, including Gmail, Blogger, PageCreator, Picasa, Reader, Groups, and more recently Maps and Google Automotive Services. Sam was also a principal investor at Google Ventures, has founded six startups, and was the SVP of engineering at Box through their IPO. In this episode, we discuss:• The journey of building Google Docs• The importance of taking risks, embracing failure, and finding joy in your work• The importance of asking “what if” questions vs. “why not”• Why convenience always wins• How, and why, Sam stays optimistic• Inside Microsoft's culture• Why you should solve problems without asking for permission• Early-career advice• Why “pixels are free” and “bots are docs”—Brought to you by Teal—Your personal career growth platform | Vanta—Automate compliance. Simplify security | Ahrefs—Improve your website's SEO for free—Find the full transcript at: https://www.lennyspodcast.com/how-to-be-more-innovative-sam-schillace-microsoft-deputy-cto-creator-of-google-docs/—Where to find Sam Schillace:• LinkedIn: https://www.linkedin.com/in/schillace/• Newsletter: https://sundaylettersfromsam.substack.com/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Sam's background(03:45) The first Google Docs file(06:45) Disruptive innovation(10:11) First-principles thinking(11:00) Recognizing disruptive ideas(13:17) Examples of first-principles thinking(15:46) The power of optimism(19:47) Sam's motto: Get to the edge of something and f**k around(21:53) User value and laziness(24:31) People are lazy (and what to do about it)(28:36) Building Google Docs(31:06) The evolution of Google Docs(37:15) Finding product-market fit(39:52) The future of documents(44:57) The value of playing with technology(47:58) Taking risks and embracing failure(49:21) Thinking in the future(53:48) Finding joy in your work(01:01:20) Just do the best you can(01:02:34) The transformational power of AI(01:09:27) Advice for approaching AI(01:13:07) The culture at Microsoft(01:16:51) Closing thoughts(01:17:32) Lightning round—Referenced:• Google Docs began as a hacked-together experiment, says creator: https://www.theverge.com/2013/7/3/4484000/sam-schillace-interview-google-docs-creator-box• Edna Mode: https://disney.fandom.com/wiki/Edna_Mode• Sergey Brin's profile on Forbes: https://www.forbes.com/profile/sergey-brin/• People Who Were No Smarter Than You: https://medium.com/thrive-global/people-who-were-no-smarter-than-you-4e1c88c3fee6• Nat Torkington (O'Reilly Media): https://www.oreilly.com/people/nathan-torkington/• How Tesla Has Shaken (Not Stirred) Established Carmakers—and Why It Really Matters: https://www.forbes.com/sites/jenniferdungs/2021/04/23/how-tesla-has-shaken-not-stirred-established-carmakersand-why-it-really-matters/• First Principles: Elon Musk on the Power of Thinking for Yourself: https://jamesclear.com/first-principles• Ashton Tate: https://en.wikipedia.org/wiki/Ashton-Tate• Learning by Doing: https://www.linkedin.com/pulse/learning-doing-sam-schillace• Kevin Scott on LinkedIn: https://www.linkedin.com/in/jkevinscott/• How do we make sense of all of this?: https://sundaylettersfromsam.substack.com/p/how-do-we-make-sense-of-all-of-this• Steve Newman on LinkedIn: https://www.linkedin.com/in/stevescalyr/• Eric Schmidt on LinkedIn: https://www.linkedin.com/in/eric-schmidt-02158951/• Michael Arrington on X: https://twitter.com/arrington• TechCrunch: https://techcrunch.com/• “Hello, Computer” scene from Star Trek: https://www.youtube.com/watch?v=hShY6xZWVGE• Writely—Process Words with your Browser: https://techcrunch.com/2005/08/31/writely-process-words-with-your-browser/• Satya Nadella on LinkedIn: https://www.linkedin.com/in/satyanadella/• Poor Charlie's Almanack: The Essential Wit and Wisdom of Charles T. Munger: https://press.stripe.com/poor-charlies-almanack• Calvinism: https://en.wikipedia.org/wiki/Calvinism• This Quote from Seth Godin Could Change How You Think About Pursuing Your Passion: https://friedchickenandsushi.com/blog/2021/7/5/this-quote-from-seth-godin-could-change-how-you-think-about-pursuing-your-passion• AI isn't a feature of your product: https://sundaylettersfromsam.substack.com/p/ai-isnt-a-feature-of-your-product• Introducing Gemini: our largest and most capable AI model: https://blog.google/technology/ai/google-gemini-ai/• Invisible Cities: https://www.amazon.com/Invisible-Cities-Italo-Calvino/dp/0156453800• The Wasp Factory: https://www.amazon.com/WASP-FACTORY-NOVEL-Iain-Banks/dp/0684853159• Where Good Ideas Come From: The Natural History of Innovation: https://www.amazon.com/Where-Good-Ideas-Come-Innovation/dp/1594485380/• Slow Horses on Apple TV+: https://tv.apple.com/us/show/slow-horses/umc.cmc.2szz3fdt71tl1ulnbp8utgq5o• Monarch: Legacy of Monsters on Apple TV+: https://tv.apple.com/us/show/monarch-legacy-of-monsters/umc.cmc.62l8x0ixrhyq3yaqa5y8yo7ew?mttn3pid• Scavengers Reign on Max: https://www.max.com/shows/scavengers-reign/50c8ce6d-088c-42d9-9147-d1b19b1289d4• 2023 Mustang Mach-E: https://www.ford.com/suvs/mach-e/• Boccalone Salumeria (now closed) on X: https://twitter.com/boccalone—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Oggi vi raccontiamo la storia di Loris Degioanni, founder di Sysdig, startup basata in Silicon Valley che a dicembre 2021 ha raccolto $350 milioni e raggiunto una valutazione da $2.5 miliardi. Eppure questa storia inizia a Vinadio, un paesino di soli 400 abitanti sperduto in mezzo alle montagne piemontesi. Loris ci racconterà ogni passo della sua storia con umiltà e trasparenza. Ci direte cosa ne avete pensato, ma per noi è stata una grande intervista con un grande imprenditore. Loris ha condiviso tantissime lezioni imparate nello scalare due startup tech, la seconda ad altissimi livelli. Quando abbiamo chiesto a Loris cosa lo ha spinto a ributtarsi nel vuoto per cominciare la sua seconda startup dopo la sua prima exit, ha citato un articolo di Michael Arrington di TechCrunch intitolato “Are You A Pirate?”, “Sei Un Pirata?” che compara gli imprenditori ai pirati. Spiega infatti che la maggior parte delle persone prendono le loro decisioni calcolando i rischi e benefici delle loro azioni. Ma gli imprenditori vedono il calcolo tutto al contrario perché traggono utilità dal rischio stesso. In altre parole, sono degli avventurieri.  Quindi vi lasciamo ascoltare la storia di un'altro pirata. Che dal Piemonte si è trovato in Silicon Valley a fondare e crescere una startup di Cloud computing, leader al mondo nei settori sicurezza e del monitoraggio dei Container, un'evoluzione del cloud. SPONSORS Made IT è powered by ⁠⁠⁠Alchimia⁠⁠⁠, società di investimento che opera principalmente nel settore del Venture Capital. Investono e co-investono in opportunità ad alto potenziale di crescita, offrendo capitale e risorse strategiche e operative dedicate. ⁠Barberino's⁠ è molto più di un semplice barbiere, ha infatti trasformato una semplice necessità come tagliarsi i capelli o radersi in un'esperienza goduriosissima. Barberino's ha deciso di regalare a tutti voi un fantastico omaggio! Con il codice MADEIT avete il 20% di sconto su ⁠www.barberinosworld.com⁠ fino al 24/12/23 su tutti i prodotti a marchio Barberino's, senza minimo di spesa. SOCIAL MEDIA Se vi piace il podcast, il modo migliore per dircelo o per darci un feedback (e quello che ci aiuta di più a farlo diffondere) è semplicemente lasciare una recensione a 5 stelle o un commento su Spotify o l'app di Apple Podcast. Ci ha aiuta davvero tantissimo, quindi non esitate :) Se volete farci delle domande o seguirci, potete farlo qui: Instagram ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@madeit.podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@madeitpodcast⁠⁠⁠⁠⁠⁠⁠⁠⁠

Shanee Ben Zur is the Chief Marketing and Growth Officer for Crunchbase, a company founded in 2007 by Michael Arrington, initially as a place to track the startups his parent company TechCrunch was writing about. Then Aol bought TechCrunch and Crunchbase in 2010 but Crunchbase went private again in 2015. Shanee worked at a PR firm founded by ex-Apple executives and from there she held roles at Salesforce, Nvidia, and Dropbox. Now after 3 years at Crunchbase she's CMO. She has a degree in Management Science from UC San Diego.Shanee and Jim talk about the importance of holding on to relationships in business, and how important it is to explain the CMO's impact on business metrics. Also both Shanee and Jim have a hard time discussing what makes them special. CMOs often hold one of the most innovative and challenging roles in business today. Those who excel can operate at the highest level to drive growth and create value for their organizations. To learn more how Deloitte helps bolster the value CMOs deliver, visit www.cmo.deloitte.com.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Isn't that the truth?  In this episode, Mike and Blaine break down this quote from Michael Arrington.  There are several different reasons that people start businesses, but there is always a driving factor.  Maybe you have a cause you are passionate about, or you're just tired of not being heard at your current job.  Whatever your motivation is, there is an itch that needs to be scratched.  OH! And here is a special treat.  We will be joined by Roger Knecht, President of Universal Accounting and the host of The Acountreprenuer's Journey Podcast.  Today's Beer:Mike: Equal Parts Brewery - Logger BeerBlaine: Annex Ale Project - Force Majeure NEIPA@EqualPartsBrewing @annexalesWatch on Youtube at https://youtu.be/5cEFGhV_QmYListen to all our episodes at: https://www.mikeandblaine.com/podcasthttps://mikeandblaine.com/#smallbusiness, #cashflow #finance #beer #friends #entrepreneur #smbs #craftbeer Support the show

Michael Arrington, who is the founder of TechCrunch and Arrington Capital, talks about the current Crypto market situation. We discuss navigating the crypto bear market, bitcoin, Arrington capital's Moonbeam fund, XRP, Algorand, Terra Luna, and US crypto regulations.Sponsor

Empower Oversight obtains additional documents shedding light on potential Cryptocurrency conflicts of interest within the SEC. This could lead to a settlement soon in the Ripple XRP lawsuit. Tesla, Block and Blockstream team up to mine #Bitcoin off solar power in Texas.https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Kevin O'Leary says regulation will lead to more money coming into the Crypto market. Robinhood adds crypto wallet features for Bitcoin, Ethereum, & Dogecoin and will add BTC lightning network. Ripple releases new update XRP Ledger update.https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Ron Hammond of the Blockchain Association talks about the latest news on crypto regulations which includes Janet Yellen's speech today, Senator Pat Toomey Stablecoin bill, Senators Cynthia Lummis and Kristen Gillibrand crypto legislation, and Accountability for Cryptocurrency in El Salvador Act.https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

SEC losses a case against Binance and may experience additional losses such as the Ripple XRP lawsuit. Gary Gensler gets called out. Intel launches their new Bitcoin mining chip, the Blockscale ASIC. UK's Finance Minister says he's taking steps to position the UK as a global crypto tech hub. Elon Musk has taken a 9.2% stake in Twitter. Luxury fashion brand Off-White has begun accepting cryptocurrency payments across its flagship stores in Paris, Milan and London. 1 in 4 Millennials now using crypto to fund retirement.Brett Harrison Interview - https://youtu.be/Y2bzSkODo-ghttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Steve Adler is the Mayor of Austin Texas. In this interview we discuss Austin's plans for crypto, web3, and blockchain. We also touch on Bitcoin mining in Texas, President Biden's Crypto Executive order, Digital Dollar and CBDCs, NFTs and more.https://twitter.com/MayorAdlerhttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Bitcoin and altcoins are looking bullish as the crypto market is in an uptrend. Kevin O'Leary talks about crypto and there is big Bitcoin adoption news.https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Brett Harrison is the president of FTX US crypto exchange. In this interview we talk about FTX's growth, strategy, marketing via Super Bowl and with athletes such as Tom Brady and Steph Curry, FTX's CEO Sam Bankman-Fried, US crypto regulations, Bitcoin, NFTs, CBDCs and more.https://ftx.us/https://twitter.com/Brett_FTXUShttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Ripple's general council shared states from SEC Hester Pierce regarding the fair notice which is good news for XRP holders. of the highest-profile US senators, while both agreeing on the need for more defined cryptocurrency regulation, are divided on the value of digital assets and their place in consumers' portfolios. 19 million Bitcoin have been mined leaving only 2 million left.Gareth Soloway Interview - https://youtu.be/edwHToBRWT0https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

In crypto news today the IMF says the Russia-Ukraine crisis could boost crypto adoption. SEC's Hester Pierce pushes back on the SEC's new crypto bulletin. VeChain partners with Alchemy Pay for fiat payment rails and Crypto on-ramps.Congressman Byron Donalds Interview - https://youtu.be/73AeD9KWEGQJoseph Grundfest Interview - https://youtu.be/u8SCtNyXR-Ahttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Gareth Soloway is the President & CFO, Chief Market Strategist at InTheMoneyStocks.com and VerifiedInvestingCrypto.com. In this interview Gareth explains what he sees on the charts for Bitcoin, Altcoins, Crypto market, and Stocks.https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Huge Cardano ADA crypto news today Wave Financial is launching a fund designed to offer liquidity for new DeFi platforms launched in the Cardano ecosystem. Visa has launched a program to help content creators grow their businesses through NFTs. OpenSea to integrate Solana NFTs in April.Hashdex has poached an executive from competitor 21Shares as the Brazilian cryptoasset manager looks to extend its presence in Europe.Charles Hoskinson Interview - https://youtu.be/a-httMQj0wEFred Thiel Interview - https://youtu.be/mZMU7I-MGWEhttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Big crypto drama news today as Bitcoiners attacked Ripple's Chris Larson over his suggestion that Bitcoin move away from Proof of Work. MacroStrategy, a subsidiary of MicroStrategy, has closed a $205 million bitcoin-collateralized loan with Silvergate Bank to purchase bitcoin. The Ronin bridge has been exploited for 173,600 Ethereum and 25.5M USDC. Vietnam's Deputy Prime Minister Le Minh Khai has tasked the country's Ministry of Finance with spearheading research for the implementation of a legal framework governing digital assets.J.W. Verret Interview - https://youtu.be/1giPIDdrcEQhttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

J.W. Verret is a Professor of Law at George Mason University, Consultant at Veritas Financial Analytics LLC, Former SEC Advisory Committee Member. In this interview we discuss the SEC and crypto regulations, need for a new Howey test, Ripple XRP lawsuit, Bitcoin Spot ETF, Biden Crypto Executive order, Janet Yellen, crypto regulations, CBDCs, NFTs and more.https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

In crypto news today Bitcoin and Altcoins continue to pump today, Grayscale threatens legal action if SEC rejects Bitcoin spot ETF. Cryptocurrency exchange FTX has considered setting up a fund of funds operation to supply investor capital to outside digital asset portfolio managers. Deutsche Bank: Instagram's NFT efforts could lead to mainstream adoption.Sunny Lu Interview - https://youtu.be/_ES0It54IWYhttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Sunny Lu is the co-founder and CEO of VeChain. In this interview we discuss the latest news with VeChain such as VeUSD, the first stablecoin on VeChain, VeCarbon, VeChain Foundation's expansion to Europe and future plans for the Foundation in San Marino and beyond, Draper University's accelerator/ incubator for Web 3 founders, NFTs on VeChain, Biden Crypto Executive order, Ukraine, Crypto regulations and more.https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Jeremy Kauffman is the CEO of LBRY. In this interview we discuss the LBRY platform, SEC's lawsuit against LBRY, US Crypto regualtions, SEC Ripple Lawsuit, Bitcoin, CBDCs, NFTs, and more.https://lbry.com/https://twitter.com/lbrycomhttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Bitcoin and the crypto market is pumping, could we see big news tomorrow? Britain will reveal crypto regulation plans in coming weeks. Rio de Janeiro will be the first Brazilian city to receive tax payments in Bitcoin & crypto. Coinbase to control Latin America's largest crypto exchange via acquisition.Jeremy Kauffman Interview - https://youtu.be/JzG9QTO7XhYhttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Huge crypto news today as Janet Yellen makes positive states about the future of crypto in the US. Senator. Senators Kirsten Gillibrand and Cynthia Lummis are working together on cryptocurrency regulations. Bank Leumi, one of the biggest banks in Israel, will start to offer crypto trading. LG Electronics adds blockchain and crypto as new areas of business. Luna Foundation buys 2,900 MORE bitcoin worth $128 MILLION to back UST stablecoin. https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Big crypto news today as BlackRock looks to offer Crypto services as Client demand rises. Portsmouth, New Hampshire, will allow residents to pay their bills in Bitcoin and other cryptocurrencies through PayPal. ExxonMobil, the largest US oil producer is using excess gas to power #Bitcoin and crypto mining. The Chamber of Digital Commerce will support Ripple in the SEC XRP lawsuit.Paul Riegle Interview - https://youtu.be/UobTSpiVJ3IPerianne Boring Interview - https://youtu.be/GVuJxFJW98khttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

In cryptocurrency news today Goldman Sachs website is promoting crypto and the metaverse. Wall Street bank Cowen Inc. to offer spot Bitcoin and crypto trading to institutional clients. Luna Foundation confirms 6,000 bitcoin purchase worth $250 million to back its UST stablecoin. Federal Reserve Chair Jerome Powell says US regulations have to be updated to fit cryptocurrencies. New crypto venture fund raises $125 million with plan to become a DAO In 2025. Tetris has filed a trademark application for NFTs and the metaverse.Sheila Warren Interview - https://youtu.be/vVbr8D1pwVYJack McDonald PolySign CEO Interview - https://youtu.be/zChIii8tGB4Sponsorshttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Paul Riegle is the Chief Product Officer at Algorand. In this interview we discuss Algorand's Network upgrades which expands Smart Contract functionality with Contract-to-Contract calls, releases post-Quantum secure keys for Trustless Cross-Chain Interoperability.Also, Algorand State Proofs are a new interoperability standard that securely connects blockchains to the outer world without trust in an intermediary. Limewire NFT marketplace and Run-DMC's Darryl McDaniels and The Song That Owns Itself (STOI) adoption of Algorand.https://twitter.com/paulriegleSponsorshttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto--

Sheila Warren is the CEO of the Crypto Council For Innovation. In this interview we discuss the mission, members, and projects of the Crypto Council for Innovation. We also touch on global crypto regulations, EU's proposed ban on Bitcoin PoW mining, President Biden's Crypto executive order, Ukraine crypto adoption, Elizabeth Warren and Russia Cryptocurrency Sanctions.https://cryptoforinnovation.org/https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto

In crypto news today Florida governor confirms the state is working on a plan to let businesses pay taxes in bitcoin and crypto. Draper University, a training center for entrepreneurs founded by billionaire venture capitalist and early crypto adopter Tim Draper, has partnered with blockchain application platform VeChain to launch new programs for those interested in starting and scaling Web 3 businesses. Japan to simplify the listing of Bitcoin, Ethereum and 14 other cryptos in Japanese crypto exchanges. Katie Haun, a former partner at venture capital firm Andreessen Horowitz (a16z), has raised $1.5 billion for two new crypto-focused funds for her new firm, Haun Ventures.Congressman Byron Donalds Interview https://youtu.be/73AeD9KWEGQhttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto

Congressman Byron Donalds was part of a bi-partisan group that sent a letter to SEC Chair Gary Gensler regarding the overburdensome reporting requirements for Crypto and Blockchain companies. We also touch on Bitcoin Mining, CBDCs, and US crypto regulations.https://twitter.com/RepDonaldsPressSponsorshttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto

In cryptocurrency news today Goldman Sachs makes its first over-the-counter Bitcoin options trade. World's largest hedge fund, Ray Dalio's Bridgewater, is preparing to invest in its first crypto fund. Malaysia's Communication Ministry has proposed to the government that crypto currency such as bitcoin be adopted as legal transfer.https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto

Bitcoin closed the week very bullish, could this be the start of an uptrend in BTC's retracement and then Altseason after? Hondusras may add Bitcoin as a legal tender soon. SEC's Gary Gensler gets called out as Elizabeth Warren's pet. Is Cardano planning a ADA token burn?https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto

In Cryptocurrency news today J.W. Verret calls out the SEC Gary Gensler's abuse of the Howey test in the Ripple XRP lawsuit. Ripple's Stuary Alderoty talks crypto regulations and the SEC. Tom Brady Tweets about Bitcoin and FTX again. Spotify is planning to add NFTs to its streaming service.https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto

In Crypto news today Elizabeth Warren puts out a Crypto bill. Coinbase gets sued over unregistered securities and Ripple commits 1 billion xrp the XRP ledger grants.https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto

Big crypto news today Congress sends SEC Gary Gensler a bipartisan letter about crypto documentation requests. Ukrainian President Volodymyr Zelenskyy legalized crypto in the country, signing into law a bill on virtual assets. Ripple (XPR) adds Michael Warren to their Board of Directors. Ripple's David Schwartz talks about tokenization on the XRP ledger.Alessio Quaglini CEO Hex Trust Interview - https://youtu.be/dWxkj5vJgDQ & https://youtu.be/BeAlL6a5tSIhttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto

Greg Dickerson talks about the impact of the Fed's interest rate increase of .25% on Bitcoin and Crypto, Stocks, and Real Estate market. We also discuss the economic outlook for 2022.https://twitter.com/AGregDickersonhttps://www.youtube.com/user/agregdickersonhttps://www.dickersoninternational.com/Sponsorshttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto

In crypto news today Elon Musk tweets about inflation and still holding his cryptocurrency which includes Bitcoin, Ethereum, and Dogecoin. EU Parliament votes against a proof-of-work ban. US Senator Cory Booker: Bitcoin and crypto could "bring growth to the American economy. U.S. senator' Cynthia Lummis' Bitcoin bill aims to provide a tax exclusion for purchases up to $600 using BTC.Austin, Texas is exploring ways to accept Bitcoin as a payment option.https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto

In crypto news today a lot of cryptocurrency companies have hundreds of jobs open. FTX and Binance get new licenses. The first bitcoin-backed bonds issued by El Salvador could launch this week. Elizabeth Warren's anti-crypto crusade splits the left.https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto

In Crypto news today Bitcoin continues to move sideways, when will it breakout upwards with altseason following. $1.8 Billion was invested in crypto this past week. https://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto

Monica Long is the General Manager of RippleX. In this interview she discusses the latest XRPL grants to NFT creators. We also touch on Stablecoins, CBDCs, and Xange developing a Carbon Credit Solution on the XRP Ledger. Sponsorshttps://itrust.capital/thinkingcryptohttps://taxbit.com/invite/thinkingcrypto/?fpr=thinkingcrypto